Hybrid Solar-Wind Energy System with Enhanced Power Optimization Using Nature-Inspired Egret Swarm Algorithm

A new hybrid renewable energy system comprised of solar and wind power is presented and also an innovative optimization approach using Egret Swarm Algorithm (ESA), a nature inspired algorithm based on Egret hunting strategies. The realized system performs enrollment, control and learning over solar panels and wind turbines, adapting energy output and storage by dynamic regulation of power distribution in real time according to relevant environmental data. Since the goal of energy harvesting is to match the timing of electrical demand to the harvesting regime, ESA improves energy harvesting efficiency by tuning the balance between energy production and storage to reduce losses from unknown weather. Simulation has shown that power stability and overall system performance is significantly improved by comparison with currently used methods. The hybrid energy system optimized for the ESA application is a robust and sustainable solution for the remote and off grid energy demands.