master controller requirements specification for perfect power

Master Controller Requirements Specification for Perfect Power Systems

(as outlined in Galvin Electricity Initiative)

Rev 3, 02162007

February 16, 2007

Galvin Electricity Initiative 3412 Hillview Avenue

Palo Alto, CA 94304 650-855-2400

Master Controller Requirements Specification for Perfect Power Systems, Rev. 3 Page ii

Galvin Electricity Initiative The Galvin Electricity Initiative seeks to identify opportunities for technological innovation in the electric power system (broadly defined) that will best serve the changing needs of consumers and businesses over at least the next 20 years. Of paramount importance will be insuring that the electricity system provides absolutely reliable and robust electric energy service in the context of changing consumer needs.

For more information about this publication or the Galvin Electricity Initiative, please contact Galvin Electricity Initiative at 650-855-2400 or visit us at www.galvinelectricity.org.

© 2007 Galvin Electricity Initiative

All rights reserved.

Galvin Electricity Initiative and the Galvin Electricity Initiative logo are trademarks of Galvin Project, Inc.

Master Controller Requirements Specification for Perfect Power Systems, Rev. 3 Page iii

Table of Contents

1. Introduction.................................................................................... 1 1.1. Purpose 1 1.2. Intended Audience and Reading Suggestions..........................................2 1.3. Project Scope .........................................................................................3

1.3.1. Advancement of Microgrid Research ....................................... 3 1.3.2. Functions Described in This Report ......................................... 4

1.4. References .............................................................................................5

2. Overall Description ........................................................................ 8 2.1. Overview of Microgrid Architecture.......................................................8

2.1.1. System Controller..................................................................... 8 2.1.2. Microgrid Master Controller .................................................... 9 2.1.3. Slave Controllers.................................................................... 11 2.1.4. Other Sensors and Transducers .............................................. 13

2.2. Operating Modes for the Master Controller ..........................................14 2.3. Operating Environment and Other Assumptions ...................................15

3. Description of Master Controller Functions ................................ 17 3.1. Optimization Functions in Mode 1 – Normal Operation Connected to the

Supply System .....................................................................................19 3.1.1. Microgrid Economic Optimization (Operating Schedule and

Continuous Optimization) ...................................................... 20 3.1.2. Load Economics Calculator and Forecaster............................ 21 3.1.3. Microgrid Generation Economics Calculator and Forecaster.. 22 3.1.4. Renewable Generation Calculator and Forecaster .................. 23 3.1.5. Microgrid Storage Economics Calculator and Forecaster ....... 23 3.1.6. Microgrid Risk Manager Function ......................................... 24 3.1.7. Microgrid Continuous Technical Performance Assessment.... 25 3.1.8. Microgrid Ancillary Services (Reactive Power) Calculator.... 25

3.2. Optimization Functions in Mode 2 – Emergency Operation Connected to the Supply System................................................................................26

3.2.1. Microgrid Economic Optimization in Emergency Mode ........ 27 3.2.2. Microgrid Continuous Technical Performance Assessment ?

Emergency Mode ................................................................... 27 3.3. Commercial Functions Supporting Interface between Resources and

Supply System - Configuration.............................................................28

Master Controller Requirements Specification for Perfect Power Systems, Rev. 3 Page iv

3.3.1. Electricity Price Forecasting Configuration (via UI) .............. 28 3.3.2. Supply Alternatives Configuration (via UI)............................ 29 3.3.3. Demand Bid Alternatives Configuration (via UI) ................... 29 3.3.4. Default Tariff or Retail Contract Configuration ..................... 30 3.3.5. Unit Economics Configuration............................................... 30 3.3.6. Resource Characteristics Set Up............................................. 31

3.4. Commercial Functions Supporting Interface between Resources and Supply System – Implementation .........................................................31

3.4.1. Electricity Price Forecasting................................................... 32 3.4.2. Process Dynamic Pricing Information .................................... 32 3.4.3. Electricity Cost Calculation.................................................... 33 3.4.4. Electricity Cost Forecast ........................................................ 34 3.4.5. Demand Bid Opportunity Assessment.................................... 34 3.4.6. Demand Bid Submission ........................................................ 35 3.4.7. Bid Award Notification .......................................................... 35 3.4.8. Microgrid Resource Availability Update................................ 36 3.4.9. Microgrid Resource Deployment Scheduler ........................... 36 3.4.10. Microgrid Resource Dispatch................................................. 37

3.5. Optimization Functions in Mode 3 – Island Operation ..........................38 3.5.1. Microgrid Continuous Optimization in Island Mode .............. 38 3.5.2. Microgrid Risk Manager Function – Island Mode.................. 40 3.5.3. Microgrid Continuous Technical Performance Assessment –

Island Mode ........................................................................... 41 3.5.4. Black Start Control................................................................. 41

3.6. Functions that are Independent of Operating Mode...............................42 3.6.1. Microgrid Power Quality Assessments................................... 42 3.6.2. User Defaults Set Up.............................................................. 42 3.6.3. Preferences Configuration ...................................................... 42 3.6.4. User Notification Alert........................................................... 43

4. Other Requirements ..................................................................... 44 4.1. User Interfaces .....................................................................................44 4.2. Software Interfaces ..............................................................................44 4.3. Communication Interfaces....................................................................45 4.4. Time Synchronization ..........................................................................45 4.5. Software Quality Attributes..................................................................45 4.6. Data Management Requirements ..........................................................47

A. Appendix: Abbreviations/Acronyms and Glossary..................... 49 Abbreviations/Acronyms .............................................................................49

Master Controller Requirements Specification for Perfect Power Systems, Rev. 3 Page v

Glossary ......................................................................................................50

B. Appendix: Scenarios for Requirements Development................ 56 List of scenarios ..........................................................................................56 “Emergency Response” – Response to emergency loading conditions on the

supply system.......................................................................................57 “Dynamic Price Response” – Response to dynamically changing prices ......60 “Demand Bidding to Sell Services” – Selling services to the supply system.64 Incorporating Environmental Values into Decisions for Microgrid Operations66 Forecasting Microgrid Load and Generation Profiles ...................................67

Daily Load Profiles............................................................................. 68 Including local renewable generation in the load forecasts ................. 69

Determining and Implementing the Day-Ahead Operating Plan ...................71 Daily Objective Functions .................................................................. 72 Normal Mode Constraints................................................................... 73 Developing the Day-Ahead Operating Plan ........................................ 74

Implementing the Daily Operating Plan (Real-Time Adjustments and Optimization) .......................................................................................76

Responding to a Supply System Disturbance ...............................................77 Island Operation Control .................................................................... 79 Resynchronizing with the Supply ....................................................... 81

Operator Changes to Default Settings ..........................................................82 Response to Contingencies within the Microgrid (e.g. loss of generator)......82

Normal Mode...................................................................................... 82 Island Mode........................................................................................ 83

Missing Data or Lack of Communications ...................................................83 Black Start ..................................................................................................84

Grid Connected................................................................................... 84 Island Mode........................................................................................ 84

Master Controller Requirements Specification for Perfect Power Systems, Rev. 3 Page vi

Figures

Figure 2-1 Microgrid Architecture...........................................................................................8

Figure 3-1 Overall View of Inputs and Outputs ...................................................................19

Figure B-1 Information Flows for the Master Controller Responding to Emergency Conditions.............................................................................................................60

Figure B-2 Information Flows for the Master Controller Responding to Dynamically Changing Prices .............................................................................64

Figure B-3 Information Flows for the Master Controller Participating in Demand Bidding..................................................................................................................66

Figure B-4 Examples of Daily Load Curves (Normailized).................................................68

Figure B-5 Example of a Daily Solar and Wind Generation Profile for West Texas Plains .....................................................................................................................70

Figure B-6 Illustration of Variability in Solar Generation for a Summer Day....................71

Figure B-7 Information Flows for the Master Controller Determining Daily Operating Plans.....................................................................................................72

Figure B-8 ITIC Sensitivity Curve as Default for Detection of Supply System Disturbances..........................................................................................................78

Master Controller Requirements Specification for Perfect Power Systems, Rev. 3 Page iii

Citations This report was prepared by

EPRI for The Galvin Electricity Initiative 3412 Hillview Avenue Palo Alto, CA 94304

Project Manager C. Gellings

Authors Angela Chuang, EPRI Mark McGranaghan, EPRI Solutions Mack Grady, University of Texas at Austin

Acknowledgments

This document was informed by guidance from technical and market experts who participated in the EPRI workshops on Master Controller Specifications held in August and September 2006. The authors would like to thank:

David Cohen, Infotility Dave Crudele, EPRI Solutions Roger Dugan, EPRI Solutions Terrance Heng, software consultant Roger Gale, GF Energy Frank Goodman, EPRI John Kelly, Gas Technology Institute Jean-Louis Poirier, GF Energy James Reich. Palo Alto Research Center

This report describes research sponsored by The Galvin Project, Inc.

The report is a corporate document that should be cited in the literature in the following manner:

Master Controller Requirements Specification for Perfect Power Systems (as outlined in the Galvin Electricity Initiative), Revision 3, EPRI, Palo Alto, CA, and The Galvin Project, Inc., Chicago, IL: February, 2006.

Master Controller Requirements Specification for Perfect Power Systems, Rev. 3 Page iv

Preface Why Are the Capabilities of a Master Controller Needed?

Spurring industry development of a power system that does not fail (Perfect Power) is the goal of the Galvin Electricity Initiative. One of the critical technologies that enables such a Perfect Power system is a master controller, by which customer preferences for electricity utilization can be expressed and automatically implemented in a no-fail power system.

The master controller accommodates varying customer needs and preferences for electric service by coordinating the operation of various components within microgrids—which are local power systems that feature distributed (on-site) power generation, such as internal combustion engines or solar cells, and energy storage such as batteries. To advance the efficiency of electricity utilization, the master controller coordinates the integral operation of microgrids within the physical power grid, considering latest grid and market conditions.

Other aspects of the master controller that enable perfection from the end-use customer’s point of view include:

< Configurable priority of service for loads, which allows for perfection per customer selection

< Capture of customer contractual arrangements to model varying subscriptions for electric service with electricity suppliers

< Configurable user interface (UI) that allows customer preferences to change over time

< Consideration of market opportunities and other alternatives for energy supply

< Ability to select electricity utilization objectives (e.g., service level, price point, environmental considerations)

Designing a power system that does not fail requires distributed intelligence for “fail safe” operation that continues to supply critical loads in the event of any contingency condition, either inside or outside the microgrid. Essential to this design is a grid connection, since combining the microgrid system and the conventional power grid achieves both increased reliability and allows optimization of the economics of operating the distributed generation and storage, as well as intelligent load controls.

Master Controller Requirements Specification for Perfect Power Systems, Rev. 3 Page v

With the dual objectives of reliability and optimized economics, the master controller is critical. The master controller coordinates the elements of the microgrid along with the connection to the supply system to improve the reliability (by looking ahead at possible contingencies and optimizing the configuration to minimize the risk) and to achieve the most economical operation possible (by coordinating the microgrid generation and loads with prices and market opportunities from the supply system). In addition, the master controller provides the interface that allows the microgrid operator and the customers within the microgrid to monitor and manage the system.

Although initial demonstrations of important concepts that are integral to the proposed microgrid configuration have been achieved, a fully functional master controller as described in this functional design does not yet exist. Industry experts consulted as part of the Initiative anticipate it could be developed within 3 to 5 years, with a relatively modest industry investment, if important foundations that would enable the master controller software are developed first.

Most importantly, information exchange models need to be developed for the interfaces between the master controller and other critical elements of the microgrid:

< Interface between the master controller and the supply system. Here, the supply system represents the electrical grid that supplies the microgrid as well as the commercial markets for electricity that the microgrid will be part of.

< Interface between the master controller and the local generators and storage devices within the microgrid. These interfaces will allow optimizing the operation of the local generation and storage in combination with supply conditions, market conditions, and load controls.

< Interface between the master controller and the load controllers. The load controllers could be building energy management systems or other load interfaces that permit control and management of loads in response to electricity prices, supply risks, local generation conditions, and load priorities.

< Interface between the master controller and the fast switch (solid state breaker). This can isolate the microgrid from the supply system virtually instantaneously in the event of a problem with the supply system. The master controller will enable reconnection to the supply based on an assessment of the quality of the supply and the local generation/load conditions.

Master Controller Requirements Specification for Perfect Power Systems, Rev. 3 Page vi

This document provides the initial functional requirements for the master controller that can serve as the basis for more detailed information model development. Development of the information models as an open industry effort and coordination of these models with industry standards will provide the basis for commercial development of the master controller, as well as the distributed controllers for generators, storage technologies, loads, and fast switches. These functional requirements are the first step in the path to the Perfect Power System. The next step is development of the detailed information models that will form the basis of commercial controllers and actual implementation of the proposed microgrid configuration.

Master Controller Requirements Specification for Perfect Power Systems, Rev. 3 Page 1

Master Controller Requirements Specification for Perfect Power Systems (as outlined in Galvin Electricity Initiative)

1. Introduction

1.1. Purpose This document describes requirements for an innovative intelligent device identified under the Galvin Electricity Initiative to be a key technology enabler for realizing a “Perfect Power System.” The device is the microgrid master controller. The microgrid is the portion of the power system that achieves enhanced reliability and power quality (perfect power) through the combined use of local generation and storage sources, power conditioning, responsive load, and connection to a conventional power grid. The master controller provides the overall control that coordinates the set points for the individual generation and storage devices in the microgrid and provides the interface to the electricity supply grid for participation in energy markets and coordination of response to conditions in the electricity supply system.

The master controller considers economic, environmental, comfort and other end-use objectives as well as physical and regulatory constraints to help automate and optimize day-to-day customer decision-making on electricity utilization. While many of the capabilities identified for the intelligent device are being researched and developed today in various microgrid R&D activities around the world, many other capabilities do not yet exist and are also identified as enablers in the path to the Perfect Power System. This report describes some of these additional capabilities as they are required for the master controller to achieve the objectives of the Galvin Perfect Power System.

The master controller specified here enables perfection perceived from the end-use customer point of view. Such a perspective accommodates varying customer needs and choices for electric service, such as varying needs for service quality and reliability. Technically perfection is the absence of failure. Galvin Electricity Initiative team members have defined failure as not meeting explicit commitments commercially in place with all customers 100% of the time. This definition extends beyond measuring perfection against meeting customer expectations, but requires considering commercial information pertinent to microgrid operations.


The master controller must operate cognizant of relevant commercial parameters like utility tariffs, energy market conditions, and prices from alternative sources of supply. Such commercial-type information typically originates outside of the physical microgrid. The information can be made available to the master controller through Internet-based information feeds or manual user entry of relatively static data. In coordinating microgrid operations, the controller must not only differentiate end-user preferences but also end-use characteristics to achieve perfection in customer utilization of electric service. Section 2 provides an overview of the various components and aspects of the microgrid controller that enable the described concept of perfection to be realized.

The master controller operates within an end-use electric subsystem connected within the utility distribution system. The master controller provides the interface between the elements of the microgrid and the supply system (see Figure 2-1 in Section 2). The master controller coordinates with “slave controllers” to manage important elements of the microgrid, namely:

< Local generation sources.

