Decision-Making in Energy Storage Participation in Multi-Variety Power Market Transactions

This paper delves into the decision-making processes of energy storage systems (ESS) participation in multi-variety power market transactions, focusing on the operational strategies and market dynamics that maximize revenue and enhance grid stability. We propose a bi-level decision-making model that addresses the complex interactions between ESS operations and market mechanisms. The upper-level model is designed to maximize the revenue of ESS by determining the optimal bidding strategy across energy, frequency regulation, and reserve markets, while the lower-level model aims to minimize the system's electricity procurement costs through joint clearing of the spot market. By applying the Karush-Kuhn-Tucker (KKT) conditions and dual theory, we transform the lower-level model into constraints for the upper-level problem, converting the bi-level model into a solvable Mixed Integer Linear Programming (MILP) problem. A case study based on a modified IEEE-30 node electrical system demonstrates the effectiveness of the proposed model in optimizing ESS operations within the market framework, contributing to grid stability and the economic viability of energy storage technologies. The paper concludes with directions for future research, including the incorporation of additional factors such as weather impacts and real-time market data to refine the model's predictive capabilities and strategic recommendations.