An Oracle White Paper

August 2011

Advanced Distribution Management

Advanced Distribution Management

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Advanced Distribution Management

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An Introduction to Advanced Distribution Management

Distribution grids need data and systems to drive safe and reliable operations. As SCADA,

distribution automation, and outage management systems prove, dramatic improvement in grid

efficiency and reliability can be achieved through increased real-time analytics driven by larger

data volumes.

The Smart Grid increases the volume and variety of grid management data available by

hundreds—potentially thousands—of orders of magnitude. Legacy applications for grid

operations are generally not equipped to handle even the increase in data from today’s smart

meters and sensors, much less maximize data use.

A new set of functions is emerging to respond to this challenge — Advanced Distribution

Management (ADM or ADMS, for Advanced Distribution Management System). ADM

organizes and analyzes the enormous volumes of new near-real-time data, then uses that

data to achieve goals like:

Decreasing the number and length of outages by using self-healing unfaulted circuit sections

to restore customers automatically.

Integrating larger amounts of intermittent renewable generation into the grid.

Supporting electric vehicle recharging.

Managing microgrids and virtual power plants.

Supporting demand reduction programs.

Advanced Distribution Management

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Business Drivers Behind the Growth of Advanced Distribution Management

Utilities have long made incremental investments in the power grid. Today, the pace of that investment

is increasing. So are the environmental and economic pressures demanding that utilities quickly

demonstrate maximum benefits from both the existing grid and new Smart Grid investments.

Software plays a key role in benefit maximization. As utilities add hardware to the grid—sensors,

nodes, embedded devices, and advanced meters—they are also demanding software that exercises full

control over the new equipment, better connects customers to the smart grid, supports new renewable

generation, enables customer options like demand response and real-time pricing, and analyzes near-

real-time data in ways that improve business performance.

Advanced Distribution Management (ADM) has become an umbrella name for a software “system-of-

systems” that can fill these demands. Utilities and software vendors envision ADM as a group of

capabilities—as yet only partially defined—that can fill the gap between current and emerging grid-

management needs.

ADM unites outage management and SCADA integration with existing and emerging distribution

management software to:

Increase grid efficiency, reliability, and security.

Defer the need for new grid construction.

Respond to new challenges like electric vehicle adoption and efficient use of beyond-the-meter,

customer renewables generation (e.g. solar rooftops)—including operational and forecast modeling.

Maximize use of intermittent, renewable power produced both locally and remotely.

1 Chartwell, “Report: Smart Grid Communications Networks,” Darren Epps, 3 March 2011.

Utilities are seeing the value in convergence of AMI and distribution automation, particularly in advanced distribution

management systems (ADMS). The ADMS is a system to safely connect smart grid customers with distributed resources and

provide a utility operations platform with real-time information to the distribution network.

Darren Epps, Chartwell Inc.1

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Existing distribution applications like distribution SCADA and outage management—while still vital—

are generally unable to respond to these challenges in and of themselves. They cannot predict and

respond to many grid problems before they cause outages. They cannot handle—much less analyze

and act on—new, relevant data coming from both grid sensors and customers’ smart meters. They do

not have the information management platforms or functions vital to managing such emerging

technologies as microgrids, virtual power plants, and electric vehicles.

In contrast, ADM is designed with these goals in mind. It encompasses new processes, more accurate

forecasting, better use of grid sensors, real-time monitoring, and the ability to handle a rapidly

escalating volume of new data.

Advanced Distribution Management Tasks

Advanced Distribution Management (ADM) connects Smart Grid customers, distributed resources,

and utility operations technologies to a real-time information-rich distribution network.

Product Contributions Across the Grid Life Cycle

Source: Gartner (December 2010) 2

2 Gartner, Inc., Market Definition: Advanced Distribution Management System Products, Randy Rhodes and Zarko Sumic, 14 December 2010.

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ADM builds on its outage management and SCADA roots to:

Enhance safe and reliable automated operations by building out the Outage Management System

(OMS) electrical connectivity model with full engineering impedance model attributes to run real-

time load flow optimization functions and link to SCADA.

