A Hybrid Genetic Algorithm for Optimal Power Flow Incorporating 
 FACTS Devices

Vijayakumar, K.; Kumudinidevi, R.P.

doi:10.3923/ajsr.2008.403.411

Cited by 16 publications

(1 citation statement)

References 8 publications

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“…In order to overcome this negativity, researchers have intensified their efforts on artificial intelligence and evolutionary methods for determining the parameters of FACTS. There are some studies in the literature using these methods such as GA [7,8], PSO [8,9] non-linear interior point [10], fuzzy logic [5] and some hybrid methods created by combining a few of them [11,12,4]. But there is a main disadvantage that these methods doesn't exactly converge the local optimum and have huge computational time.…”

Section: Introductionmentioning

confidence: 99%

Optimal power flow incorporating FACTS devices using Gravitational Search Algorithm

Sönmez

Güvenç

Duman

et al. 2012

2012 International Symposium on Innovations in Intelligent Systems and Applications

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This paper aims to solve the optimal power problem (OPF) incorporating flexible AC transmission systems (FACTS) devices using Gravitational Search Algorithm (GSA) that minimizes the fuel cost function in the problem. In the optimization problem, Thyristor controlled series compensation (TCSC) and thyristor controlled phase shifter (TCPS) FACTS devices are considered to find their optimum location in transmission lines. In order to evaluate the effectiveness of proposed algorithm, it has been tested on modified IEEE 30 bus system and compared with particle swarm optimization (PSO) and hybrid tabu search and simulated annealing (TS/SA) approach which are used in solving the same problem and reported before in the literature. Results show that GSA produces better results than others and has fast computing time for solving OPF problem with FACTS.

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