< Storage devices.

< Responsive load.

< Smart switch controls.

Together, these elements of the microgrid assure continuous supply to critical loads while achieving economic operation of local generation, storage, and responsive loads.

Section 3 summarizes functional requirements of the master controller. Primary functions are described in terms of information requirements, decision-making or information processing requirements, and user interface issues for presenting information and setting up parameters of the master controller. Section 4 describes non-functional requirements including interface requirements, communications, and software quality attributes.

1.2. Intended Audience and Reading Suggestions The intended user of this document is a technical evaluator for a company that is considering implementation of a master controller in a Perfect Power System featuring a microgrid. The reader is assumed to have an engineering background or is familiar with reviewing software requirement specifications. The reader is also familiar with common units of measures for electric power and other forms of energy. He/she is assumed to be comfortable with electric power system and power market terminology or has glossaries available for reference. A glossary is also provided in Appendix A of this document.


The suggested reading sequence is to begin with the overview sections that provide relevant background on the scope and novel elements in the specification. Before proceeding to functional requirements details in Section 3, the reader is advised to review the microgrid operating scenarios in Appendix B of this report. The scenarios provide specific examples of applications that the functional requirements are intended to address.

1.3. Project Scope This document provides functional requirements for an innovative microgrid master controller designed to enable a “Perfect Power System”, as defined in Section 1.1. The scope of this report and how it furthers existing microgrid research is described below.

1.3.1. Advancement of Microgrid Research

The concepts of microgrids that have been developed in previous and ongoing research efforts provide a foundation for the master controller functional specifications provided here. In particular:

< The European MICROGRIDS project investigated operation and control issues for local microgrids, especially under islanded operation. Centralized and decentralized control techniques, based on agent technologies, present the microgrid to the grid as a controlled entity that is operated as a single aggregated electricity load. Given attractive remuneration, it can support the network, providing services such as a small source of power or ancillary services, when required or when market conditions favor it. From the customer’s point of view, microgrids provide both thermal and electricity needs and, in addition, have the potential to enhance local reliability. Preliminary studies were performed on an actual demonstration microgrid that consisted of microturbines, wind turbines, fuel cells and photovoltaic cells.

< In the DISPOWER project (also part of the European Framework 5 research), a power quality (PQ) management algorithm was developed that is able to solve voltage limit violations in low-voltage grids by optimizing control of generators, storage units and controllable loads. The algorithm automatically adapts its behavior in the light of network performance by changing its frequency of scheduled tasks and sensitivity limits without requiring triggering by external control. A demonstration project showed the voltage control benefits that can be achieved with this controller.

< The CERTS Microgrids project developed a new control strategy for microgrids that is based on a “plug and play” concept where local


controllers operate in a peer-to-peer manner to make decisions about operating conditions at each local generator (“SmartSource”) and at the switch between the microgrid and the supply system (“SmartSwitch”). The idea is that the system can operate without the loss of any component in the system because all critical decisions are made locally by the local controllers.

The microgrid concept for the Galvin Perfect Power System builds on this fundamental research by adding a master controller to the microgrid that can provide a number of critical functions to enhance the overall reliability, power quality, and economic operation of the local power system. This document focuses on the requirements of the master controller.

1.3.2. Functions Described in This Report

Section 2 provides a system-level description of the microgrids concept for the Galvin Perfect Power System. Key functional components of the master controller are identified in Section 3. Functions address a broad range of services to be supported in a perfect power paradigm. These services may include providing ancillary services for sale in electricity markets and optimizing the level of “green power” given latest fuel prices and other economic considerations on end-use.

This report primarily describes the master controller functions identified as highest priority by the Galvin project team. Functional requirements that are critical for enabling perfection are included. The coordination of master controller functions with the requirements of local (slave) controllers is also described. Note that slave controllers (e.g., slave controllers for generators and for the switch between the microgrid and the supply system) are assumed to operate according to detailed principles developed in prior research programs as described in [Reference 3]. These principles assure reliable operation and fast response to disturbances. The slave controller concepts are expanded in the Galvin Perfect Power Microgrid to include a controller for storage elements and a controller for local loads that can provide load dispatch and notification functions.

Two primary classes of functions are identified: 1) microgrid reconfiguration according to conditions, as well as 2) functions related to the economic, environmental, and customer comfort objectives. The main objective of the Galvin Perfect Power System is enhanced reliability and quality to assure 100% availability of electric service to critical customer processes and loads. The master controller helps enable this availability by controlling operating points of microgrid resources (i.e., generators, storage units, and responsive loads). The operating points determined by the master controller assure supply of quality power to critical loads and processes, taking into account actual and potential contingency conditions. Actual response to disturbances is achieved at the slave controller level due to the speed of response required. So the first class of master controller functions supports


management of the microgrid for reliability and quality in multiple configurations that occur in response to system supply and local microgrid conditions. The second class of functions for the master controller considers economic, environmental and end-use comfort objectives and adjusts operating conditions accordingly. The master controller supports both classes of functions to achieve overall customer utilization objectives.

Each function specified in this report includes a basic description, identification of inputs and outputs, and default actions of the function. Diagrams are also provided to collectively illustrate information exchanged between the controller and other components of the microgrid. The various types of information exchanged by the master controller at the interface with the supply system, microgrid resources, and users, respectively, are categorized and depicted in Figure 3-1 of Section 3.

1.4. References The concept of enabling perfect power at utility substations has been previously investigated by EPRI as described in [References 7 and 8] below. A substation controller was specified in [Reference 8] to provide uninterruptible delivery of power from a substation. The UPS Substation™ controller delivered uninterruptible power through advanced substation control and management, unlike the Galvin Perfect Power System which takes a customer-centric perspective over electricity management.

In Reference 1, EPRI examines requirements to advance the efficiency of electricity utilization by end-use customers. The paper describes four required building blocks: innovative markets, innovative regulation and rates, advanced communications, and smart end-use devices. The master controller accommodates each of these building blocks through functions that support demand-side market participation, dynamic pricing, and innovative rate structures. The master controller can also provide price and dispatch signals to smart end-user devices and may leverage advanced communications to interface with the supply system and microgrid resources.

Prior work referenced above as well as other relevant research referred to in this report are listed below.

1. Advancing the Efficiency of Electricity Utilization: “Prices to DevicesSM”, Background Paper, 2006 EPRI Summer Seminar, EPRI, Palo Alto, CA: 2006. Publicly available at www.epri.com.

2. CERTS Energy Manager Design for Microgrids, Consultant Report, California Energy Commission: Sacramento, CA: March 2005, CEC500-2005-051.


3. Control and Design of Microgrid Components: Final Project Report, Power Systems Engineering Research Center, University of Wisconsin-Madison, Madison, WI: 2006.

4. Autonomous Control of Microgrids, Paigi, Paolo and R. Lasseter, IEEE PES General Meeting, Montreal, June 2006.

5. Distributed Generation With Heat Recovery and Storage, Siddiqui, Afzal S., Chris Marnay, Ryan M. Firestone, and Nan Zhou, LBNL-58630, July 2005

6. MicroGrid Design, Development. and Demonstration, Bose, Sumit, presentation at the Office of Electricity Delivery and Energy Reliability Electric Distribution R&D FY06Annual Program and Peer Review, San Ramon CA, 25-26 May 2006. (Available at http://www.energetics.com/meetings/electricdist06/pdfs/Bose.pdf)

7. MicroGrids: Large Scale Integration of Micro-Generation to Low Voltage Grids WorkPackage C, Deliverable_DC1 Part 1, MicroGrid Central Controller Strategies and Algorithms, European Commission: 2005, Contract Number ENK5-CT-2202-00610.

8. MicroGrids: Large Scale Integration of Micro-Generation to Low Voltage Grids WorkPackage C, Deliverable_DC1 Part 2, Software Description, European Commission: 2004, Contract Number ENK5-CT-2002-00610.

9. SCE’s Preliminary AMI Requirements, SCE’s Advanced Metering Infrastructure Program, Southern California Edison, Rosedale, CA: 2006. Available via www.sce.com/ami.

10. UPS SubstationTM: Evaluation, Conceptual Design and Generic Specification, EPRI, Palo Alto, CA: 1999. TR-111091.

11. UPS SubstationTM: Control System Feasibility Evaluation, EPRI, Palo Alto, CA: 2000. 000000000001000002.

12. Cell Architecture for Distributed Generation Management for the Danish Electric Power System, Per Lund, et al.

13. A Collaborative Operation Study of Hybrid New Energy Type Dispersed Power Supply System, M. Kobayashi et all, 2006 IEEE PSCC Conference, Atlanta, Ga.


14. Microgrids:Large Scale Integration of Microgeneration to Low Voltage Grids, Nikos Hatziargyriou, Nick Jenkins, Goran Strbac, Joao Abel Pecas Lopes, Jose Ruela, Alfred Engler, José Oyarzabal, George Kariniotakis, Antonio Amorim, Special Issue of DER Journal, 2006.

15. Microgrids: An Overview of Ongoing Research, Development and Demonstration Projects, Nikos Hatziargyriou, Hiroshi Asano, Reza Iravani, and Chris Marnay, Power and Energy Magazine, December 2006.


2. Overall Description

2.1. Overview of Microgrid Architecture The microgrid architecture for the Galvin Perfect Power Microgrid is illustrated in Figure 2-1.

Figure 2-1 Microgrid Architecture

The main elements of this architecture are described briefly here to put the role of the master controller in perspective with other elements of the microgrid.

2.1.1. System Controller

The overall system controller may involve multiple levels of control but, for purposes of the master controller specification, we can consider it as the next level of control above the microgrid master controller. For instance, for a master controller that is located on a local distribution system, the system controller could be a combination of a distribution management system (DMS) and Internet resources for other information. It has the role of providing information needed by the master controller to make economic decisions for microgrid operation and to manage the operation of the overall power supply system.


Specific functions and information flows at this level include:

1. Manages the overall system performance (optimization, reliability, and security). This is done with information from master controllers on the system, as well as information from other power system elements (automated elements throughout the power system).

2. Provides information to master controller about overall system conditions and needs.

a. Electricity and gas price information (real time and day ahead).

b. Needs for ancillary services (reactive power, voltage support).

c. Emergency conditions (required load reduction or generation support).

3. Gets information from the master controller about existing and expected conditions within the microgrid.

a. Load characteristics.

b. Reactive power characteristics.

c. Power quality characteristics (harmonics, load variations).

d. Load forecast.

e. Controllable load and generation.

f. Economics of load and generation control available (including factors such as green credits, etc.).

g. Storage condition and availability.

h. Power conditioning equipment within the microgrid and characteristics.

2.1.2. Microgrid Master Controller

The microgrid master controller is the main focus of this functional requirements document. The master controller provides the local control function for optimizing performance of the microgrid and for interfacing with the system controller.

1. Provides interface between the system controller and the individual loads, generators, storage, and power conditioning equipment within the microgrid.


2. Provides the local optimization function for the loads, generation, storage, and power conditioners within the microgrid based on economics of local vs. system conditions. This control is implemented by providing set points for individual generators, storage devices, and responsive loads.

a. Cost of electricity.

b. Cost of gas.

c. Local generator characteristics and availability.

d. Local load response available.

e. Storage conditions.

f. Green credits and other environmental factors.

3. Provides monitoring and control functions for real-time conditions.

a. Monitoring and status of loads, generators, power conditioning, static switch.

b. Evaluation of conditions with respect to expected conditions.

c. Risk assessment functions – the master controller is continually evaluating both existing and possible conditions and choosing operating points for local devices to assure required reliability and power quality.

d. Adjustments to control signals based on optimization functions and risk assessment functions (different optimization functions for normal operation with supply from the grid and island operation when isolated from the grid supply).

e. Adjustments in control settings based on information from system controller (new prices, emergency conditions).

f. Alarms.

4. Provides information to the system controller.

a. Status of microgrid loads and generation.

b. Forecasts for microgrid loads and generation (may be in the form of forecasts vs. costs based on optimization functions and expected conditions).

c. Availability of load modification during system disturbances (e.g. load reduction in response to system load curtailment requirements).


5. Gets information from the system controller.

a. Prices.

b. Forecasts of system conditions.

c. Specific needs for support (reactive power, voltage control, load reduction, capacity reserves, and other forms of system support).

d. Environmental conditions – weather conditions and forecasts, historical weather conditions, lightning detection network, etc.

e. Emergency conditions.

6. Provides interface for users (microgrid operator, end-use customers, etc.) to review conditions in the microgrid.

a. Summary of existing conditions.

b. Summary of economics (e.g. monthly, weekly report).

c. User selected preferences for optimization and risk assessment functions.

d. Differentiation between master controller information requirements and overall information requirements of a communications gateway at the customer premise. This gateway is referred to by the Electric Power Research Institute as a “consumer portal.”

e. Status alarms.

The description above outlines some information requirements to achieve the desired functionality. The master controller must also deal with uncertainty and the potential for erroneous data as part of information processing. The master controller must have default data for cases where information is not available and error processing functionality to identify potentially bad data that could result in erroneous responses. User preferences can be used to define default responses that assure the integrity and reliability of the system operation. Some initial guidelines for default data and responses are outlined for the different operating modes in Section 3. In general, default responses will be designed to assure safe operation (number one) and reliability (Perfect Power System concept – number two).

2.1.3. Slave Controllers

The slave controllers in the Galvin Perfect Power System microgrid architecture are critical for maintaining the reliability of the overall system. These controllers operate on principles that have been developed in the CERTS microgrid research and are


currently being demonstrated at American Electric Power (AEP), a large electric utility that serves 11 states.

There are four kinds of slave controllers in the Galvin microgrid:

1. Local generators. These are the primary type of slave controller conceived in the CERTS research. This type of slave controller is referred to as a “SmartSource” in the CERTS research. The generator controller response to disturbances is basically the same regardless of the type of generation but the generator controller interface to the master controller will be somewhat different for different generation technologies:

a. Microturbines, gas turbines, fuel cells operating as combined heat and power (CHP) units.

b. Microturbines, diesels, gas turbines, fuel cells without CHP.

c. Photovoltaics (extension to the basic model).

d. Wind turbines (extension to the basic model).

2. Storage devices. Energy storage devices are a critical element of the Galvin Perfect Power System microgrid. They help provide ride through during transition conditions and provide power to loads during generation shortages. The slave controller determines the short term requirements of the storage devices operating in a power conditioning mode and coordinates with the master controller for maintaining storage capacity.

3. Loads. Loads are controllable in Galvin Perfect Power System model. The load controller provides information to the master controller about the load/price relationship and the availability of load for curtailment in emergency conditions. Loads can be characterized with multiple levels of importance for prioritizing during emergency conditions and island conditions. This helps assure 100% availability for critical loads and processes.

4. Microgrid switch or breaker. In the Galvin microgrid, this switch will be a solid state switch to allow essentially instantaneous disconnection from the grid during disturbance condtions. The control for this switch is also developed in the CERTS research (“SmartSwitch”). The slave controller for the solid state switch will operate the switch based on pre-defined criteria regarding the quality required by the microgrid loads (e.g. the ITIC curve). This controller also coordinates the


resynchronization function when connecting the microgrid back to the supply.

Some general functions of the slave controllers are summarized here.

