Battery Energy Storage Train Scheduling in Power System Considering Renewable Power Generation

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI:10.1109/ICONAT57137.2023.10080735

Komal Mohan Todakar, P. P. Gupta, V. Kalkhambkar

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Abstract

Uncertain nature of renewable power sources (RES) like wind generation presents a significant issue for system operators. To reduce the negative effects of network congestion on the power system, battery energy storage (BES) Trains offer a potential way to deliver the energy produced by RES to the load center. The effects of stochastic scheduling of BES trains for railway transportation networks with uncertain wind power generation are evaluated in this paper. Using Autoregressive Integrated Moving Average (ARIMA) models, the uncertainties related to wind power for scenario generations are considered. Also, the vehicle routing problem related to the railway transportation system is solved using the time-space network model. As a case study, the BES Train integrated six-bus system with a three-station and three-line railway network is investigated. Simulation results evaluate the impact of BES Train, wind uncertainty, BES Train charging/discharging schedule, wind curtailment and computational time. In addition, BES Train can economically reduce network congestion and decreases operational cost.

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考虑可再生能源发电的电力系统电池储能列车调度

风力发电等可再生能源的不确定性是系统运营商面临的一个重要问题。为了减少电网拥塞对电力系统的负面影响，电池储能列车为将可再生能源产生的能量输送到负荷中心提供了一种潜在的途径。研究了风力发电不确定条件下铁路运输网BES列车随机调度的效果。利用自回归综合移动平均(ARIMA)模型，考虑了不同情景下风电的不确定性。同时，利用时空网络模型求解了与铁路运输系统相关的车辆路径问题。以北京列车为例，研究了三站三线铁路网络的六总线集成系统。仿真结果评估了BES列车、风不确定性、BES列车充放电计划、弃风和计算时间的影响。此外，BES列车可以经济地减少网络拥塞，降低运营成本。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2023 International Conference for Advancement in Technology (ICONAT)

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