Energy-Optimal Power Conversion Control Strategy for Hybrid Solar–Wind Renewable Energy Systems Using Model Predictive Control

Abstract

A solution to sustainable generation of power has been encouraged by hybrid solar-wind renewable energy systems, but its operation is mostly crippled by an ineffective conversion of power and unpredictability due to varying weather patterns like varying amounts of solar-radiation and speed of wind. In an attempt to deal with these issues, the proposed paper is an energy-optimal power conversion control approach as an implementation of Model Predictive Control (MPC). The suggested solution utilises predictive system modelling and real time optisation to dynamically control converter duty cycles and to synchronize the flow of power through various sources of energy. The MPC framework boosts the accuracy of control by introducing constraints to systems and forecast of future states that make it an effective means of energy use. It is shown in simulation that the proposed method can greatly enhance the conversion efficiency, minimise the switching and conduction losses and stabilise the DC bus voltage at a range of operating conditions. Additionally, the performance of the MPC-based strategy is comparatively discussed with the conventional PI and fuzzy logic controllers indicating the high efficiency, quickness, and resilience. The results support the usefulness of the suggested control scheme to next-generation hybrid renewable energy systems, which also provides an efficient scaled and trusted solution to the high-efficiency conversion of power in smart grid and distributed energy systems.