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A New Hybrid Statistically Tracked PSO for PID Controller of Wind-Solar System Incorporating Effect of AVR

Cheshta Jain, Dr. H.K. Verma


In modern power systems, alternative energy generating sources are integrated with conventional energy sources to meet increasing power demand with environmental constraints. A hybrid system with voltage regulator having a wind-solar system, diesel generator (DG), aqua electrolyzer (AE) and ultracapacitor (UC) is analyzed. This paper Introduce new variant of basic PSO known as hybrid statistically tracked particle swarm optimization (STPSO) for evaluation of optimized controller gains for DG, UC, AE and voltage regulator. The work presented in this paper focuses on comparative analysis of optimized controller for a proposed hybrid system to control the frequency and voltage deviation using evolutionary algorithms. The performance of controllers obtained by hybrid STPSO has been compared with controllers optimized by particle swarm optimization (PSO), chaotic PSO (CPSO), differential evaluation (DE), teaching learning based optimization (TLBO) and big bang- big crunch (BB-BC) algorithms. A significant improvement in convergence characteristic of hybrid STPSO algorithm over other evolutionary algorithms is observed in renewable hybrid system problems.

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