A new hybrid GA–GSA algorithm for tuning damping controller parameters for a unified power flow controller

•A new hybrid GA–GSA algorithm is proposed for FACTS based damping controller design.•The performance of the algorithm is tested with some standard bench-mark function.•Simulation results are presented and compared with other conventional techniques. Tuning of damping controller parameters for optim...

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Veröffentlicht in:	International journal of electrical power & energy systems Jg. 73; S. 1060 - 1069
Hauptverfasser:	Khadanga, Rajendra Ku, Satapathy, Jitendriya Ku
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.12.2015
Schlagworte:	Damping controller Flexible AC transmission systems (FACTS) Hybrid Genetic–Gravitational Search Algorithm (hGA–GSA) Modified Heffron–Phillips (P–H) model Unified power flow controller (UPFC) Damping controller Hybrid Genetic–Gravitational Search Algorithm (hGA–GSA) Modified Heffron–Phillips (P–H) model Flexible AC transmission systems (FACTS) Unified power flow controller (UPFC)
ISSN:	0142-0615, 1879-3517
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Zusammenfassung:	•A new hybrid GA–GSA algorithm is proposed for FACTS based damping controller design.•The performance of the algorithm is tested with some standard bench-mark function.•Simulation results are presented and compared with other conventional techniques. Tuning of damping controller parameters for optimal setting, such as gain and signal wash out block parameters, has major effects on its performance improvement. Estimation of optimum values for these parameters requires reliable and effective training methods so that the error during training reaches its minimum. This paper presents, a suitable tuning method for optimizing the damping controller parameters using a novel hybrid Genetic Algorithm–Gravitational Search Algorithm (hGA–GSA). The primary purpose is that the FACTS based damping controller parameter can be optimized using the proposed method. The central research objective here is that, how the system stability can be improved by the optimal settings of the variables of a damping controller obtained using the above proposed algorithm. Extensive experimental results on different benchmarks show that the hybrid algorithm performs better than standard gravitational search algorithm (GSA) and genetic algorithm (GA). In this proposed work, the comparison of the hGA–GSA algorithm with the GSA and GA algorithm in term of convergence rate and the computation time is carried out. The simulation results represent that the controller design using the proposed hGA–GSA provides better solutions as compared to other conventional methods.
ISSN:	0142-0615 1879-3517
DOI:	10.1016/j.ijepes.2015.07.016