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Optimal Power Flow Solution Using Particle Swarm Optimization Technique with Global-Local Best Parameters 被引量:4

Optimal Power Flow Solution Using Particle Swarm Optimization Technique with Global-Local Best Parameters
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摘要 This paper proposes an efficient method for optimal power flow solution (OPF) using particle swarm optimization (PSO) technique. The objective of the proposed method is to find the steady state operation point in a power system which minimizes the fuel cost, while maintaining an acceptable system performance in terms of limits on generator power, line flow limits and voltage limits. In order to improvise the performance of the conventional PSO (cPSO), the fine tuning parameters- the inertia weight and acceleration coefficients are formulated in terms of global-local best values of the objective function. These global-local best inertia weight (GLBestlW) and global-local best acceleration coefficient (GLBestAC) are incorporated into PSO in order to compute the optimal power flow solution. The proposed method has been tested on the standard IEEE 30 bus test system to prove its efficacy. The results are compared with those obtained through cPSO. It is observed that the proposed algorithm is computationally faster, in terms of the number of load flows executed and provides better results than the conventional heuristic techniques.
出处 《Journal of Energy and Power Engineering》 2010年第2期46-51,共6页 能源与动力工程(美国大卫英文)
关键词 Particle swarm optimization swarm intelligence optimal power flow solution inertia weight acceleration coefficient. 粒子群优化 优化技术 最优潮流 最佳参数 电源系统 测试系统 计算速度 稳态工作点
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  • 1H.W. Dommel, W.F. Tinney, Optimal power flow solutions, IEEE Trans. Power Apparatus Systems 87 (10) (1968) 1866-1876. 被引量:1
  • 2J.A. Momoh, R.J. Koessler, M.S. Bond, B. Stott, D. Sun, A. Papalexopoulos, P. Ristanovic, Challenges to optimal power flow, IEEE Trans. Power Systems 12 (1997) 444-455. 被引量:1
  • 3R. Jabr, Coonick, B. Cory, A homogeneous linear programming algorithm for the security constrained economic dispatch problem, IEEE Trans. Power Systems 15 (3) (2000)930-936. 被引量:1
  • 4W. Hua, H. Sasaki, J. Kubokawa, R. Yokoyama, An interior point non linear programming for optimal power flow problem with a novel data structure, IEEE Trans. Power Systems 13 (3) (1998) 870-877. 被引量:1
  • 5G. Torres, V. Quintana, On a non linear multiple-centrality corrections interior-point method for optimal power flow, IEEE Trans. Power Systems 16 (2) (2001) 222-228. 被引量:1
  • 6D.I. Sun, B. Ashley, B. Brewer, A. Hughes, W.F. Tinney, Optimal power flow by Newton approach, IEEE Trans. on Power Systems 103 (1984) 2864-2880. 被引量:1
  • 7L.L. Lai, J.T. Ma, Improved genetic algorithms for optimal power flow under both normal and contingent operation states, International Journal of Electrical Power Energy Systems 19 (5) (1997) 287-292. 被引量:1
  • 8J. Yuryevich, K.P. Wong, Evolutionary programming based optimal power flow algorithm, IEEE Trans. on Power Systems 14 (4) (1999) 1245-1250. 被引量:1
  • 9D.B. Fogel, Evolutionary computation towards a new philosophy of machine intelligence, Newyork, IEEE Press, 1995. 被引量:1
  • 10K.S. Swarup, Swarm intelligence approach to the solution of optimal power flow problem, J. Indian Inst. Scie. 86 (2006) 439-455. 被引量:1

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