Modeling and Simulation ofa DG-Integrated Intelligent Microgrid

Lead PIs: Saifur Rahman (srahman@vt.edu) and Manisa Pipattanasomporn (mpipatta@vt.edu)Student: Shengnan Shao (sshao@vt.edu)Institute: Virginia Tech – Advanced Research Institute, Arlington, VA 22203

esearch Objective:esearch Objective: The objective of the proposed work is to model and simulate a specialized microgridcalled an Intelligent Distributed Autonomous Power Systems (IDAPS), which will play a crucial role in building ascalable power grid that facilitates the use of renewable energy technologies.

RR

BB ackgroundackground::

The electric power system is an enabling infrastructurethat supports the continuous operation of variousmission critical facilities, both at the component andthe systems levels. For example, a reliable, efficient andsecure power system is necessary for the operation ofcritical buildings in a base or the whole base itself. Thisis also applicable for deployed force in forward bases,which have to be put into service quickly and reliably.At present, there is a need to design a distributed andautonomous subset of a larger grid or a microgrid toincrease the security and reliability of electricity supplyin such facilities. This microgrid must be capable ofintelligently controlling and networking a variety oflocal distributed energy resources (DERs) that includerenewable energy technologies to reduce the use offossil fuels.

IIntelligent ntelligent DDistributedistributed

AAutonomous utonomous PPower ower SSystemsystems

Aims at:Intelligently controlling and coordinating internalloads and various supply alternatives to achieve

any mission-based environmental, operationaland economic performance criteria

Normal Operating

Upstream Outage

• Is complementary to the main grid• Optimize the operation of internal generation and loads• Perform demand management

• Island from the grid and operate autonomously• Perform adaptive load shedding to secure critical loads

The technical approach for modeling and simulation of anIDAPS microgrid consists of the following five steps:

Task 1: the development of IDAPS physical components inMatlab/Simulink – which include a distribution network, DERsand loads;

Task 2: the development of local control algorithms tocontrol each DER and loads in an IDAPS microgrid;

Task 3: the development of an IDAPS energy managementsystem based on multi-agent technologies that follow theIEEE standard on Foundation for Intelligent Physical Agents(FIPA);

Task 4: the demonstration of how a connection between theIDAPS physical components and the IDAPS decision supportsystem can be established using addressable IP-basedcommunication interfaces;

Task 5: the simulation and evaluation of the IDAPSmicrogrid in both parallel and islanded operations to ensurethat the IEEE 1547 standard for interconnecting distributedresources with electric power systems are followed.

rocessrocess & Technologies & TechnologiesPP

A distributed and autonomous subset of thelarger grid that can increase the security of

energy supply.

Cyber layer

Physical LayerIDAPS Building Blocks comprise both physical and

cyber layers.

ER technologies ER technologiesSolar cells

Wind turbines

Fuel cells

Electric vehicles

Diesel gensets

Microturbines

Storage devices

DDDER = Distributed Energy Resources

Modeling and Simulation ofa DG-Integrated Intelligent Microgrid

Lead PIs: Saifur Rahman (srahman@vt.edu) and Manisa Pipattanasomporn (mpipatta@vt.edu)Student: Shengnan Shao (sshao@vt.edu)Institute: Virginia Tech – Advanced Research Institute, Arlington, VA 22203

2 4 6 8 10 12 14 16 18 20 22 240

2

4

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14

16

18

Time(hour)

Load Demand(kWh)

Summer Load Curve for One Distribution Feeder with Seven Houses

SpaceCoolingWaterHeatingCookingClothesDryingRefrigerationFreezingLightingOther

2 4 6 8 10 12 14 16 18 20 22 240

2

4

6

8

10

12

14

16

18

20

Time(hour)

Load Demand(kWh)

Winter Load Curve for One Distribution Feeder with Seven Houses

SpaceHeatingWaterHeatingCookingClothesDryingRefrigerationFreezingLightingOther

From EPRI-RELOAD Database

Load Model Load Model

Household load Types: spaceheating, space cooling, waterheating, cooking, cloth drying,refrigeration, lighting and others.

