A Hybrid Robust-Stochastic Operation Model for BESS in the Day-Ahead and Automatic Frequency Restoration Markets

Battery energy storage systems (BESS) are essential for managing the increased penetration of renewable energy sources (RES). The limited energy capacity of these assets requires tools for optimising the stacking of multiple services. This work proposes a hybrid robust-stochastic mixed-integer linear program (MILP) to effectively schedule the participation of BESS in the day-ahead market (DAM) and the automatic frequency restoration market (aFRR). The adopted BESS model uses a piecewise linear interpolation to describe the system's efficiency. A robust formulation tackles the uncertainty in the DAM prices, while a stochastic formulation addresses the uncertainty of the aFRR energy request. The model determines the bids to submit in the day-ahead electricity markets and the aFRR market. A case study assesses the model's daily profit. The robust formulation reduces the risk of an incorrect DAM decision by more than 63.66 %. The stochastic formulation increases the revenues by 31.94 %.