Optimal economic and environmental arbitrage of grid-scale batteries with a degradation-aware model

Abstract

Energy arbitrage is a potential revenue stream for battery operators with access to variable electricity prices. However, the power shifted by grid-scale energy storage has the potential to influence the production mix in real time, impacting the carbon emissions of the electricity system. Little research is available on the CO₂ emissions induced by arbitrage operations, and studies that consider arbitrage-related CO₂ emissions often neglect battery degradation. To address this gap, this study proposes a novel modeling and assessment framework based on mixed-integer linear programming to analyze the trade-offs between profit and CO₂ emissions of battery arbitrage operations as well as the impact of degradation on arbitrage profit and emissions. We present the results in terms of Pareto-optimal solutions that identify maximum profit and minimum CO₂ emissions. We illustrate our model through a case study in Germany and we show that performing maximum-profit arbitrage increases the system emissions by up to 7.5 tCO₂ per MWh of storage capacity (or about 12% of battery life cycle emissions per year). 60% of the added emissions can be avoided by sacrificing only 1.5% to 2.7% of the net arbitrage profit, and CO₂-neutral operation can be achieved by sacrificing about 7% of the profit. Our findings also highlight the importance of modeling battery degradation, as degradation-unaware arbitrage models may lead to a substantial profit loss (potentially to negative profits) and higher CO₂ emissions (up to +260%) with respect to degradation-aware models.