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

Abstract

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 ultra-capacitor (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.