Winter Peak: January

Summer Peak: August

Distributed Energy Resource ModelDistributed Energy Resource Model

Solar PV Module: Wind turbine:

Microturbine: Battery & Electric Vehicle:

Internal Combustion Engine:Fuel cells:

Distribution Network ModelingDistribution Network Modeling

Step-uptransformer

Generation

<30kV

Transmission

230, 345,500kV

Switchyard

Transformer Information:

Single phase or three-phase distributiontransformer: 12.47kV/240V, 25-100kVAData source: VTES (Virginia Tech Electric Service)

69, 115kV

Distribution

12.47kV

Distribution Substation

Customers utilization voltage120V, 208V, 240V, 277V, 480V

Distributiontransformer

Droop ControlDroop Control

Voltage

Reactive Power

Voltage

V0

VﾕVΔ

1QΔ 2QΔ

m1 m2

Q1 Q’1 Q2 Q’2 Reactive Power

Frequency

Active Power

Frequency

Active Power

f0

f1fΔ

1PΔ 2PΔ

k1 k2

P1 P’1 P2 P’2

• Operate in islanding Mode

• Use as a back up for Agent Control

• Distribute load according to DG size

• Maintain system’s voltage and frequency

f-P DroopV-Q Droop

Δf=-k1ΔP1=-k2ΔP2 ΔV=-m1ΔQ1=-m2ΔQ2

Modeling and Simulation ofa DG-Integrated Intelligent Microgrid

Lead PIs: Saifur Rahman (srahman@vt.edu) and Manisa Pipattanasomporn (mpipatta@vt.edu)Student: Shengnan Shao (sshao@vt.edu)Institute: Virginia Tech – Advanced Research Institute, Arlington, VA 22203

esearch esearch Tasks and TimelineTasks and TimelineRR

FY08, Q2

Start6/11/08

FY08, Q3 FY08, Q4 FY09, Q1 FY09, Q2 FY09, Q3

Today12/04/08

End09/09/09

Task 1: Build IDAPS physical componentsTask 2: Develop local control algorithmsTask 3: Develop an IDAPS agent-based energy management systemTask 4: Establish addressable IP-based communication interfacesTask 5: Simulate the IDAPS microgrid and validate the results

Droop Control: Simulation ResultsDroop Control: Simulation Results

0 0.05 0.1 0.15 0.2 0.25 0.30

10

20

30

40

50Active Load

Time(sec)

P

L

o

a

d

(

k

W

)

0 0.05 0.1 0.15 0.2 0.25 0.30

1

2

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5Reactive Load

Time(sec)

Q

L

o

a

d

(

k

V

a

r

)

Agent-Technology and TCP/IP ConnectionAgent-Technology and TCP/IP Connection

Database AgentStoring system information, recording

the messages and data, serving as a data access point for other agents

Control AgentMonitoring system voltage and frequency,

receiving electricity price signal from the main gridpublishing information to the rest of IDAPS entities

DER AgentStoring DERinformation,monitoring

andcontrollingDER power

levels and itsON/OFFstatus

User AgentActing as a

usergateway,providingusers withreal-time

informationof entitiesresiding inthe IDAPS

system

The implementation of an IDAPS microgrid in a missioncritical facility optimizes the operation of internalgeneration and loads during normal conditions andincreases the security of energy supply to critical loadsby shedding non-critical loads during emergencies. TheIDAPS control agents have an embedded intelligencethat works in collaboration with local controllers tocoordinate both DERs and loads to achieve anymission-based environmental, operational andeconomic performance criteria. The proposed approachonce validated is believed to help remove certainbarriers in the interconnection and control of DER unitsin a microgrid environment. As a result, the IDAPSmodel will help facilitate the use of cleaner, greenerand more efficient distributed energy resources,including renewable energy technologies,microturbines, fuel cells, storage devices and plug-inhybrid electric vehicles.

enefitsenefitsBB

SimulationSetup