2012
DOI: 10.1016/j.ijepes.2012.04.017
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Optimal placement and parameter setting of SVC and TCSC using PSO to mitigate small signal stability problem

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Cited by 96 publications
(48 citation statements)
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“…(18) where s shows the separation weight, Si indicates the separation of the i-th individual, a is the alignment weight, A is the alignment of i-th individual, c indicates the cohesion weight, Ci is the cohesion of the i-th individual, f is the food factor, Fi is the food source of the i-th individual, e is the enemy factor, Ei is the position of enemy of the ith individual, w is the inertia weight, and t is the iteration counter.After calculating the step vector, the position vectors are calculated as follows: (19) To improve the randomness, stochastic behaviour, and exploration of the artificial dragonflies, they are required to fly around the search space using a random walk (Levy flight) when there is no neighbouring solutions. In this case, the position of dragonflies is updated using the following equation:…”
Section: Dragonfly Algorithm (Da)mentioning
confidence: 99%
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“…(18) where s shows the separation weight, Si indicates the separation of the i-th individual, a is the alignment weight, A is the alignment of i-th individual, c indicates the cohesion weight, Ci is the cohesion of the i-th individual, f is the food factor, Fi is the food source of the i-th individual, e is the enemy factor, Ei is the position of enemy of the ith individual, w is the inertia weight, and t is the iteration counter.After calculating the step vector, the position vectors are calculated as follows: (19) To improve the randomness, stochastic behaviour, and exploration of the artificial dragonflies, they are required to fly around the search space using a random walk (Levy flight) when there is no neighbouring solutions. In this case, the position of dragonflies is updated using the following equation:…”
Section: Dragonfly Algorithm (Da)mentioning
confidence: 99%
“…PSO is a novel population based method which utilizes the swarm intelligence generated by the cooperation and competition between the particle in a swarm and has emerged as a useful tool for engineering optimization. [18][19][20]. S.Meerjaali (2015) proposed a new approach of optimization by using Dragon fly algorithm [21].…”
Section: Introductionmentioning
confidence: 99%
“…PSO é uma técnica de otimização estocástica robusta, não-linear com base no comportamento dos enxames de abelhas em procura de pólen, com este método é possível obter soluções de ótima qualidade, em intervalos de tempos curtos e características de convergência estáveis (Mondal et al, 2012).…”
Section: Introductionunclassified
“…The method proposed in [14] was aimed to determine the optimal locations and settings for SVC and TCSC installations by using a PSO algorithm to mitigate small signal oscillations in a multimachine power system. While the strategy proposed in [15], comprised of the tabu search (TS) and a nonlinear programming method, was utilized to optimize FACTS devices investment and recovery.…”
Section: Introductionmentioning
confidence: 99%