Abstract In recent years, the use of renewable energy (RE) sources has an upward trend due to the environmental and economic reasons. However, finding a solution method to manage the fluctuating nature of these sources and more efficient utilization of total generation capacity are challenging problems, especially when there is a high penetration of REs in power systems. On the other side, the network congestion in power grids is another obstacle that inhibits the full utilization of REs. Battery-based energy storage transportation using a railway network leads to emerging high-efficiency technology called transportable battery-based energy storage (TBES) system. TBES technology is a practical and economical option to reduce transmission congestion and increase the utilization of the energy storage systems’ (ESSs’) capacity by providing additional facility to transfer power. As a flexible resource, TBES can adapt to the load profile of the system at peak-load hours and result in cost reduction and more prudent management of wind power variations. The demand response (DR) program is another solution to deal with wind power uncertainty and has a considerable impact on reducing power network congestion and total operation cost by peak-load shaving. Hence, to overcome the mentioned challenges and obstacles, this paper focuses on solving a robust network constrained unit commitment (NCUC) with TBES and DR programs. To manage the wind power uncertainty, an information gap decision theory (IGDT)-based robust optimization technique is proposed to obtain maximum robustness against the wind power uncertainty. The advantage of the presented model is that neither probability distribution functions (PDFs) nor scenario generation are required. The 6-bus power system coordinated with the 3-station railway network is applied as the test system. Numerical studies pointed out that integrating TBES technology in IGDT-based robust NCUC problems and considering the DR program has improved the power system’s flexibility and uncertainty management of wind power, alleviated the congestion, and reduced the optimized cost. Simulation results revealed a 6.5% cost reduction by applying TBES and also 11.3% cost decrement by developing coordinated TBES and DR.

中文翻译：

---

综合电力和铁路运输网络的鲁棒日前调度中可移动电池储能的技术经济评估

摘要 近年来，由于环境和经济原因，可再生能源（RE）资源的使用呈上升趋势。然而，找到一种解决方案来管理这些能源的波动性质和更有效地利用总发电容量是具有挑战性的问题，尤其是当电力系统中可再生能源的渗透率很高时。另一方面，电网的网络拥堵是阻碍可再生能源充分利用的另一个障碍。使用铁路网络的基于电池的储能运输导致了称为可移动电池储能（TBES）系统的新兴高效技术。TBES 技术是一种实用且经济的选择，可通过提供额外的电力传输设施来减少传输拥堵并提高储能系统 (ESS) 容量的利用率。作为一种灵活的资源，TBES 可以在高峰负荷时段适应系统的负载情况，从而降低成本并更谨慎地管理风电变化。需求响应（DR）计划是应对风电不确定性的另一种解决方案，对通过削峰填谷减少电网拥堵和总运营成本具有相当大的影响。因此，为了克服上述挑战和障碍，本文重点解决了具有 TBES 和 DR 程序的鲁棒网络约束单元承诺 (NCUC)。为了管理风电的不确定性，提出了一种基于信息差距决策理论（IGDT）的鲁棒优化技术，以获得针对风电不确定性的最大鲁棒性。所提出模型的优点是既不需要概率分布函数 (PDF) 也不需要场景生成。试验系统采用与3站铁路网相协调的6母线电力系统。数值研究指出，将TBES技术集成到基于IGDT的鲁棒NCUC问题中，并考虑DR方案，提高了电力系统对风电的灵活性和不确定性管理，缓解了拥塞，降低了优化成本。模拟结果表明，通过应用 TBES 可以降低 6.5% 的成本，并且通过开发协调的 TBES 和 DR 可以降低 11.3% 的成本。