Adaptive P&O MPPT algorithm based wind generation system using realistic wind fluctuations

• Published in: International journal of electrical power & energy systems Vol. 112; pp. 294 - 308
• Main Authors: Mousa, Hossam H.H., Youssef, Abdel-Raheem, Mohamed, Essam E.M.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.11.2019
• Subjects: Adaptive P&O; Five-phase PMSG; MPPT; WECS; Wind speed estimation; Adaptive P&O; MPPT; Wind speed estimation; Five-phase PMSG; WECS
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2019.04.038

•An adaptive P&O algorithm is proposed for Multi-phase PMSG based WECS.•The AD-PO strategy eradicates the conventional P&O associated limitations.•The AD-PO enhances the operation strategy of the variable-step P&O algorithms.•The AD-PO utilizes the adaptive step-sizes using the estimated wind speed.•The AD-PO exhibits a fast response with very small steady state oscillations. In this study, an efficient and fast adaptive perturb and observe (AD-PO) maximum power point tracking (MPPT) algorithm based on the variable - speed wind energy conversion system (WECS) is proposed to eradicate drawbacks of conventional fixed step-size P&O (CPO) algorithms and to enhance the operation of variable step-size P&O (VS-PO). The AD-PO divides the power-speed (P-ω) curve into modular sectors that depend on the estimated wind speed. The step-size is varied adaptively in each sector by observing the distance between the theoretical maximum power point (MPP) and operating power point. The AD-PO enhances the speed convergence with low steady-state oscillations around the MPP. The system configuration involves a 1.5 MW five-phase permanent magnet synchronous generator (PMSG). A back-to-back converter (BTBC) with a dc-link capacitor is used to integrate the PMSG with the utility grid. Simulation results confirm the superiority of the AD-PO over the CPO and the VS-PO MPPT algorithms based on speed convergence and oscillation levels. The performance of the proposed control scheme is validated by real wind data (Boulder City, Colorado) using MATLAB/SIMULINK environment.