REAL TIME BALANCING OF SUPPLY AND DEMAND IN SMART GRID BY USING STORAGE, CONTROLLABLE LOADS AND SMART

GENERATIONS

Abdulfetah Shobole, Dr. Arif Karakaş Yildiz Technical University Department of Electrical Engineering

Yildiz Technical University, Department of Electrical Engineering

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Outline

1. Why to balance between generation

and supply?

2. What are the couses of mismatch?

3. How to balance the mismatch?

4. The proposed method.

5. Modeling and Simulation.

6. Results and Conclusion.

2

Why to balance between generation and supply?

– To make the system stable– For maintaining frequency– Prevent black outs due to cascading outages

BALANCE

3

What are the couses of mismatch?

– Consumption change with time.

– Intermittent Energy Sources

– Contingencies

4

How to balance the mismatch?• In Traditional Power System.

– Deterministic ahead of time dispatching– Through telephone communication and paper. – The balancing is done by controlling the

conventional generations with reserve.

5

How to balance the mismatch?• In Smart Grid.

– The operation component in SG model is concerned with managing the energy flow in Smart grid.

– Balancing demand and supply in real time is one of the characteritics of Smart Grid.

– Demand response and Storages in addition to conventional generations.

from NERC 6

The Proposed Method

Data are automatically read from power system– Smart communication

technologies are involved.– AMI for the loads– WASA

• Generations • Storage• Metrological data• Contingencies

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The Proposed Method

Yes

Yes

Yes

No

No

No

Is the available storage

enough for frequecy control?

Are the available

loads enough for frequency control?

Calculate the left share for the next step and

set the available storage.

Is the balance achieved?

Calculate the left share for the next step and Adjust the

available Load.

UpdateLoad dataGeneration dataStorageFrom AMI, WASA, Smart grid data servers, market data servers, etc.

Adjust the storage to reset the mismatch

.

Adjust the loads to reset the mismatch

.

Start

Adjust Distributed Generation

s.

Is adjusting DGs feasabl

e?

Adjust convention

al Generation

s.

NoYes

Make decisions in Real Time Optimize the decisions by

considering the situations DGs are considered as VPP

by aggregating their output. Use all the available

apportunities Demand response Storage Conventional generations Distributed generations

Take your share and pass to the next algorithim is used.

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DigSilentPowerFactory It is Commercial has the ability to simulate load flow, RMS

fluctuations and transient events in the same software environment

It has programming feature (DigSilent Programming Language)

The Modeling and Simulation

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The Modeling and Simulation

The DigSilent Network model to test the proposed algorithm. 10

Simulation Results and Conclusion

Generation from DGs, Generation from Conventional Power Power Plants, Total

Generation

The storage system tracks the variation from the DGs and resetting the mismatch

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Simulation Results and Conclusion

Storage, Controllable load and smart generation are involved in adjusting mismatch

Generation from DGs, Generation from Conventional Power Power Plants, Total

Generation

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Simulation Results and ConclusionThe smart grid enables the power system to be more efficient and

stable, especially when renewable energy systems which are intermittent resources.

In smart grid it is possible to integrate renewable energy systems and handle the mismatch between demand and supply by controlling the system in real time. This requires the access to data from generations, loads, storage systems, energy markets, etc. This is possible in smart grid due to communication, information and sensor infrastructures laid throughout the electricity network.

The system mismatch can be handled even if the ratio of the renewable energy resources in the system is very high.

The proposed method is also applicable for the variation of the load or any other contingency conditions that disturb the balance between demand and supply. The order of choice of the controller whether to use storage, controllable loads, smart generations or load shading depends on the factors like available capacity, environmental data, market data, location of the resources, etc.

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