Modeling and Decision-Making of a Hybrid Energy System for Multi-Energy Station Design

Abstract

Global electricity demand has continued to grow, and the limitations of centralized transmission networks have raised concerns regarding the reliability and efficiency of power supply. At the same time, the expansion of renewable energy capacity to achieve carbon neutrality increases variability in the grid and heightens operational instability. Urban areas, where electricity demand is highly concentrated, are particularly vulnerable to outages that can cause widespread social disruption, including transportation interruptions, communication failures, and safety issues. The large-scale blackout that occurred in Spain in 2025 illustrated that, although multiple factors can contribute to such events, transmission overload remains a fundamental cause. To enhance system resilience, microgrids equipped with distributed energy resources, energy storage systems, and controllable loads have emerged as an important solution. However, optimizing only the electrical sector is insufficient for improving overall efficiency and achieving carbon neutrality. Sector coupling can convert electricity into gaseous or thermal energy and integrate it with mobility, industrial, and residential sectors, thereby improving flexibility and supporting the transition to multi-energy microgrids. The mobility sector is rapidly shifting toward electric and hydrogen vehicles, and the decline of conventional gas stations has encouraged the transition toward multi-energy stations that incorporate photovoltaics, fuel cells, and water electrolysis. A hybrid configuration consisting of photovoltaics, alkaline water electrolysis, batteries, and solid oxide fuel cells is increasingly recognized as a key distributed resource capable of supplying both residential and mobility sectors. Previous studies have primarily focused on capacity optimization based on economic or environmental indicators, yet they often do not reflect the dynamic behavior of energy systems under fluctuating renewable inputs and therefore fail to capture system robustness. In this study, a dynamic model of the ‘PV-AWE-Batt-SOFC’ hybrid system was developed using AMESim®. The alkaline water electrolyzer includes a stack, pump, heat exchanger, gas–liquid separator, cooling system, condenser, oxygen catalytic combustor, and dryer, while the solid oxide fuel cell system consists of a stack, blower, heat exchanger, and after-burner. The electrochemical reactions in both stacks were modeled using in-house code for accurate transient representation. To determine the optimal configuration and energy management strategy of the multi-energy station, various scenarios were evaluated. The simulation results provide economic, environmental, and technical indicators, as well as physics-based variability metrics such as crossover behavior, voltage variation, system efficiency, and fuel utilization fluctuation. These metrics reflect the combined effects of temperature dynamics, KOH concentration changes, hydrogen loss during purification, SOFC temperature and conversion characteristics, and degradation of both stacks and the battery.