< Controls for individual loads, generators, storage devices, solid state switch.

§ The response to instantaneous changes in supply conditions is accomplished in the slave controllers so that a new stable operating point is achieved.

§ Value relationships for different loads must be understood.

§ Cost functions for generators and storage.

§ Functions for CHP economics.

< Accept set point information from master controller for desired operating point.

§ Set points for normal operation with supply from the grid.

§ Set points for emergency conditions.

§ Set points for operation in islanded mode.

< Respond to real-time conditions based on established control algorithms.

§ Power vs. frequency curves.

§ Voltage vs. reactive power curves.

§ Emergency control signal.

§ Changing set point.

< Provide voltage, current, power, reactive power, set point, etc. to master controller.

2.1.4. Other Sensors and Transducers

The master controller will also take advantage of other monitoring around the system. Some important signals will include:

< Microgrid power and reactive power.

< Microgrid power quality parameters (based on voltage and current monitoring).

< Temperature and other environmental conditions.

< Actual voltages, currents, power, reactive power at:


§ Loads.

§ Generators.

§ Storage devices.

2.2. Operating Modes for the Master Controller The master controller has three main OPERATING MODES that are the basis of the functional requirements definition in this document:

1. MODE 1 – Normal operation connected to the supply grid. In this mode, the master controller is performing optimization functions to continuously determine appropriate set points for the individual generators, storage elements, and loads in the microgrid. The set points are determined based on a combination of two factors:

a. Reliability considerations (predictive function to make sure that microgrid is able to respond to system contingencies – storage, status of generators, load conditions).

b. Economics of local generation and loads vs. grid supply.

c. Combined heat and power needs for the local system.

2. MODE 2 – Emergency operation connected to the supply grid. In this mode, normal economic optimization functions cannot be used and are replaced by override functions that are designed to balance the local reliability needs and the needs of the supply system during emergency conditions. The response will depend on the needs of the supply system as expressed by either economic penalties or specific load reduction requirements. The response can include: changing generator conditions, reducing load, or actually disconnecting from the supply system (move to Mode 3 described below).

3. MODE 3 – Operation in island mode. In this mode, the supply grid is not available or there are quality/reliability problems with the grid supply. The master controller is optimizing the set points for generators, storage devices, and loads based on reliability considerations during this condition. This will also take into account information from the supply (if available) regarding expected future conditions of the supply (e.g. how long will the supply problems last).

The master controller switches between these modes based on local and supply system conditions.


Besides the actual operating modes, the master controller is also performing a continuous monitoring and diagnostics function to make sure that slave controllers and other system elements are operating properly. This includes:

< Comparing overall power levels (real and reactive power) with desired levels – comparisons to projections for system conditions.

< Loads – load conditions with respect to projected conditions and targets.

< Generators – generation conditions with respect to target values.

< Storage devices – available capacity compared to expected capacity.

< Supply conditions – based on information received from the supply system, the master controller tracks prices and other parameters with respect to expectations.

< Environmental conditions – some environmental parameters are used in the master controller functions (e.g. temperature, storm conditions, etc.). These are monitored with respect to projected conditions.

2.3. Operating Environment and Other Assumptions An underlying assumption is that the master controller is set up in an operating environment that facilitates automated response to latest supply system conditions. By default, user settings are configured to enable automated response of local resources, power conditioning equipment, and end-users to actual system and market conditions. The master controller coordinates the response in an optimized fashion by establishing set points for slave controllers and determining day-ahead dispatch schedules for resources. The user may override master controller default settings during times a manual response is preferred.

It is anticipated that the master controller would be implemented in a computing architecture that is compatible with Internet protocol (IP) connectivity. Common communication protocols and standard information models for slave controllers are also anticipated. IP connectivity is assumed independent of actual physical communication media. The communications media may include a combination of wireless, Ethernet, cable, or broadband over powerline (BPL) technologies that accommodate communications with the supply system, slave controllers, users, and individual resources. The microgrid communication infrastructure is likely to accommodate a wireless communication standard such as Zigbee, Z-Wave, or Wi-Fi for flexibility, but could also accommodate hardwire local area network (LAN) connections or powerline carrier (PLC).

Other assumptions are described below.


Communication availability – network connectivity to supply system information and within the microgrid is assumed. This allows communications with the supply resources and the slave controllers using standard network communication protocols (e.g., IPv6).

Monitoring within the microgrid – the master controller will have access to the microgrid metering information and other monitoring information as needed through appropriate network connectivity and defined information models and protocols.

Information available from the supply system – it is assumed that supply system information and environmental conditions will be available from appropriate network connections (e.g., web sites). This information will include market conditions, supply system constraints, and environmental conditions like temperature and humidity, weather forecasts, lightning conditions, etc. In addition, fast notification of emergency conditions via appropriate communications protocols is assumed.

User interface – The master controller user interface (UI) allows designation of user preferences and characteristics of physical resources located within the microgrid. Preferences for electric service reliability are expressed within the UI by ranking load priority orders among end-uses. Information sources that provide economic information on supply system conditions, fuel costs for local generation, and other operating economics and constraints are also configured via the UI. An underlying assumption is that by default, user settings are configured to enable automated response of resources, switches, and loads to latest system and market conditions.

While appropriate interfaces are assumed for information resources, it is important to emphasize that the system must accommodate the lack of information at any time and be able to operate in default modes that assure the system reliability and integrity. The master controller must use resource models and user preferences to determine system configurations and settings when limited information is available. In a similar way, local slave controllers must be able to operate in default modes that assure system integrity when information is not available from the master controller.


3. Description of Master Controller Functions The master controller for the Galvin Perfect Power Microgrid System provides the overall control and optimization functions for the microgrid. The system operates on the basis of distributed intelligent slave controllers that perform the very fast control and protection functions without direction from the master controller. This assures that the system operates properly and safely even without ongoing communication with the master controller. The master controller also serves as the interface with the grid supply system, providing decision support on microgrid participation in markets and other demand-side opportunities. Optimization functions support economic operation of various elements of the microgrid including local generation, responsive load, and storage resources.

This section describes in general terms the main functions required of the master controller. The functions described in this section support microgrid operations under the scenarios provided in Appendix B, which were written with particular attention to the required actions of the master controller.

Note that the functions described in this section are not all equal in priority and that a prioritization of functions will be an important initial task in the detailed design effort. The prioritization will permit cost-benefit assessments to be performed in terms of the actual implementation requirements associated with each of the functions. Based on this analysis, specific functions may be deferred to a future development of the master controller. At this stage, functions associated with assuring the reliability of the overall system operation (achieving the Perfect Power System) shall receive the highest priority in implementation. Functions related to optimization of performance can be evaluated with respect to the associated economic benefits that can be achieved (e.g. energy efficiency, responding to real-time prices, etc.). Functions related to safety have the highest priority (even more important than reliability functions).

As described in Section 2, the master controller has three primary modes of operation:

< Normal mode.

< Emergency mode.

< Island mode.

The specific operating mode of the master controller at any given time is determined by conditions external to the microgrid. For example, emergency conditions in the supply or a disturbance in the supply system may require microgrid operation in island mode.


Functions of the master controller are described below as part of one of the three operating modes or as independent of operating mode. Optimization functions are included in all three modes. Most of the functions related to the commercial operation of the microgrid are associated with the normal mode, in which the microgrid is optimizing resources based on market conditions. Market conditions are also considered for emergency response when emergency conditions are defined by pricing incentives, as in the case of a critical peak pricing (CPP) event.

Each function below is described by its primary inputs, outputs, processing requirements, and default actions. Figure 3-1 collectively illustrates information inputs and outputs of the master controller.


Figure 3-1 Overall View of Inputs and Outputs

3.1. Optimization Functions in Mode 1 – Normal Operation

Connected to the Supply System The steps taken to determine optimal operating plans given overall economic, environmental, and customer comfort objectives are described in this section.


Functions required for optimization and decision support under normal operation mode are identified. Constraints are processed and respected in the master controller’s optimal utilization planning. Associated functions handle all types of information (physical, commercial, regulatory, and user preferences).

In the normal mode, the master controller is performing optimization functions to continuously determine appropriate set points for the individual generators, storage elements, and loads in the microgrid. The set points are determined based on a combination of factors, including:

< Reliability considerations ? This entails a predictive function to make sure the microgrid is able to respond to system contingencies (e.g., based on storage, status of generators, and load conditions).

< Economics of local generation and loads versus electricity prices from grid supply.

< Combined heat and power needs for the local system.

3.1.1. Microgrid Economic Optimization (Operating Schedule and Continuous Optimization)

Description

This function uses models representing individual economic characteristics of microgrid resources to determine appropriate set points for each resource. Economic models are provided by slave controllers and/or by user specification for individual microgrid resources (i.e., local generators, storage, and responsive loads). The economic model for grid supply is also available (e.g., expected daily hourly prices for electricity). These models provide latest economics and forecasted economics for individual resources. The master controller considers the combination of individual resource economics to determine the appropriate set points and operating points for each component of the microgrid.

This function responds to changes in load conditions, generator economics or availability, and supply conditions to adjust the optimized operating plan accordingly.

Inputs

< Load economics (determined from load economics calculator and forecaster function) – load requirements versus price over the period of the day.

< Generator economics (determined from the microgrid generator economic calculator and forecaster function) – generator availability versus cost over the period of the day, including alternative fuel costs and heating/cooling requirements for the microgrid.


< Renewable generation availability forecast.

< Storage economics (determined from the storage economics function) – storage availability versus cost over the period of the day.

< Reliability manager constraints – this determines a minimum amount of generation and storage that must be available to minimize risk and assure that the system can successfully go to island mode.

Output

Operating plan for load, generator, and storage set points that is continuously adjusted based on actual and projected conditions. These set points and schedules are provided to load controllers, generator controllers, and storage controllers for operation of the microgrid.

Default (Missing data, bad data, or loss in communications)

A default operating plan based on typical operation for the day of the week is used when information from any of the specific sources is not available (e.g., missing supply pricing schedule). Default operating plans are also used by slave controllers in the event of communication loss with the master controller. The default operating plan maximizes the reliability priority to make sure that generation and storage is available for system contingencies.

3.1.2. Load Economics Calculator and Forecaster

Description

Determine the load economics function for the forecast period and update this function based on actual conditions. The function must calculate the load value vs. time and load level. This will be based on user preferences for specific portions of the load and the load profiles for those portions of the load.

The load controller will be the interface to a variety of different load devices. Each of these devices can have a specific load profile vs. cost characteristic. Some of the functions will be simple on/off functions. Other functions can be more complicated, like an air conditioner where the value can be a function of the temperature set point and the load profile is derived from the set point and external temperature conditions.

Inputs

< Set-up information about the specific loads interfaced with each load controller and the default load profiles as a function of electricity cost for each element.

< Historical profile data for the different load elements (as a function of electricity cost).


< Historical temperature/humidity data for correlation of heating/cooling load with environmental conditions.

< Actual load information from the load controllers – expected load profile as a function of electricity price and actual conditions sampled on one minute intervals.

Outputs

Consolidated load profile vs. electricity price as a forecast for the day and updated based on actual conditions.


Default load economics provided by user.

3.1.3. Microgrid Generation Economics Calculator and Forecaster

Description

Determine the economics of operating the microgrid generators as a schedule and based on actual conditions. The function must take into account costs of fuels for the local generation, basic operating economics, and heating/cooling needs for the microgrid for the CHP portion of the generation. This function does not address the availability of renewable generation – forecasting the available renewable generation is handled separately. The function calculates the generator economics as a generation availability vs. cost function over the forecast period.

Inputs

< Mapping of generators connected to each generator controller (slave controller) – set-up information.

< Default economics of generator operation for each unit.

< Temperature/humidity forecasts for use in calculating heating/cooling needs.

< Projected alternative fuel costs for adjusting the generator unit economics and for calculation of alternative heating/cooling costs.

< Actual generator availability vs. cost profile from slave controller (updated based on actual conditions).

Outputs

Consolidated profile of generator availability vs. cost as a forecast for the day and updated based on actual conditions.



Default generator economics provided by user.

3.1.4. Renewable Generation Calculator and Forecaster

Description

The renewable generation (photovoltaics, wind, possibly biomass) can be treated as a special case because we want to use this generation when it is available. However, it is important for the master controller to have accurate forecasts of this available generation so that it can be considered in combination with the economics of other generators and the load economics. This function provides the renewable generation forecast schedule and updates the schedule based on actual conditions.

Inputs

< Mapping of renewable generators connected to each generator controller (slave controller) – set-up information.

< Information needed to forecast availability of renewable generation – solar insolation forecasts, wind forecasts (forecast and actual).

< Information from generator controllers on actual conditions of the renewable systems.

Outputs

Schedule (forecast and updates) of renewable generation availability.


Default renewable generator profile based on historical data (initially input by user).

3.1.5. Microgrid Storage Economics Calculator and Forecaster

Description

Determine the economics of operating the microgrid storage as a schedule and based on actual conditions. The function must take into account costs of operating the storage, including losses associated with discharging and charging as well as operating costs. The reliability manager will also be determining the required storage that must be available for system contingencies. Even though the main objective of the storage is probably for reliability, the storage may also be available for peak load management based on the costs of electricity, load requirements, etc.

Inputs

< Mapping of storage connected to each storage controller (slave controller) – set-up information.


< Default economics of storage operation for each unit.

< Actual storage availability vs. cost profile from slave controller (updated based on actual conditions).

Outputs

Consolidated profile of storage availability vs. cost as a forecast for the day and updated based on actual conditions.


Default storage economics and minimum maintained storage level provided by user.

3.1.6. Microgrid Risk Manager Function

Description

The microgrid risk management function is designed to assure that the microgrid will be able to go into island mode without any disruption to critical loads. The function continually assesses both projected and actual load levels and matches these with available generation and storage to assure that a transition will not cause the microgrid to shut down. The function can also take into account the risk of problems in the supply to increase the safety margins appropriately when problems are more likely (e.g., thunderstorm forecasts, temperature forecasts that indicate emergency conditions as possible, scheduled maintenance on the supply, etc.). Three basic objectives:

< Make sure there is sufficient storage to provide needed ride through for switching to microgrid operation and handle any generator start up required, load changes, etc.

< Make sure that generation on line or available is sufficient to handle the required load in island operation.

< Make sure that load strategy is in place according to on line and available generation and storage.

Inputs

< Actual levels and projections for load levels, generation levels, storage levels updated each minute.

< System conditions that could be important risk factors – loading conditions, possibility of reconfiguration needs, etc.

< External inputs for risk assessment of the supply – weather forecasts, lightning conditions, system condition risk level, projections of overall system supply and demand.


Outputs

Schedules for minimum requirements of local generators, storage systems, and required load management to assure reliable operation. These are provided to the economic optimization function.


Minimum generation and storage levels that must be maintained without additional information about actual loads, load management, or system conditions.

3.1.7. Microgrid Continuous Technical Performance Assessment

Description

This function uses a model of the overall microgrid (grid supply, generators, storage, loads) conditions based on the set points. This is continuously compared with actual microgrid characteristics – load conditions, generation conditions (including CHP, renewable energy, etc.), storage conditions, and supply conditions – to identify any problems with the operation.

