基于数据挖掘技术的变电站无功蚁群优化算法  

A new Var optimal compensation strategy based on data mining and ant colony algorithm

作　　者：解大[1] 龚锦霞[1] 徐劲松[1] 张延迟[2] 

机构地区：[1]上海交通大学电气工程系,上海200240 [2]华东理工大学自动控制系,上海200237

出　　处：《电力系统保护与控制》2009年第10期19-26,共8页Power System Protection and Control

摘　　要：针对变电站在集中控制模式下的无功补偿与电压控制的问题,充分利用变电站运行过程中的大量数据,将数据挖掘技术应用于变电站电压无功自动调节系统,提出了基于关联规则的系统蚁群无功优化方法。将改进Apriori算法应用于无功优化方案的确定,并对蚁群优化算法进行改进,建立了基于实际数据挖掘结果的无功全局优化总体数学模型。以上海220kV万航变电站为例,以其日常运行的历史数据为基础,运用本文算法得到在各种典型工况下的最优方案,以指导实际运行。实验结果表明,基于数据挖掘的系统无功优化目标值方法可以提高系统运行效率,降低损耗,对系统电压稳定,经济运行意义重大。For the problem of the Var compensation and voltage control in center-substations, this paper induces a new algorithm to find the reactive optimization method of power system, using the data collected in power substations. The new algorithm is combined with improved Apriori data mining techniques and ant colony algorithm. The mathematic mode1 of Vat＂ optimization of power system are described and applied to resolve the reactive optimal compensation problem of Wanhang substation in Shanghai. Test results show that the application of the new algorithm proposed in this paper for determining the plan of reactive optimization operation can raise the system operation efficiency and reduce the loss. And it is of great economical significance for the system voltage control.

关 键 词：无功优化 蚁群算法 数据挖掘 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TM63[自动化与计算机技术—控制科学与工程]