Ensure operational safety through use of a common network model, along with tagging, clearance

and switching logs

Prevent faults and minimize outages using automated modeling plus control and switching plans and

processes. ADM can, for instance, gather temperature, loading, and operational history at device

locations, use a device model to recalculate expected life in light of its operational history, and alter

grid operations, such as dynamic ratings and load-transfers in order to minimize negative

consequences.

Automatically minimize the impact of outages using self-healing capabilities like Fault Location,

Isolation, and Service Restoration (FLISR). FLISR reduces the number of customers affected by an

outage by automatically sensing faults and circuit lockouts to identify and isolate the faulted circuit

sections. It then restores power to all of the unfaulted circuit section’s affected customers by

automatically switching them to adjacent sections of the line.

Optimize reliability. ADM might, for instance, forecast what the circuit loading will be during the

peak hours of the day and identify any overload equipment or lines. Then ADM could generate

an optimal switching plan to relieve the overload by transferring loads to adjacent circuit sections

with available capacity. Automated switching could be done by a click of the button, with manual

switching scheduled and dispatched.

Reduce distribution system losses. In a process called volt/var optimization, ADM calculates the

amount of active and reactive power on a line. It then reduces the effect of the loss-producing

reactive power by switching on devices like capacitor banks in locations close to the loads

consuming the reactive power (e.g. electric motors, fluorescent lights).

Reduce demand and energy consumption through conservation voltage regulation (CVR). This is an

extension of volt/var optimization used to fine-tune the end-use customer voltage levels toward the

lower-end of service voltage standards (e.g. ANSI C84.1-2006). Many smart grid business cases have

found CVR to yield major benefits, especially when utilities operate under a regulatory mechanism

that incents load reduction to improve overall grid efficiency. Without such incentives, CVR

ultimately reduces revenue.

Manage distributed intelligent devices. These may include smart switches, sensors, controls,

substation automation, and microgrid controllers that need a simplified model of electrical

connectivity in order to optimize their distributed processes.

Designating ADM as the overarching authority to the network model solves a serious problem for

smart grids: the need to maintain safe and secure grid operations even as the network constantly

changes to re-route power for maintenance, construction, and line extensions. As the network

topology changes, distributed devices may need to be modified. ADM tracks and controls the

distribution configuration, providing the model changes for these devices and keeping them current.

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As part of the management function, ADM will gather and analyze sensor signals to predict device

failures. It will use data from smart metering systems to monitor voltage and ensure service quality.

And it can provide lockout-tagout functions to the distributed intelligent devices, further enhancing

the safety and reliability of other utility-owned systems like AMI and smart meters, as well as

customer-owned equipment like smart appliances and storage devices.

Control microgrids and virtual power plants. Microgrids—semi-independent sections of the grid—

efficiently marshal local distributed generation and storage to handle some or even most local

demand. While distributed master controllers oversee routine microgrid activities, ADM coordinates

those controllers to provide power to microgrids with a supply deficit, adjust energy flows elsewhere

to accommodate excess electricity from distributed resources, and route excess supply to other

microgrids or to storage.3

Incorporate increasing amounts of generation from intermittent renewables. ADM can, for instance,

use forecasts to identify probable locations and durations of intermittent supply drops. It can then

identify and notify back-up suppliers of potential need. If the need materializes, ADM can

orchestrate alternative generation, demand response options, and storage supplies to accommodate

both short-and long-duration supply drops.

Minimize the impact of electric vehicle (EV) recharging on the environment and the distribution

grid. ADM can orchestrate EV chargers to operate during periods of available capacity—for

instance, at night, when both base generation and wind generation tend to exceed demand, and when

loading on transmission and distribution networks is light. During grid events, ADM could invoke

demand response to delay EV charging and thus prevent larger-scale disturbances.

Advanced Distribution Management Technologies

ADM builds on technologies developed over previous decades to analyze the grid, operate it, and

restore service following outages. Graphical displays (including schematics and GIS-based

visualization), a wide variety of engineering tools, substation automation, safety tagging, and switching

management all play a part.

Specific functions assigned to ADM may include:

Volt/var optimization.

Calculation of loadflow.

