Abstract
The main objective of photovoltaic system controller is to reduce the price of the kWh compared to traditional fuel-based electricity. Thus, the improvement of simple and low – cost controllers is a major challenge. Perturb and Observe (P&O) is the commonly used algorithm in order to ensure the power maximization of the photovoltaic system, due to its simplicity and effectiveness. However, on the main drawbacks of that algorithm is the fixed step size of perturbation, due to working environmental changes, which require dynamic tuning of the controller parameter. In order to overcome the cited disadvantage, a new Takagi - Sugeno variable step P&O is proposed. Based on the real-time measurements of the solar radiation and temperature, the proposed fuzzy system schedules the appropriate step size based on human expertise. A zero order Takagi – Sugeno with singleton output is proposed. The fuzzification were carried out using triangular and trapezoidal membership functions. The centroid defuzzification method based 25 If -Then rules are adopted. In order to verify the effectiveness of the improved P&O, three scenarios were used. The obtained results show the effectiveness of the proposed controller under shaded conditions and various temperatures.
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