akıllı Şebekeler ve enerji yönetim

Akıllı Şebekeler ve Enerji Yönetim

Sistemleri Hacettepe Üniversitesi - SEC510

Enerji Sektöründe Mühendislik/ 22.03.2019

Erk Dursun / RC-TR EM DG R&DSiemens 2019

SEC510 - Enerji Sektöründe Mühendislik

03.2019 Erk Dursun / RC – TR EM DG R&D CCA

Smart Grids & Energy Management SystemsTable of content

• Fundementals of Power Systems

• Smart Grids from NIST Perspective

• An overview about Turkish Electricity Market

• Fundementals of Distribution Management Systems

• Network Analysis Tools to Analyze and Optimize the Network



Electrical Power SystemsFundementals

The Four Main Elements in Power Systems:

• Power Production / Generation

• Power Transmission

• Power Distribution

• Power Consumption / Load



Electrical Power SystemsControl Challanges on Power Systems

• The system must be able to meet the continually

changing load demand

• The power system should supply energy at minimum

cost and minimum ecological impact

• The quality of power supply must meet certain

minimum standards:

• Constancy of frequency

• Constancy of voltage

• Level of reliability

“Electricity cannot be stored directly as electrical

energy unless converted into another form”

Fundamental principle and very important characteristic of

electricity:

Production = Consumption

Exactly when a bulb is lighted some

generator will deliver power

Exactly when a power plant is

stopped, the corresponding power

will be delivered from another plant

instead

Main Objectives Main Challenges



Electrical Power SystemsTransformation of Power Systems

Traditional Power Grid:

Centralized, bulk generation

Heavy reliance on coal and oil

Limited automation

Limited situational awareness

Consumers lack data to

manage energy usage



Electrical Power SystemsTransformation of Power Systems

Smart Grid:

“Smart grid” generally refers to a class of technologies

that people are using to bring utility electricity delivery

systems into the 21st century, using computer-based

remote control and automation. These systems are

made possible by two way digital communications

technologies and computer processing that has been

used for decades in other industries. They are beginning

to be used on electricity networks, from the power

plants and wind farms all the way to the consumers of

electricity in homes and businesses. They offer many

benefits to utilities and consumers -- mostly seen in big

improvements in energy efficiency and reliability on

the electricity grid and in energy users’ homes and

offices.

U.S. Department of Energy (DoE)



NIST Conceptual Reference Model for Smart GridAnticipated Smart Grid Benefits

1. Improving Power Reliability and Quality

– Better monitoring using sensor networks and communications

– Better and faster balancing of supply and demand

2. Minimizing the Need to Construct Back-up (Peak Load) Power

Plants

– Better demand side management

– The use of advanced metering infrastructures

3. Enhancing the capacity and efficiency of existing electric grid


– Consequently, better control and resource management in real-time

4. Improving Resilience to Disruption and Being Self-Healing


– Distributed grid management and control

5. Expanding Deployment of Renewable and Distributed Energy

Sources


– Consequently, better control and resource management in real-time

– Better demand side Management

– Better renewable energy forecasting models

– Providing the infrastructure / incentives



NIST Conceptual Reference Model for Smart GridAnticipated Smart Grid Benefits (cont.)

6. Automating maintenance and operation


– Distributed grid management and control

7. Reducing greenhouse gas emissions

– Supporting / encouraging the use of electric vehicles

– Renewable power generation with low carbon footprint

8. Reducing oil consumption

– Supporting / encouraging the use of electric vehicles

– Renewable power generation with low carbon footprint

– Better demand side Management (Q: Why?)

9. Enabling transition to plug-in electric vehicles

– Can also provide new storage opportunities

10. Increasing consumer choice

– The use of advanced metering infrastructures

– Home automation

– Energy smart appliances

– Better demand side Management



NIST Conceptual Reference Model for Smart GridCustomer Domain

Example

Application

Description

Building or Home

Automation

A system that is capable of controlling various functions within a

building, such as lighting and temperature control.

Industrial

Automation

A system that controls industrial processes such as manufacturing or

warehousing. These systems have very different requirements

compared to home and building systems.

Micro-generation

Includes all types of distributed generation including: solar, wind, and

hydroelectric generators. Generation harnesses energy for electricity

at a customer location. May be monitored, dispatched, or controlled

via communications.