Alarms are provided when operating conditions are outside allowable bands around expected conditions.

Inputs

< Actual operating conditions from load controllers, generator controllers, storage controllers, and the overall metering.

< Schedules for loads, generators, storage from economic optimization function.

Outputs

Summary information about actual operation compared to schedules; alarms for conditions outside of allowable bands.

3.1.8. Microgrid Ancillary Services (Reactive Power) Calculator

Description

The microgrid may be able to provide ancillary services for the distribution system or other parts of the grid that are not completely represented in the base economic functions. This could include reactive power support or harmonic filtering. This function interfaces with the system controller to accept requests or economics of ancillary services that could be used by the supply system and adjusts settings for microgrid elements accordingly. We will focus on VAR support as an ancillary service in this case – harmonics would be more complicated but would also be possible.


The master controller will perform a continuous assessment of both the real and reactive power needs and availability in the local power system. Just as with the continuous control of real power balance between local loads, generation, storage, and the supply system, the master controller can help optimize the reactive power conditions of the overall system. This is also an economic function based on reactive power penalties, characteristics of the local sources (generator reactive power functions, storage device reactive power functions, reactive power control that may be available in the load controllers, etc.), and value of reactive power to the supply system.

Inputs

< Electricity rates, including reactive power penalties. This should be part of the real-time pricing, day-ahead pricing, or basic rate structure.

< Information from the supply system that indicates a value for incremental reactive power. This would be an optional signal if there is a market for this ancillary service. This information would be included as part of the market information interface.

< Local generation cost functions that include the impact of reactive power control on the overall economics of the generator operation. Sometimes, using the generator to provide more reactive power can limit the real power available from the generator.

< Reactive power availability functions for storage devices. These devices are likely to have converter interfaces that may have reactive power control capability.

< Reactive power availability from local loads, as determined by the load controllers. Load equipment may also have reactive power control capability in a similar manner as storage devices or the loads may include actual power factor correction capacitor banks or filters that can be switched on or off.

Outputs

The VAR support function will determine the availability of reactive power support from loads, generators, and storage devices (converters) to determine a reactive support vs. economics function that can be used for responding to supply requirements or market bidding opportunities.

3.2. Optimization Functions in Mode 2 – Emergency Operation Connected to the Supply System

In this mode, normal economic optimization functions cannot be used and are replaced by override functions that are designed to balance the local reliability needs


and the needs of the supply system during emergency conditions. The response will depend on the needs of the supply system as expressed by either economic penalties or specific load reduction requirements. The response can include changing generator conditions, reducing load, or actually disconnecting from the supply system (move to Mode 3 – Island Mode). The optimizing functions that must operate in this mode are similar to the functions described in the previous sections but they have additional constraints that may be related to commercial arrangements (agreement to curtail load during emergencies) or unusual economics (e.g. critical peak pricing).

3.2.1. Microgrid Economic Optimization in Emergency Mode

Description

This function will determine the optimum operating schedule and conditions in response to emergency conditions. The emergency response function will operate in a similar manner to the normal economic optimization function but will have additional constraints based on special economics and requirements from the supply system (e.g., required load reductions).

Inputs

The inputs are the same as the normal economic optimization function in terms of the slave controllers but there is additional input from the supply system regarding the characteristics of the emergency conditions – required load to be curtailed, emergency prices (schedule), etc.

Note that the reliability and risk manager continues to operate in this mode to make sure that reliability to critical loads is not compromised.

Output

Operating plan for load, generator, and storage set points that is continuously adjusted based on actual and projected conditions. These set points and schedules are provided to load controllers, generator controllers, and storage controllers for operation of the microgrid. These are new operating points in response to the emergency conditions.

3.2.2. Microgrid Continuous Technical Performance Assessment ? Emergency Mode

Description

This function uses a model of the overall microgrid (grid supply, generators, storage, loads) conditions based on the set points. This is continuously compared with actual microgrid characteristics? load conditions, generation conditions (including CHP, renewable energy, etc.), storage conditions, and supply conditions? to identify any


problems with the operation. Note that the expected load profiles, generator profiles, and storage profiles are adjusted for emergency conditions.

Alarms are provided when operating conditions are outside allowable bands around expected conditions. These alarms may be adjusted for emergency conditions.

Inputs

< Actual operating conditions from load controllers, generator controllers, storage controllers, and the overall metering.

< Schedules for loads, generators, storage that apply during emergency conditions.

Outputs

< Summary information about actual operation compared to schedules.

< Alarms for conditions outside of allowable bands.

3.3. Commercial Functions Supporting Interface between Resources and Supply System - Configuration

These functions deal with commercial information that must be processed by the master controller to take advantage of commercial market opportunities. This section focuses on the configuration of the master controller to obtain the required information for these functions.

The functions described below support master controller operation of the microgrid under the following scenarios: emergency demand response, dynamic price response, and demand bidding to sell services to the supply system.

3.3.1. Electricity Price Forecasting Configuration (via UI)

Description

Provide ability for user to select methods and sources of information to use for forecasting prices.

Input

User entries into UI, specifying preferred forecasting method(s), information sources reporting system and market conditions to use for forecasting, and customer default tariff or retail contract.

Output

On-display confirmation that configured parameters have been registered.


Default (Invalid entry or entry out of bounds)

Reject and do not update entries. Display error message and prompt for valid input from user or exit from configuration operation.

3.3.2. Supply Alternatives Configuration (via UI)

Description

Provide ability via UI for user to specify alternative sources of supply. The master controller monitors the configured alternative supply opportunities and compares against purchases from the default provider. Supply alternatives may include bilateral electricity sales and regional markets for electricity, natural gas, or other fuels within the microgrid.

Input

User entries into UI specifying alternative sources of supply and associated information sources to monitor for latest prices and quantities available.

Output




3.3.3. Demand Bid Alternatives Configuration (via UI)

Description

Provide ability via UI for user to specify demand bidding opportunities to monitor for potential sales of services from the microgrid. Opportunities may include sale of ancillary service capacity reserves, balancing energy, local voltage support, and emergency demand response.

Input

User entries into UI specifying bid alternatives and associated information sources that report latest prices and quantities of services demanded. Bid alternative details include timing of opportunities and other bid submission rules. It is assumed that the user only configures bid alternatives the microgrid is eligible to participate in.

Output





3.3.4. Default Tariff or Retail Contract Configuration

Description

Provide ability for customer to specify commercial contract in place with its electricity service provider.

Input

User entries into UI specifying default tariff or retail contract structure. Pricing structure details may include applicable demand charges and penalty terms for failure to interrupt during system emergencies. Pricing structure details may also include quantity and price of firm service, as well as quantity and price of non-firm service commercially contracted with the default energy provider.

Output




3.3.5. Unit Economics Configuration

Description

Provide ability via UI for microgrid operator or other user to configure economic functions for loads, generation and storage units within the microgrid by which the master controller can determine the economic optimization of loads, generators, and storage in response to market conditions.

Input

User entries into UI specifying priority of service for individual loads and economics of generation and storage resources. In particular, the user inputs outage cost information or priority of service ranking for each unit of dispatchable load. The user also inputs fuel costs for each generation unit and/or specifies online information sources providing fuel cost updates. Finally, the user inputs charge-up cost for each storage unit along with any maintenance or other cost factors significantly impacting life cycle of the storage unit.


Output



Reject and do not store entries. Display error message and prompt for valid input from user.

3.3.6. Resource Characteristics Set Up

Description

Provide ability for microgrid operator to configure resource characteristics via master controller UI.

Input

User entries into UI specifying physical resource characteristics like resource capability (e.g., ramp up/down rates or charge up/down rates), predictability, equipment type, rated capacity, historic dependability, fuel type (e.g., dirty diesel, green), and emissions restrictions.

Output




3.4. Commercial Functions Supporting Interface between Resources and Supply System – Implementation

These functions deal with the actual implementation of functions that support the interface of the microgrid with the commercial market. These may also include environmental conditions and restrictions that could influence the optimization functions described previously.

The functions described below support master controller operation of the microgrid under the following scenarios: emergency demand response, dynamic price response, and demand bidding to sell services to the supply system.


3.4.1. Electricity Price Forecasting

Description

Forecast prices using preferred forecasting methods and latest reported system and/or market conditions configured via the electricity price forecast configuration function. Also updates price forecasts with latest available intraday supply system information.

Input

Live information feeds on latest system and/or market conditions on the supply system (e.g., weather, transmission system congestion, wholesale market conditions and intra-day prices). This function is also cognizant of default retail contract or tariff terms.

Output

Daily price forecasts are made available to the user through the UI or processed by the master controller to support optimization functions.

Default (System or market data missing for latest time interval)

Compute the average of the last N values received from system controller, where N and M are user configured parameters via the UI. After M consecutive intervals of missing data, alert the microgrid operator of this condition to prompt for investigation or other action.

3.4.2. Process Dynamic Pricing Information

Description

The microgrid master controller will be designed based on the assumption that prices can change dynamically (real-time pricing or RTP). This is the most flexible design configuration for the master controller. Pricing methods such as time-of-use rates, day-ahead forecasts, etc. can all be accommodated as simplified versions for real-time pricing. Therefore, the master controller must be able to process the real-time pricing information and provide it for the economic optimization function for determining the appropriate operating point for slave controllers (load controllers, generator controllers, storage controllers) within the microgrid. This information is used by the electricity cost calculator and the electricity price forecasting as well.

Input

Retail price signal received from supply system including system controller.

Output

Retail price signal to individual resources including price responsive loads. Also passes prices to customer display and relevant master controller functions like


economic optimization function, electricity cost calculator, and electricity price forecaster.

Default (Retail price missing for latest time interval)

Compute the average of the last N prices received from system controller, where N and M are user configured parameters via the UI. Pass the average price value together with indication of the estimated nature of “repaired” price. After M consecutive intervals of missing prices, alert the microgrid operator of this condition to prompt for investigation or other action.

3.4.3. Electricity Cost Calculation

Description

Provides latest estimated electricity cost based on actual metered usage and retail prices. Retail prices are determined by the default retail tariff pricing terms which may include some form of dynamic pricing.

Note that this function requires that the master controller provide a general electricity rate engine that can be configured with the appropriate electricity rates for the specific application. This can actually be a very complex task due to the tremendous range of variations in electricity rate structures from one location to another. It is beyond the scope of this specification to detail all aspects of the rate engine that would be required but it is important to note the need for the rate engine and the ability to update the rate engine based on changes in rate structures as well as the specific elements of the rates.

Input

Actual metered usage from local revenue meter, pricing per retail contract or dynamic price received from system controller. In order to compute costs for electricity this function must be cognizant of the pricing structure of the customer’s retail contract or tariff with its default electricity provider.

Output

Electricity cost estimated for time interval of user interest (e.g., day, hour, etc).


Use latest valid data and flag cost as estimated “repaired” value.


3.4.4. Electricity Cost Forecast

Description

Provides latest forecasted electricity cost based on forecasted or scheduled usage and dynamic prices or static tariffs.

Input

Scheduled or other forecasted local consumption, daily forecasted prices from applicable dynamic pricing tariffs, or forecasted peak load events, and structure of retail contract or tariff.

Output

Electricity cost forecasted for time interval of user interest (e.g., day, hour, etc).


Use latest valid data and flag cost as “repaired” forecasted value.

3.4.5. Demand Bid Opportunity Assessment

Description

Provides continuous updates on opportunities to sell services to supply system by assessing available bid opportunities among configured bid alternatives, given latest system and market conditions.

Input

Latest system and market conditions from supply system indicating market opportunities for demand-side participation.

Output

List of eligible demand-side opportunities along with any desired quantities, fixed prices, and timeframes for each opportunity as specified by the supply system. This information is provided to the economic optimization function to determine appropriate response to the opportunities.

Default (Demand-side opportunity not recognized)

If there is insufficient information from the supply system for the master controller to recognize the opportunity reported by the system controller (i.e., can not determine demand-side participation eligibility of the microgrid), then log as error and alert operator of the potential opportunity once.


3.4.6. Demand Bid Submission

Description

Considering opportunities reported by demand bid opportunity assessment and the economic optimization function, submit any outstanding bids to sell services to the supply system (e.g., market participation offers) within appropriate bidding timeframes configured in the UI via the demand bid alternatives configuration function.

Input

Schedule of available services to sell to the supply system along with identification of resource type and resources that can be offered, as determined by outcome of optimization functions.

Output

Bid submissions to the supply system. Bid prices, quantities, and schedules are submitted for the targeted opportunity along with identification of resource type and resources backing each bid.

Default (Bid rejected or not acknowledged by supply system)

Resubmit same bid if opportunity is still open. Notify operator if bid not acknowledged after R tries to resubmit, where R is configured in the UI.

3.4.7. Bid Award Notification

Description

Monitor, acknowledge, and process notification of any awarded bids received from the supply system.

Input

Bid award notification received from supply system.

Output

Acknowledgement of award sent to supply system.

Default (Receipt of erroneous bid award notification)

If bid associated with award notification is not recognized by the master controller, do not send acknowledgement to system controller upon receipt of bid award notification. Notify master controller operator of exception and manually determine a course of action.


3.4.8. Microgrid Resource Availability Update

Description

Continuously assess latest status of resources in microgrid and provide aggregated availability information to system controller. The aggregated information is sent as polled by the system controller or automatically at regular time intervals as configured by the master controller operator. Examples of resource availability includes new generation that can be brought on line, load controls that can be implemented to reduce loads, and storage that could be available for short term system support. In price-based systems, this information can be provided as resource available as a function of time and price. Note that the resource availability should include information about the resource characteristics (time to get on line, time available, other constraints).

Input

Resource status (received from slave controllers – both load controllers and generator controllers can be long term resources for the interface to the market, storage can typically be a short term resource). Characteristics of the resources from tables of information that are initially set up by the user but may be updated based on historical information.

Output

Resource availability and characteristics (to keep system controller apprised of latest resource availability from microgrid).

Default (Missing latest status data from resource)

Substitute missing data with latest time interval data received from the resource, but assume zero resource available if data is missing for more than X time intervals where X is user-configured in the UI. Notify master controller operator in the latter case.

3.4.9. Microgrid Resource Deployment Scheduler

Description

This function uses the output of the economic optimization function to actually implement the resource deployment schedule. The optimum resource schedule is going to depend on many factors:

< Market conditions and bidding actions with responses from the market on requested resources.

< Electricity prices.

< Prices of other fuels used by microgrid generating resources.


< Microgrid heating needs related to CHP operation.

< Availability of renewable resources (photovoltaic, wind, other).

< Risk assessment calculations to make sure that generation and storage is available in the event of requirement for islanding.

The master controller uses the output of functions that process these different conditions and priorities to develop a resource schedule (“normal operation”) for the microgrid resources and provides this resource schedule as information for the system controller and to the various slave controllers as set points for their operation.

Inputs

Priorities for resources and loads from market and various optimization functions.

Outputs

Resource deployment or dispatch schedules (to slave controllers of individual resources).

Default (Valid resource deployment schedule can not be determined)

Notify master controller operator of exception and utilize default resource deployment schedule based on user preferences and historical operating conditions.

