【摘要】 电动汽车作为分布式储能资源参与车网互动前景广阔，但实际应用却遭遇用户参与度低的问题，电池老化与里程焦虑担忧是关键影响因素。为提高车主参与车联网(vehicle-to-everything, V2X)的积极性，基于电池老化感知能力量化，设计一种多场景V2X能量管理系统，将电池健康状态量化为“生命周期行驶周期”,运用多层感知器神经网络实现快速表达。同时，为模拟用户受到禀赋效应，存在电池资源溢价估值心理预期，建立信息物理社会系统(cyber-physical-social system, CPSS),通过虚拟系统中的人工电动汽车群体进行基于条件生成对抗网络(conditional generative adversarial network, CGAN)的响应数据增强，得到能量管理系统激励策略，最终实现用户侧与网侧双赢的局面。算例分析表明，所提方案能有效评估车网互动对电池寿命影响，缓解用户里程焦虑，为车主参与车网互动提供参考。更多还原

【Abstract】 Electric vehicles, as distributed energy storage resources, have broad prospects for participating in vehicle-to-everything(V2X) interactions. However, they encounter the problem of low user participation in practical applications. The key influencing factors are battery aging and range anxiety. In order to improve the enthusiasm of vehicle owners to participate in V2X technology, a multi-scenario V2X energy management system is designed based on battery aging perception capacity quantification. The battery health status is quantified as the "lifetime driving cycles", and a multi-layer perceptron neural network is used to achieve a fast linearized expression. At the same time, in order to simulate the psychological expectation of users experiencing endowment effects and having a premium in battery resource valuation, this paper establishes a cyber-physical-social system(CPSS) and enhances the response data based on conditional generative adversarial network(CGAN) through the artificial electric vehicle group in the virtual system to obtain the incentive strategy of the energy management system, ultimately achieving a win-win situation for both the user side and the grid side. Finally, a series of case studies show that the proposed scheme can effectively evaluate the impact of V2X interactions on battery life, alleviate range anxiety of users, and provide a reference for vehicle owners to participate in V2X interactions.更多还原