MPP detection of a partially shaded PV array by continuous GA and hybrid PSO

• Published in: Ain Shams Engineering Journal Vol. 6; no. 2; pp. 471 - 479
• Main Authors: Shankar, G., Mukherjee, V.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.06.2015; Elsevier
• Subjects: Continuous genetic algorithm; Hybrid particle swarm optimization; Maximum power point tracker; Perturb and observe algorithm; Photovoltaic array; Maximum power point tracker; Perturb and observe algorithm; Continuous genetic algorithm; Hybrid particle swarm optimization; Photovoltaic array
• ISSN: 2090-4479; 2090-4495; 2090-4495
• DOI: 10.1016/j.asej.2014.10.017

Power versus voltage curve of a uniformly shaded photovoltaic (PV) array has only one maximum power point (MPP). However, when the array is partially shaded, there may be several local MPPs and there exists only one global MPP. The commonly employed perturb and observe (P&O) algorithm works well in detecting the MPP of a PV array when the array is uniformly shaded. However, when the array is partially shaded, the operating point based on P&O method may converge to a local MPP of the array rather than the global one resulting in its under-utilization. In this paper, continuous genetic algorithm (CGA) and hybrid particle swarm optimization (HPSO) algorithm are adopted in detecting the global MPP of a partially shaded PV array. It is observed that the performance of the HPSO is better than either P&O method or the CGA in finding the global maxima of a partially shaded PV array.