Optimal Power Flow in Power Networks with TCSC Using Particle Swarm Optimization Technique

被引：5

作者：

Monal, Patil ^{[1
]}

Heistrene, Leena ^{[1
]}

Pandya, Vivek ^{[1
]}

机构：

[1] Pandit Deendayal Petr Univ, Elect Engn Dept, Gandhinagar, Gujrat, India

来源：

ADVANCES IN ELECTRIC POWER AND ENERGY INFRASTRUCTURE | 2020年 / 608卷

关键词：

Optimal power flow; Optimization technique; Artificial intelligence; Particle swarm optimization;

D O I：

10.1007/978-981-15-0206-4_8

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Optimal power flow (OPF) plays an important role in power system operation and control. The OPF mainly aims to optimize the certain objective function such as minimizing the generation fuel cost, while at the same time satisfying load balance constraints and bound constraints. Particle swarm optimization (PSO) technique is an artificial intelligence-based technique. PSO technique is used to optimize the parameters like bus voltages, angles, real power generation fuel cost and the reactance values of TCSC. In this paper, the TCSC is incorporated using reactance model at fixed locations and power flow studies are carried out using Newton-Raphson method. The proposed approach is examined on modified IEEE 14-bus test system with and without TCSC device. The results are compared to the performance of the overall power network in the presence and absence of TCSC, and it is representing an analysis in order to show effectiveness of presented work.

引用

页码：91 / 101

页数：11

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