TY - JOUR
T1 - Coordinating demand response strategies for electric vehicles and second-life battery energy storage to optimize renewable energy absorption under demand and supply uncertainties
AU - Xin, Qing Yao
AU - Zhang, Bin
AU - Zhang, Fang
AU - Bansal, Prateek
N1 - Publisher Copyright:
© 2025 Elsevier Ltd
PY - 2025/12
Y1 - 2025/12
N2 - Coordinating the individual charging behavior of electric vehicle (EV) users could enhance grid reliability and renewable energy (RE) integration. However, the absorption potential of RE may be restricted when the demand response for EV charging fails to adapt to the spatialtemporal dynamics of RE output. Moreover, this constraint intensifies under conditions of uncertain charging schedules and fluctuating RE output. To address this issue, our study proposes an innovative combined demand response strategy that integrates EV and second-life battery energy storage (BES) to deliver a responsive and adaptable electricity balancing mechanism for residential loads considering demand and supply uncertainty. A two-stage stochastic programming problem is developed, to maximize the response-related benefits and charging/discharging schedules given the optimized BES installation decision. Practical applicability is tested through a residential neighborhood case in Beijing, where charging characteristics are obtained from large-scale granular charging data through the Gaussian Mixture Model. Results show our combined strategy achieves an additional 10.3 % improvement in peak-valley difference mitigation and a 2.1 % enhancement in RE integration, compared with the EV-focused strategy. While gaining greater overall benefits, higher installation costs of BES may achieve lower cost-effectiveness, underscoring the need for sophisticated pricing strategies that incentivize BES deployment.
AB - Coordinating the individual charging behavior of electric vehicle (EV) users could enhance grid reliability and renewable energy (RE) integration. However, the absorption potential of RE may be restricted when the demand response for EV charging fails to adapt to the spatialtemporal dynamics of RE output. Moreover, this constraint intensifies under conditions of uncertain charging schedules and fluctuating RE output. To address this issue, our study proposes an innovative combined demand response strategy that integrates EV and second-life battery energy storage (BES) to deliver a responsive and adaptable electricity balancing mechanism for residential loads considering demand and supply uncertainty. A two-stage stochastic programming problem is developed, to maximize the response-related benefits and charging/discharging schedules given the optimized BES installation decision. Practical applicability is tested through a residential neighborhood case in Beijing, where charging characteristics are obtained from large-scale granular charging data through the Gaussian Mixture Model. Results show our combined strategy achieves an additional 10.3 % improvement in peak-valley difference mitigation and a 2.1 % enhancement in RE integration, compared with the EV-focused strategy. While gaining greater overall benefits, higher installation costs of BES may achieve lower cost-effectiveness, underscoring the need for sophisticated pricing strategies that incentivize BES deployment.
KW - Electric vehicles
KW - Renewable energy integration
KW - Second-life battery energy storage
KW - Two-stage stochastic programming model
KW - Uncertain charging behavior
UR - https://www.scopus.com/pages/publications/105019377994
U2 - 10.1016/j.tra.2025.104725
DO - 10.1016/j.tra.2025.104725
M3 - Article
AN - SCOPUS:105019377994
SN - 0965-8564
VL - 202
JO - Transportation Research Part A: Policy and Practice
JF - Transportation Research Part A: Policy and Practice
M1 - 104725
ER -