Bidding strategies for energy storage players in 100% renewable electricity market: A game-theoretical approach

In electricity systems supplied by renewable energy sources (RES), storage operators shift energy across time, helping maintain system adequacy. However, characterizing their strategic role and identifying the conditions under which individually optimal storage operations align with social welfare is challenging. In this paper, we develop a Cournot competition model in which storage operators bid quantities to maximize profits in a 100% RES-supplied electricity market, where price-based competition is uninformative. Market clearing is embedded via a residual-demand construction that treats intermittency as an intertemporal arbitrage opportunity for storage. To this end, we propose a mixed-integer linear programming (MILP) formulation that addresses key nonlinearities through i) a big-M linearization and ii) an equivalent continuous reformulation using demand blocks. The strategic game is solved via a diagonalization (iterative best-response) algorithm, and a centralized social planner benchmark is cast as a one-shot optimization for welfare comparisons. We apply the model to Denmark, using 2024 day-ahead auction data and 2030 capacity and demand projections to reflect both present and forward-looking scenarios. The results show that, in our stylized DK1 day-ahead market, storage arbitrage smooths supply-demand imbalances and increases welfare relative to the no-storage case. With limited competition, however, strategic withholding increases prices and reduces welfare, while expanding storage capacity beyond a threshold yields no significant additional gains. These results highlight storage's dual role in stabilizing markets and creating market power, suggesting potential benefits of market designs that better align storage operators' incentives with social welfare under the idealized conditions examined.