Optimal Scheduling of Mobile Energy Storage Devices for Energy Management

Abstract

This paper addresses the problem of scheduling the optimal power outputs and moving paths of mobile energy storage devices (MESDs) in a distribution network with the aim of minimizing total energy loss cost during a day. These MESDs operate as large-size batteries that can be loaded on electric trucks and timely connected to charging stations for electric vehicles, in contrast to stationary energy storage systems (ESSs). Distribution system operators (DSOs) can own and optimally operate the MESDs to provide cost-effective and reliable energy services adaptively. In this paper, the moving distances and transit time periods of the MESDs are modeled using a set of linear equations with consideration of traffic congestions. For the optimal scheduling, the linearized model is integrated with the linear constraints for the stable operation of a distribution power network. The optimization problem can then be solved using a mixed-integer linear programming (MILP) algorithm. Simulation case studies are performed using a modified IEEE 34-Node Test Feeder with the forecast data on the load demand, renewable power generation, and traffic time periods. The case study results demonstrate that the proposed scheduling method successfully leads to the effective use of the MESDs for the reduction in the total energy loss in the power and traffic networks, compared to the conventional method using stationary ESSs.