在智能电网环境下,提出了一种家庭能源管理系统框架和优化调度算法。根据室外温度预测值、可再生能源功率输出预测值、日前电价信号和用户偏好,算法对可调度用电负载、电动汽车、储能系统的运行进行优化调度从而最小化用户用电费用。算法考虑了电动汽车在高电价时段通过V2H(vehicle to home,V2H)功能向负载供电的情形,采用情景分析法处理室外温度和可再生能源功率输出预测的不确定性。通过仿真实验验证了算法性能,结果表明与只对负载或家庭能源管理系统部分组成部件进行优化调度的算法相比,所提算法显著降低了用电费用。
This paper focuses on the energy optimal operation problem of microgrids(MGs) under stochastic environment.The deterministic method of MGs operation is often uneconomical because it fails to consider the high randomness of unconventional energy resources.Therefore,it is necessary to develop a novel operation approach combining the uncertainty in the physical world with modeling strategy in the cyber system.This paper proposes an energy scheduling optimization strategy based on stochastic programming model by considering the uncertainty in MGs.The goal is to minimize the expected operation cost of MGs.The uncertainties are modeled based on autoregressive moving average(ARMA) model to expose the effects of physical world on cyber world.Through the comparison of the simulation results with deterministic method,it is shown that the effectiveness and robustness of proposed stochastic energy scheduling optimization strategy for MGs are valid.
Hepeng LiChuanzhi ZangPeng ZengHaibin YuZhongwen Li
