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

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.