Storage

Means to store energy that may be converted directly or through a

process to electricity. Examples include thermal storage units, and

batteries (both stationary and electric vehicles)



NIST Conceptual Reference Model for Smart GridMarket Domain

Example

Application

Description

Market

Management

Market managers include ISOs for wholesale markets or New York

Mercantile Exchange (NYMEX)/ Chicago Mercantile Exchange

(CME) for forward markets in many ISO/RTO regions. There are

transmission, services, and demand response markets as well.

Some DER Curtailment resources are treated today as dispatchable

generation.

Retailing

Retailers sell power to end-customers and may in the future

aggregate or broker DER between customers or into the market.

Most are connected to a trading organization to allow participation in

the wholesale market.

DER Aggregation

Aggregators combine smaller participants (as providers, customers,

or curtailment) to enable distributed resources to play in the larger

markets.

Trading

Traders are participants in markets, which include aggregators for

provision, consumption, curtailment, and other qualified entities.

There are a number of companies whose primary business is the

buying and selling of energy.

Market Operations

Market operations make a particular market function smoothly.

Functions include financial and goods-sold clearing, price quotation

streams, audit, balancing, and more.

Ancillary

Operations

Ancillary operations provide a market to provide frequency support,

voltage support, spinning reserve, and other ancillary services as

defined by FERC, NERC, and the various ISOs. These markets

normally function on a regional or ISO basis.



NIST Conceptual Reference Model for Smart GridService Provider Domain

Example

Application

Description

Customer

Management

Managing customer relationships by providing point-of-contact and

resolution for customer issues and problems.

Installation &

Maintenance

Installing and maintaining premises equipment that interacts with the

smart grid.

Building

Management

Monitoring and controlling building energy and responding to smart

grid signals while minimizing impact on building occupants.

Home

Management

Monitoring and controlling home energy and responding to smart

grid signals while minimizing impact on home occupants.

BillingManaging customer billing information, including providing billing

statements and payment processing.

Account

ManagementManaging the supplier and customer business accounts.



NIST Conceptual Reference Model for Smart GridOperations Domain

Example

Application

Description

Monitoring Network operation monitoring roles supervise network topology, connectivity, and loading conditions, including

breaker and switch states, as well as control equipment status. They locate customer telephone complaints

and field crews.

Control Network control is coordinated by roles in this domain. They may only supervise wide area, substation, and

local automatic or manual control.

Fault

Management

Fault management roles enhance the speed at which faults can be located, identified, and sectionalized, and

the speed at which service can be restored. They provide information for customers, coordinate workforce

dispatch, and compile information statistics.

Analysis Operation feedback analysis roles compare records taken from real time operation related with information on

network incidents, connectivity, and loading to optimize periodic maintenance.

Reporting and

Statistics

Operational statistics and reporting roles archive online data and perform feedback analysis about system

efficiency and reliability.

Network

Calculations

Real-time network calculations roles (not shown) provide system operators with the ability to assess the

reliability and security of the power system

Records and

Assets

Records and asset management roles track and report on the substation and network equipment inventory,

provide geospatial data and geographic displays, maintain records on non-electrical assets, and perform

asset-investment planning.

Operation

Planning

Operational planning and optimization roles perform simulation of network operations, schedule switching

actions, dispatch repair crews, inform affected customers, and schedule the importing of power. They keep the

cost of imported power low through peak generation, switching, load shedding, DER or demand response.

Maintenance

and

Construction

Maintenance and construction roles coordinate inspection, cleaning, and adjustment of equipment; organize

construction and design; dispatch and schedule maintenance and construction work; and capture records

gathered by field technicians to view necessary information to perform their tasks.

Extension

Planning

Network extension planning roles develop long-term plans for power system reliability; monitor the cost,

performance, and schedule of construction; and define projects to extend the network, such as new lines,

feeders, or switchgear

Customer

Support

Customer support roles help customers to purchase, provision, install, and troubleshoot power system

services. They also relay and record customer trouble reports.



NIST Conceptual Reference Model for Smart GridGeneration Domain

Example

Application

Description

Control

Performed by roles that permit the Operations domain to manage the

flow of power and the reliability of the system. Currently a physical

example is the use of phase-angle regulators within a substation to

control power flow between two adjacent power systems.

Measure

Performed by roles that provide visibility into the flow of power and

the condition of the systems in the field. In the future, measurement

might be built into increasingly more discrete field devices in the grid.

