基于多场景随机规划和MPC的冷热电联合系统协同优化

摘要

以包含可再生能源及多种分布式资源的区域冷热电联合系统为研究对象,针对风光和负荷的不确定性,提出多场景随机规划结合模型预测控制(MPC)的方法,建立多时间尺度协调优化模型,其中日前和日内尺度主要以运行经济性最优为目标,求解机组的运行及出力计划;实时尺度采用模型预测控制技术,以日内尺度经济调度结果为参考,通过反馈校正与滚动优化调整机组运行出力,实现机组出力的精确控制,消除可再生能源波动性影响,并进一步讨论了出力扰动对调度结果的影响.算例分析证明所提模型和方法能够有效消除不确定性和风光波动性的影响,实现多能源互补协调优化运行.%A method based on multi-scenario stochastic programming and model predictive control is proposed for a regional combined cooling heating and power system with renewable resources and multiple distributed resources.A multiple time scale optimal dispatch framework is proposed considering the uncertainty of wind power and photovoltaic and loads.In the day-ahead and intraday optimization,the optimal operation economy is taken as the objective by regulating the operation and power output plans of each unit.While during the real-time scheduling,taking economic dispatch results as references,a model predictive control model is proposed to realize the accuracy control of unit outputs,in which the power output is regulated through feedback and rolling horizon optimization so that the power deviation can be eliminated.Case analysis shows that the proposed model and method can eliminate the influence of uncertainty and fluctuation of wind power and photovoltaic,and promote the complementary and coordination of operation for the integrated energy system.