基于模型预测控制的冷热电联供型微网动态优化调度

Optimal Dynamic Dispatch for Combined Cooling Heating and Power Microgrid Based on Model Predictive Control

冷热电多能联供(combined cooling heating and power,CCHP)型微网具有节能、环保、经济等特点,有良好的发展前景和应用价值。为应对可再生能源的大规模接入及负荷的不确定性,该文提出基于模型预测控制的CCHP型微网动态优化调度策略。该优化策略首先对设备效率曲线模型进行分段线性化处理,以日前计划联供设备的出力值为参考值,在日内调度下建立可再生能源及负荷预测模型,基于多步滚动优化求解出各联供设备的平滑出力。仿真结果表明:分段线性效率曲线模型不但能更好模拟系统实际运行工况,且计算时间满足在线调度需求;滚动时长选取4h,不仅满足鲁棒性也能满足快速性;所提模型能够有效应对系统不确定性对系统经济调度的影响,实现其经济及安全运行。

Combined cooling, heating, and power（CCHP） systems have the characteristics of energy saving, environmental protection, economical efficiency, and so on, which bring it a good prospect and great application value. In order to track the fluctuation of the renewable energy and load in real time, a dynamic optimal scheduling strategy based on the model predictive control was proposed in this paper. This scheduling strategy linearizes the efficiency curves of the devices, takes the day-ahead dispatch plan as the reference, establishes the prediction model for the daily renewable energy and load, and then obtains smooth output results of the devices based on the multi-step rolling optimization. Through the case study, the model of linearizing the efficiency curve of the gas turbine can not only reflect the actual operation conditions of the combined cooling heating and power micro-grid, but also meets the calculation of online scheduling. In the case, the rolling period in the case are 4 hours, which can reach a stable and a quick response speed. The proposed model is able to depress the effect of uncertainties to the system dispatching, and ensures the system running with high economic efficiency and security.