Evolutionary programming based optimal power flow and its validation for deregulated power system analysis

被引：84

作者：

Sood, Yog Raj ^{[1
]}

机构：

[1] Natl Inst Technol, Dept Elect Engn, Hamirpur 177005, Himachal Prades, India

来源：

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS | 2007年 / 29卷 / 01期

关键词：

optimal power flow; evolutionary programming; deregulation; steepest descent method; genetic algorithm;

D O I：

10.1016/j.ijepes.2006.03.024

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Optimal power flow (OPF) has been widely used in power system operation and planning. In deregulated environment of power sector, it is of increasing importance, for determination of electricity prices and also for congestion management. The classical methods are usually confirmed to specific cases of the OPF and do not offer great freedom in objective functions or the types of constraints that may be used. With a non-monotonic solution surface, classical methods are highly sensitive to starting points and frequently converge to local optimal solution or diverge altogether. This paper describes an efficient evolutionary programming based optimal power flow and compares its results with well known classical methods, in order to prove its validity for present deregulated power system analysis. (c) 2006 Elsevier Ltd. All rights reserved.

引用

页码：65 / 75

页数：11

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