A past global optimization approach to VAr planning for the large scale electric power systems
A past global optimization approach to VAr planning for the large scale electric power systems
复制标题
大型电力系统VAr规划的过去全局优化方法
DOI：
10.1109/59.575761
复制
发表时间：
1997
影响因子：
6.6
通讯作者：
Y. Hsiao
中科院分区：
文献类型：
--
作者：
Chih;Wu;Chun;Y. Hsiao
本文提出了一种新的快速全局优化方法--混合部分梯度下降/模拟退火法（HPGDSA），用于无功优化规划。引入HPGDSA算法，同时兼顾质量和速度，搜索全局最优解。HPGDSA的基本思想是部分梯度下降和模拟退火彼此交替，使得它减少了传统模拟退火（SA）方法的CPU时间，同时保留了SA的主要特性，即，获得全局最优解的能力。HPGDSA已应用于一个实际的电力系统，台湾电力系统（台电系统），取得了令人满意的结果。
In this paper, an innovative fast global optimization technique, hybrid partial gradient descent/simulated annealing (HPGDSA), for optimal VAr planning is presented. The HPGDSA is introduced to search the global optimal solution considering both quality and speed at the same time. The basic idea of the HPGDSA is that partial gradient descent and simulated annealing alternate with each other such that it reduces the CPU time of the conventional simulated annealing (SA) method while retaining the main characteristics of SA, i.e., the ability to get the global optimal solution. The HPGDSA was applied to a practical power system, Taiwan Power System (Tai-Power System), with satisfactory results.