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By: Mahdi Zolfaghari Load Sharing Improvement Between Parallel-Connected Inverter based DGs Using a GA based Optimization Control Strategy in Microgrids
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Load Sharing Improvement Between Parallel- Connected Inverter based DGs Using a GA based Optimization Control Strategy in Microgrids

Apr 15, 2017

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Page 1: Load Sharing Improvement Between Parallel- Connected Inverter based DGs Using a GA based Optimization Control Strategy in Microgrids

By: Mahdi Zolfaghari

Load Sharing Improvement Between Parallel-Connected Inverter based DGs Using a

GA based Optimization Control Strategy in

Microgrids

Page 2: Load Sharing Improvement Between Parallel- Connected Inverter based DGs Using a GA based Optimization Control Strategy in Microgrids

Aims of The PaperStudying the load sharing problem among

DGs in microgrid

Analysis of the effects of changing in the line impedance on the load sharing between DGs

Introducing an improvement to the commonly used IACS(instantaneous average current control scheme)

Page 3: Load Sharing Improvement Between Parallel- Connected Inverter based DGs Using a GA based Optimization Control Strategy in Microgrids

Problem Statements

• A desired load sharing is an important challenge with the future microgrids

• Undesired load sharing results in:A circulating current among DGsUnbalanced sharing of active and reactive

powers between DGsVoltage drop and power loss

Page 4: Load Sharing Improvement Between Parallel- Connected Inverter based DGs Using a GA based Optimization Control Strategy in Microgrids

Related Works

• In [2], a master-slave control approach was proposed.

The main disadvantage of this method is its poor reliability

• In [3,4], a strategy based on the conventional voltage and frequency droop

a well-known limitation, in which an inherent tradeoff exists between the output voltage regulation and power sharing accuracy.

Page 5: Load Sharing Improvement Between Parallel- Connected Inverter based DGs Using a GA based Optimization Control Strategy in Microgrids

Contribution of the paper• Overall diagram of the IACS

Page 6: Load Sharing Improvement Between Parallel- Connected Inverter based DGs Using a GA based Optimization Control Strategy in Microgrids

Contribution of the paper• conventional PI Based IACS Controller

Page 7: Load Sharing Improvement Between Parallel- Connected Inverter based DGs Using a GA based Optimization Control Strategy in Microgrids

Contribution of the paper• Proposed OPI Based IACS Controller

Page 8: Load Sharing Improvement Between Parallel- Connected Inverter based DGs Using a GA based Optimization Control Strategy in Microgrids

Contribution of the paper

• Flowchart of optimizing the OPI using GASTART

Create initial population

Applied in concentration

control

Evaluate objective

function, ITAE

Fitness selection

Is termination criteria reached?

Create new population by reproduction,

crossover, mutation

Optimal PI parameters

End

Yes

No

t

dtvtITAE0 0

Optimization index:

Page 9: Load Sharing Improvement Between Parallel- Connected Inverter based DGs Using a GA based Optimization Control Strategy in Microgrids

Simulation Results• Case I: the resistance of transmission line 1, is reduced from

0.8Ω to 0Ω in 0.1Ω steps

Page 10: Load Sharing Improvement Between Parallel- Connected Inverter based DGs Using a GA based Optimization Control Strategy in Microgrids

Simulation Results• Case II: The inductance of transmission line 2 is increased

from 0mH to 0.5mH in 0.1mH steps

Page 11: Load Sharing Improvement Between Parallel- Connected Inverter based DGs Using a GA based Optimization Control Strategy in Microgrids

Discussion• The parameters of the PI controller were tuned by

conventional Zeigler-Nichols method and obtained as: Kp=3.7, Ki=1.8

• For the two cases, the load is considered with lagging power factor as 1000 W, 400 VAr and the voltage at load bus is 230 V, 50 Hz and the DC side voltage of inverter is 400 V.

• For case I, circulating current by using the PI controller is 0.3A whereas it is reduced to 0.2 A by using the OPI

• For case II, the PI controller reduces the circulating current to 0.4 A while the OPI reduces to 0.18 A. The reactive power difference: is 280 VAr when using PI and it is 100 VAr by implementing OPI

Page 12: Load Sharing Improvement Between Parallel- Connected Inverter based DGs Using a GA based Optimization Control Strategy in Microgrids

Conclusiono Microgrids are an essential parts of future smart gridso A desired load sharing between DGs is in important

challengeo This work presented an improvement to the IACS

strategyo The parameters of the controller were optimally tuned

using GAo The simulation results indicated the effectiveness of

the controller

Page 13: Load Sharing Improvement Between Parallel- Connected Inverter based DGs Using a GA based Optimization Control Strategy in Microgrids