Multi-Objective Capacity Configuration Optimization of an Off-Grid Highway Microgrid Considering Different Energy Storage Structures

Abstract

To meet the off-grid operation demand of highway facilities, this study proposes a capacity configuration optimization method for an off-grid highway microgrid. First, based on the monthly electricity consumption data of tunnels, toll stations, service areas, and electric vehicle charging stations along the highway, a load profile is reconstructed by considering the operating characteristics of different load types. Then, an off-grid highway microgrid model integrating wind turbines, photovoltaic arrays, battery storage, and hydrogen energy storage is established. A multi-objective capacity configuration optimization model is developed with the annualized total cost, loss of power supply probability (LPSP), and energy excess ratio (EER) as the optimization objectives, and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is adopted for the solution. To analyze the influence of storage structure on the configuration results, three structures are compared: battery storage, hydrogen storage, and hybrid storage. The results show that all three structures can satisfy the reliability requirement of an off-grid power supply. Among them, the hybrid storage structure achieves the best overall performance, with an annualized total cost of 26.381 million CNY/year, an LPSP of 0.095%, and an EER of 36.709%, outperforming the single storage structures. Additional optimization under alternative dispatch strategies and repeated NSGA-II runs further confirm the consistency of the main conclusion. The typical-day operation results and annual storage-state variations further indicate that the hybrid storage structure can better coordinate the output of storage devices and reduce the capacity demand and operating pressure of a single storage system. The results can provide a reference for capacity configuration and storage structure selection of off-grid highway microgrids.