计及光热电站不确定性的CHP系统两阶段优化调度方法

针对光热电站和热电联供（combined heat and power，CHP）系统联合优化调度难题，提出了一种以运行成本最低为目标的两阶段随机优化调度模型。在日前调度阶段，以能源出力预测值作为输入量，制定各微元出力的日前调度计划。在实时调整阶段，采用动态场景生成和削减的方法，建立光热出力的不确定性模型，从而制定日内实际备用计划。通过天津地区典型案例仿真分析，表明本文提出的两阶段优化调度模型能够保证所制定的日前调度阶段出力计划和日内实时调整阶段备用计划的有效性，提高了系统可靠性且降低运行成本。

A Two-Stage Optimal Scheduling Method for CHP Systems Considering the Uncertainty of Solar-Thermal Power Stations

A two-stage stochastic optimization scheduling model with the lowest operating cost is established to solve the problem of joint optimal scheduling of solar-thermal power station and CHP system. In the day-ahead scheduling stage,prediction error is not considered,and the predicted value is used as the input quantity to make a daily effort to arrange each micro-element. In the real-time adjustment stage,the uncertainty model of PV generation output is established,and the standby demand under the scheduling scheme of the previous dispatch stage is evaluated. A typical case in Tianjin is presented,the simulation results of which show that the two-stage optimal scheduling model proposed in this paper can guarantee the effectiveness of the scheduling plan and the standby demand in real time,and can improve the reliability and reduce the running cost.