Currently, an example is the digital and analog measurements

collected through the supervisory control and data acquisition

(SCADA) system from a remote terminal unit and provided to a grid

control center in the Operations domain.

Protect

Performed by roles that react rapidly to faults and other events in the

system that might cause power outages, brownouts, or the

destruction of equipment. Performed to maintain high levels of

reliability and power quality. May work locally or on a wide scale.

Record

Performed by roles that permit other domains to review what

happened on the grid for financial, engineering, operational, and

forecasting purposes.

Asset Management

Performed by roles that work together to determine when equipment

should have maintenance, calculate the life expectancy of the

device, and record its history of operations and maintenance so it

can be reviewed in the future for operational and engineering

decisions.



NIST Conceptual Reference Model for Smart GridTransmission Domain

Example

Application

Description

Substation The control and monitoring systems within a substation

StorageA system that controls the charging and discharging of an energy

storage unit.

Measurement &

Control

Includes all types of measurement and control systems to measure,

record, and control, with the intent of protecting and optimizing grid

operation.



NIST Conceptual Reference Model for Smart GridDistribution Domain

Example

Application

Description

Substation The control and monitoring systems within a substation.

StorageA system that controls the charging and discharging of an energy

storage unit.

Distributed

GenerationA power source located on the distribution side of the grid.

DEREnergy resources that are typically located at a customer or owned

by the distribution grid operator.

Measurement &

Control

Includes all types of measurement and control systems to measure,

record, and control, with the intent of protecting and optimizing grid

operation.



Smart Grid ApplicationsA Use Case: Demand Response

A typical residential load profile with and without PHEVs in

California:

Demand response (DR) is defined as

changes in electric usage by end ‐use

customers from their normal consumption

patterns in response to changes in the price

of electricity over time, or to incentive

payments designed to induce lower electricity

use at times of high wholesale market prices

or when system reliability is jeopardized.

U.S. Department of Energy




In Direct Load Control:

The utility has remote access to certain load of users

• Air conditioner

• Water heater.

It remotely turns on or off the load when ever needed.

An alternative for DLC is smart pricing.

Instead of directly controlling customers’ load,

Let them know about the price changes:

They will naturally try to avoid higher price hours: This will

reduce the load at peak hours.

Users are directly involved in decision making




The users should be informed about prices (price

changes):

• Utility Website

• Email

• Text Message

• Automated Voice Calls

• Energy Orbs [We will learn about it soon]

• Smart Meter




Can help users understand smart pricing and DR but DR

decision making can still be difficult task for users.

Solution: Automated Energy Consumption Scheduling

(ECS)

• Could be Part of Smart Meter

• Could be Part of Energy Detective Device

• Could be a Separate Device



Electricity Market in TurkeyAn Overview

As of 2010: for a population of 73 million,

Energy consumed per person = 2,870 kWhr/year

World average: 2,700 kWhr/year

OECD average: 8,700 kWhr/year,

European average: 5,200 kWhr/year

Norway: 26,300 kWhr/year, USA: 13,800

kWhr/year, Germany: 7,000 kWhr/year, Italy:

5,700 kWhr/year, Greece: 5,300 kWhr/year

In 1980: Turkey: 500 kWhr/year, World average:

1500 kWhr/year



Electricity Market in TurkeyAn Overview



Electricity Market in TurkeyDeregulation, private investments, competition/market environment, trading

The electric power industry is undergoing the most

profound changes in its history. The disintegration of

the vertically integrated industry structure is resulting

in the unbundling of products and services and the

advent of new players and structures. The cooperative

and collegial environment of the past in which the

obligation to serve was of paramount importance is

rapidly being replaced by a fiercely competitive

atmosphere of contracts and markets. The significant

and wide-ranging legislative and regulatory

developments in many countries serve to spur on

these developments at an even more frantic pace. The

engineering, planning, operations and control that

evolved in the vertically integrated industry structure

are themselves changing to reflect the new realities of

the emerging regime.



Electricity Market in TurkeyUnbundling Process



Electricity Market in TurkeyHistorical Development Process



Electricity Market in TurkeyMarket Actors



Electricity Market in TurkeyAvailable Markets



Distribution Management SystemsChallenges for DSOs

Fast and reliable actions

should be taken by DSO

within technical and

regulatory constraints to

provide sustainable

customer demand

Difficulty to supply continuous increase in

demand by using old infrastructure

Growing regulations to provide reliability and

costumer satisfaction

Financial and regulatory pressure to operate

the grid more efficiently

Dependency to experienced operator who

knows the details of distribution system

Event based data handling & reporting

Increasing complexity of distribution grids like

distributed generation, electricity vehicles, etc.