3.4.10. Microgrid Resource Dispatch

Description

Dispatch individual resources within the microgrid by sending dispatch schedules or control signals to slave controllers and send notification alerts to trigger manual user action. Resource dispatch is based on optimal method determined by microgrid resource deployment scheduler. Also waits for resource acknowledgement of dispatch request and sends resulting acknowledgements to system controller or market interface.

Input

Optimal resource dispatch schedules determined by microgrid resource deployment scheduler and dispatch signals received from system controller.

Output

Resource dispatch schedule or control signals (to individual resources).

Default (Microgrid dispatch request violates operating constraints)

Flag constraints violated. Notify master controller operator of conflict. Do nothing to dispatch resources automatically.


Default (Lost communications or other connectivity with resources)

Notify master controller operator and customer housing the resource of the connectivity loss for attention and correction.

Default (Dispatch request not acknowledged by individual resources)

Resend dispatch request to resource. After a user-configured timeframe Y has elapsed without acknowledgement, notify master controller operator of potential resource failure.

3.5. Optimization Functions in Mode 3 – Island Operation In this mode, the supply grid is not available or there are quality/reliability problems with the grid supply. The master controller is optimizing the set points for generators, storage devices, and loads based on reliability considerations during this condition. This will also take into account information from the supply (if available) regarding expected future conditions of the supply (e.g., how long the supply problems will last).

Note that different utilities may have different requirements regarding islanding of power systems that are connected to the distribution system. The issue is safety of personnel who would be working on the distribution system and having the ability to assure that supply from local generation is not energizing the supply system when workers are unaware of the source. IEEE 1547 requirements and local regulations are designed to assure that these conditions do not exist. The master controller operation of local isolating switches (fast switch and isolating breakers) will be consistent with the requirements of IEEE 1547 and local utility requirements. This should not impact the reliability benefits of the microgrid configuration. In fact, the system may be designed to separate from the utility supply system for many conditions that would not actually require separation in IEEE 1547.

3.5.1. Microgrid Continuous Optimization in Island Mode

Description

This function uses a model of the microgrid components individual characteristics to determine appropriate set points for each individual component. In this case, the optimization function is less related to economics than reliability. The optimization must make sure that the critical loads continue to be supplied in the island mode. Adjustments to set points for loads, generation, and storage are made based on actual conditions and reliability assessments.

Load slave controllers have information about controllable load that can be used in emergency modes and island modes. This information is used in conjunction with generation and storage characteristics to determine island mode set points on a continuous basis.


In the initial response to islanding, the individual generator controls, and storage controls will operate according to their power vs. frequency curves to reach new stable operating points. Load controllers will have underfrequency load shedding algorithms that reduce load if necessary to reach this stable operating point. The master controller works to optimize the performance after this initial response is completed.

Note that the set points in island mode should include the settings for the voltage vs. reactive power curves and the frequency vs. real power curves for the individual generation sources to assure that the sources are operating within their proper range. This is discussed briefly here for reference.

Active power control

The basic principle that lets the generators coordinate without an explicit network that links them, is to allow the frequency at the terminal to change as a function of power demand. When two points in the network are operating at different frequencies there is an increase of active power delivery from the place at higher frequency to the location at lower frequency. As this happens, the two frequencies tend to drift towards a common value until the new steady state is reached (self-synchronizing torque).

Voltage regulation

Voltage regulation is necessary for local reliability and stability. Without local voltage control, systems with high penetrations of local generation could experience voltage and/or reactive power oscillations. Voltage control must insure that there are no large circulating reactive currents between sources. In the power grid, the impedance between generators is usually large enough to greatly reduce the possibility of circulating currents. However, in a microgrid, the problem of large circulating reactive currents is significant. This situation requires a voltage vs. reactive current droop controller so that, as the reactive current generated by the local source becomes more capacitive, the local voltage set point is reduced. Conversely, as the current becomes more inductive, the voltage set point is increased.

Like the economic optimization in the normal and emergency modes, this function uses a model of the microgrid components individual economic characteristics to determine appropriate set points for each individual component.

Inputs

< Load requirements – Critical load characteristics that must be maintained, loads available for curtailing.

< Generator availability – reliability is more important than economics so availability of generators (and costs) must be considered for maintaining the system.


< Storage availability – storage will likely be used in the island mode, as part of the transition and to help supply loads until additional generators can be started or until appropriate loads can be reduced or shut off.

< Reliability manager constraints – the reliability manager in this case will provide continuous updates of expected conditions and priorities for generation, storage, and loads.

Output

Updates to schedules for load, generator, and storage set points for the island conditions. These are updated based on changing load conditions and changing forecasts for when power may be restored.


The default operating plan for island mode is based on assumption of extended outage condition and supply to critical loads. There may be two stages for the assumed response – short term response for a period of time and then a response that assumes an extended outage.

3.5.2. Microgrid Risk Manager Function – Island Mode

Description

This function will continuously evaluate current conditions and make sure that there is sufficient generation and/or storage to supply the loads based on the forecasts of loads and set points that have been established by the function above. This function will look ahead at availability of storage vs. time and generation forecasts to make sure these match with load forecasts in the island mode. Adjustments to controls for loads, generation, and storage are made based on projected conditions and reliability concerns. Also, alarms are provided for projected reliability concerns.

Inputs

< Actual levels and projections for load levels, generation levels, storage levels updated each minute.

< External inputs for risk assessment of the supply – weather forecasts, system condition risk level, projections of overall system supply and demand.

Outputs

These are schedules for minimum requirements of local generators, storage systems, and required load management to assure reliable operation. These are provided to the economic optimization function.



Minimum generation and storage levels that must be maintained without additional information about actual loads, load management, or system conditions.

3.5.3. Microgrid Continuous Technical Performance Assessment – Island Mode

Description

This function uses a model of the microgrid (generators, storage, loads) conditions based on the set points in the island mode. This is continuously compared with actual microgrid characteristics? load conditions, generation conditions (including CHP, renewables, etc.), and storage conditions—to identify any problems with the operation.

Alarms are provided when operating conditions are outside allowable bands around expected conditions.

Inputs

Actual operating conditions from load controllers, generator controllers, storage controllers, and the overall metering.

Schedules for loads, generators, storage from economic optimization function.

Outputs

Summary information about actual operation compared to schedules; alarms for conditions outside of allowable bands.

3.5.4. Black Start Control

Description

This function provides a schedule for starting generation and load after an outage of the microgrid that can be applied in either a grid-connected mode or island mode. It uses information about available generators, storage, and critical load characteristics to connect storage, start-up generators, and connect loads in an optimum sequence.

Inputs

Generator availability, load characteristics, storage characteristics; operating mode.

Outputs

Sequence of signals to generator controllers, storage controllers, and load controllers to get the microgrid started.


3.6. Functions that are Independent of Operating Mode

3.6.1. Microgrid Power Quality Assessments

Description

This function monitors power quality conditions within the microgrid. This is mainly an assessment and alarming condition. Steady state power quality is expected to be maintained by power conditioning technologies that are part of the basic microgrid design and respond without specific direction from the master controller.

Inputs

Power quality conditions within the microgrid.

Output

Summary reports and alarms when conditions are outside limits.

3.6.2. User Defaults Set Up

Description

Provide ability for microgrid operator to configure controller default settings via master controller UI.

Input

User entries into UI specifying master controller default settings for overrides, presets, comfort settings, notification preferences, and schedule constraints.

Output




3.6.3. Preferences Configuration

Description

Provide ability for microgrid operator or other user to configure user preferences via UI.


Input

User entries into UI specifying user preferences for overrides, presets, comfort settings, notification preferences, and user established schedule constraints.

Output




3.6.4. User Notification Alert

Description

Send notification or alert message to specified user(s).

Input

Entity to alert (e.g., operator, customer or other user), conditions triggering the alert, and actual alert message (from master controller function with default condition satisfied or microgrid resource dispatch function). User contact information and preferences (from master controller user interface and/or customer interface).

Output

Page, email, computer display, and fax of alert message and conditions triggering the alert.

Default (Primary contact information is invalid)

Send alert message to secondary contact information.

Default (Secondary contact information is invalid)

Send alert message to master controller operator.

Default (Master controller operator is not specified)

Log alert message in master controller system log.


4. Other Requirements This section provides preliminary specifications of non-functional requirements including interface requirements, communications, and software quality attributes for the master controller. The non-functional requirements are provided at an overview level.

4.1. User Interfaces The primary user interface (UI) to the master controller will be web-based, with UI displays served by a web server. The master controller user interface allows designation of user preferences. Physical characteristics of resources within the microgrid are also configured via the user interface. Preferences for electric service are expressed within the UI by ranking load priority orders among end-uses. Information sources that provide economic information on supply system conditions, fuel costs for local generation, and other operating economics and constraints are also configured via the UI. Besides supporting user set-up configurations, the UI is also used for reporting functions that primarily inform the microgrid operator. However, other potential users may access a subset of UI screens for configuration and information access purposes, including end-use customers.

Through the web interface, the UI should support both full web connectivity as well as “thin client” connectivity. For instance, checking of conditions and basic controls should be supported via interfaces such as cell phones and PDAs (personal digital assistants).

4.2. Software Interfaces The master controller is capable of running on a standard PC operating system such as Windows or Linux. The operating system is widely available and commercially supported.

Software interfaces with the supply system controller should comply with IEC standards for Common Information Model. Note that the Common Information Model (IEC 61968, 61970) representations for the distribution system and especially for distributed generation interfaces are not well defined and will, therefore, be a moving target. The important design consideration is that the master controller be designed with an “open API” and a component-based (plug-in) architecture. This will minimize the integration requirements that are inevitable with each specific installation and will allow configuration for compliance with future open standards, such as the Common Information Model and IEC 61850 object models.


4.3. Communication Interfaces It is anticipated that the master controller would be implemented in a computing architecture that is compatible with Internet protocol (IP) connectivity. Common communication protocols and standard information models for slave controllers are also anticipated. IP connectivity is assumed independent of actual physical communication media. The communications media may include a combination of wireless, ethernet, cable, or broadband over powerline (BPL) technologies that accommodate communications with the supply system, slave controllers, users, and individual resources. The microgrid communication infrastructure is likely to accommodate a wireless communication standard such as Zigbee, Z-Wave, or Wi-Fi for flexibility.

4.4. Time Synchronization The master controller should support synchronization of the timing for different elements of the local microgrid. Timing synchronization signals can be obtained from a GPS antenna or a Network Time Protocol signal. This will allow accurate time stamping of information from the supply system, individual elements of the microgrid, and monitoring equipment within the microgrid.

4.5. Software Quality Attributes < Adaptability – The master controller must be able to quickly and

seamlessly integrate changes to the underlying physical microgrid set up. It must be able to accommodate new microgrid resources, power conditioning equipment, and markets as they come into commission. Furthermore, software/firmware must be remotely upgradeable. In particular, software/firmware for slave controllers should be remotely upgradeable to facilitate quick low-cost adaptation of latest communication protocols and information models of microgrid components.

< Availability – The master controller must be highly available at all hours to determine day-ahead operating plans and update daily plans based on latest supply system conditions. Hence the master controller must be available to establish day-ahead and day-of operating decisions and monitor and manage local resources in real time. The controller should be available and capable of operation during a system upgrade as well. This may be achieved through redundancy or through careful design of the master controller to allow proper operation during system upgrade. The supporting communications infrastructure must also have sufficient bandwidth and robustness to enable high availability.


< Configurability – The master controller processes informational inputs for forecasting, demand bidding, and optimal dispatch of microgrid resources. The user directly inputs static data into the UI. The user also configures any online information sources that provide dynamic pricing and other information that the master controller functions rely on. As additional resources are added to the microgrid, the master controller allows configuration of their physical characteristics for inclusion in operating decisions. In addition, user notification preferences for receiving alarms and exception alerts are configurable as well as master controller default settings. For example, users may configure the master controller to provide notification of emergency conditions and system disturbances and request confirmation prior to execution of an automated response.

< Interoperability – The master controller will support interoperability among various intelligent devices including slave controllers and the system controller. To enable this, the devices must be able to communicate with each other. This implies the establishment of a common communication protocol and information models for microgrid components. To support information exchange the receiving functions understand the language used by the sending function.

< Performance – High performance is required by the master controller. The delivery of perfect power is a mission critical objective. In addition, demand bidding is a commercially binding activity requiring attentiveness in participation to avoid undue penalty charges. Furthermore, in order to better optimize economics of microgrid operations, real-time or latest intraday data should be utilized to inform the optimization functions and the resulting resource dispatch and demand bids.

< Safety – The master controller establishes settings for slave controllers which in turn operate physical resources to ensure availability of electric service for end uses within the microgrid. Safe operation of microgrid resources is ensured primarily by slave controllers. Slave controllers accommodate fast control and protection functions to ensure safe operation of generation, storage, and responsive load resources. The master controller monitors actual and forecasted emergency conditions and disturbances on the supply system and can inform users of potential impacts on end-user comfort. Automated notification alerts also enable users to anticipate microgrid operating states and adjust priority of end uses to address latest safety considerations. As an additional precaution the microgrid operator has system override option and can configure the master controller to wait for confirmation prior to execution of an automated response.


< Scalability – The microgrid must be able to support a growing customer base, as more users join the microgrid. The master controller should flexibly accommodate a growing number of applications, resources, end-uses, and other devices within the microgrid.

< Security – The master controller authenticates users through a password protection system that provides different levels of access for varying classes of users. Classes of users are defined by configuration along with access permissions. A microgrid operator, for example, would typically be granted greater access and configuration privileges than an end-use customer. Security requirements also vary depending on what the master controller is communicating with. Highest security is required for communications with a system controller and slave controllers since these impact commercial obligations and physical microgrid operation. Security considerations also include the following:

§ Authentication (you are who you say you are). § Access control (authorized entities have different access rights

and authorized access is not denied). § Information integrity (data have not been subject to

unauthorized changes). § Confidentiality (only authorized access to information). § Non-repudiation (cannot deny interaction took place).

§ Expandability – system will grow and can change with time.

4.6. Data Management Requirements The master controller supports data management functions to enable storage, query, and display of information relevant to microgrid operation. A significant number of data sources need to be managed for forecasting and other master controller functions. Dimensions of data that are processed and managed by the master controller include:

< Real-time data versus day-ahead or earlier.

< Actual versus forecasted or scheduled.

Electricity markets typically produce and operate on real-time and day-ahead data. Occasionally markets also produce data further ahead such as two days ahead to support earlier preparation for real-time market and system operations. Furthermore, electricity markets utilize actual, forecasted, and scheduled data for load and generation supply available to balance system generation and system load within the regional market.


The master controller database also maintains information on physical characteristics of local resources and profiles of loads, storage, and generation. The information is maintained in a standardized manner to enable data access, display, and processing. The master controller operator can easily manage the database without requiring a specialized database administrator.

Historical archive of all types of data is supported. Actual, forecasted, and scheduled data are distinctly stored as well as real-time and day-ahead data. The frequency of data capture, storage, and archiving is configurable. Historical data captured over time is utilized to improve intelligence and decision-making by the master controller and facilitate advanced applications.


