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Stochastic Weight Trade-Off Particle Swarm Optimization for Optimal Power Flow

Luong Dinh Le1, Loc Dac Ho1, Jirawadee Polprasert2, Weerakorn Ongsakul2, Dieu Ngoc Vo3, and Dung Anh Le3
1 Faculty of Mechanical-Electrical-Electronic, Ho Chi Minh City University of Technology, HCMC, Vietnam
2. Energy Field of Study, School of Environment, Resources and Development, Asian Institute of Technology, Pathumtnani 12120, Thailand
3. Department of Power Systems, Ho Chi Minh City University of Technology, HCMC, Vietnam

Abstract—This paper proposes a stochastic weight trade-off particle swarm optimization (SWT-PSO) method solving optimal power flow (OPF) problem. The proposed SWTPSO is a new improvement of PSO method using a stochastic weight trade-off for enhancing search its search ability. The proposed method has been tested on the IEEE 30 bus and 57 bus systems and the obtained results are compared to those from other methods such as conventional PSO, genetic algorithm (GA), ant colony optimization (ACO), evolutionary programming (EP), and differential evolution (DE) methods. The numerical results have indicated that the proposed SWT-PSO method is better than the others in terms of total fuel costs, total loss and computational times. Therefore, the proposed SWT-PSO method can be a favorable method for solving OPF problem. 

Index Terms—optimal power flow, particle swarm optimization, stochastic weight trade-off, quadratic fuel function, valve point effects

Cite: Luong Dinh Le, Loc Dac Ho, Jirawadee Polprasert, Weerakorn Ongsakul, Dieu Ngoc Vo, and Dung Anh Le, "Stochastic Weight Trade-Off Particle Swarm Optimization for Optimal Power Flow," Jounal of Automation and Control Engineering, Vol. 2, No. 1, pp. 31-37, March, 2014. doi: 10.12720/joace.2.1.31-37
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