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Article

Battery Swapping Stations for Grid Peak Shaving Under Virtual Power Plant Aggregation: A Complex-Network Evolutionary Diffusion Analysis

School of Business, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
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Author to whom correspondence should be addressed.
Systems 2026, 14(9), 1037; https://doi.org/10.3390/systems14091037
Submission received: 30 June 2026 / Revised: 4 August 2026 / Accepted: 19 August 2026 / Published: 23 August 2026
(This article belongs to the Section Complex Systems and Cybernetics)

Abstract

The rapid growth of distributed renewable generation and electric vehicles has increased the demand for flexible peak-shaving resources. Battery swapping stations (BSSs), which centrally manage standardized batteries under the battery-as-a-service model, can provide station-to-grid (S2G) services when aggregated by virtual power plants (VPPs). However, S2G adoption is influenced by contract design, market returns, subsidies, battery degradation, and heterogeneous consumer attitudes. This study develops a complex-network evolutionary diffusion model for VPP–BSS cooperation. The framework integrates a VPP profit-accounting module, a segmented Hotelling demand model, and an evolutionary game on a Newman–Watts small-world network. BSS strategies are updated through a partial asynchronous Fermi rule to reflect bounded rationality and investment inertia. Numerical simulations examine contract parameters, subsidy policies, consumer structures, exogenous variables, and network characteristics. The results show that S2G adoption follows an S-shaped trajectory but does not automatically reach full penetration. Successful diffusion requires a feasible combination of electricity prices, revenue sharing, settlement mechanisms, subsidies, consumer acceptance, and available battery capacity. The findings also reveal a trade-off between promoting BSS participation and maintaining VPP profitability, while robustness tests confirm the stability of the main conclusions.
Keywords: battery swapping station; virtual power plant; station-to-grid; evolutionary game; small-world network; subsidy policy; sensitivity analysis battery swapping station; virtual power plant; station-to-grid; evolutionary game; small-world network; subsidy policy; sensitivity analysis

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MDPI and ACS Style

Li, F.; Li, Q.; Li, Y. Battery Swapping Stations for Grid Peak Shaving Under Virtual Power Plant Aggregation: A Complex-Network Evolutionary Diffusion Analysis. Systems 2026, 14, 1037. https://doi.org/10.3390/systems14091037

AMA Style

Li F, Li Q, Li Y. Battery Swapping Stations for Grid Peak Shaving Under Virtual Power Plant Aggregation: A Complex-Network Evolutionary Diffusion Analysis. Systems. 2026; 14(9):1037. https://doi.org/10.3390/systems14091037

Chicago/Turabian Style

Li, Feifan, Qiuting Li, and Ying Li. 2026. "Battery Swapping Stations for Grid Peak Shaving Under Virtual Power Plant Aggregation: A Complex-Network Evolutionary Diffusion Analysis" Systems 14, no. 9: 1037. https://doi.org/10.3390/systems14091037

APA Style

Li, F., Li, Q., & Li, Y. (2026). Battery Swapping Stations for Grid Peak Shaving Under Virtual Power Plant Aggregation: A Complex-Network Evolutionary Diffusion Analysis. Systems, 14(9), 1037. https://doi.org/10.3390/systems14091037

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