A. Appendix: Abbreviations/Acronyms and Glossary

Abbreviations/Acronyms CAISO California Independent System Operator

CBEMA Computer Business Equipment Manufacturers Association

CERTS Consortium for Electric Reliability Technology Solutions. This organization was formed in 1999 to research, develop, and disseminate electric reliability technology solutions in order to protect and enhance the reliability of the U.S. electric power system under the emerging competitive electricity market structure. The founding members include four U.S. Department of Energy (DOE) National Labs (Lawrence Berkeley National Laboratory (LBNL), Sandia National Laboratory (SNL), Oak Ridge National Laboratory (ORNL), and Pacific Northwest National Laboratory (PNNL); The National Science Foundation’s Power Systems Engineering Research Center; and the Electric Power Group. Currently, CERTS is conducting public interest research for the DOE Office of Electricity Delivery and Energy Reliability and California Energy Commission (CEC) Public Interest Energy Research program.

CHP Combined heat and power. Refers to system in which heat and electricity are generated simultaneously, with the thermal energy used for end-use requirements such as water heating, process heating, or cooling. “Cogeneration” is a term that has been used to refer to combined heat and power.

CO2 Carbon dioxide, a gas formed by combustion and respiration. This is a “greenhouse” gas, since in high concentrations in the atmosphere, it contributes to the greenhouse effect, which causes global warming.

CPP Critical peak pricing

DOE U.S. Department of Energy

ERCOT Electricity Reliability Council of Texas

FERC Federal Energy Regulatory Commission

GPS Global positioning system, a satellite-based navigation and location system

HVAC Heating, ventilation, and air conditioning

IEC The International Electrotechnical Commission. This organization prepares and publishes international standards for all electrical, electronic and related technologies.


IP Internet protocol

ISO/RTO Independent System Operator/Regional Transmission Organization. A regional market operator responsible for the reliable operation of the bulk electric transmission system in its FERC-approved geographic territory.

ITIC Information Technology Industry Council. This group represents high-tech companies and performs education and lobbying activities in Washington, DC. It’s goal is to reduce barriers that stifle innovation. promote e-commerce and open markets.

MW Megawatt. This is one million watts (Very roughly equivalent to the amount of electricity needed to power 1,000 homes.)

PQ Power quality

RTP Real-time pricing

UI User interface

UL Underwriters Laboratories. A private research firm located in the United States that attempts to classify and determine the safety of various materials and products.

VAR Volt-ampere reactive, the unit of reactive power. For a two-wire circuit, the product of the voltage times the current times the sine of the angular phase difference by which the voltage leads or lags the current. VARs and watts combine in a quadrature relationship to form voltamperes.

Glossary Aggregator An entity that puts together customers into a buying group for the purchase of a commodity service.

Algorithm A mathematical rule or set of rules or step-by-step procedure for solving a problem.

Ancillary services Services necessary to support the transmission of electric energy from resources to loads while maintaining reliable operation of the transmission system. Examples include non-spinning reserve (reserve not connected to the system but capable of servicing demand), reactive power, regulation and frequency response (following moment-to-moment variations in demand or supply and maintaining scheduled interconnection frequency), and energy imbalance.

CBEMA or ITIC curve A graphical guideline for the computer industry (members of the Computer Business Equipment Manufacturers Association or the Information Technology Industry Council) in designing their power supplies. Essentially, the


curve points out ways in which system reliability could be provided for electronic equipment. The curve is a susceptibility profile, with the vertical axis representing the percent of voltage applied to the power circuit and the horizontal axis representing the time factor involved, measured from microseconds to seconds. In the center of the plot is an acceptable area. Outside this area is a danger area.

Black start capability The ability of a generator or station to go from a shutdown condition to operation without support of the electricity system.

Capacity reserve The amount of generating capacity a power station must maintain to meet peak loads

Circuit A conductor or system of conductors through which electricity can or is intended to flow.

Circuit breaker A protective device located on an electric circuit to interrupt flow of current at that particular point. If a transmission or distribution line or transformer experiences an electrical fault or short circuit, it can be disconnected from the rest of the system by means of a circuit breaker.

Common Information Model (CIM) A model for describing network management information. It is an implementation-neutral, object-oriented standard developed by a computer industry standards organization, the Distributed Management Task Force.

Consumer portal Electric Power Research Institute (EPRI) term for the communications gateway that is the interface between energy providers and consumers.

Critical peak pricing (CPP) Fairly recent variant of time-of-use electricity rates. The critical peak period is characterized by a significantly higher price that is invoked for only a few hours or days a year during the most extreme peak demand periods.

Current Flow of electrons through an electrical conductor. The strength or rate of movement of the electricity is measured in amperes at a pressure measured in volts.

Demand bidding Type of demand response program in which customers can bid into the power exchange indicating the amount of electricity that the customer is willing to reduce, and if relevant, the maximum price required for same.

Demand charge The portion of the charge for electricity service, based on the capacity consumed and billed.

Demand response Customer response, in form of load control, to market and system conditions. Pricing and reliability signals inform and enable customers to exert choice


with regard to their time varying use of electricity. This use might include interrupting loads, reducing loads, or shifting energy use to non-peak periods.

Dispatching The operating control of an integrated electric system to 1) assign generation to specific sources of power supply to effect the most reliable and economical supply as the total of the significant area loads rises and falls; 2) Control operations and maintenance of high voltage lines, substations, and equipment, including administration of safety procedures; 3) operate the interconnection and 4) schedule energy transactions with other interconnected electric utilities.

Energy retailer A utility, energy service provider, or other load serving entity that sells electricity directly to energy using customers.

Frequency The number of cycles per second through which an alternating current passes. Frequency has been generally standardized in the United States at 60 cycles per second (60 Hertz).

Fuel cell A generator that converts the chemical energy in a fuel directly to direct current electricity without intermediate combustion or thermal cycles.

Galvin Electricity Initiative The Galvin Electricity Initiative, launched by former Motorola chief Robert W. Galvin, is project aimed at transforming the nation’s electric power system into one that can truly meet the needs of this new century. Of paramount importance is insuring that the electricity system provides absolutely reliable and robust electric energy service in the context of changing consumer needs For more information visit www.galvinelectricity.org.

GPS Global positioning system, a satellite-based navigation and location system.

Green credits Incentives, typically financial, for supply or use of environmentally benign power generation sources.

Grid An interconnected network of electric transmission lines and related facilities.

Harmonics Distortion of the power wave-form. Can cause heating of motors and problems in electronic equipment.

IEEE Institute of Electrical and Electronics Engineers, a professional association.

ITIC or CBEMA curve A graphical guideline for the computer industry (members of the Computer Business Equipment Manufacturers Association or the Information Technology Industry Council) in designing their power supplies. Essentially, the curve points out ways in which system reliability could be provided for electronic equipment. The curve is a susceptibility profile, with the vertical axis representing the percent of voltage applied to the power circuit and the horizontal axis representing


the time factor involved, measured from microseconds to seconds. In the center of the plot is an acceptable area. Outside this area is a danger area.

Load The amount of electric power delivered or required at any specific point or points on a system. The requirement originates at the energy consuming (end-use) equipment of the consumer.

Microgrid A local power system with generation and storage sources, power conditioning, and a responsive load, that is connected to a conventional power grid. A key feature of this distributed system is its ability to separate and isolate itself from the traditional electricity system during a utility grid disturbance.

Microturbine A very small turbine, fueled by natural gas or some other energy source, that generates electricity for use in homes or commercial establishments, and is considered a distributed generation option, which is on or near the customer premise.

Network Time Protocol A protocol used to synchronize Internet clocks to the correct time.

Open API Specification of function-call conventions that define an interface to a service.

Peak demand The greatest load or demand on an electrical system during a specified period of time.

Photovoltaic cells Devices that produce electric current by converting sunlight into electrons.

Power conditioner Any device whose main function is to provide acceptable electrical power to the load it is protecting.

Power quality A broad term used to describe the measurement of electrical power performance. Variations in voltage, frequency, wave shape (harmonics) and other aspects of power may make the power delivered to equipment less than ideal, creating compatibility problems. Electronic equipment may be especially sensitive to power quality problems.

Reactive power This power, generally regarded as “waste” power in the electricity system, is the power required to overcome the phase shift between current and voltage. It is power that is not delivered, but is used to 'energize' the circuit to allow it do useful work by establishing and sustaining the electric and magnetic fields of alternating current equipment.

Real-time pricing (RTP) A method of charging for energy that changes the price at irregular times as the marginal cost of generation changes. It is accompanied by some


form of communications system that informs customers of the current price as that price is changing, so that the customers have the opportunity to change their usage in response to price.

Requirements (software) In development of software, these are clearly stated objectives of the software to be developed, with descriptions of the specific functionality to be included. These requirements form the basis for future design and coding.

Slave controllers Local intelligent devices that control specific equipment or subsystems in a power system. In a microgrid as envisioned for the Galvin Perfect Power System, the master controller communicates with slave controllers that manage local generators, storage devices, end-use equipment (loads), and switches.

Solid state switch Electronic device used to tie together two or more electric circuits. The switch permits a circuit to be disconnected, or to change the electric connection between the circuits.

Synchronize The process of connecting two previously separated alternating current apparatuses after matching frequency, voltage, phase angles, etc. (e.g., paralleling a generator to the electric system).

Time-of-use rate A rate structure that prices electricity at different rates, reflecting the changes in the utility's costs of providing electricity at different times of the day. With time-of-use rates, higher prices are charged during the time when the electric system experiences its peak demand and marginal (incremental) costs are highest. Time-of-use rates price electricity closer to the cost of providing service, sending "better" price signals to customers than non time-of-use rates. These price signals encourage efficient consumption, conservation and shifting of load to times of lower system demand.

Turbine A device used in the generation of electricity. It has a shaft with blades at one end and electromagnets at the other. Water or steam or some other energy source pushes the blades, which make the shaft and the magnets spin very fast. The magnet end is surrounded by heavy coils of copper wire, and the spinning magnets cause electrons in the wire to begin to move, creating electricity.

Utility tariffs Rates, charges and rules and conditions under which an energy utility provides service to a customer.

WiFi Wirelss Fidelity. The name for a set of standards that set forth the specifications for transmitting data over a wireless network. Wi-Fi is a logo of the Wi-Fi Alliance that certifies that Ethernet devices comply with IEEE 802.11 wireless standard.


Z-Wave™ This is a wireless radio frequency (RF) based communications technology designed for residential and light commercial control and status reading applications such as meter reading, lighting and appliance control, HVAC, access control, intruder and fire detection, etc. Z-Wave transforms stand-alone devices into intelligent networked devices that can be controlled and monitored wirelessly.

Zigbee ZigBee is a published specification set of communication protocols designed for use in small, low power digital radios based on the IEEE 802.15.4 standard for wireless personal area networks (WPANs). The relationship between IEEE 802.15.4 and ZigBee is analogous to that existing between IEEE 802.11 and the Wi-Fi Alliance. The ZigBee 1.0 specifications were ratified on December 14, 2004, and are available to members of the ZigBee Alliance.


B. Appendix: Scenarios for Requirements Development The following list of scenarios represents possible applications of the master controller when operating a microgrid. The scenarios address operation in the different modes (i.e., grid-connected, emergency, islanded) and the transitions between these modes based on conditions both within and outside the microgrid. The scenarios provide the basis for identifying important functional requirements of the microgrid master controller, as well as other components of the microgrid.

This appendix provides brief descriptions of the scenarios considered, with a focus on the required actions and decisions of the master controller.

List of scenarios The following scenarios were identified for evaluation and consideration in the development of requirements for the master controller.

< Response to emergency loading conditions on the supply system.

< Response to dynamically changing prices.

< Selling services to the supply system.

< Incorporating environmental values into decisions for microgrid operations.

< Forecasting of microgrid load and generation profiles.

< Determining and implementing day-ahead operations plan.

< Responding to supply system disturbances.

< Operator changes to the default settings.

< Response to contingencies within the microgrid (e.g., loss of generator within microgrid).

§ During grid-connected operation.

§ During isolated operation.

< Missing data or lack of communications.

< Black start.

§ Black start with grid-connected operation.

§ Black start with islanded operation.


“Emergency Response” – Response to emergency loading conditions on the supply system An emergency signal may originate from a wholesale market, utility or other energy retailer’s system controller. Emergency signals indicate a need for the microgrid to curtail load and/or provide system generation support based on a predefined response in order to help maintain the integrity of the overall grid.

Upon detecting an emergency signal from the supply system the master controller determines a course of action by evaluating:

< Local commercial commitments to respond to the signal.

< User preferences for action during power grid emergencies.

< Latest economic conditions.

The master controller’s course of action depends on whether commercially binding terms exist for providing an immediate response to the emergency signal. If a response is commercially mandated, then the master controller will need to respond. If the response is not commercially mandated, the response can be determined based on the relative economics associated with the emergency conditions and the economics of local generation and load operation. The control decisions are made as part of an emergency response function. Master controller actions include:

< Get economics of the emergency condition from the supply system. This information will characterize the economic penalties associated with different load/generation levels at the microgrid interface with the grid and the timing requirements for response to the emergency conditions.

< Change set points on local generation to reflect emergency response conditions.

§ Generators provide economic function for their operation.

§ Master controller provides desired set point based on overall economics of the emergency condition.

< Change set points for local storage based on economics and availability to be part of the response for emergency conditions.

§ Storage controllers provide economics and availability to be part of response for emergency conditions.

§ Master controller provides desired set point as a function of time for the emergency response condition.

< Provide information for load controllers for implementation of load response to emergency conditions.


§ Load controllers provide load profile information as a function of economics.

§ Master controller provides desired load response based on overall economics of the emergency condition.

< Assess impacts on system security.

§ With new operating conditions, the master controller will be continually evaluating the security of supply using risk assessment functions and these may require adjustments to the response to the emergency signals.

< Notification to user/operator of changing conditions.

§ The master controller will provide alarms and notifications of operation under emergency conditions and a summary of the response implemented.

§ User will have the capability of overriding the response if desired to maintain certain loads or to change the operating priority of local generation.

< Information provided to system controller.

§ Actual load/generation operating conditions.

§ Projected response vs. time for duration of emergency conditions.

Based on the particular participation rules of the underlying emergency demand response program originating the signal, the controller will evaluate physical system and market conditions and any environmental restrictions at the time the signal is received. Regulatory restrictions like emissions constraints on poor air quality days may limit response from dirty fuel resources like diesel back-up generators. When operating in geographical regions not constrained by emissions the controller dispatches resources based on pure economics and end-user selections such as the desired level of “greenness” of the demand response. Curtailable load resources, on-site renewable generation, and some forms of storage, for example, could qualify as green sources of a response and weighed accordingly in the controller’s dispatch decision.

Commercial information assumed to be known:

< Facility tariff/retail contract selection with provision for emergency conditions.

< Pricing structure and constraints during emergency conditions.


§ Specific responses agreed to in contract (response of specific generators and/or loads).

§ Demand and energy charges during emergency operation.

§ Any penalties for failure to respond.

User configurable parameters via Master Controller UI:

< Unit economics

§ Priority of service and economic function for load i

§ Economics of local generator operation (fuel costs, operating costs) for generator i.

§ Economics of using storage (maintenance, life impacts, etc.) unit i.

< Physical resource characteristics for coordination with slave controllers.

§ Load range and characteristics (ramp rates, times to turn on or off, load components), power quality requirements.

