含离散变量的大规模电力系统无功优化

Reactive power optimization in large-scale powersystems with discrete variables

针对实际电力系统的数学模型包含离散变量和连续变量的特点,提出了一种精确求解电力系统无功优化的方法——内点分支定界法。通过把离散变量连续化,采用原始对偶内点法在可行域内进行全局寻优,结合广度优先遍历的分支定界法对离散变量进行归整处理等办法,找到了比传统无功优化更加合理的全局最优解。为了解决大规模系统计算耗时的问题,又提出了简化的分支定界法以加快求解速度。IEEE-118和IEEE-300系统的计算结果表明:所提出的算法对于求解大规模电力系统的无功优化问题是有效的。

This paper presents a new method, IBBM （Interior Branch- and- Bound Method）, to gain the exact solution of reactive power optimization, which coincides with that the mathematical model of a practical power system usually includes both discrete and continuous variables. By converting discrete variables into continuous variables,applying the primal- dual interior method to global optimization within the feasible domain and integrating with the branch-and- bound method based on BFS（Breadth-First-Search） for the discrete variables,the more reasonable exact solution can be obtained than the conventional result. Moreover,a simplified branch-and-bound method is proposed to reduce the execution time which increases with the size of system growing. Numerical simulations on two IEEE standard test systems,IEEE-118 and IEEE-300,respectively verify that the proposed algorithm is effective to solve reactive power optimization problem of large scale of power system.