Analysis of the Hybrid PSO-InC MPPT for Different Partial Shading Conditions

Abstract

This article addresses the Particle Swarm Optimization with Incremental Conductance algorithm (PSO-InC) performance as the maximum power point tracking algorithm (MPPT), when the photovoltaic system is under different partial shading patterns. The PSO-InC MPPT combines the global-searching capabilities of particle swarm optimization with the smoother search feature of the incremental conductance algorithm. The analysis proceeds from a systematic approach involving the system simulation for different Environmental conditions. Besides that, to accurately represent the effects of the inherent stochasticity of the PSO, diverse starting conditions were considered in each case. The main contribution, in this sense, consists of highlighting some PSC patterns that might compromise the effectiveness of the PSO, even though the average efficacy on searching the global MPP (GMPP) is over 89%. For instance, based on one of the exploited PSC patterns, one may note a decrement of the PSO effectiveness to a level as lower as 36%. This article also presents simulation results highlighting the PSO-InC MPPT dynamics under transient and steady-state conditions.

Keywords

• hybrid intelligent systems
• maximum power point trackers
• particle swarm optimization
• photovoltaic systems
• solar power generation