Why do we need DMS? Increasing Demand












2016 Yılı Sonu İtibariyle Dağıtım Sistemini Kullanan Tüketici Sayıları (Adet-%)Elektrik

Piyasası 2016 Yılı Piyasa Gelişim Raporu, EPDK, Page 64

Ahmad Faruqui, Ryan Hledik, Sam Newell, Hannes

Pfeifenberger, “The Power of 5 Percent”, The Electricity

Journal, Volume 20, Issue 8, October 2007, Pages 68- 77



Why do we need DMS? Regulations

Kullanıcılara ödenecek tazminatın

hesaplanması ve ödenmesi

MADDE 16- (1)[1] Bildirimsiz kesintiler için

Tablo 9’da belirlenen sınır değerler

aşıldığında dağıtım şirketi bu maddede

belirlenen esaslar çerçevesinde kullanıcıya

başvurusuna gerek duyulmaksızın tazminat

öder.

2016 Yılı Dağıtım Şirketlerinin Müşteri Başına Bildirimli ve

Bildirimsiz Ortalama Kesinti Süreleri (dk),Elektrik Piyasası 2016 Yılı

Piyasa Gelişim Raporu, EPDK, Page 73

Elektrik Dağıtımı ve Perakende Satışına İlişkin Hizmet Kalitesi

Yönetmeliği, EPDK



Growing regulations to provide reliability

and costumer satisfaction










Why do we need DMS? Efficiency

Difficulty of supplying continuous increase in




Financial and regulatory pressure to

operate the grid more efficiently


knows the details of grid



distributed generation, electricity vehicles, etc. Dağıtım Şirketleri Kayıp Oranı (%),Elektrik Piyasası 2016 Yılı Piyasa Gelişim

Raporu, EPDK, Page 65


Yönetmeliği, EPDK



Why do we need DMS? Digitalization














Why do we need DMS? Historical Data & Reporting













Yönetmeliği, EPDK



Why do we need DMS? Technical requirements












IPPs

Industrial

Zones

Distributed

Generation

Distribution

Network



Why do we need DMS?Benefits

DMS provides tools for dynamic visualization, monitoring and

control of electricity distribution network, together with a wide set of

power applications for operation analysis, planning and

optimization. The system is built on open standard solutions and

together with integration with SCADA, GIS, AMI, DRMS and other IT

systems in a utility.

Advanced monitoring and control of distribution network

Efficient utilization of existing distribution facilities and

postponement of investments

Reduction of power losses and network outage and

maintenance costs

Increase of revenue and profit.

Improvement of power quality and customer services

Support to justified development and construction of

distribution facilities



Fundementals of Distribution Management SystemsOverview

Monitor, control and optimize the

secure operation of the electrical

distribution network.

Proactively and safely guide

operators when needed most,

i.e. during storms and outage-

related restoration activities.

Reduce network loading at

peak times and increase asset

utilization, network efficiency

and reliability.

Monitor & Operate

Analyze & OptimizeTrack & Restore



Fundementals of Distribution Management SystemsMonitor & Operate

Increased operational efficiency

• Advanced topologic coloring and tracing in single phase

and three phase distribution networks

• Extended tracing for outages, trouble calls,

crews, etc.

• Easy-to-create switching procedures

• Visualization of switch plan and corresponding

topology changes before execution

• Online – editable Temporary Network Elements (TNEs)

• Flexible Load Shedding

Monitor & Operate




Fundementals of Distribution Management SystemsMonitor & Operate

Main Modules for Monitor & Control

Redundant

Data

Sources

User Input

Communication

Alarm Processing

Topology Processing

Common Calculation

Measure-

ment

Value

Monitoring

Control

Supervisory

Control

User Input

Communication

Application

Command

LoggingFlags & Tags



Fundementals of Distribution Management SystemsTrack & Restore

Faster detection and resolution

of outages – improved

performance indicators Outage Prediction

Trouble Call Management (TCM)

Crew Management (CM)

Storm Management

Integration with 3rd party systems (MDM, CIS, IVR, AMS, …)

• Real-time update of probable fault

location

• Leverage internal and external data for

outage prediction and resolution

• Optimal crew proposal and auto-

dispatch

• Automatic calculation of performance

indicators (SAIDI, ...)

