电池电力机车在电力系统中作为电网支撑服务的应用

Harvesting wind energy is constrained by its generation availability and variability. Energy storage systems (ESSs) partly address this limitation by absorbing the generation volatility and curtailment. However, the conventional static ESSs may lack the necessary reach and versatility to effectively support large-scale power systems. This paper presents an innovative approach suggesting the use of battery-electric locomotives (BELs) as mobile energy reserve tools. The BEL carries separable battery railcars with enhanced storage capacity that offers a flexible and far-reaching energy supply. We propose a new uncertainty-aware optimization model that holistically integrates the operation of power and railway systems. The proposed model is formulated as a mixed-integer nonlinear stochastic programming (SMINLP) problem that incorporates uncertainty through joint probabilistic constraints (JPCs). Equivalent and tractable deterministic mixed-integer linear programming (MILP) reformulations are derived using the Boolean programming and the scenario-based approaches. The numerical tests showcase the superior scalability and computational efficiency of the Boolean method, especially when many scenarios are involved. The model is validated on the IEEE 6-bus test system and scaled up to the IEEE 118-bus test system, where comparative analyses reveal the model's ability to deliver cost-saving and congestion relief, with a particular emphasis on the responsiveness of separable battery railcars.