A new arXiv paper models how Tesla, NextEra, and other storage operators should bid against each other in 100% renewable grids. The game-theoretic approach could boost revenue per MWh in high-penetration markets like California.
A new academic paper models how energy storage operators should bid into a wholesale electricity market that runs entirely on renewable generation. The approach uses game theory to account for competing storage players, each trying to maximize revenue from charging and discharging in a grid with no fossil-fuel baseload.
The paper, posted on arXiv, focuses on the strategic interaction between storage units rather than treating them as price takers. That distinction matters for listed companies that own or operate large battery fleets. If storage owners can bid more aggressively based on rivals' likely moves, revenue per megawatt-hour could rise.
Tesla's energy storage deployments reached 4.1 GWh in the second quarter. The company's Autobidder software already manages trading for some of its Megapack installations. A game-theoretic layer could improve Autobidder's pricing decisions, analysts at a clean-energy research firm said.
NextEra Energy, the largest U.S. owner of renewable generation, has been expanding its battery portfolio. The Florida-based utility reported 1.2 GWh of new storage additions in 2024. Its trading desk uses proprietary algorithms to optimize power sales. The paper's findings suggest that modeling competitor behavior explicitly could boost returns in regions with high storage penetration, such as California and Texas.
The catch is that the model assumes perfect information about rivals' costs and capacities. In practice, storage operators guard those data. The paper provides a starting point for more realistic multi-agent bidding, a trader at a regional power exchange said.
Renewable penetration already tops 80% in some grids. Storage margins in those markets will depend more on strategic bidding and less on flat arbitrage spreads. Companies that embed these algorithms first could capture a pricing advantage before the rest of the market catches up.
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