Battery Bidding under Price Uncertainty in Wholesale Electricity Markets

2026-06-11

AI Summary

This study investigates the underlying drivers of seemingly strategic bidding behavior by grid-scale batteries in wholesale electricity markets, distinguishing between market power manipulation and rational decision-making under price uncertainty. To this end, the authors develop an asset-level battery bidding model that integrates price uncertainty and risk preferences, optimizing piecewise buy-sell offer curves in the day-ahead market via a mean-CVaR objective while respecting physical and market constraints to balance expected returns against risk. Employing a finite-scenario stochastic optimization approach, the original mixed-integer linear program is exactly reformulated as a linear program, enhancing computational tractability. The analysis reveals that, absent market power, “withholding” behavior stems from energy scarcity and price volatility; state-of-charge uncertainty significantly influences offer direction; and risk aversion leads to a tiered bidding structure combining guaranteed baseline revenues with exposure to extreme high prices. Empirical results confirm that batteries raise sell offers during energy scarcity and may suppress them when energy is abundant.

Abstract

Grid-scale batteries increasingly influence outcomes in wholesale electricity markets, but their observed bid patterns remain difficult to interpret. In particular, bids that appear to reflect strategic withholding may instead arise from rational operations under price uncertainty and risk management. We develop an asset-level model of a price-taking battery that submits stepwise buy and sell bid curves in the day-ahead market under a finite set of price scenarios. The battery chooses quantity--price pairs to maximize a mean--CVaR objective subject to physical and market constraints. A direct formulation is a mixed-integer linear program, but we show that its integer decisions can be removed, yielding an exact linear programming reformulation suitable for empirical analysis. Our empirical results deliver three insights. First, withholding behavior can arise even without market power, because scarce stored energy and uncertain future prices increase the value of holding energy. Second, the effect of uncertainty depends on the state of charge: when stored energy is scarce, greater uncertainty raises sell bid prices, whereas when stored energy is abundant it can lower them. Third, risk management reshapes bid curves into layered structures that secure profitable execution across a broad set of scenarios while preserving some exposure to rare but valuable price spikes.

Problem

• battery bidding
• price uncertainty
• wholesale electricity markets
• risk management
• strategic withholding

Innovation

• mean-CVaR optimization
• linear programming reformulation
• price uncertainty
• battery bidding
• risk-aware dispatch