Optimal energy storage scheduling based on demand response signals

This paper presents an optimization framework for the scheduling of energy storage systems (ESSs) that exploits both price arbitrage opportunities and incentive-based demand response (DR) signals. The proposed model captures fine-grained DR programs by considering two complementary signal types: (1) capacity signals that commit storage capacity for demand reduction, and (2) dispatch signals that require actual energy discharge during peak events. By formulating a mixed-integer linear program (MILP), the method optimally decides charge and discharge actions and DR participation over a time horizon to maximize net revenue. A representative case study with time-varying energy prices and DR events demonstrates the benefits of the integrated approach. Results show that EES operator charges during low-price periods and discharges during DR dispatch intervals, yielding additional profit beyond standard arbitrage. This scheduling method may substantially increase the storage profitability and grid flexibility.