CityLearn v3：面向可再生能源社区控制研究的可配置仿真评估框架
原标题：CityLearn v3: A Configurable Simulation and Evaluation Framework for Realistic Control Studies of Renewable Energy Communities
AI 摘要
论文提出 CityLearn v3，一个面向可再生能源社区（REC）控制研究的可配置仿真与评估框架。该框架在单一仿真环境中表示成员与资产变化、柔性负荷截止时间、需求响应请求、本地能源共享以及数据或设备故障，并通过建筑与相位功率限制约束可控请求。框架记录控制器输入并区分请求动作与实际执行动作，配合参考控制器、服务与约束感知的性能指标及轨迹导出，支持社区内与跨社区比较。
正文节选
CityLearn v3: A Configurable Simulation and Evaluation Framework for Realistic Control Studies of Renewable Energy Communities Abstract Renewable energy communities (RECs) coordinate buildings, photovoltaic generation, batteries, electric vehicles and flexible loads. Controller studies often simplify changing participation, equipment availability, service deadlines and data quality, so lower cost or peak demand can conceal missed services or infeasible power requests. This paper presents CityLea