2003 IEEE Bologna Power Tech Conference Proceedings,
DOI: 10.1109/ptc.2003.1304363
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Optimal location of facts devices to enhance power system security

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Cited by 108 publications
(84 citation statements)
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“…In order to improve the power system static security, the TCSCs and SVCs should be installed properly so as to eliminate or relieve the overloaded lines and maintain the bus voltages at a desired [25,33] can be considered to minimize:…”
Section: Objective Functionmentioning
confidence: 99%
See 1 more Smart Citation
“…In order to improve the power system static security, the TCSCs and SVCs should be installed properly so as to eliminate or relieve the overloaded lines and maintain the bus voltages at a desired [25,33] can be considered to minimize:…”
Section: Objective Functionmentioning
confidence: 99%
“…In [25], three heuristic methods, for instance, the genetic algorithm (GA), the tabu search method (TS) and the simulated annealing (SA) are applied to optimal installation of FACTS to enhance the system security. A GA is applied for seeking the optimal placement of multi-type FACTS to maximize the loadability in a power system [26].…”
Section: Introductionmentioning
confidence: 99%
“…Some of papers have been tried to find suitable location for FACTS devices to improve power system security and loadability [14][15][16][17]. Optimal allocation of these devices in deregulated power systems has been presented in [18][19].…”
Section: Fig 1 Considered Facts Devices (A) Tcsc (B) Svc (C) Upfcmentioning
confidence: 99%
“…Such problem is solved in literatures. References [69], [70],a novel optimization based methodology such as a simulated annealing has been proposed for optimal location of FACTS devices such as TCSC and SVC in order to relive congestion in the transmission line while increasing static security margin and voltage profile of power system networks. In [177], the Goal Attainment (GA) method based on the SA approach is applied to solving general multi-objective VAR planning problems by assuming that the Decision Maker (DM) has goals for each of the objective functions.…”
Section: Simulated Annealing (Sa) Algorithmsmentioning
confidence: 99%
“…The various artificial intelligence (AI) based methods proposed in literature includes genetic algorithms (GA) [49]- [64], [175]- [176], [180], tabu search algorithms [65], [66], simulated annealing (SA) based approach [69]- [70], [177], particle swarm optimization (PSO) techniques [71]- [73], [80], artificial neural network (ANN) based algorithms [74]- [76], ant colony optimization (ACO) algorithms [77]- [78], graph search algorithms [79], fuzzy logic based approach [81]- [82], other techniques such as norm forms of diffeomorphism techniques [83], evolution strategies algorithms [84], [86], improved evolutionary programming [68], gravitational optimization techniques [85], benders decomposition techniques [42], augmented Lagrange multiplier approach [67], hybrid meta-heuristic approach [172], heuristic and algorithmic approach [178], energy approach [179].…”
Section: Introductionmentioning
confidence: 99%