Optimum Operation and Cost Scenarios of a Hybrid Wind/PV/Battery in a Radial Network using Firefly Algorithm and Surrogate Optimization

Exploiting renewable energy resources can help decrease carbon emissions by providing a reliable solution to generate electricity and tackle the climate change dilemma. Artificial Intelligence algorithms have been used in the last two decades to optimize power system networks. In this paper, we discussed the effect of replacing the existing Diesel Generator (DG) with a wind turbine to satisfy the load in the standalone hybrid (DG, PV, Battery) radial network in Tomia Island, south-east Sulawesi, Indonesia. Loss of Power Supply Probability (LPSP) and the Coefficient of determination parameters were used as technical performance indicators. Firefly Algorithm (FF) and Surrogate Optimization technique were used to optimize the system considering the minimum costs.