The Bi-level Co-optimization Model for Energy and Primary Frequency Regulation Markets Incorporating Energy Storage

Large-scale energy storage as a new type of flexible market player performs arbitrage in the energy market and can also provide primary frequency regulation (PFR) service to make a profit. This paper proposes a bilevel optimization joint model of energy storage in energy and primary frequency regulation markets. The model is nonlinear and non-convex. The reformulation-linearization technique (RLT) is used to transform them into linear constraints. The relaxation and primary-dual reformulation of the original, and penalization of the associated duality gap are used to transform the non-convex model into a single-level mixed integer linear programming problem (MILP) which can be solved directly. Case studies show the validity of the proposed bi-level model. The results reflect the influence of energy storage on system frequency and market-clearing price.