Multi-objective optimization with advanced exergy analysis of a wind-solar-hydrogen multi-energy supply system

Identifying the primary sources of exergy destruction is a powerful method for promoting the high-efficiency operation of multi-energy supply systems. Advanced exergy analysis identifies avoidable parts of the destruction and discovers interactions between subsystems of a multi-energy complementary coupled system to explore the potential for system improvement. In this paper, a wind-solar-hydrogen multi-energy supply (WSH-MES) system is studied, in which wind farms, photovoltaic power plants, solar thermal power plants, and hydrogen grid systems are coupled at the grid side to share the electrical load. To optimize power generation and improve system performance, a bi-level capacity-operation co-optimization model is developed specifically for the WSHMES system. The upper level of the model employs a multi-objective optimization approach to find the best balance between energy, exergy, and advanced exergy and economy. The model is solved using the Nondominated Sorting Genetic Algorithm-II and linear programming. To gain insights into the system's performance, advanced exergy analysis is performed under the optimal capacity configuration. By considering avoidable exergy destruction efficiency and exergy destruction proportion, the sequence of optimization potential for the WSH-MES system is determined. Surprisingly, the findings entirely different from that of conventional exergy analysis and reveal the interrelations between the analyzed subsystems. The sequence of optimization potential for the WSH-MES system is found to be as follows: concentrated solar power, photovoltaics, proton exchange membrane fuel cells, wind power, and proton exchange membrane electrolyzers. The identified optimization potential provides valuable guidance for improving energy efficiency, reducing costs, minimizing environmental impact, and serves as a reference for the design and optimization of new systems.