功率与负荷预测的智能建筑双时间尺度多能互补优化模型

Dual-time Scale Pluripotent Complementary Optimization Model for Smart Building Energy Management System Based on BIPV Power and Load Forecasting

建筑光伏(Building Integrated Photovoltaic,BIPV)发电功率出力的随机波动特性,新型负荷与传统负荷的相互作用、需求侧响应和分时电价对负荷特性的影响是智能建筑能量管理系统(Energy Management System,EMS)优化运行必须考虑且亟待解决的突出问题。以BIPV功率、负荷功率与温度预测为基础,综合考虑系统整体的经济性与用户舒适度,联合日前、日内两个时间尺度建立了智能建筑EMS的两阶段优化模型。日前尺度计及分时电价,以系统运行经济性为目标,制定可控电源机组启停、可平移负荷、储能装置的优化运行方案;日内尺度则在日前优化基础上综合平衡系统经济性和用户舒适度,对可控电源功率及可控负荷功率进行滚动优化。最后通过实际数据的算例仿真验证了本文所提模型的有效性。

Random fluctuation characteristic of the Building Integrated Photovoltaic （BIPV） power output, interaction between new type of load and traditional load, effect of load characteristics by demand response and time-of-use （TOU） price are outstanding issues that intelligent building energy management system （EMS） must be urgently resolved. Considering the energy economy and comfort level, a two-stage optimization model of smart building EMS is established in this paper from day-ahead and intra-day time-scales based on the power predictive values of BIPV, loads and temperature. The optimization objective of the day-ahead optimization is to minimize operating costs by TOU electricity price and determine the optimal operation of controllable power commitment, deferrable loads and energy storage device. The optimization objective of the intra-day is to balance operating costs and comfort level at the same time and optimize power of controllable power supply and controllable loads based on the results of day-ahead optimization. Thus, optimal operation of all kinds of generators, storages and loads that participate in demand response are optimized in the multi-time scales collaborative optimization and achieve the purpose of pluripotent complementary. Finally, the simulation example of actual data has been proposed to verify the effectiveness of the proposed model.