Stochastic Scheduling of Battery-Based Energy Storage Transportation System With the Penetration of Wind Power

Abstract

Battery-Based Energy Storage Transportation (BEST) is a potential solution for optimizing the power system operations with a high penetration of wind energy. In this paper, we propose a scenario-based stochastic model for the BEST-integrated power system scheduling. In this model, load and wind energy forecasting inaccuracies and random disturbances are modeled in scenario trees using the Monte Carlo simulation method. Random disturbances represent forced outages of both power system and railway system components, including generation units, transmission lines, railway stations, and railway lines. Benders decomposition is adopted to solve the stochastic model. Two BEST-integrated power systems are used to illustrate the proposed model and the performance of the proposed solution algorithm. The first one is a 6-bus power system integrated with a 3-station and 3-line railway network. The second one is the modified IEEE 118-bus power system integrated with a railway network composed of 8 railway stations and 10 rail lines. Simulation results show that the BEST system implementation is a viable option for managing the large-scale integration of wind power which can reduce the curtailment of wind power and accordingly lower the operation cost of power systems.