Cuckoo Search Based Approach Towards Maximum Power Point Tracking for Solar Photovoltaic System Under Partial Shading

Abstract

Extracting the maximum power from as solar PV system is a critical task when high changes in light intensity or Partial Shading Condition (PSC) are experienced. The latter case is more difficult as it creates multiple maxima points on P–V curve. In this way, it is obligatory to thoroughly pick a precise Maximum Power Point Tracking (MPPT) method which recognizes adequately the Global Maximum Power Point (GMPP) and tracks it under partial shading. This paper first describes the modeling of PV module and PV characteristics under uniform irradiance as well as effect of PSC on PV characteristics. In the latter sections, a review of conventional and intelligent MPPT methods is done. To tackle the problem of MPPT under PSC, two metaheurisric algorithms namely Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are described briefly. A new optimization method called Cuckoo Search (CS) is implemented in MATLAB SIMULINK tool and tested under three different PSC patterns. A comparative analysis of different MPPT strategies is made after analyzing the results.