Optimal Capacity and Cost Analysis of Hybrid Energy Storage System in Standalone DC Microgrid

Abstract

DC microgrid systems have been increasingly employed in recent years to address the need for reducing fossil fuel use in electricity generation. Distributed generations (DGs), primarily DC sources, play a crucial role in efficient microgrid energy management. Energy storage systems (ESSs), though vital for enhancing microgrid stability and reliability, currently lack cost-effectiveness. Each ESS technology serves a specific purpose, suggesting that hybridizing these technologies can improve microgrid stability and reliability while extending the ESS's lifespan. This paper proposes an optimization of the capacity and cost of a hybrid ESS, comprising a battery and a supercapacitor, in a standalone DC microgrid. This optimization is achieved by calculating the cut-off frequency of a low-pass filter (LPF). The supercapacitor supplies the high fluctuation component of renewable power generation and load demand, while the battery caters to the low fluctuation component. To minimize the designed objective function, including the total net present value (NPV) and replacement cost of the hybrid ESS, a meta-heuristic strategy called the Whale optimization algorithm (WOA) is employed within a MATLAB environment. The optimization takes into account real PV power, wind turbine power and load demand. The results show that reducing power fluctuation for the battery can lower the cost of the hybrid ESS. Compared to a battery-only microgrid system with an NPV_total of 6,153,059, the hybrid ESS has an NPV_total of 5,413,846. Thus, the hybrid ESS can reduce the total cost of the entire project by 12.01% compared to the system with only a battery. Consequently, the hybrid ESS's total system life-cycle cost is lower than that of a system using only a battery.