Operation Scheduling of Battery Storage Systems in Joint Energy and Ancillary Services Markets

TLDR

The paper proposes a risk‑based framework to evaluate how a battery storage system should participate in multiple energy and ancillary services markets. It models simultaneous day‑ahead energy, spinning reserve, and regulation offers under uncertain market prices and deployment, using a nonprobabilistic robust optimization max‑min formulation that is linearized through duality theory. The approach is validated on an illustrative case study, demonstrating its feasibility and effectiveness.

Abstract

This paper presents a risk-based approach for evaluating the participation strategy of a battery storage system in multiple markets. Simultaneous offering in day-ahead energy, spinning reserve, and regulation markets is considered in this paper. The uncertainties considered include predicted market prices as well as energy deployment in spinning reserve and regulation markets. A new nonprobabilistic model is introduced in this paper to handle the uncertain nature of spinning reserve and regulation markets. Robust optimization is implemented to model these uncertain parameters and manage their related risk. The proposed risk-based model is a max-min problem, which is converted to its equivalent ordinary maximization problem using duality theory. The presented model is linearized by implementing strong duality theory. Finally, the proposed method is tested and verified using an illustrative case study.