内点-分支定界法在最优机组投入中的应用

机组投入是现代电力系统编制发电计划的重要优化任务,具有显著的经济效益。从数学上讲,机组投入问题是一个多约束的NP难组合优化问题,很难得到理论上的最优解。提出运用内点-分支定界法求解最优机组投入问题。该方法将机组投入的离散变量松弛为0,1]区间上的连续变量,结合有功出力,进行优化。原始-对偶内点法收敛迅速、对初值不敏感,用来求解松弛问题,分支定界法用来处理离散变量。通过对2个算例的计算及与其它算法结果的比较,验证了该算法能得到更好的全局最优解。

Interior point method and branch-and-bound method for unit commitment

Unit commitment problem is an important optimization task in building generation planning of modern power systems,it has prominent economic benefit.From the view of mathematics,it is a NP hard combinational optimization problem with constraints and it is difficult to find the optimal solution in theory.This paper presents an application of Primal-Dual Interior Point Method(PDIPM) and Branch-and-Bound Method(BBM) for unit commitment problem.This method optimizes the relaxed zero-one variables and the active power continuous variables simultaneously.Interior Point Method,which convergences fast and is not sensitive to the initial point,is adopted to solve the relaxed problems,Branch-and-Bound Method is used to deal with the discrete variables.Compared with other methods,numerical results on two cases demonstrate the algorithm can get better global optimal solution.