Working Papers

  • Pairing Batteries with Renewables: How Ownership Shapes Operational Incentives and Market Outcomes (download here)

    This paper examines how battery storage ownership structure affects wholesale electricity market outcomes by shaping operational incentives. Using a dynamic dispatch model calibrated to Texas data, I show how transmission congestion creates conditions in which batteries operated jointly with a renewable plant are used strategically to increase the value of renewable production. The strength of this incentive depends on supply elasticity and the timing of renewable production. Because of this strategic behavior, co-owned batteries reduce consumer surplus gains by approximately $16,000 per MWh of installed storage capacity over their lifetime relative to standalone batteries, but earn $36,000 per MWh higher profits. Market conditions do not generate enough profits for battery investment to be viable, regardless of ownership. Yet if subsidized, co-owned projects yield the highest net consumer surplus, because the additional revenues they generate reduce the required subsidy sufficiently to outweigh their smaller gross consumer gains. Co-owned projects deliver roughly $1.38 of net consumer surplus for every $1.00 of subsidy, compared with about $1.00 per $1.25 for standalone projects.

Work in Progress

  • Estimating the Curtailment-Mitigating Role of Battery Energy Storage Systems

    The rapid expansion of variable renewable energy (VRE) in Texas—reaching 27 GW of solar and 43 GW of wind capacity by 2024—has been accompanied by rising curtailment. When available generation exceeds transmission capacity or contemporaneous demand, grid operators must curtail zero-marginal-cost renewable output. This paper quantifies how battery energy storage systems (BESS) mitigate curtailment by absorbing surplus generation. Using hourly Texas data from 2019-2024, I exploit the staggered deployment of new battery installations to estimate the causal effect of storage on market-level curtailment. The identification strategy relies on exogenous variation in battery deployment driven by declining capital costs. I find that each additional MWh of battery capacity reduces curtailment by approximately 0.1 MWh during nighttime and early morning hours (6 PM to 8 AM), when wind generation is abundant, but has negligible effects during midday solar peak hours (9 AM to 5 PM).