Fuzzy logic-based hill climbing technique for photovoltaic maximum power point tracking converter

Photovoltaic (PV) is a fast growing segment among renewable energy systems,whose development is owed to depleting fossil fuel and climate-changing environmental pollution. Its weaknesses, however, are its variable generation and non-linear characteristic due to its intermittent nature. These disadvantages contribute to issues of high per-kW installation cost and further low efficiency in PV generators. An important consideration for achieving high efficiency in PV operation is to match the PV source and load impedance properly for any weather condition. The maximum extractable power from PV panels depends not only to the strength of the solar irradiation but also to the operating point of the energy conversion system. Maximum power point tracking (MPPT) is of paramount importance to the system as it not only maximizes system efficiency but also minimizes the return of investment in the PV installation. The hill climbing algorithm is the most common method of MPPT due to its simplicity, ease of implementation, and good performance. However, it has issue of perturbation step size and trade off between faster response and steady-state oscillations. Therefore, in this research work, the hill climbing search method has been modified based on fuzzy logic control for improvement of MPPT operation. This proposed MPPT algorithm is named as fuzzy logic based hill climbing.The proposed MPPT was implemented by fuzzifying the rules of hill climbing search method to reduce its drawbacks, and with this technique, not only the real maximum power point can be readily tracked, but also fast dynamic response and small steady state error can be achieved. In this study, the characteristics of a PV module (Kyocera KD210GH) were mathematically modeled and simulated using MATLAB simulation tool. Then, the proposed MPPT algorithm and dc-dc boost converter were designed and developed in the same tool. Simulation results are presented to validate performance of the algorithm under different irradiation schemes, and to compare with the results obtained from conventional algorithm. Further experimental setup was carried out for comparative evaluation and the MPPT algorithm was implemented to performance verification of the algorithm by using digital signal processor (TMS320F28335). The results obtained clearly confirm the proposed MPPT exhibits at least two times faster converging speed than the conventional MPPT in optimum configuration, and the oscillations around maximum power point under steady state condition show improvement up to 75%.

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