Dynamic Energy Scheduling Algorithm for an End-user with Energy Storage Device to Save Total Costs

Abstract

Energy storage can save end user costs in local energy markets that have time-varying pricing. However, energy storage device incur fixed acquisition costs which depend on their capacity. End user is faced with sophisticated energy scheduling tradeoffs in the local energy markets to account for these costs. In this paper, we consider a typical energy usage scenario where the end user draws energy from multiple types of energy supplies: the local power provider, the external power grid, and the user’s own energy storage device. Our objective is to minimize the user’s total costs (the total of purchased energy and storage) while meeting their energy demand in each time slot. Furthermore, the end user’s energy demand, the local power supplier’s prices, and the external power grid prices all vary over time. To deal with this variability, we formulated the energy scheduling problem as a stochastic optimization. We propose a dynamic algorithm based on Lyapunov optimization, and it is theoretically proved that the proposed algorithm can make the optimization target infinitely close to optimum. Finally, the effectiveness of the proposed algorithm is verified by simulation comparison. The algorithm provides a tool for end user energy scheduling where the user is equipped with energy storage device.