• Visualization of outages, crews and

calls on maps

• Integration with mobile field devices



Fundementals of Distribution Management SystemsOutage Management – Outage Prediction (simplified)

Predicted

Local Service Outage

110 kV

20 kV

T1 T2

CB1 CB2

Substation

Transformer

Substation

Transformer

Substation

FT1

T5

CB3

T3 T4

T6 T7

S1

10 6

7 3

F1

2

Single

customer call

Confirmed

Local Service Outage

Field crews verifies the outage &

operator changes outage status.




110 kV

20 kV

T1 T2

CB1 CB2

Substation

Transformer

Substation

Transformer

Substation

FT1

T5

CB3

T3 T4

T6 T7

S1

10 6

7 3

F1

2

Several

customer calls


operator updates switch position

Predicted

Transformer Outage

Confirmed

Transformer Outage




110 kV

20 kV

T1 T2

CB1 CB2

Substation

Transformer

Substation

Transformer

Substation

FT1

T5

CB3

T3 T4

T6 T7

S1

10 6

7 3

F1

2

Several

customer calls

Several

customer calls


operator updates switch position

Predicted outage at

protective device

Confirmed outage

at protective device




110 kV

20 kV

T1 T2

CB1 CB2

Substation

Transformer

Substation

Transformer

Substation

FT1

T5

CB3

T3 T4

T6 T7

S1

10 6

7 3

F1

2

Fuzzy calls come in

fuzzy outages are created

Fuzzy Call: a call that does not

refer to a specific customer

installation e.g. ‚fallen tree hits

overhead line‘ Fuzzy Call

Field crew identifies the reason of the

fault e.g. protection tripped

an outage is created

Operator assigns the fuzzy

calls to the outage.

… or: operator identifies an already

existing outage the calls are related to



Fundementals of Distribution Management SystemsOutage Management - Workflow

Enter new

Trouble Call

Predicted

Outage

Review

Outage

Details and

Location

Assign Crew

to Assess

Fault

Repair Fault

Close Outage

Assign Crew

for Repair

Work

Assess Fault

Manual

Update of

Network

Status

Manual

Update of

Network

Status

Trouble Call Operator (Back

Office)

Operator (Control Room)

Un

pla

nn

ed

Ou

tag

e

Crew (On Site)

Smart Meter:

Power Off

Monitor & Operate




Fundementals of Distribution Management SystemsAnalyze & Optimize

Reduced network loading

at peak times and increased

efficiency and reliability

Fault Location (FLOC)

Fault Isolation and Service Restoration (FISR)

Distribution System Power Flow (DSPF)

Distribution System State Estimator (DSSE)

Short Term Load Scheduler (STLS)

Volt-/Var Control (VVC)

Optimal Feeder Reconfiguration (OFR)

• Real-time assessment of network status for

instant identification of equipment

overloads, voltage limit violations,

losses, loops, parallels, and other

abnormal operating conditions

• Ability to evaluate and optimally select

network control actions

• Improved fault location process, incl.

coordination with field crews, and

accelerated restoration of service

• Improved field crew safety and reduced

service interruptions

Monitor & Operate




Distribution System State EstimationOverview

• DSSE estimates loads (active and reactive power) based on existing measurements using weighting factors for measurements and loads

• DSSE calculates voltages for all busbars, flows through lines and transformers(active and reactive power and currents) and active and reactive power losses

• DSSE is used to assess the real-time operating conditions of the distribution network and monitor for overloads and/or voltage limit violations

• Operation from and Visualization in the one-lines

• Executes periodically, on event and on demand

Used to identify gross measurement errors and measurement inconsistencies

Provides a reliable basis for optimal network operation



Distribution System State EstimationInput / Output

Input

• P, Q, I, V measurements at substations and a limited set

of additional measurements along the feeders

• Load models

Algorithm

The estimation problem is mathematically defined as

minimization function - nearest estimate to a given

measurement set (measurement area) consisting of

• P and Q measurements

• Pseudo P and Q measurements at loads/load groups

• Current and voltage magnitude measurements

Output

• Detailed current, voltage and power information for every

single element in the network

• Voltage and thermal limit violations

• Active and reactive power losses



Distribution System State Estimation Load Adaptation and STLS - Advantages of using real measurements

1.

