Enhancing Day-Ahead Power System Flexibility with Independent Energy Storage Operators by Stochastic Chance-Constrained Game-Theoretic Model

The high penetration of renewable energy sources (RES) creates huge peak-to-valley net load difference and poses great challenges on the operational flexibility of power systems. Despite that energy storage (ES) has been regarded as a key solution to provide flexibility, lack of appropriate market mechanism still hinders the positive contribution of ES. In this paper, a bi-level stochastic chance-constrained optimization model is built to allow strategic bidding of ES in both the day-ahead electricity market and the reserve capacity market. In the upper level of the proposed model, independent ES operators will maximize the profit by arbitrage from the energy market and providing the reserve capacity. In the lower level, the independent system operator (ISO) will minimize the total system cost to clear the energy market and the reserve capacity market. Case studies using the IEEE 14-bus system are conducted to validate the proposed model, showing that the profitability of ES is increased compared to that under Time-of-Use pricing, and the operational flexibility of the power grid is also enhanced.