Multi-objective chance-constrained optimal day-ahead scheduling considering BESS degradation

Abstract

As battery technology matures, the battery energy storage system (BESS) becomes a promising candidate for addressing renewable energy uncertainties. BESS degradation is one of key factors in BESS operations, which is usually considered in the planning stage. However, BESS degradations are directly affected by the depth of discharge (DoD), which is closely related to the BESS daily schedule. Specifically, the BESS life losses may be different when providing the same amount of energy under a distinct DoD. Therefore, it is necessary to develop a model to consider the effect of daily discharge on BESS degradation. In this paper, a model quantifying the nonlinear impact of DoD on BESS life loss is proposed. By adopting the chance-constrained goal programming, the degradation in day-ahead unit commitment is formulated as a multi-objective optimization problem. To facilitate an efficient solution, the model is converted into a mixed integer linear programming problem. The effectiveness of the proposed method is verified in a modified IEEE 39-bus system.