Abstract: Traditional techniques employed to monitor the maximum power point in wind energy conversion systems (WECS) encounter numerous challenges. One of the most prevalent methods is the perturb and observe (P&O) algorithm, which tracks and logs the highest achievable power point. Nevertheless, a significant drawback of this algorithm is the challenge of determining an optimal step size. To tackle this problem, this research introduces an innovative approach that combines fuzzy logic control with the trapezoidal rule. The suggested method is evaluated against two existing techniques: the trapezoidal rule-based P&O (TRPO) algorithm and the standard P&O method. MATLAB/Simulink simulations are conducted to assess the performance of all three algorithms under randomly fluctuating wind speeds. The findings indicate that the proposed approach markedly decreases power oscillations while improving DC output current, voltage, and power. Furthermore, this study expands the methodology by integrating a wind-solar hybrid system with an artificial neural network (ANN) model, thereby enhancing the efficiency and stability of renewable energy generation.

Downloads: | DOI: 10.17148/IJIREEICE.2025.131119