§ Generation capacities, power vs. frequency curves, reactive power vs. voltage curves, ramp rates.

§ Storage charge/discharge rates, capacities.

< Resource constraints for emergency response.

§ Loads that are available for control or have specific constraints.

§ Generation priorities for responding to emergency conditions.

§ Availability of storage as part of emergency response.

§ Specific constraints for response to emergencies (individual load response to emergency conditions, generator and storage constraints).


Figure B-1 Information Flows for the Master Controller Responding to Emergency Conditions

.

“Dynamic Price Response” – Response to dynamically changing prices There are many different types of pricing options for the interface between the microgrid and the supply. Time-of-use rates are the simplest form of flexible pricing. In this case, prices are defined for specific periods of the day and this profile is applied each day (although it may be different for different days of the week). The microgrid master controller will be able to interface with more sophisticated pricing schemes as well. More sophisticated dynamic pricing schemes involve prices that can vary with changing system conditions. The dynamics may be related to macro conditions of generation and load or could be related to local constraints in a specific portion of the overall power system.


The microgrid master controller must be able to respond to dynamically changing prices as it optimizes the mix of local generation with the grid supply. These decisions are made in conjunction with constraints associated with ongoing risk assessments and other economic factors.

The possibility of electricity price variability over time leads to electricity cost uncertainty. This uncertainty can be addressed by including forecasting functions in the master controller by which the controller may determine an optimal course of action for operating the microgrid based on forecasted prices. The prices are determined based on user-configured information source(s) and preferred forecasting method(s). For example, forecasts may utilize day-ahead market prices available from regional system operators, which are then updated with intra-day prices as they become available. More complex forecasting techniques would process various user-selected information feeds and translate latest data into forecasted results. More sophisticated techniques may consider physical conditions like weather and the state of transmission system congestion in estimating need for demand reduction based on pricing. The master controller may also develop price forecasts by translating wholesale information into forecasted retail prices according to contracts between the microgrid customer and its energy retailer.

Given that electricity prices may fluctuate over time, the master controller’s objective is to coordinate price response in a fashion that minimizes costs yet meets microgrid operational constraints and service criteria. It does so in several ways. Respecting the possibility of local intelligence to respond to prices, the master controller directly passes retail price signals received from the system controller to end-use devices. In addition, the master controller directly dispatches resources that lack local intelligence or are associated with global objectives that require coordinated operation.

In the dynamic price response scenario, a response to prices is not commercially mandated but rather encouraged through the impact of prices on customer bills. Therefore, a critical function of the master controller is to compute electricity cost information for use in optimizing the mix of load response, local generation, and storage with the grid-supplied power based on user-defined preferences. Costs are calculated according to existing retail tariffs or contracts in place with customers. Besides actual or estimated usage and prices, the master controller also computes forecasted electricity costs based on forecasted or scheduled usage and prices. The resulting cost information is useful for general resource dispatch decision-making by the master controller. For example, it may not be economic to start end-use processes during forecasted critical peak hours when the processes must run continuously over consecutive hours. The master controller generally considers such forecasted prices and associated electricity costs in dispatching resources to optimize economics of response to prices.


Pricing information is obtained from the system controller (or other source like a web site) on a regular basis. It is likely that the pricing information would be provided as a day-ahead profile but the master controller will be designed to deal with continuously variable prices to make it as flexible as possible. In addition to the pricing information, other factors that relate to the pricing can also be collected for use in forecasting future prices. This information can include:

< Weather data

< Overall system demand/generation conditions

< Transmission congestion factors

Using both the current and forecasted electricity prices, the master controller determines the optimum mix of load response, local generation, and storage use for the microgrid. These decisions will be based on user-defined priorities that can be reconfigured by the microgrid manager at any time.

Implementation of the optimization results includes:

< Control set points on local generation.


§ Master controller provides desired set point based on overall economics.

< Change set points for local storage.

§ Storage controllers provide continuous information about state of charge, availability, charging economics.

§ Master controller provides desired set point as a function of time.

< Provide information for load controllers for implementation of load management.

§ Load controllers provide load profile information as a function of economics. Load profiles should include forecasted load as a function of prices.

§ Master controller provides desired load profiles to the load controllers based on overall economics.


§ The master controller is continuously evaluating the capability of the microgrid to withstand a disruption in supply and may adjust settings to assure electric service reliability and the security of supply.


< Provide information to user/operator.

§ The master controller will provide reports of both actual and forecasted conditions along with the control plans for load, generation, and storage.

Commercial information assumed to be known:

< Facility tariff/retail contract selection.

< Pricing structure including demand charges, power factor charges, limits, etc.

User configurable parameters via master controller UI:

< Unit economics.

§ Priority of service and economic function for load i.

§ Economics of local generator operation (fuel costs, operating costs) for generator i.

§ Economics of using storage (maintenance, life impacts, etc.) unit i.

< Physical resource characteristics for coordination with slave controllers.

§ Load range and characteristics (ramp rates, times to turn on or off, load components), power quality requirements.

§ Generation capacities, power vs. frequency curves, reactive power vs. voltage curves, ramp rates.

§ Storage charge/discharge rates, capacities.


Figure B-2 Information Flows for the Master Controller Responding to Dynamically Changing Prices

“Demand Bidding to Sell Services” – Selling services to the supply system In regional electricity markets, various services can be procured competitively through market or bilateral long-term contract mechanisms. For example, electric services offered for sale to the supply system may include balancing energy and other ancillary services like capacity reserve, voltage support, and black start. In particular, capacity reserve and balancing energy are well-recognized ancillary services that many regional market operators procure competitively through spot electricity markets, some of which allow demand-side resources to participate. When


coordinated with market conditions, a net reduction in electricity consumption provided through demand response is recognized as a valuable service supporting reliable operation of the bulk power system and compensated accordingly. With increasing encouragement and investigative orders from FERC, other services like voltage support and black start capability may one day also be procured through competitive spot markets operated by regional market operators. These services could conceivably be provided by local generation and storage within a microgrid.

In the electric power system of the future, resources within a microgrid could be utilized to provide valuable services to the supply system in return for some form of compensation or incentive payment. In this scenario, the master controller coordinates the operation of microgrid resources to take advantage of latest market opportunities. In particular, the master controller facilitates information exchange with the system controller on resource availability and capability within the microgrid. It also submits any market participation offers (i.e., bids to sell services to the supply system). During times when the master controller is to meet electric service demand first and foremost within the microgrid, offers to sell services are comprised only out of any excess supply within the microgrid. Since market participation awards are commercially binding, demand-side bids are only submitted by the master controller when and to the extent resources could be spared without jeopardizing service to critical loads within the microgrid.

After a bid is accepted and awarded, actions taken by the master controller are similar to those in the emergency response scenario except the controller receives and processes market participation awards instead of emergency signals. Market participation awards are sent by notification from the system controller indicating awarded bid schedules and resource commitments. The master controller acknowledges the award received, processes the resource commitment information, and optimizes the dispatch of individual on-site resources within the microgrid to meet the scheduled commitment. The microgrid operator is also notified of awarded bids and resulting resource commitments, as are resource owners/operators impacted by the participation scheduled. Individual resources are dispatched by the master controller through dispatch schedules, control signals, and/or notification alerts sent to resources collectively providing the awarded service to the supply system.


Figure B-3 Information Flows for the Master Controller Participating in Demand Bidding

Incorporating Environmental Values into Decisions for Microgrid Operations The microgrid master controller considers user-configured environmental values as part of its objective in optimizing operation of the microgrid. For example, users may configure preferences for level of “greenness” of power utilized by the microgrid. These preferences can be expressed as priorities for using local renewable generation as part of the overall load/generation mix. The preferences can be configured as economic preferences (e.g., value assigned to renewable generation or associated emissions reduction values) or specific overriding preferences (e.g. solar and wind generation sources are maximized whenever available).


Individual users within the microgrid have preferences that can be specified through a web interface or equivalent. These preferences put a value on emissions or other environmental quantity associated with their own energy use.

Overall microgrid preferences are selectable by the microgrid operator and include emissions/environmental values that are applied to local generation operation.

Environmental restrictions can also be inputs to the master controller in operational decision-making. These information sources may include web services reporting latest air quality ratings or other local indications on carbon emission restrictions. Such information sources would be configured at the time of set up as inputs to the master controller. The inputs are translated into a value relationship for emissions and become part of the overall value assessment for optimizing the load/generation mix within the microgrid.

Forecasting Microgrid Load and Generation Profiles As in any power system, load forecasting in microgrids is necessary to maintain reliability and reduce operating costs. The time period of interest for a master controller will most likely be limited to short term, i.e., day-ahead or hour-ahead. Variables that are fixed over the day-ahead period, for example fuel price, need not be included in the forecasts.

Some of the compelling reasons for forecasting daily load in microgrids are:

< To permit accurate unit commitment of dispatchable microgrid power sources to assure that the peak demand is met and that daily energy cost is minimized.

< To allow for the development of a daily plan to best utilize the available energy in case the microgrid is islanded from the main grid.

< To develop a daily plan for charging and discharging energy storage devices.

< In situations where time-of-day pricing is used or based on a prediction of daily price profiles in dynamic pricing situations, to maximize the potential profit from buying, storing, and selling electricity to the main grid.

Hour-ahead forecasts are the building block of day-ahead forecasts. Once a day-ahead forecast has been made, the master controller can continually update the individual hour-ahead forecasts by examining hourly errors and then making intelligent corrections.


Daily Load Profiles

Total load tends to have characteristic daily profiles. (See normalized examples below, where the summer profile is dominated by the late-afternoon air conditioning peak, and the winter profile has twin morning and afternoon peaks due to electric heating.) The actual MW peak values of the curves vary considerably with weather, day of week, and holiday.

Figure B-4 Examples of Daily Load Curves (Normailized)

Average Daily Load Profiles

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Naturally, there is considerable hour-by-hour variation of the averages shown in the curves, and the variation in microgrids can be expected to be considerably greater than for electric utilities because the off/on status of any single large load in a microgrid can noticeably affect the total. But for any grid, large or small, historical daily load curves, coupled with observed weather-related parameters such as heating- and cooling-degree days, can provide excellent day-ahead load forecasts with only a few percentage points of error.

The microgrid controller should be adaptive and capable of learning daily load profiles and their dependency on weather and other factors.


Each slave load controller will be responsible for providing information about the load characteristics for the loads that are associated with its control. This information should include:

< Types of loads

< Load profile as a function of critical parameters (temperature, electricity price, day of week)

< Critical loads that must be maintained

The microgrid master controller must be able to combine the expected load profiles (expressed as functions of important parameters) and combine these to develop an overall load forecast for the microgrid. The relationship between the load profiles and other parameters that are monitored by the master controller can be verified over time and the overall load forecasts improved accordingly.

The load forecast is used in combination with local generation availability forecasts and economics to develop the daily operating plan for the microgrid. This operating plan takes into account reliability constraints for the Perfect Power System as described in the next scenario.

Including local renewable generation in the load forecasts

A microgrid might have renewable sources such as solar and wind. If so, and unlike the case for large grids, the renewable power generating capability might be a significant percentage of the total load. Renewable sources are non-dispatchable and can be considered as “negative loads.” They add considerable uncertainty to load forecasts, and next-day load forecasts will require wind and solar predictions. There will be greater accuracy if wind and solar forecasts are provided by regional forecasting services and then distributed by electric utilities because, unlike temperature forecasts, wind and solar forecasts are not readily available to the general public.

The master controller will be able to accept information from a web site or other information source that will provide data needed to forecast local renewable generation. This information will be provided to the local slave controllers for the renewable generation (wind, solar) to develop appropriate daily forecasts of available generation. The master controller will use these forecasts in combination with the forecasts from the load controllers to develop daily and hourly updated forecasts of overall microgrid load profiles as a function of time and economics.

The average solar generation looks quite smooth (see below). However, for any particular day, the solar generation varies considerably with cloud cover. An example variation is illustrated below for a July day. The predicted profile will provide


guidance on the local generation that will be available, but the master controller will take into account the variability that can occur when developing the daily plan.

Figure B-5 Example of a Daily Solar and Wind Generation Profile for West Texas Plains

Average Daily Generation Profiles for August

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Figure B-6 Illustration of Variability in Solar Generation for a Summer Day

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Long-term forecasts such as fuel prices are not likely to be needed by master controllers because fuel prices are expected to be quoted for longer terms. This will affect the economics of local generation other than renewable sources, and information in the master controller will be updated as new information becomes available.

Determining and Implementing the Day-Ahead Operating Plan The master controller must be able to plan ahead in a next-day mode to minimize cost or some other cost-sensitive objective function. It will have three operating modes – normal, emergency, and islanded.

< The normal mode exists when the grid connection is intact and the supply is operating with normal daily electricity price values (time-of-use, dynamic pricing, etc.).

< The emergency mode exists during special conditions when the supply system needs support or critical peak pricing conditions exist.

< The islanded mode exists when the microgrid is disconnected from the supply system. Local controls (solid state switch, generator controls, load controls) will respond during the first few seconds after islanding occurs as described in a separate scenario. After the initial


adjustments, the controller can adjust set points to maximize the reliability for critical loads (the most likely objective function for islanded operation).

Figure B-7 Information Flows for the Master Controller Determining Daily Operating Plans

Daily Objective Functions

The most important objective in the Perfect Power System is to maintain service to critical loads. This will be an objective function that is assessed continually by the master controller to make sure that normal economic objective functions do not compromise the reliability requirement.

Besides the reliability objective, the master controller will be working to minimize a daily objective function. It is appropriate to think of the role of the master controller


as one of constantly working to minimize an objective function, whose constraints may be changing.

The main objective function that is likely to be the focus of the master controller can be stated as follows:

Minimum total costs (payment to the grid supply, plus costs of operating local generation and storage plus costs associated with load management, including reliability impacts, plus costs of environmental impacts)

Objective functions that can be part of this overall objective function include:

< Minimum payment to utility.

< Maximum numbers of “nines” in reliability.

< Minimum kWh from the electric utility (not same as minimum $ if rate depends on time-of-day or peak kW).

< Minimum CO2 impact on the environment (not the same as minimum kWh if the electric utility has multiple fuel sources).

Other objective functions that could be important during some periods of operation include:

< Minimum peak kW from the electric utility (average over 15 minute billing period).

< Best load leveling for the electric utility daily load shape (but this would likely be accomplished through a time-of-day rate).

The daily objective function can be implemented as a weighted combination of objective functions that are components of the overall objective function, for example:

Obj. Fun. = a1 ? (minimum payment to reliability) + a2 ? (minimum costs of local generation) + a3 ? (CO2 impact) + a4 ? (reliability impact and load impact),

where a1, a2, a3, a4 are the weighting coefficients.

Normal Mode Constraints

Of course, the optimization problem is complex because it has constraints. Likely constraints for the normal mode are:

< Acceptable level of reliability.


< Temperatures stay within an acceptable range.

< Lighting levels stay above a lower limit.

< Available discretionary short-term power stays above a lower limit.

< End-of-day battery and thermal stored energy stay above lower limits.

< Daily payment to the electric utility stays below an upper limit.

< Maximum power drawn from the electric utility (demand) stays below an upper limit.

