A Modified Particle Swarm Optimization Based Maximum Power Point Tracking for Photovoltaic Converter System

Introduction In the past decade, the photovoltaic (PV) system has gained wide popularity as a renewable-energy source due to the possibility of the depletion of conventional energy sources as well as the high cost of conventional energy sources and their negative effects on the environment. An essential feature of all PV systems is the efficacy of its maximum power point tracking (MPPT). This aspect has drawn immense attention from photovoltaic researchers and industry experts as the most economical means to enhance the photovoltaic system efficacy. Several MPPT techniques have been proposed [1 10]. These methods differ in their accuracy, speed or complexity. Hossain et al [4], Eltawil et al [5] and David et al [6] reviewed and discussed various techniques. For the partially-shaded condition where the shaded cell in a PV module causes a decrease in power, the conventional MPPT technique becomes invalid due to the PV characteristics becoming more complicated and also displaying multiple MPP. This effect of partial shading has been analyzed by many researchers [7, 8]. In [10], a global stage was employed to locate the regions of the local MPP, while a perturband-observe algorithm was employed at the local stage to find the global MPP. Adaptive P&O MPPT was proposed in [11]. Particle swarm optimization (PSO) has high potential for MPPT due to its simple structure, easy implementation and fast computation capability. Since PSO is based on search optimization in principle, it should be able to locate the MPP for any type of PV curve regardless of environmental variations. The direct control structure was adopted by some researchers where the positions of the PSO particles are used as the duty cycles. Excellent dynamic tracking speeds under severe partial-shading conditions were able to be handled using the method. Furthermore, the steady state oscillations were found to be exceptionally low. For instance, to track the global point in a constant bus voltage application, the conventional PSO was employed in [12]. An analytical expression of the objective functions based on PV current, irradiance and temperature was formulated in order to track the MPP. The current-based PSO method was proposed by Miyatake et al [13], where the series inductor current of the boost converter is used as the reference signal to generate the PWM signals for the switching converter. A repulsive term in the velocity equation of the PSO was also introduced. Miyatake et al [13] proposed an adaptive perceptive PSO (APPSO)-based MPPT algorithm. Ishaque et al [14] presented an improved PSO-based MPPT algorithm for PV systems and discussed the advantages of using PSO in conjunction with the direct duty cycle control in detail. However, no system design guidelines and practical design considerations are provided in these papers. Miyatake et al [15] attempted to approach the global MPP using the PSO algorithm. The authors tried to realize centralized MPPT control of the modular (multi-module) PV system. The MPPT algorithms have good performance under various partial-shading conditions; however, these methods are only suitable for systems that consist of multiple converters. However, the use of one central highpower single-stage electronic converter is very common in the PV system due to the economic reasons and the relative ARTICLE INFO Art icle his tory: