Day-Ahead Electricity Price Forecasting and Scheduling of Energy Storage in LMP Market

This paper proposes an optimization strategy for the day-ahead planning of utility owned energy storage operation while considering the electricity price volatility in locational marginal pricing (LMP) market. The proposed optimization strategy works upon the predicted day-ahead electricity prices while considering the consequences of energy storage scheduling on the next day's electricity prices. In this study, a piecewise linear relation between load and LMP is established using historical load and LMP data. The piecewise linear relation results are provided to the next stage for the proposed energy storage optimization which is solved using Quadratic Programming. This study is performed using the real historical data from New York Independent System Operator which provides price-based demand response program including day-ahead dynamic pricing which is suitable for the proposed study. The simulation is carried out for two energy storage sizes. The simulation result of our proposed optimization strategy, considering impact of energy storage charging/discharging on LMP, was compared with the optimization result considering no impact of energy storage on LMP. The results show that the proposed optimization strategy not only increases the revenue for the utility but also helps in smoothing the next day's electricity price curve.