Online operating of photovoltaic–energy storage-charging and swapping stations in coordinated energy and regulation markets

With the rapid and sustained growth of electric vehicles (EVs), integrated photovoltaic-energy storage-charging and swapping stations (PV-ES-CSSs) are emerging as a new business model that enhances station profitability while providing flexible resources for mitigating EV-induced grid impacts and promoting renewable energy accommodation. However, uncertainties in PV generation and EV charging/swapping demand, along with volatile real-time electricity prices, challenge the reliable and economic operation of PV-ES-CSSs. This paper proposes an online operation strategy for PV-ES-CSSs in a multi-market environment to maximize station revenue while ensuring operational feasibility under uncertainty. First, a state of charge (SOC)-consistency-based flexibility aggregation model is developed to quantify heterogeneous regulation capability and reduce station-level flexibility overestimation, providing a unified scheduling basis for coordinated participation in energy and regulation markets. Then, an opportunity value function model integrating supervised learning and dynamic programming is proposed to map the residual energy states of ES, charging EVs, and swapping batteries into future revenue, enabling coordinated optimization of immediate profits and future regulation potential. Furthermore, a geometric-water-filling-based power allocation strategy with urgency indicators is designed to decompose station-level dispatch commands online under different market conditions while ensuring service demand fulfillment and regulation response accuracy. Simulation results show that the proposed strategy satisfies real-time response requirements, and reduces flexibility overestimation by 4.81%. Compared with coordinated multi-market operation without considering future opportunity values, the proposed strategy increases the total revenue by 2.98%. Moreover, compared with the cases involving participation only in the energy market and only in the regulation market, the total revenue is increased by 176.84% and 2.37%, respectively.

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Publication Details

Journal
Applied Energy
Published
2026-09-15
DOI
https://doi.org/10.1016/j.apenergy.2026.128821
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
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Online operating of photovoltaic–energy storage-charging and swapping stations in coordinated energy and regulation markets

Yanlei Zhao, Jiajia Chen, Yanxin Wang, Nikita Tomin et al.
Applied Energy
Electric Vehicles and Infrastructure
article

Online operating of photovoltaic–energy storage-charging and swapping stations in coordinated energy and regulation markets

Yanlei Zhao, Jiajia Chen, Yanxin Wang, Nikita Tomin, Dechang Yang
article en

Abstract

With the rapid and sustained growth of electric vehicles (EVs), integrated photovoltaic-energy storage-charging and swapping stations (PV-ES-CSSs) are emerging as a new business model that enhances station profitability while providing flexible resources for mitigating EV-induced grid impacts and promoting renewable energy accommodation. However, uncertainties in PV generation and EV charging/swapping demand, along with volatile real-time electricity prices, challenge the reliable and economic operation of PV-ES-CSSs. This paper proposes an online operation strategy for PV-ES-CSSs in a multi-market environment to maximize station revenue while ensuring operational feasibility under uncertainty. First, a state of charge (SOC)-consistency-based flexibility aggregation model is developed to quantify heterogeneous regulation capability and reduce station-level flexibility overestimation, providing a unified scheduling basis for coordinated participation in energy and regulation markets. Then, an opportunity value function model integrating supervised learning and dynamic programming is proposed to map the residual energy states of ES, charging EVs, and swapping batteries into future revenue, enabling coordinated optimization of immediate profits and future regulation potential. Furthermore, a geometric-water-filling-based power allocation strategy with urgency indicators is designed to decompose station-level dispatch commands online under different market conditions while ensuring service demand fulfillment and regulation response accuracy. Simulation results show that the proposed strategy satisfies real-time response requirements, and reduces flexibility overestimation by 4.81%. Compared with coordinated multi-market operation without considering future opportunity values, the proposed strategy increases the total revenue by 2.98%. Moreover, compared with the cases involving participation only in the energy market and only in the regulation market, the total revenue is increased by 176.84% and 2.37%, respectively.

Applied EnergyVol. 427
Shandong University of Technology (CN), Melentiev Energy Systems Institute (RU), China Agricultural University (CN)
Affordable and clean energy
Openalex Percentile: Top 20%
Electric Vehicles and Infrastructure
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