Optimal sizing of a wind/solar/battery hybrid grid‐connected microgrid system

TLDR

Intermittent renewable energy resources are costly and stochastic, complicating their planning, integration, and operation in electric power systems. The study aims to determine optimal sizes of wind turbines, solar PV, and battery storage for efficient, economic, and reliable grid‑connected microgrid operation by proposing two constraint‑based iterative search algorithms. The authors develop a sources‑sizing algorithm to optimize renewable capacities and a battery‑sizing algorithm to compute BESS capacity, jointly searching the solution space for maximum reliability and minimum cost while accounting for forced outage rates and BESS utilization. Simulation results demonstrate that the proposed approach effectively balances cost and reliability, confirming its practical viability.

Abstract

Higher cost and stochastic nature of intermittent renewable energy (RE) resources complicate their planning, integration and operation of electric power system. Therefore, it is critical to determine the appropriate sizes of RE sources and associated energy storage for efficient, economic and reliable operation of electric power system. In this study, two constraint‐based iterative search algorithms are proposed for optimal sizing of the wind turbine (WT), solar photovoltaic (PV) and the battery energy storage system (BESS) in the grid‐connected configuration of a microgrid. The first algorithm, named as sources sizing algorithm, determines the optimal sizes of RE sources while the second algorithm, called as battery sizing algorithm, determines the optimal capacity of BESS. These algorithms are mainly based upon two key essentials, i.e. maximum reliability and minimum cost. The proposed methodology aims to avoid over‐ and under‐sizing by searching every possible solution in the given search space. Moreover, it considers the forced outage rates of PV, WT and utilisation factor of BESS which makes it more realistic. Simulation results depict the effectiveness of the proposed approach.