Open AccessA novel approach for optimal allocation of series FACTS device for transmission line congestion management
Author(s) -
Sarwar Md,
Siddiqui Anwar Shahzad
Publication year - 2021
Publication title -
engineering reports
Language(s) - English
Resource type - Journals
ISSN - 2577-8196
DOI - 10.1002/eng2.12342
Subject(s) - particle swarm optimization , electricity market , electricity , computer science , thyristor , sensitivity (control systems) , mathematical optimization , transmission system , electric power transmission , transmission (telecommunications) , electric power system , power (physics) , engineering , voltage , electrical engineering , telecommunications , mathematics , algorithm , electronic engineering , physics , quantum mechanics
The reformed electricity market structure has forced the transmission network to operate near its operational limits. Due to competition in electricity market and with increasing demand, the probability of occurrence of congestion in transmission network has also increased. This resulted in insecure operation of power system and inefficient operation of the electricity market. The main aim of this article is to achieve efficient management of congestion in terms of minimum cost of electricity. This is accomplished by optimally allocating thyristor‐controlled series capacitor (TCSC) in the system. Since flexible alternating current transmission system (FATCS) devices involve heavy installation cost, its proper allocation plays a vital role in achieving the electricity market economics. Therefore, in this article, a new sensitivity index called line flow sensitivity factor is proposed to find the optimal location of TCSC while its control parameter setting is optimally obtained with particle swarm optimization algorithm. The obtained results are validated through implementation of TCSC based on its minimum installation cost. Further, two different penalty factors for violation of system constraints are also introduced in the problem formulation to effectively consider the competitive nature of the electricity market. The proposed method is tested on IEEE 30‐bus system, IEEE 118‐bus system, and 33‐bus Indian network and the results are found to be encouraging. The performance of the optimization algorithm on different systems is also analyzed in this article.