Optimal Maximum Power Point Tracking Control Using a Sugeno - Type Fuzzy Logic Controller and Genetic Algorithm Techniques for a Solar Photovoltaic System

Abstract

In today's global energy scenario, the current fossil fuel-based energy crisis as well as concerns about global warming are increasing rapidly. Power generation based on renewable energy sources (RESs) can be a way to address such long-term challenges. Among the various available RESs, demand for solar photovoltaic (PV) technology has been increasing rapidly over the last few decades. However, PV systems have some drawbacks, such as non-linear characteristics of the PV cell and power output reliance on unpredictable external factors such as solar radiation and ambient temperature. Determining the optimal values of unknown PV cell characteristics and maximum power point (MPP) tracking under partial shade are two among research challenges in this area. The conventional maximum power point tracking (MPPT) controllers such as perturb and observe (P&O) and incremental conductance (INC) algorithms where the output power has been tracking only a single local peak considering different irradiation patterns. Therefore, in the present study, a genetic algorithm (GA)-based single-diode PV cell model for estimating the unknown parameters of solar PV cells is proposed. From the simulation, optimum values of estimated single diode model parameters of Kyocera KC200G obtained is Rs=0.2286 Ω, Rsh=471.9264 Ω, Ish=8.21 A, Isd=0.0839 A and n=1.24475. Moreover, for 600 Wp PV system, a GA-fuzzy logic controller (FLC) has also been implemented for tracking the global MPP of the PV output both under constant and variable irradiation scenarios. Comparison with P&O and INC MPPT algorithms for Scenario-1, Scenario -2 and Scenario-3, the high PV system efficiency were obtained for the proposed GA-FLC MPPT controller found to be 99.7 %, 99.8 % and 99.9 %, respectively. Besides, in terms IAE, the least obtained value found to be 3.73 (Scenario-1), 1.7748 (Scenario-2) and 1.3932 (Scenario-3) while considering GA-FLC MPPT.