2.

Load

Scheduler

State

EstimatorLoad Profile

Measured P,

Q

Information

Model Manager

(IMM)

Estimated

Network State

0

0.5

1

1 3 5 7 9 11 13 15 17 19 21 23

Normalized Load Profile

1. Scaling of loads based on normalized

load profile and nominal load

2. Adaptation of loads according to

measured and estimated values

0

500

1 3 5 7 9 11 13 15 17 19 21 23

Scaled Load

Scheduled / Adapted Load



Distribution System State EstimatorHow accure?

A – averaged absolute deviation of the pre-estimated from

the measured value [%]

B – maximal absolute deviation of the pre-estimated from

the measured value [%]

C – averaged deviation of the estimated from the

measured value [%]

D– maximal absolute deviation of the estimated from the

measured value [%]

Z. J. Simendic, V. C. Strezoski, G. S.Svenda, “In-Field

Verification of the Real-Time Distribution State Estimation”,

18th International Conference on Electricity Distribution, 2005



Fault ManagementFault Location

• Handles outage faults (i.e. short-circuit

faults) and

non-outage faults (i.e. earth faults)

• Triggered on state change of fault indicators

and

feeder CB’s unexpected tripping

• Fast localization of faulty section

• Designed to determine the smallest

possible faulted section

based on available real-time information

• Essential to restore supply fast and to as

many customers as possible

• Uses remote metered and manually

updated information

Circuit

Breaker

Tripped

Faulted area

calculated by

FLOC

Fault Indicator

active / passive

Fault Indicator

active / passive



Fault ManagementFault Isolation and Service Restoration

Isolation and

restoration procedure is

calculated for faulted

area

Proposed steps are

highlighted

Once the faulty segment has been identified (e.g. by

FLOC):

• FISR finds out how to isolate the faulty

segment

• FISR finds out how to restore power to all

related

non-faulty segments

Minimizes the outage time for the affected

customers

Establishes the series of required switching

operations

Used also for outage planning (equipment isolation

for planned maintenance)



Fault ManagementWorkflow & Benefits

Popovic, D.S.; Strezoski, V.C.; Katic, N. A., "Power applications-a powerful tool for

distribution networks management,“ Electricity Distribution, 2001. Part 1:

Contributions. CIRED. 16th International Conference and Exhibition on (IEE Conf.

Publ No. 482) , vol.3, no., pp.5 pp. vol.3,, 2001



Volt/VAR CalculationOverview

DSSE detects violations

• Network is monitored continuously

by DSSE

• Voltage violations are indicated in

single line diagram and reported

as alarm

Run VVC

• VVC manual start: User selects

violated equipment, defines objective

and other settings and starts VVC

• VVC automatic start - DSSE

violations trigger VVC with

preconfigured settings

• VVC proposes switching actions for

volt / var controls to improve the

voltage profile

Forward solution

to SPM and execute

• User may review the proposed

changes/optimization

• The switching actions are

forwarded as switching procedure

to SPM (Switching Procedure

Management)

• The switching actions are

executed via SPM

• The VVC application provides distribution network

optimization, typically loss minimization, using

voltage, var and watt controls like Load Tap

Changers/Line Voltage Regulators and

Regulating Capacitors as well as Batteries

• This optimization consists in minimizing an

objective function that is user selectable as one of

the following objectives:

• Minimize violations

• Minimize power losses

• The optimization is subject to the network

constraints, i.e. the load flow equations and the

operational like. voltage, transformer, etc. limits

• VVC is executed periodically and upon events in

the real-time context and on user request in the

study context.

• All proposed switching actions can be reviewed

and forwarded to SPM for implementation



Volt/VAR CalculationBenefits

N. Katic, “Benefits of Smart Grid Solutions in Open Electricity Market”, Acta PolyTecnica Hungarica, vol.10, no:2, 2013. E. T. Jauch, “Volt/VAR management – An essential Smart Function”, Power Systems Conference and

Exposition, 2009EEIA: injected electrical energy annually into the DS



Optimum Feeder ReconfigurationOverview

DSSE detects violations

• Network is monitored continuously by

DSSE

• Violations are indicated in single line

diagram and reported as alarm

Run OFR

• Manual start:

