Gravitational search algorithm based optimization technique for enhancing the performance of self excited induction generator

Swati Paliwal (), Sanjay Kumar Sinha () and Yogesh Kumar Chauhan ()
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Swati Paliwal: Amity University Uttar Pradesh
Sanjay Kumar Sinha: Amity University Uttar Pradesh
Yogesh Kumar Chauhan: Kamla Nehru Institute of Technology

International Journal of System Assurance Engineering and Management, 2019, vol. 10, issue 5, No 16, 1082-1090

Abstract: Abstract In wind based micro generation schemes, 3-phase self excited induction generators are prominently used in order to fulfil single phase load requirement. Hence in this context, this paper presents a 3-phase, 5.5 kW, 415 V, 50 Hz short shunt self excited induction generator for improving the voltage regulation and optimum performance of induction machine by using heuristic approach named as gravitational search algorithm. It is used in order to get the optimum capacitance values at specified speed for optimized voltage regulation and performance characteristics in terms of root mean square error and mean absolute error and mean square error. This optimization technique works on Newton law of gravity and it provides average best results for validating the performance in order to enhance machine parameters used in wind energy conversion system.

Keywords: SEIG; Gravitational search algorithm; Optimization; Gravitational law; Loadability (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s13198-019-00838-1

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