Some constraints could be “hard,” and others “soft” (e.g., quadratic functions outside the boundaries).

Developing the Day-Ahead Operating Plan

The controller should prepare the next-day forecast based upon recent experience plus day-of-week and hourly trends. Thus, it is important for the controller to include historical trends for, among others:

< Total building usage – kWh

< HVAC usage – kWh (from load controller)

< Major appliance(s) usage – kWh (from load controller)

< Lighting – kWh (from load controller)

< Small electronic – kWh (from load controller)

< All other – kWh (from load controller)

< Solar generation – kWh (from renewable generation controller)

< Wind generation – kWh (from renewable generation controller)

< Net battery output – kWh (from storage controller)

< Battery stored energy – kWh (from storage controller)

< Net thermal storage output – kWh (from CHP controller)

< Thermal stored energy – kWh (from CHP controller)

< Net meter – kWh (from meter)

< Degree-days (heating or cooling)

< Wind and solar measurements

Also, at the end of a day, the controller should give a value of the daily objective function and a summary of constraint violations.


Data from the system are also needed. These might include forecasts for:

< Heating and cooling degree days

< Solar and wind forecast – expected kWh per standard 1 kW rated unit

< Likelihood of thunderstorms (i.e., outages)

plus next-day hourly data for:

< Cost per kWh and demand

< CO2 (or other emissions) per kWh

Developing the next day plan is very similar to the standard electric utility generator unit commitment problem. Once the daily objective function is properly formulated, the best daily plan can be developed using dynamic programming. Corrections can be made during the day as described below.

The controller should be able to evaluate the errors in each daily plan after the fact, to learn and thus improve future plans. It should be capable of tracking differences between actual utility price signals, degree-days, solar, wind and their last day-ahead forecasts, making the necessary adjustments for the present day. It should also be able to suggest changes in energy usage patterns and quantify their benefits to the daily objective function.

A playback feature, where the controller can evaluate actual (or simulated data), can be very valuable in selecting the best sizes for system components as far as the daily objective functions are concerned:

< Installed kW of PV array

< Installed kW of wind generation

< Installed kW of conventional generation

< Installed kWh of storage battery

< Installed kWh of thermal storage

Uncertainties in load, weather, and renewable sources can be factored into the controller, and the user can input appropriate reliability constraints to achieve objectives of the Perfect Power System. Naturally, there will have to be trade-offs every day between reliability constraints and the overall economics.


Implementing the Daily Operating Plan (Real-Time Adjustments and Optimization) The daily operating plan provides the expected set points for local generation, the load controllers, and the storage controllers over the period of the day.

Actual set points can be adjusted in real time based on changing operating conditions by the master controller.

Data monitoring and acquisition speed is not critical during normal operation because continuous adjustments to power balance, voltage control requirements, etc. are made by the slave controllers locally. The master controller is only responsible for the overall economic and reliability optimization functions.

For the normal mode, one-minute data are probably adequate. Some key measurements are totaled by class, and others singled out as large individual loads. Examples of continuous monitoring information that will be collected by the master controller include:

< Overall microgrid.

§ Voltage, frequency.

§ Real and reactive power.

< Grid conditions.

§ Electricity prices and schedule.

< Generator controllers.


§ Fuel supplies; economics of operation (schedule).

< Renewable generation controllers.


< Load controllers.


§ Critical load power requirements (schedule).

§ Curtailable loads and economics.

< Storage controllers.


§ State of storage.

§ Charging requirements, economics (schedule).


< Other inputs from the system.

§ Temperature.

§ Thermal storage.

§ Risk factor of problems from the grid (based on storms and other factors).

This information is used for continuous updates to set points for the local slave controllers in order to minimize the risk of compromising reliability constraints while also minimizing total operating costs for the microgrid. Updates to set points can be implemented at one-minute intervals and the overall schedules updated accordingly.

Responding to a Supply System Disturbance For the Perfect Power System, the response of the microgrid to system disturbances is one of the most important characteristics of the operation. The entire design of the Galvin Perfect Power System microgrid is based on being able to improve the reliability (broad definition to coordinate with the power quality requirements of the loads and processes of the users) for the microgrid tenants.

The scenario assumes that the microgrid is operating in a mode interconnected with the supply system with optimization of the local generation based on heating, cooling, and energy management within the microgrid.

A disturbance occurs in the supply system that results in a voltage variation that exceeds the allowable tolerance of the microgrid power quality requirements (default is the ITIC curve).


Figure B-8 ITIC Sensitivity Curve as Default for Detection of Supply System Disturbances

The following describes the response of the master controller (and the associated slave controllers) to this event.

1. The solid state switch controller (slave controller) determines that the voltage disturbance is out of specifications and opens the static switch immediately (this occurs within about ¼ cycle of the detection of voltage condition out of specifications.

2. Prior to the operation of the static switch, the master controller was coordinating the load and the microgrid generators and storage units so that the generators (in combination with the storage units) would be able to handle loss of the supply without exceeding their generating capabilities. This is done by making sure that the necessary generators are operating and/or there is sufficient storage to provide any necessary ride through to start up additional generators.

3. The slave controllers for individual generation and storage elements in the microgrid respond by adjusting their outputs to match the load according to pre-defined power vs. frequency


droop characteristics that are coordinated between the different generating units. The local generation controllers also use reactive power vs. voltage characteristics to maintain the voltage within prescribed limits.

4. The master controller monitors the supply voltage to see if the disturbance is momentary in nature (e.g., less than a minute) before adjusting any set points for the local generators. If the supply voltage returns to normal and is maintained for more than the required time (e.g. one minute), the master controller goes through the resynchronizing with the supply routine and directs the static switch to close when resynchronizing has been achieved.

5. The master controller collects inputs about the final operating conditions of each generator and storage unit with respect to the loads.

Island Operation Control

Once the master controller has determined that the island condition is more than a momentary disturbance in the supply, it takes over the function of optimizing performance in the islanded mode.

Information from the supply system will be collected to see if there are projections possible about the duration of the supply system disturbance. The master controller will project the duration of the supply system disturbance assuming a maximum duration event (defined by the user) without any additional information.

In the island mode, the master controller uses an objective function that maximizes the reliability for critical loads as the primary and optimizing the economics for other loads and generation as secondary functions.

Implementation of the optimization in the island mode includes the following:

< Get forecasts of supply conditions to update estimates of the required duration for operating in the island mode. The forecasted duration will be part of the function for optimizing use of storage, local generation, and load management.

< Change set points on local generation to reflect island conditions.


§ Start up generating units as required that may not have been in operation but are needed to maintain supply to the loads as storage is depleted.


§ Master controller provides desired set point based on overall economics of the island condition.

< Change set points for local storage based on economics and availability to be part of the response to island conditions.

§ Storage controllers manage the initial response of the storage units to the islanding, which likely involves providing output from storage to support the transition and adjustments following disconnection from the supply.

§ Storage controllers provide economics and availability to be part of ongoing response during island conditions.

§ Master controller provides desired set point as a function of time for the island conditions. These set points are updated as new generation comes on line and new estimates of the disturbance duration become available.

< Provide information for load controllers for implementation of load response to island conditions.

§ Load controllers provide information about the critical loads that must be maintained during island conditions.

§ Load controllers provide load profile information as a function of economics and reliability requirements.

§ Master controller provides desired load response based on overall reliability requirements, estimates of duration of event, generation availability, storage availability. This response will likely include set points for load curtailment during the island condition. The load controllers will actually implement the required load curtailment.


§ With new operating conditions, the master controller will be continually evaluating the security of supply to critical loads based on available generation and storage vs. load requirements and expected duration of the disturbance.

< Notification to user/operator of changing conditions.

§ The master controller will provide alarms and notifications of operation under island conditions and a summary of the response implemented.

§ User will have the capability of overriding the response if desired to maintain certain loads or to change the operating priority of local generation.


Once the initial load/generation rebalance is completed and voltage and frequency are stabilized, the controller can assess the overall power balance situation and determine how long the load can be supplied with the existing sources. The controller will have information from load controllers about critical loads and will be able to adjust the automatic load shedding set points at non-critical loads (load shedding functions will be included in the load controllers as part of fast coordination between the slave controllers). Shedding non-critical loads by the slave controllers will be accomplished based on underfrequency set points. The controller can also adjust the frequency and voltage droop set points of the sources as new generation comes on line.

Resynchronizing with the Supply

The last stage of the response to a system disturbance occurs when the system supply has been restored.

The master controller monitors the system supply and determines when the supply has been restored for an adequate time to allow reconnection of the microgrid with the supply. For instance, the master controller will delay reconnection to allow for multiple recloser operations in the protection settings of the supply system.

Once it is determined that the microgrid can be reconnected with the supply, the master controller gives the solid state switch the command to close the switch and reconnect with the supply.

< First the master controller makes any adjustments to local generator set points that are necessary to make sure that they are operating at a point that will allow automatic adjustment to a new operating point when connected to the supply and there is a new frequency that is determined by the supply system.

< Then the master controller gives the solid state switch the command to close in with the supply.

< The solid state switch resynchronizes by closing the switch at a point where the phase angle of the supply and the phase angle of the microgrid are the same (even though the frequencies are not the same).

< After the switch closes, the microgrid frequency will be determined by the supply. The local generators will adjust their operation based on the power vs. frequency curve to achieve a new operating point.

< The master controller will change the mode of operation to normal operation and adjust generator settings and load settings accordingly. This will allow:

§ Load controllers to bring back loads that had to be shed and to restore load control based on economic optimizing functions.


§ Storage controllers can go into a mode of recharging storage so that it is available for next disturbance.

§ Generator controllers will operate based on economic optimizing functions as directed by the master controller.

Operator Changes to Default Settings The microgrid operator may change default controller settings via the master controller UI. Operator interaction with the controller occurs through the user interface. The master controller stores default settings and any user-configured settings entered into UI. User configurable settings include overrides, presets, comfort settings, notification preferences, and user established schedule constraints.

Default settings describing physical characteristics and status of resources are also defined using the master controller UI. For each resource that is set up within the microgrid, the UI allows configuration of information on the resource’s capability (e.g., ramp up/down rate), equipment type (e.g., generation, curtailable load, or storage unit), and rated capacity. The UI may also store information indicating the resource’s predictability (e.g., intermittent nature or any statistics available on its historic dependability), fuel type (e.g., dirty or green), and any environmental emissions restrictions on the resource. The operator can change default settings at any later time by accessing the UI. The master controller can send stored information on resource characteristics to the system controller upon request.

Response to Contingencies within the Microgrid (e.g. loss of generator) The master controller must be able to adjust settings when problems occur either in the supply system (emergency mode was discussed in a previous scenario) or within the microgrid. An example of a problem within the microgrid would be tripping of a generator.

As part of the risk assessment function, the master controller should have contingency plans for N-1 scenarios for any of the components of the system. Loss of a generator within the microgrid will be handled by adjusting the outputs of other devices to compensate for this loss. There are two separate cases for this scenario – loss of a generator when connected to the grid (normal mode) or when islanded (island mode). They are discussed separately here.

Normal Mode

In the normal mode, loss of a generator is not a big problem because the supply from the grid can handle the full load of the microgrid anyway. The response of other generators, loads, and storage within the microgrid occurs automatically when there


is a step change of any of these elements. Each of the slave controllers responds according to its local control to arrive at a new steady state operating point.

The basic control is a power vs. frequency control with a reactive power vs. voltage control for voltage management. Since the grid is still connected, there will not be a significant change in frequency and the other generators will continue to operate at essentially the same operating level. Loads will also not be affected since there is supply available.

After the initial response, the master controller will adjust the set points of other generators and loads to meet appropriate constraints. For instance, if loss of the generator results in a load level that would exceed the desired demand level for the microgrid, load management measures or increase in other generator outputs can be implemented. Basically, a new optimum economic operating point is determined for the new constraints with the generator out of service.

Island Mode

In island mode, the response of the slave controllers will be more significant to the original event of losing a generator in the microgrid. The other generators and the storage units will operate on power vs. frequency curves to arrive at a new equilibrium point. If the frequency is slow enough, automatic load shedding may be required to maintain service to the critical loads in balance with the available generation and storage.

After the initial response which is handled by the slave controllers directly, the master controller develops a new optimum operating point for all microgrid elements which continues to provide uninterrupted service. This could require starting up additional generation or curtailing loads. Risk assessment functions will also help determine the set points for the loads, generation, and storage to minimize risk associated with another event.

Missing Data or Lack of Communications Problems with data collection or lost communications between different parts of the system should not result in reliability impacts to the system operation. As described previously, the slave controllers along with system protection equipment assure the safe and reliable operation of the system, even without connection to the master controller at all. The master controller provides an optimizing function and a risk management function but is not needed for safe operation of the grid, either in normal mode or island mode.

With loss of connection to the master controller, each slave controller will continue to operate with selected set points and will respond to disturbances according to the appropriate control settings (droop curves, etc.). Load controls also help assure


reliable operation of the system since the last resort is to shed load to make sure that the grid remains stable and the voltage acceptable.

If the master controller is missing data from only a portion of the system, assumed characteristics can be used from historical data (e.g. load profiles). If the data problem persists beyond an acceptable time frame defined by the operator via the UI, then the controller will notify the operator of the condition and any resulting exceptions created by poor data. The notification message prompts operator attention and/or intervention. For example, the operator may be notified of a default condition that has occurred in the microgrid and any ready course of action that can be taken to remedy the situation. The controller may further prompt the operator for confirmation prior to executing the recommended course of action. These interactions occur via the master controller UI.

Black Start Another function of the master controller is to coordinate start up of the system after a shut down for any reason. This could occur in an island mode or connected to the grid. If the grid is available, it makes sense to restart the system with supply from the grid. This is the simplest scenario. If the system must be started in an island mode, a different startup sequence is required.

Grid Connected

In the grid connected mode (normal mode), the start up should be straightforward. The grid connection is closed first and then the different elements of the microgrid can be closed without too much concern for the order of switching.

All of the load can be connected. Load controllers should provide load profile vs. economic operation information as described in previous scenarios.

Local generators can be connected and begin operating according to set points based on optimization of economics (heating requirements, economics of local generation vs. grid supply, etc.).

Storage can be operated based on requirements fro recharging that may be needed after an outage.

Island Mode

It may be necessary to restart the system in island mode. In the case of an interruption of the grid supply and a problem that causes shutdown of the microgrid, it may be necessary to restart the microgrid before the grid is available.

This requires a predefined script for restarting the different components of the microgrid based on the types and characteristics of the generators and storage


elements, as well as the load characteristics. The script would be set up via the master controller UI as part of the basic configuration of the master controller parameters.

An example scenario for startup in the island mode would be the following:

1. Start up generator(s) that have black start capability. For instance, microturbines, fuel cells, or diesel generators can probably be started without any connection to the grid.

2. Once these units are operating, storage devices can be put in service for recharging or support that may be required for load startups.

3. The load controllers will have sequencing procedures for bringing loads back on line after indication from the master controller. The most critical loads will be started first.

4. Once critical loads are back on line, additional loads that are capable of being supported by the local generation can also be brought on line.

5. Finally, the system set points will be set up based on island mode optimization as described in a previous scenario.

master controller requirements specification for perfect power

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