• User selects violated part, defines

objective and other settings and starts

OFR

• Automatic start

• DSSE violations trigger OFR. OFR runs

with preconfigured settings

Forward solution

to SPM and execute

• OFR proposes switching actions to

reconfigure feeder

• User may review the proposed

changes/optimization

• The switching actions are forwarded as

switching procedure to SPM (Switching

Procedure Management)

• The switching actions are executed with

SPM

OFR determines the optimal radial

distribution network configuration,

means the specification of the normally

open switches, accounting for

equipment loading limits, voltage limit,

and feeder losses. The user may select

any combination of the following

individual objectives:

• Minimize violations

• Minimize active power losses on

feeders

• Load balancing among supply

substation transformers



Optimum Feeder ReconfigurationBenefits

G. D. Lembo, P. Petroni, C. Noce, “Reduction of Power Losses

and CO2 Emissions: Accurate Network Data to Obtain Good

Performance of DMS Systems”, CIRED, 20th International

Conferance on Electricity Distribution, Prague, Paper 1185

N. Katic, “Benefits of Smart Grid Solutions in Open Electricity Market”, Acta PolyTecnica Hungarica,

vol.10, no:2, 2013.

EEIA: injected electrical energy annually into the DS



Real World – A Case StudyOverview of Distribution System

DPS: Distribution Primary Substation

DSS: Distribution Secondary Substation

Power Peak of Distribution Network System (DNS): 50 MW

Anual Injected Electrical Energy (AIEE) from HV: 200 GWh

AIEE Price: 8.000.000$

Avarage purchase price from HV: 40$/MWh

DNS Power Losses: 10 – 15%

Anual sale energy: 170 – 180 GWh

DNS consists 80 % Residential and 20 % Industrial costumers

Katic, N.; Marijanovic, V.; Stefani, I., "Smart Grid Solutions in distribution networks Cost/Benefit

analysis," Electricity Distribution (CICED), 2010 China International Conference on , vol., no.,

pp.1,6, 13-16 Sept. 2010



Real World – A Case StudyReduction of power and energy losses

• Reduction of technical losses

Optimal Network Reconfiguration results applied in network operation

(seasonal change of open switches locations) may provide 20% reduction of

MV network technical power losses. Costs to change locations of open-

switches are insignificant. Since MV network technical energy losses

participate in AIEE with 1-3 %, the reduction of AIEE will be in range of 0,2

- 0,6 %.

Volt/Var Control will improve voltage profile in network and reduce losses,

test results give 0,4 % reduction of AIEE.

• Reduction of non-technical losses

AMR systems enables archiving of (metered) energy injection in MV feeders

and with State Estimator (calculated) technical losses on feeders and MV/LV

transformers is known, so the energy injection on LV busbars is also known. If

available DMS LV functions, technical losses in LV network can be calculated,

then using billing data of LV customers ”non-technical” losses can be

allocated (theft, bad meters). Now, distribution transformers areas can be

ranked according to non-technical losses, and available field crews sent to

critical locations for control. After controlling a theft or metering failures, the

injection of energy will be reduced, with the same or higher sale on output

side. The reduction of non-technical energy losses may reach 0,5% of

AIEE.



Real World – A Case StudyReduction of network operation costs

• Average MV feeder load is 1.25 MW and 625 costumer for each feeder

• Non-supplied energy is 2 - 2.5 MWh per average fault (2 h).

• Average failure rate of MV lines is in range of 0,2 (cables) to 0,5 (overhead) annually/km, therefore in DNS (360 km) there are approximately 140 faults/year.

• Energy non-supplied annually (ENS) is approximately 300 MWh.

• Real cost of non – delivered kWh will average 1,6 $/kWh

• Payment for the compensation of 30 Eur to every customer for outages longer than 4h. In DNS there are only 15% of outages longer than 4h

• Utility Fault Management Costs

Revenue lost (ENS=300 MWh x 40 $/MWh)= 12,000 $

One Breaker failure (300 switching on fault) ≈ 5,000 $

4 switches failures (800 switching) ≈ 16,000 $

Field crew costs (800 x 20 $/switching) ≈ 16,000 $,

Total for DNS ≈ 50.000 $

• Costumer Costs

The total annual damage to all customers in DNS =

480.000 $ (300 MWh x 1600 $/MWh)

• Penalties paid by Utility

≈20 fault’s duration are longer than 4h (140 x 0,15)

