Optimal Design of Hybrid AC/DC Microgrids with Solar–Wind Generation and Energy Storage Systems

Abstract

In this study, an autonomous hybrid AC/DC power system for remote areas is modeled, integrating photovoltaic (PV) units in the DC subsystem and wind turbines (WT) in the AC subsystem. Battery energy storage systems (BESS) and diesel generators (DGs) are incorporated to improve reliability and ensure continuous power supply. The optimal sizing of system components, including PV and WT capacities and the number of BESS and DG units, is obtained using the Teaching-Learning-Based Optimization (TLBO) algorithm. The main objective is to minimize total system cost while maintaining a balance between electricity generation and demand.To address the stochastic nature of renewable generation and load demand, hourly time-series data over one year are processed using clustering techniques. The k-means algorithm is applied to derive representative scenarios for PV output, wind power, and load profiles under different geographical conditions.Finally, a comparative analysis of optimal configurations is performed for different regions, demonstrating effective combinations of PV, WT, BESS, and DG units. The results support the design of reliable and cost-efficient autonomous hybrid power systems.