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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.
Xin et al. (Thu,) studied this question.