Constrained MPPT Strategy for Sustainable Wave Energy Converters with Magnetic Lead Screw

Abstract

Emerging magnetic lead screws (MLSs) have been proven to be promising in sustainable wave energy conversion areas due to their high efficiency and power density. This study is aimed at developing a constrained maximum power point tracking (MPPT) strategy for MLS-based wave energy converters (WECs). In this paper, the mechanism of the MLS is analyzed and the dynamic model of the MLS-based WEC is established. The variations in hydrodynamic coefficients were analyzed using ANSYS AQWA, based on which the theoretical MPPT requirements were explored. Afterward, two constraints (stroke and translator force constraint) were introduced to ensure the safe operation of the converter. An adaptive constrained genetic algorithm (ACGA) was applied to realize MPPT under constraints. For irregular wave situations, an extended Kalman filter (EKF) was applied to estimate the frequency and amplitude of the wave excitation force with which the constrained GA can be realized. Simulations and experiments were carried out to verify the constrained MPPT. In the two cases (wind speed u = 7 m/s and u = 10 m/s) of the simulation, the proposed ACGA can improve the energy harvest rate by 3.95% and 3.57% compared to the standard constrained genetic algorithm (SCGA), while this rate was improved by 6% in the experimental case.