Abstract :
Partial shading is a phenomenon, whereby, certain spots of the photovoltaic (PV) array are shaded, while other parts are left uniformly irradiated. It is caused by the shadow that originates from the obstruction of tall building, chimney, tree, telecom tower and utility power lines. Due to its significant influence in reducing the energy yield, partial shading has attracted considerable interest-particularly for the building integrated PV (BIPV) system in urban areas. For large PV power plant, the primary concern is shading due to the passing cloud. For economic and technological reasons, researchers concentrate on maximizing the energy yield during partial shading by adding more intelligence to the maximum power point tracking (MPPT) algorithm of the inverter. Improvement can be achieved in various ways, but recently, the soft computing (SC) techniques have been extensively applied to enhance the efficiency of the MPPT. In view of the growing importance of this issue, this keynote paper will deliberate on six important SC-based MPPT techniques proposed in literature. The main discussions will be on the technological aspects, merits/drawbacks and their comparative performance. It is envisaged that this paper would be a valuable reference source for those who require more information to design an improved MPPT for their inverters.
Keywords :
building integrated photovoltaics; invertors; maximum power point trackers; particle swarm optimisation; power engineering computing; search problems; BIPV; MPPT; PV power plant; building integrated PV; energy yield; inverters; maximum power point tracker; partial shading; photovoltaic array; photovoltaic system; soft computing; Arrays; Artificial neural networks; Inverters; Maximum power point trackers; Niobium; Optimization; Power engineering; MPPT; Photovoltaic; inverter; partial shading; soft computing;