TY - JOUR ID - 3086 TI - Genetic Algorithm Based Fuzzy Multi-Objective Approach to FACTS Devices Allocation in FARS Regional Electric Network JO - Scientia Iranica JA - SCI LA - en SN - 1026-3098 AU - Kalantar, M. AU - Gitizadeh, M. AD - Department of Electrical Engineering,Iran University of Science and Technology Y1 - 2008 PY - 2008 VL - 15 IS - 6 SP - EP - KW - FACTS devices allocation KW - multi-objective optimization KW - Genetic Algorithm KW - fuzzy DO - N2 - In this investigation, a novel approach is presented to nd the optimum locations and capacity of Flexible AC Transmission Systems (FACTS) devices in a power system using a fuzzy multi-objective function. Maximising the fuzzy satisfaction allows the optimization algorithm to simultaneously consider the multiple objectives of the network to obtain active power loss reduction; i.e., new FACTS devices cost reduction, robustifying the security margin against voltage collapse, network loadability enhancement and a voltage deviation reduction of the power system. A Genetic Algorithm (GA) optimization technique is then implemented to solve the fuzzy multi-objective problem. Operational and control constraints, as well as load constraints, are considered for optimum device allocation. Also, an estimated annual load pro le has been utilized in a Sequential Quadratic Programming (SQP) optimization sub-problem to nd the optimum location and capacity of FACTS devices, accurately. A Thyristor Controlled Series Compensator (TCSC) and a Static Var Compensator (SVC) are utilized as series and shunt FACTS devices in this study. The Fars regional electric network is selected as a practical system to validate the performance and e ectiveness of the proposed method. UR - https://scientiairanica.sharif.edu/article_3086.html L1 - https://scientiairanica.sharif.edu/article_3086_677b0491d0ebf41ea8a8d72f60ee312d.pdf ER -