计及需求响应的光热电站参与深度调峰的分层优化调度策略

HIERARCHICAL OPTIMAL SCHEDULING STRATEGY FOR CONCENTRATING SOLAR POWER PARTICIPATING IN DEEP PEAK SHAVING CONSIDERING DEMAND RESPONSE

从源、荷两侧挖掘系统调峰潜力,建立计及需求响应的光热电站参与深度调峰的分层优化调度模型。上层从负荷侧出发,提出一种基于负荷分类的价格需求响应模型,可有效缓解系统调峰压力;中层从电源侧出发,利用光热电站灵活的调节特性在深度调峰时段协调火电机组参与辅助调峰,构建以运行总成本最小为目标函数的日前调度模型;下层提出一种基于模型预测控制的日内动态调整模型,在滚动优化的同时,通过状态反馈环节实时调整光热电站储热装置充放热修正日前调度计划。仿真结果表明,所提调度策略在降低系统调峰成本的同时能有效抑制风光以及负荷的短时功率波动,在保证系统安全稳定运行的前提下提升风光消纳率。

The peak regulation potential of the system is excavated from both sides of the source and load,and a hierarchical optimal scheduling strategy for concentrating solar power participating in deep peak shaving considering demand response is established.Starting from the load side,the upper layer proposes a price demand response model based on load classification,which effectively alleviates the pressure of system peak regulation.Starting from the power supply side,the middle layer uses the flexible regulation characteristics of the concentrating solar power to coordinate the thermal power units to participate in the auxiliary peak regulation during the deep peak regulation period,and constructs a day-ahead scheduling model with the minimum total cost as the objective function.In the lower layer,an intra-day dynamic adjustment model based on model predictive control is proposed.While rolling optimization,the day-ahead scheduling plan of the heat storage device of the concentrating solar power is adjusted in real time through the state feedback link.The simulation results show that the proposed scheduling strategy can effectively suppress the short-term power fluctuation of wind-solar and load while reducing the peaking cost of the system,and improve the wind-solar consumption rate under the premise of ensuring the safe and stable operation of the system.