考虑光伏不确定性的双层协同优化机组组合

Two-level collaborative optimization method for unit commitment considering photovoltaic uncertainty

为实现光伏系统高经济性、高环保性的运行,基于负荷与光伏发电的不确定性,设计了一种机组组合双层协同优化方法。第一层优化运用离散粒子群法,以系统污染排放最少为目标,求解最优机组启停状态问题;第二层优化运用改进粒子群法,以系统运行成本最小为目标,求解最优机组出力的问题。在机组组合问题上引入需求响应与光伏发电等手段,并考虑到用户负荷与需求侧的波动特性,建立了不确定性模型。以10机组系统为对象,通过MATLAB仿真验证表明,文章所提出的机组组合模型与优化方法能够使系统在允许存在预测误差的前提下,实现经济环保的运行。

A two-stage collaborative optimization method for unit commitment based on the uncertainty of demand side resources is proposed in this paper. On the first stage, the discrete particle swarm optimization(PSO) is applied to solve the optimal unit start-up and shutdown state with the decrease of the system emission. On the second stage, the cost of running the system is be cut down, and the improved PSO is adopted to deal with the problem of optimal unit output.Demand side resources, such as demand response(DR) and photovoltaic power generation, are also introduced into the unit commitment problem. Moreover, in consideration of the fluctuation characteristics of user load and demand side,the uncertainty model is established. Finally, the proposed method is verified by MATLAB simulation using the 10 unit system as the object. The results show that the unit combination model and optimization method proposed in this paper can effectively implement the system’s economic and environmental operation on the premise of allowing the existence of prediction error.