Adaptive algorithm for fast maximum power point tracking in wind energy systems

Wind energy systems are being closely studied because of its benefits as an environmentally friendly and renewable source of energy. Because of its unpredictable nature, power management concepts are essential to extract as much power as possible from the wind when it becomes available. In this paper an algorithm has been developed to keep the system at its highest possible efficiency at all times. The proposed algorithm uses a modified version of hill climb search (HCS) and intelligent memory to implement its power management scheme. Because it does not require that the turbinepsilas characteristics be pre-programmed to obtain the optimal operating points for maximum power transfer, it can be applied to a wide range of wind turbines. The algorithm determines the turbinepsilas internal characteristics through operation. Once the algorithm obtains knowledge of the turbinepsilas characteristics, it can infer the optimum rotor speeds for wind speeds that have not occurred before. The main focus of this paper is the algorithm structure and its effectiveness under fluctuating atmospheric conditions. PSIM simulation studies have been done to confirm the effectiveness of the proposed algorithm.