An Improved Dual Grey Wolf Optimization Algorithm for Unit Commitment Problem

被引：4

作者：

Liu, Jian ^{[1
]}

Liu, Sanming ^{[2
]}

机构：

[1] Shanghai Dianji Univ, Dept Elect Engn, Shanghai 201306, Peoples R China

[2] Shanghai Dianji Univ, Dept Math & Phys, Shanghai 201306, Peoples R China

来源：

INTELLIGENT COMPUTING, NETWORKED CONTROL, AND THEIR ENGINEERING APPLICATIONS, PT II | 2017年 / 762卷

关键词：

Unit commitment; GWO; bGWO; Dynamic weight;

D O I：

10.1007/978-981-10-6373-2_16

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

An improved dual grey wolf optimization (GWO) algorithm with binary and dogmatic parts were proposed. The up and down state of units were optimized by binary grey wolf optimization (bGWO), and the exchange velocity was modified by adding two dynamical factors in random number producing. The GWO was used in units' load scheduling during the process of deciding up-down states and after the solution. One examples with 10 units including 24 period of time was simulated, the results showed the proposed algorithm improved convergence rate and accuracy of the solution.

引用

页码：156 / 163

页数：8

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