Enhancement of ATC with FACTS devices using Real-code Genetic Algorithm

• Published in: International journal of electrical power & energy systems Vol. 43; no. 1; pp. 1276 - 1284
• Main Authors: Nireekshana, T., Kesava Rao, G., Siva Naga Raju, S.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.12.2012; Elsevier
• Subjects: Applied sciences; ATC improvement; Contingency; Continuation Power Flow; Deregulation; Devices; Disturbances. Regulation. Protection; Electric power generation; Electrical engineering. Electrical power engineering; Electrical power engineering; Exact sciences and technology; Genetic algorithms; Miscellaneous; Operation. Load control. Reliability; Optimization; Power networks and lines; Real-code Genetic Algorithm; SVC; TCSC; Voltage; ATC improvement; TCSC; SVC; Continuation Power Flow; Real-code Genetic Algorithm; Deregulation; Flexible AC transmission systems; Power transmission; Power system economics; Optimization; Load flow; Bus system; Trade; Electrical network; Genetic algorithm; Power flow; Static VAr compensators; Available transfer capability; Contingency table; Thyristor controlled series capacitor; Power markets; IEEE standards; Reliability; Energy transfer
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2012.06.041

► We focus on the impact of FACTS devices to maximize Available Transfer Capability. ► Enhancement of ATC is more with TCSC when compared to SVC. ► Implementation of the proposed Real-code Genetic Algorithm gives good result. ► Installing SVC will improve voltage profile as well as resulting ATC enhancement. ► TCSC can improve ATC in both thermal dominant case and voltage dominant case. Determination and enhancement of Available Transfer Capability (ATC) are important issues in deregulated operation of power systems. This paper investigates the use of FACTs devices, like SVC and TCSC, to maximize power transfer transactions during normal and contingency situations. ATC is computed using Continuation Power Flow (CPF) method considering both thermal limits and voltage profile. Real-code Genetic Algorithm (RGA) is used as an optimization tool to determine the location and controlling parameters of SVC and TCSC. The suggested methodology is tested on IEEE 14-bus system and also on IEEE 24-bus reliability test system for normal and different contingency cases.