Hybrid Renewable Energy Microgrid Design Optimization of Karimunjawa Island Using Intelligent Algorithm

Karimunjawa Island, Indonesia, relies on diesel generators (PLTD) and photovoltaic (PLTS) systems to fulfill its electricity needs. Despite this hybrid setup, the island faces persistent energy challenges, including high operational costs, limited energy storage, fuel supply disruptions, and intermittent renewable generation. In addition, wind energy potential, with average speeds ranging from 4 to $6.6 ~\mathrm{m} / \mathrm{s}$, remains underutilized. However, most previous studies on Karimunjawa have relied on conventional simulation tools such as HOMER and have not explored intelligent optimization algorithms to improve hybrid microgrid design. This study proposes an optimized hybrid microgrid system that integrates photovoltaic (PV), wind turbines (WT), battery energy storage systems (BESS), diesel generators, and inverters. The optimization process aims to minimize the cost of energy (COE) and find the optimal capacity configuration for Karimunjawa microgrid. Three intelligent algorithms are employed in this study, namely Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA), to determine the optimal configuration. The HOMER optimization is conducted to compare the results with the intelligent algorithms. The result shows that the optimization using the ABC algorithm achieved the lowest COE of $0.263 \text{USD} / \text{kWh}$ and an NPC of 18.23 million USD, outperforming both PSO, GA, and HOMER-based designs.