Stochastic Cournot Model for Coordinated Strategic Bidding of Wind-Storage Systems

In recent years, government incentives and subsidies have driven significant growth in wind power plant (WPP) capacity, establishing WPPs as key players in the evolving electricity market. However, the inherent variability of wind generation introduces challenges, including potential penalties for deviations in energy output. Energy Storage Systems (ESS) serve as a versatile solution to mitigate the uncertainties associated with wind power variability. This paper proposes a comprehensive model for the joint bidding of WPPs and ESS in competitive electricity markets. The interactions between WPPs and ESS are modeled using a stochastic Cournot framework, accounting for wind power uncertainties through inter-hour ramp constraints. A Location-Based Dual Imbalance Price (DIP) mechanism is adopted for wind-storage systems operating within a network-constrained oligopolistic electricity market. The Nash equilibrium strategy is used to optimize the WPP-ESS bids, considering the competitive behavior of other market participants. A Mixed Integer Linear Programming (MILP) model is developed to determine the Nash equilibrium by evaluating a payoff matrix. Various practical scenarios are analyzed to demonstrate the efficacy of the proposed approach. Furthermore, the study investigates the influence of different imbalance price mechanisms on WPP-ESS profits, market clearing operations, and Nash equilibrium outcomes.