A Fuzzy Logic–MPC Driven Multi-Objective PSO Optimization Approach for Coordinated Energy Management and Maximum Power Point Tracking in Integrated Wave–wind Conversion System

Abstract

Wave–wind energy conversion systems integrated have become an interesting alternative for enhancing the reliability of renewable power generation, mainly at maritime/coastal sites with severe resourcevariation. However, the interconnection of two very fluctuating energy sources impose great power quality challenges, dynamic stability and coordinated control. In this study, a new hybrid wave–wind system aimed at real time energy management and MPPT has been developed based on Fuzzy Logic –MPC driven MOPSO optimization algorithm is proposed. The proposed structure combines: (i) a Fuzzy Logic Controller (FLC) for adaptive MPPT control in non-linear and fast changing sea states; (ii) a Model Predictive Controller (MPC) for short-horizon optimisation of active/reactive power flows and converter dynamics; and, (iii), a MOPSO supervisory layer that continuouslymonitors the efficiency, power smoothness and mechanical stress system-wide.Numerical results indicate that the proposed FLC–MPC control is truly responsive to fast variations of wave height and wind turbulence, up to 22% improvement in MPPT tracking accuracy with respect to conventional approaches being reported. By allowing the system to adjust the number of optimal control parameters off grid the MOPSO algorithm achieves a 17% decrease in power oscillations, 28% improved energy capture ratio as well as significant decreases on turbine and point absorber mechanical loading. Moreover, the hierarchical mode guarantees that both the storage use and grid-connected operation are implemented in a coordinated manner, such that with complex ocean–wind disturbances, the voltage and frequency can be stably regulated.In conclusion, it can be noted that the multi-layer intelligent control approach satisfied energy capture maximum effort and system reliability, as well as improved power quality for in integrated wave–wind energy systems. This work provides a scalable platform for the next-generation marine renewable hybridization and enables the transition to sustainable offshore energy infrastructure and secure coastal microgrids.