Robust Adaptive HCS MPPT Algorithm-Based Wind Generation System Using Power Prediction Mode

In this research, an innovative approach is presented to enhance the power energy production of the wind turbines (WTs). Robust adaptive hill climbing search (HCS) algorithm based on variable step size is integrated with power prediction mode (PPM) technique. The objective is to achieve the maximum power point of the wind energy conversion system (WECS), thereby capturing the highest possible power from the wind source. Conventional methods of maximum power point tracking (MPPT) are unable to precisely track and reach the optimal point under unpredicted wind speeds. To address this issue, adaptive HCS is utilized due to its ability to overcome certain well-perceived challenges such as detection delays and the number of iterations in detecting the optimal peak point. More specifically, the PPM technique is combined with the adaptive HCS algorithm. The proposed Adaptive HCS-PPM technique is shown to demonstrate higher efficiency and faster trenching capability in reaching the optimal point, resulting in reduced power fluctuations, and improved overall performance of WECS as well as overcoming the oscillations around the optimal point.