The growing adoption of electric vehicles (EVs) creates opportunities to support power system reliability by using EV batteries as decentralized storage resources. This paper proposes an optimization framework for EV aggregators participating in ancillary service markets through unidirectional smart charging (V1G) and vehicle-to-grid (V2G) operation, explicitly accounting for battery lifetime degradation. Eleven scenarios are evaluated in the context of the Swedish electricity market to examine different market participation strategies, degradation modeling approaches, and degradation compensation schemes. Two degradation models are considered: a simplified empirical model and a detailed lithium-ion degradation model based on solid electrolyte interphase (SEI) formation — a passivation layer that forms on the negative electrode during battery operation and contributes to capacity fade and internal resistance increase. Unlike most prior studies that focus only on capacity loss, the proposed framework captures both capacity fade and power capability fade, enabling more realistic scheduling and cost estimation. Results demonstrate that controlled EV charging and participation in ancillary services significantly improve economic outcomes compared to uncontrolled charging. In a case study with 55 EVs, the EV aggregator achieves a daily net revenue of up to €100, even for a relatively small-scale system. At the same time, EV owners receive charging cost reductions of up to 40% compared to the baseline uncontrolled charging scenario. Scenarios with explicit degradation compensation achieve fairer cost allocation at minimal profit reduction for the EV aggregator. A sensitivity analysis further demonstrates that the main economic conclusions remain robust across a wide range of degradation cost assumptions. Overall, the study confirms that battery degradation-aware V1G/V2G strategies can deliver significant economic benefits while respecting operational constraints. • Degradation-aware V1G/V2G optimization for Swedish pay-as-bid reserve markets. • Compare simplified and SEI-based LFP aging models including power capability fade. • Validated with aging data; 11 market scenarios quantify aggregator and owner gains.
Anggraini et al. (Mon,) studied this question.