Spatiotemporal Optimization of Grid-Connected Energy Storage to Maximize Economic Benefits

This paper proposes a spatiotemporal optimization strategy for an energy storage system (ESS) connected to the power grid, with an objective of maximizing its economic benefits. This optimization framework includes both spatial and temporal aspects by optimizing the location of the ESS in the network and the annual dispatch strategy, respectively. Energy arbitrage and frequency regulation are chosen to be the revenue streams as they have proved to be the most profitable applications for grid-connected storage systems. A lithium-ion battery is used for this study due to its widespread popularity, which arises from its high energy density, high efficiency, and decreasing costs. The degradation cost of the battery is taken into account while calculating the revenue to generate a more realistic estimate. Mixed-integer nonlinear programming is utilized in solving the spatiotemporal optimization problem. Results for the proposed method are validated using the IEEE Reliability Test System along with PJM Interconnection historical data.