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.