Abstract
To improve the performance of recent perturb and observe (P&O) maximum power point tracking (MPPT) algorithms, an intelligent and robust P&O (IR-PO) algorithm is investigated for variable-speed wind energy conversion systems (WECSs). The proposed IR-PO algorithm reduces the search area for the maximum power point (MPP) by using the optimal hypothetical position of generator speed. Initially, the proposed IR-PO algorithm assesses the optimal generator speed via a simple wind speed estimation (WSE) algorithm which adopts a considerable miscalculation. So, the specified optimal generator speed is not accurate which in turn influences the overall dynamic performance. Hence, the proposed IR-PO algorithm assumes that the operation point of the estimated optimal generator speed is hypothetical, and from this virtual point it begins to search for the real point of the optimal generator speed. Below the optimal hypothetical position, the large adaptive step-sizes are established to rapidly perturb the generator speed to the optimal position and tightens the searching area of the MPP. Otherwise, very small adaptive step-sizes are applied. The proposed IR-PO algorithm not only rapidly hunts the MPP with low-speed fluctuations around the MPP, but also it evades the estimation error of both wind and generator speeds. To verify the superiority of the proposed IR-PO algorithm, it is compared to other MPPT algorithms. As a result of the proposed IR-PO algorithm, the smallest fluctuations and settling time around the MPP with a 4.42% increase in the system efficiency, are accomplished. Furthermore, the performance assessment of the proposed IR-PO algorithm is confirmed by real wind data (Hokkaido-Island, Japan) using MATLAB/SIMULINK.