Annually penalty: 20x625x30 Eur = 375.000 Eur

• Utility Fault Management Costs

Revenue lost (ENS = 60 MWh x 40 $/MWh) ≈ 2,400 $

Breaker failures once in 2 years ≈ 2,500 $

One switch failure (300 switching) ≈ 4,000 $

Field crew costs (300 x 20 $/switching) ≈ 6,000 $,

Total for DNS ≈ 15.000 $

• Costumer Costs

The total annual damage to all customers in DNS =

90.000 $

Outage duration will shorten 5 times, down to 15 – 20 minutes (if there are

more RTUs in MV network, even shorter); besides, ENS will decrease 5

times

• Utility direct fault management annual costs will reduce 70% (35.000$

reduction), giving annual improvement of 0,4 % compared to AIEE value.

• Penalties paid by Utility (if applied) will reduce 80% (360.000$ reduction),

giving annual improvement of 4,5% compared to AIEE value.



Real World – A Case StudyReduction of network development costs and Improved Power Quality

DMS network operation optimization and planning tools enable efficient

utilization of existing distribution facilities and postponement of investments

in network constructions.

•Normally, the construction of distribution network (new customers or power

problems) increases the number of distribution transformers 1 %

annually, comparing to the total number of transformers. It also annually

increases the length of power lines for 0,5% of the total length of

power lines. In DNS, 4 new DSS and 2 km of MV power lines should be

built every year, however, with DMS, investment will be postponed and

reduced for one DSS and 500 m of MV power line. Investment will be

reduced for 20.000 $ annually.

• DMS Large Area Restoration function enables efficient solutions and

planning of large supply transformers outages in HV Substations. Available

resources in MV network and adjacent HV Substations will be more efficient

utilized and the construction of one new HV Substation postponed. Since,

every 10 years one new HV Substation should be built in DNS

(1.000.000 $ investment), investment postponement can release 50 -

100.000$ per year.

•The total postponement of network development costs in DNS (approx

80.000 $ annually) will reach 1,0 % of AIEE value.

DMS optimal voltage regulation supports on-line regulation

of on-load tap-changers (HV/MV transformers), as well as

planning of the setting of off-load tap-changers (MV/LV

transformers).

Voltages are maintained within technical limits and in optimal

level, to minimize damages to customers due to voltage

deviations and reduce active and reactive losses in

distribution network. Improved power quality can be provided

for special sensitive customers, as well as electricity sale

can be impacted by the change of voltage level

according to electricity market prices. In this way, Utility

revenue can be increased up to 1 % of AIEE value.



Real World – A Case StudyTotal Benefits & Cost Benefit Analysis

The total annual benefits of distribution automation and DMS applications, as

discussed are as follows:

2 - 3 % of AIEE value, annually, if utility does not pay penalties for outages

7,5 % of AIEE value, annually, if utility pays penalties for outages.

A utility with 1000 MW peak load is considered, then AIEE will be approximately

4000 GWh/year (1000 MW x 4000 h), with the AIEE purchase value of

approximately 160 Million $/year (4000 GWh x 40 $/ MWh). Total investment costs

in distribution automation (12,5 % of AIEE) will reach 20 Million $, with project

execution time of 2 – 3 years. Starting with the third year, benefit will be 2 % of

AIEE (3,2 Million $/year) and raise up to 5 % annually (8 Million $/year). During 10

years operation period of SCADA/DMS system, maintenance and operation cost will

reach 5 % of investment costs (approximately 1 Million $/year). Period of analysis is

10 years, as life time of HW, RTU and communication equipment (without interest rates

and time actualization for the simplicity of analysis).

Total costs: 20 Million $ investment cost + 8 Million $ operation

and maintenance costs in 10 years = 28 Million $ in 10 years

Total benefit is 54,4 Million $ in 10 years.

Cost/benefit ratio - C/B = 0,51

Profitability - B/C = Benefit / Costs = 1,94

Payback period = C/B x T = 0,51 x 10 ≈ 5 years

Smart Grid Solution with distribution automation has high profitability, because

investment will have double return in 10-year period, with 5-year payback period.

Erk Dursun – RG TR EM DG R&D CCA

Thank you for

your attention!

Erk Dursun

[email protected]

Energy Management

Smart Grid R&D

Control Center Application

Adress:

ODTU Teknokent Silikon Bloklar

Kat:1 No:1 06531 - Ankara,TURKEY

akıllı Şebekeler ve enerji yönetim

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