Abstract
Improving power efficiency for a Photovoltaic (PV) system becomes important issue for researchers. To achieve maximum power extraction from PV panels, different kinds of Maximum Power Point Tracking (MPPT) methods have been investigating in the literature. In all techniques, direct and indirect mode approaches can be implemented. Based on the physical application of the PV system under different condition, the efficiency and convergence speed become important. In this paper, a grid connected simple single stage PV system by using different MPPT methods in direct and indirect modes has been analysed to find out the best mode and technique for a specific PV system application. Three of the most preferred MPPT algorithms: the perturb & observe (P&O), incremental conductance (Inc. Cond.) and fuzzy logic control (FLC) have been performed in MATLAB Simulink and compared their performance in direct and indirect modes in terms of convergence speed and tracking accuracy by the proposed single stage PV system. The results show that direct mode MPPTs have better tracking accuracy but less convergence speed than indirect MPPTs. Therefore, indirect mode MPPTs present better performance for the rapid atmospheric changing applications. Additionally, FLC based MPPT exhibits almost best tracking performance for direct and indirect modes.DOI: http://dx.doi.org/10.5755/j01.eie.24.4.21477
Highlights
Concern over the limited stock of conventional energy sources such as coal and other petroleum products has pushed the researches to the development of renewable sources of energy [1]
Indirect mode Maximum Power Point Tracking (MPPT) are more successful for rapid atmospheric changes and they are more convenient for roof installed PV systems, mobile vehicle installed PV applications, i.e. The rest of this paper is organized as follows: Section II discusses modelling of PV cell and PV panel by using equivalent circuit model
To extract maximum power from the PV panel for any environment condition, the switches in the converter must be triggered in a specific delay angle (α) which is calculated by MPPT controller
Summary
Concern over the limited stock of conventional energy sources such as coal and other petroleum products has pushed the researches to the development of renewable sources of energy [1]. To detect actual MPP against the changing of solar irradiance or temperature, Maximum Power Point Tracking (MPPT) algorithms are used. This problem especially becomes very important issue in some applications such as mobile and roof-based PV power generation units due to fast change of environmental conditions To avoid these drawbacks, softcomputing based MPPT techniques such as Particle Swarm Optimization (PSO) [9], Fuzzy Logic Control (FLC) [10], Artificial Neural Network (ANN) [11], Genetic Algorithm (GA) [12] are widely used for PV systems. Direct mode MPPTs have better tracking performance but worse convergence speed than indirect mode MPPTs. indirect mode MPPTs are more successful for rapid atmospheric changes and they are more convenient for roof installed PV systems, mobile vehicle installed PV applications, i.e. The rest of this paper is organized as follows: Section II discusses modelling of PV cell and PV panel by using equivalent circuit model. The relationships between PV panel power-solar irradiance and power-temperature curves are shown in Fig. 2 respectively
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