Abstract
There has been tremendous growth in the use of renewable energy sources (RES) over the last few years. Solar systems, because of their unique properties, such as being noiseless, eco-friendly, and free of pollutants, are the most feasible source of energy among all RESs. However, a major drawback of photovoltaic (PV) systems is their low energy conversion efficiency, unstable and intermittent nature. In order to extract electrical energy from solar panels, it is necessary to connect them to the power system through DC-DC converters. As a result, maximum power point tracking (MPPT) algorithms are necessary in order to increase the amount of power harvested from solar PV systems. Accordingly, a method is presented in this paper for the design of an MPPT control approach for PV systems using fuzzy gain scheduling for proportional-integral-derivative (FGS-PID) controllers coupled with adaptive scaling factors for fuzzy input signals. The developed adaptive FGS-PID controller uses a two-level control system structure that incorporates the advantages of fuzzy logic and conventional PID control. Additionally, to fine-tune the member functions (MFs) of FGS, an integration of the fuzzy logic controller (FLC) and the modified fluid search optimization (MFSO) algorithm is employed. In order to evaluate the efficiency of the developed control systems, MATLAB software has been chosen for the simulations. The developed approach has proven highly effective in automatically regulating the triangular MFs of inputs and outputs and has shown superior performance. One of the key benefits of the proposed technique is that it enables fast and accurate tracking of the PV system's highest generated power in a short period of time.
Published Version
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