Coherency Approach by Hybrid PSO, K-Means Clustering Method in Power System

被引：25

作者：

Davodi, Moez ^{[1
]}

Modares, HamidReza ^{[1
]}

Reihani, Ehsan ^{[1
]}

Davodi, Mehdi ^{[1
]}

Sarikhani, Ali ^{[1
]}

机构：

[1] Shahrood Univ Technol, Fac Elect & Robot Engn, Shahrood, Iran

来源：

2008 IEEE 2ND INTERNATIONAL POWER AND ENERGY CONFERENCE: PECON, VOLS 1-3 | 2008年

关键词：

Coherency; Particle Swarm optimization (PSO); K-Means; Clustering; Coherent generators;

D O I：

10.1109/PECON.2008.4762659

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 [计算机科学与技术];

摘要：

This paper presents a new method for recognition the identical behaviors of synchronous generators for particular fault location on power system. In this method, a hybrid algorithm combining particle swarm optimization (PSO) algorithm with k-means algorithm, also referred to PSO-KM algorithm is proposed to find the specified number of clusters in electric network. Each cluster represents a number of generators such that these generators named coherent generators. Clustering process is based on similarity of time domain data in transient stability studies. The new algorithm is evaluated on 39-Bus New England test system. Results show that the proposed algorithm has much potential in finding coherent generators.

引用

页码：1203 / 1207

页数：5

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