基于分布鲁棒优化的多源发电系统联合调度

Joint Dispatching of Multi-source Power Generation System Based on Distributed Robust Optimization

为解决传统的随机优化和鲁棒优化方法不能同时兼顾经济性和安全性去处理风光等可再生能源大规模接入电力系统时的调度问题,采用在经济性和安全性上取得平衡的分布鲁棒优化方法来处理风光出力不确定的风-光-火-储联合发电系统日前经济调度问题。建立以运行成本最小为目标的多源发电系统联合调度模型,并利用分布鲁棒优化方法将其写成鲁棒机会约束形式。用Kullback-Leibler(KL)散度作为分布函数之间距离的度量,并建立风光出力的分布函数集合,以此来描述风光出力的不确定性。为加快求解速率,将鲁棒机会约束优化模型转化为混合整数优化模型。通过算例分析,验证了分布鲁棒优化方法的合理性和优越性,同时得出随着两个分布函数之间距离或置信度的增加,该方法的保守性也会增加。

When dealing with the dispatching problem in power system with the connection of large-scale renewable energy such as wind and photovoltaic(PV)power,the traditional random optimization and robust optimization methods cannot take into account the economy and safety at the same time.To solve this problem,a distributed robust optimization method that strikes a balance between the economy and safety is used to deal with the day-ahead economic dispatching problem of wind-PV-thermal-storage combined power generation system with uncertain wind and PV output.A joint dispatching model of multi-source power generation system with the goal of minimizing the operating cost is established,which is further written into the form of robust chance constraint using the method of distributed robust optimization.The Kullback-Leibler(KL)divergence is used as a measure of the distance between distribution functions,and the set of distribution functions ofwind and PV output is established to describe the uncertainty in wind and PV output.To speed up the solving rate,the robust chance-constrained optimization model is transformed into a mixed integer optimization model.Through the analysis of a numerical example,the rationality and superiority of the distributed robust optimization method are verified.At the same time,it is concluded that as the distance or confidence between the two distribution functions increases,the conservativeness of the proposedmethod will also increase.