Capacity Allocation Optimization of a Zero-Carbon Railway Station Integrated Energy System Incorporating PV, Energy Storage, Hydrogen, and Charging Infrastructure: A Review
Linmao Ren, Yan Ren, Feng Zhang, Kang Luo, Jiangtao Chen, Kai Zhang, Junxiao Yang, Bo Wang, Peng Zhang, Xin ZhangWith the advancement of China’s “dual carbon” goals and the green transformation of the railway sector, railway stations, as key energy-consuming nodes, require integrated energy systems that support low-carbon and renewable energy utilization. This review focuses on zero-carbon railway station integrated energy systems incorporating photovoltaic (PV) generation, energy storage, hydrogen systems, and charging facilities. Based on existing studies, the paper systematically reviews system configuration methods, operational strategies, and capacity optimization approaches. It first summarizes the roles of photovoltaic, energy storage, and hydrogen systems in railway station energy supply and outlines representative integration frameworks. It then compares standalone operation and coordinated multi-energy complementary operation, with particular attention to technical challenges in renewable energy accommodation, energy storage coordination, and hydrogen utilization. Mainstream capacity optimization approaches are further reviewed according to different energy configurations, including photovoltaic systems, energy storage systems (ESSs), hydrogen systems, and multi-energy complementary systems, with emphasis on optimization objectives, constraint formulations, and solution methodologies. The review shows that existing studies have gradually shifted from single-energy configurations toward coordinated multi-energy planning, but limitations remain in load forecasting accuracy, dynamic operational optimization, and large-scale engineering validation. Existing uncertainty management methods mainly include stochastic programming, robust optimization, chance-constrained optimization, and scenario-based approaches, which are used to address renewable energy fluctuations and load uncertainties. Future research should strengthen uncertainty modeling, real-time scheduling, and case study platforms considering diverse meteorological and load scenarios. This review provides a theoretical reference for planning and optimizing zero-carbon railway station integrated energy systems.