Congestion management in deregulated power system by series facts device using heuristic optimization algorithms

• Published in: Journal of intelligent & fuzzy systems 2022-01, Vol.42 (6), p.6195-6208
• Main Authors: George, Sophia Jasmine, Ramaraju, Satish Kumar, Venkataraman, Vanitha, Kaliannan, Thenmalar, Kumaravel, Umadevi, Veerasundaram, M.
• Format: Article
• Language: English
• Subjects: Algorithms; Congestion; Customer satisfaction; Deregulation; Electric industries; Electric power distribution; Electric power systems; Electric utilities; Electricity pricing; Flexible AC power transmission systems; Heuristic methods; Krill; Optimization; Particle swarm optimization; Power flow; Security; Transmission lines
• ISSN: 1064-1246; 1875-8967
• DOI: 10.3233/JIFS-212717

Conventionally in many countries, electrical power industry is organized as vertically integrated system. Under this system, large utilities are authoritative for the generation, transmission and distribution of electrical power. Such utilities are governed by the rules and regulations of the government and are forced to operate within the prescribed guidelines with minimal profit. This confirmation causes an ineffective and sluggish perspective in power industry with a lack of technical innovation, competent management and customer satisfaction. To overcome these deficiencies, power sector around the globe is getting restructured. This paper addresses an inevitable technical disputes occurring in deregulated environment i.e., transmission congestion which has an adverse effect on system security, increase in electricity pricing and line losses. Flexible AC Transmission System (FACTS) is a boon to the power sector which helps in a better and reliable power flow through the transmission lines. The problem is articulated as a multi objective function satisfying all the operational and security limits. Three heuristic algorithms namely Particle Swarm Optimization (PSO), Symbiotic Organism Search (SOS) and hybrid Quantum based PSO-Bio-geography based krill herd optimization (Q-PSOBBKH) algorithms were applied in finding solution to this complex congestion problem. To study the effectiveness of the proposed objective, IEEE 14 bus system was considered as the test system. In order to validate the proposed methodology three congestion cases i.e. bilateral transaction, multilateral transaction and overloading were imposed on the test bus system. Simulation was carried out in MATLAB.