Optimal gravitational search algorithm for automatic generation control of interconnected power systems
An attempt is made for the effective application of Gravitational Search Algorithm (GSA) to optimize PI/PIDF controller parameters in Automatic Generation Control (AGC) of interconnected power systems. Initially, comparison of several conventional objective functions reveals that ITAE yields better...
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doaj-296cdbf4be364de489c687f767fce3ab2021-06-02T04:29:03ZengElsevierAin Shams Engineering Journal2090-44792014-09-015372173310.1016/j.asej.2014.02.004Optimal gravitational search algorithm for automatic generation control of interconnected power systemsRabindra Kumar SahuSidhartha PandaSaroj PadhanAn attempt is made for the effective application of Gravitational Search Algorithm (GSA) to optimize PI/PIDF controller parameters in Automatic Generation Control (AGC) of interconnected power systems. Initially, comparison of several conventional objective functions reveals that ITAE yields better system performance. Then, the parameters of GSA technique are properly tuned and the GSA control parameters are proposed. The superiority of the proposed approach is demonstrated by comparing the results of some recently published techniques such as Differential Evolution (DE), Bacteria Foraging Optimization Algorithm (BFOA) and Genetic Algorithm (GA). Additionally, sensitivity analysis is carried out that demonstrates the robustness of the optimized controller parameters to wide variations in operating loading condition and time constants of speed governor, turbine, tie-line power. Finally, the proposed approach is extended to a more realistic power system model by considering the physical constraints such as reheat turbine, Generation Rate Constraint (GRC) and Governor Dead Band nonlinearity.http://www.sciencedirect.com/science/article/pii/S2090447914000276Automatic Generation Control (AGC)Proportional Integral Derivative ControllerGravitational Search Algorithm (GSA)Governor dead-band nonlinearityGeneration Rate Constraint (GRC)Sensitivity |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rabindra Kumar Sahu Sidhartha Panda Saroj Padhan |
spellingShingle |
Rabindra Kumar Sahu Sidhartha Panda Saroj Padhan Optimal gravitational search algorithm for automatic generation control of interconnected power systems Ain Shams Engineering Journal Automatic Generation Control (AGC) Proportional Integral Derivative Controller Gravitational Search Algorithm (GSA) Governor dead-band nonlinearity Generation Rate Constraint (GRC) Sensitivity |
author_facet |
Rabindra Kumar Sahu Sidhartha Panda Saroj Padhan |
author_sort |
Rabindra Kumar Sahu |
title |
Optimal gravitational search algorithm for automatic generation control of interconnected power systems |
title_short |
Optimal gravitational search algorithm for automatic generation control of interconnected power systems |
title_full |
Optimal gravitational search algorithm for automatic generation control of interconnected power systems |
title_fullStr |
Optimal gravitational search algorithm for automatic generation control of interconnected power systems |
title_full_unstemmed |
Optimal gravitational search algorithm for automatic generation control of interconnected power systems |
title_sort |
optimal gravitational search algorithm for automatic generation control of interconnected power systems |
publisher |
Elsevier |
series |
Ain Shams Engineering Journal |
issn |
2090-4479 |
publishDate |
2014-09-01 |
description |
An attempt is made for the effective application of Gravitational Search Algorithm (GSA) to optimize PI/PIDF controller parameters in Automatic Generation Control (AGC) of interconnected power systems. Initially, comparison of several conventional objective functions reveals that ITAE yields better system performance. Then, the parameters of GSA technique are properly tuned and the GSA control parameters are proposed. The superiority of the proposed approach is demonstrated by comparing the results of some recently published techniques such as Differential Evolution (DE), Bacteria Foraging Optimization Algorithm (BFOA) and Genetic Algorithm (GA). Additionally, sensitivity analysis is carried out that demonstrates the robustness of the optimized controller parameters to wide variations in operating loading condition and time constants of speed governor, turbine, tie-line power. Finally, the proposed approach is extended to a more realistic power system model by considering the physical constraints such as reheat turbine, Generation Rate Constraint (GRC) and Governor Dead Band nonlinearity. |
topic |
Automatic Generation Control (AGC) Proportional Integral Derivative Controller Gravitational Search Algorithm (GSA) Governor dead-band nonlinearity Generation Rate Constraint (GRC) Sensitivity |
url |
http://www.sciencedirect.com/science/article/pii/S2090447914000276 |
work_keys_str_mv |
AT rabindrakumarsahu optimalgravitationalsearchalgorithmforautomaticgenerationcontrolofinterconnectedpowersystems AT sidharthapanda optimalgravitationalsearchalgorithmforautomaticgenerationcontrolofinterconnectedpowersystems AT sarojpadhan optimalgravitationalsearchalgorithmforautomaticgenerationcontrolofinterconnectedpowersystems |
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1721408479800852480 |