3 For more information, see Oracle’s white paper Microgrids: An Oracle Approach.

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Incorporation of increasingly diverse supply (for instance, from intermittent renewables and small,

distributed generation sources).

Fault location, isolation, and service restoration (FLISR).

Conservation through voltage reduction (CVR).

State estimation.

Support for reducing peak demand and recharging electric vehicles.

Microgrid control.

The Role of the Real-time Network Model

At the heart of today’s outage management and SCADA applications lies an accurate, real-time

network model of the distribution network connectivity. The demands that ADMS puts onto that

model require it to include:

Circuit models showing the lines connected to nodes, equipment, devices, etc. These are usually

derived from a GIS or circuit mapping system source.

Customer connectivity through secondary services or data linkage to service transformers.

Conductor and cable type, including overhead line construction type and underground cable spacing

to calculate engineering parameters such as line impedances and thermal loading limits that add

unbalanced 3-phase impedance and capacity characteristics to the model. This operates the real-time

unbalance load-flow for system optimization.

Engineering and forecasting models of intermittent renewable resources, electricity storage, and their

connections to the model.

Models of customer meters and beyond-the-meter resources (e.g. distributed generation, electricity

storage, electric vehicle charging facilities, demand response capability).

The ADM Information Management Challenge

Every advance in grid management rests on information management. As those advances accumulate,

utilities must gather, validate, store, and analyze ever-increasing data volumes.

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ADM starts with interval data from smart meters—an estimated 1.7 gigabytes of data per year.4

Sensors add an equal amount. Add to that the network model of electrical connectivity required by

outage management—an estimated 100 times more data. Distribution management requires phase level

impedance models to run power flow simulations—another 20 times more data than is needed for

OMS As the ADM begins to incorporate data from distributed generation, demand response, storage,

and electric vehicles, data volumes ratchet up still further.

The huge volume of anticipated data forces utilities to examine carefully the potential ADM

information management platform. It must be able to model:

A fast-growing real-time network.

Major storm events.

Detailed substation configurations.

Detailed switching devices—to accurately reflect actual operations.

4 Andres Carvallo, Austin Energy, quoted in SmartGridNews.com, 3 November 2009, http://www.smartgridnews.com/artman/publish/Technologies_Security/That-Smart-Grid-Data-Surge-We-Mentioned-Earlier-You-Can-t-Ignore-It-1351.html.

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Upstream subtransmission networks—for consistent switching and outage reporting.

Secondaries and services down to customer meters.

Beyond-the-meter customer resources, including distributed generation, storage, electric vehicle

charging states, and demand response potential.

Smart devices (to synchronize their network topology).

Customer load shapes.

Forecasted load shapes for distributed generation, based on historical output, time of day, wind

speed, solar incidence, etc.

Performance and security testing (including Critical Infrastructure Protection (CIP) compliance) are

obvious additional requirements.

Conclusion

Today, the utility industry has rallied behind the Smart Grid as a way to make valuable infrastructure

improvements, increase customer options, and improve efficiency. Along the way, the Smart Grid will

require not only new hardware like smart meters and sensors but also major new software functions

that can maximize hardware and business process performance.

ADM is the emerging umbrella term for the set of advanced functions that will turn today’s

distribution grid into the Smart Grid of tomorrow. By analyzing the massive amounts of new data

generated by Smart Grid hardware and by making that analysis available across the utility enterprise,

ADM speeds cost recovery for Smart Grid investments, delays the need to construct new central

generation, and provides a flexible grid-management platform that can accommodate emerging

demands.

5 Gartner, Inc., Market Definition: Advanced Distribution Management System Products, Randy Rhodes and Zarko Sumic,, 14 December 2010.

The same way advanced metering infrastructure (AMI) is perceived as a cornerstone of the smart grid that can deliver

customer-related and social benefits, utility companies are increasingly looking for the product that can be a cornerstone in

delivering utility-centric infrastructure benefits. Among all technologies listed in the smart grid Hype Cycle, ADMS is in the best

position to be that cornerstone.

Randy Rhodes, Gartner5

Advanced Distribution Management

August 2011

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