基于模型预测控制的户用微电网在线能量管理方法

针对户用微电网中可再生能源出力和负荷需求的不确定性问题,对负荷需求响应特性、可再生能源出力特征、户用微电网能量控制系统的结构特征和运行机理等方面进行了研究,提出一种基于模型预测控制的在线能量管理方法。以用户最小用电成本作为优化目标,基于模型预测控制方法对户用微电网进行动态优化。同时根据用户的用电行为建立事件驱动机制,设置相应的触发条件,只有系统接收到触发信号时才进行在线决策优化。研究结果表明:所提的在线能量管理方法能够实时响应负荷需求,降低用电成本,提高微电网供需平衡能力,并且有效降低计算量。

Residential Micro-grid Online Energy Management Approach Based on Model Predictive Control

Aiming at the uncertainty of the output and load demand of renewable energy sources in the residential micro-grid,a study was made on response characteristics of load demand,output characteristics of renewable energy,as well as structural characters and operational mechanism of the energy control system of the residential micro-grid.An online energy management approach was proposed on the basis of model predictive control (MPC).Aiming at minimum power consumption cost of the user,the residential micro-grid was dynamically optimized in the MPC method.Moreover,an event-driven mechanism was established according to the user's power consumption behavior,and trigger conditions were so set that online decision optimization was only made when the system received the trigger signal.Research results indicated that the proposed online energy management approach could make real-time response to load demand,reduce power consumption cost,and improve supply-demand balance of the micro-grid.In addition,the calculation workload was effectively reduced.