Risk-Aware Stochastic Optimization for Battery Energy Arbitrage Dispatch Planning

This paper presents a risk-aware stochastic optimization framework for dispatch planning of Battery Energy Storage Systems (BESS) in volatile market conditions. By integrating quantile-based price forecasting with a stochastic optimization approach, the proposed model effectively captures market uncertainties and incorporates user-defined risk preferences. Simulation results demonstrate the framework’s ability to optimize dispatch schedules under varying risk scenarios, balancing profitability and risk mitigation. The findings provide actionable insights for flexibility service providers, enabling efficient and profitable energy arbitrage while managing exposure to adverse market conditions.