MAXIMUM POWER POINT TRACKING (MPPT) CONTROL OF SOLAR-PV USING SOFT COMPUTING TECHNIQUES

Abstract

The efficiency of solar panel is very low which is about 15-30%, so for the commercial use of solar PV the operating efficiency is to be maximized to reduce cost of installation. The I-V characteristics of commercial solar PV cell is non-linear and it is a function of ambient temperature, angle of incidence, solar irradiance and load current. For maximum operating efficiency the solar panel have to be operate at a voltage corresponding to maximum power output at all changing environmental conditions. All controllers implement maximum power point tracking (MPPT) for this purpose. . The design of fuzzy-logic-based solar power MPPT algorithms using different fuzzy input variables is being investigated in this thesis. Three fuzzy MPPT algorithms, based on different input variables, is being considered in this study, namely (i) slope and variation of the power; (ii) variation of power and variation of voltage; (iii) sum of conductance and increment of the conductance; Algorithms (i),(ii) have two input variables each while algorithms (iii) use a single input variable. Buck-boost power converter is used in fuzzy logic MPPT function to make it more effective. Details of the determinations, considerations of the fuzzy rules, as well as advantages and disadvantages of each MPPT algorithm based upon photovoltaic (PV) cell properties is being presented in this thesis. Using input variable of Algorithm (iii) the maximum power point condition is well defined in steady condition. It can be used for multipurpose controller design. Design is verified by computer simulations.