Degradation Aware Optimal Revenue Stacking of BESS-PV Plants Considering Electricity Markets’ Price Uncertainty

The paper proposes a stochastic optimization framework for the multi-market participation of a hybrid photovoltaic (PV) and battery storage system in the Italian electricity market. The problem is formulated as mixed-integer linear programming (MILP) that jointly determines the day-ahead energy schedule and the optimal bidding strategy in the ancillary services market (ASM), while considering the battery degradation. To account for the uncertainties of ASM, a scenario-based representation of price and activation probabilities is introduced. In addition, a novel logarithmic reformulation is proposed to incorporate a risk constraint on the daily bidding trajectory to model products of probabilities in MILP framework without additional approximations. The proposed approach is tested using historical Italian market data over a multi-day simulation horizon. Results show that coordinated participation in the day-ahead and ancillary services markets significantly improves the profitability of PV-BESS plants compared to energy-only strategies, while the proposed probabilistic constraint enables the adoption of statistically robust bidding strategies.