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ผู้วิจัย
Numphetch Sinsuphun, Uthen Leeton ,Umaporn Kwannetr, Dusit Uthitsunthorn,Thanatchai Kulworawanichpong
บทคัดย่อ
This paper describes optimal power flow based on swarm intelligences in which the power transmission loss function is used as the problem objective. Although most of optimal power flow problems involve the total production cost of the entire power system, in some cases some different objective may be chosen. In this paper, to minimize the overall power transmission losses, four decision variables are participated. They are i) power generated from generating plants, ii) specified voltage magnitude at control substations, iii) tap position of tap changing transformers and iv) reactive power injection from reactive power compensators. Swarm intelligences are wellknown and widely accepted as potential intelligent search methods for solving such a problem. In this paper, Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC) and Differential Evolution (DE) are employed to solve optimal power flow problems. A 6-bus and 30-bus IEEE power systems are used for test. As a result, all swarm intelligences search algorithms can solve optimal power flow problems efficiently. The artificial bee colony and the differential evolution provide results better than other swarm intelligent techniques.
บรรณานุกรม
[1] M.R AlRashidi and M.E El-Hawary, "Hybrid Particle Swarm Optimization Approach for Solving the Discrete OPF Problem Considering the Valve Loading Effects," IEEE Transactions on Power Systems, Issue 4, Vol. 22, pp.2030 2038, 2007. [2] B. Zhao, C.X. Guo and Y.J. Cao, "Improved particle swam optimization algorithm for OPF problems," IEEE-PES Power Systems Conference and Exposition, Vol. 1, pp.233 - 238, 10-13 October 2004. [3] C.A Roa-Sepulveda and B.J. Pavez-Lazo, "A solution to the optimal power flow using simulated annealing," Power Tech Proceedings 2001, Vol. 2, pp. 5, 10-13 September 2001. [4] R.N. Banu and D. Devaraj, "Optimal Power Flow for Steady state security enhancement using Genetic Algorithm with FACTS devices," 3rd International Conference on Industrial and Information Systems, pp. 1 6, 8-10 December 2008. [5] L.L. Lai and J.T. Ma, "Power flow control in FACTS using evolutionary programming," IEEE International Conference on Evolutionary Computation, pp. 10, 29 November-1 December 1995. [6] C. Gonggui and Y. Junjjie, "A new particle Swarm Optimization Solution to Optimal reactive power Flow Problem," Asia-Pacific Power and Energy Engineering Conference, pp.1 4, 27-31 March 2009. [7] L. Weibing, L. Min and W. Xianjia, "An improved particle swarm optimization algorithm for optimal power flow," IEEE 6th International Power Electronics and Motion Control Conference 2009, pp. 2448 2450, 17-20 May 2009. [8] W. Cui-Ru, Y. He-Jin, H. Zhi-Qiang, Z. Jiang Wei and S. Chen-Jun, "A modified particle swarm optimization algorithm and its application in optimal power flow problem," International Conference on Machine Learning and Cybernetics 2005, pp. 2885 2889, 18-21 August 2005. [9] S. M. Kumari, G. Priyanka and M. Sydulu , "Comparison of Genetic Algorithms and Particle Swarm Optimization for Optimal Power Flow Including FACTS devices," IEEE Power Tech 2007, pp. 1105 - 1110, 1-5 July 2007. [10] C. Chokpanyasuwant, S. Anantasate1, S. Pothiya ,W. Pattaraprakom and P. Bhasaputra1, "Honey Bee Colony Optimization to solve Economic Dispatch Problem with Generator Constraints," ECTI-CON 2009. 6th International Conference, Vol. 1, pp. 200 203, 2009. [11] S. Anantasate, C.Chokpanyasuwan and P. Bhasaputra, "Optimal Power Flow by using Bees Algorithm," ECTI Conference, pp.459 463, 2010. [12] U. Leeton, D. Uthitsunthorn, U. Kwannetr, N. Sinsuphun and T. Kulworawanichpong, "ower Loss Minimization Using Optimal Power Flow Based on Particle Swarm Optimization," ECTI Conference, pp.469 473, 2010. [13] P. Dutta and A. K. Sinha, "Voltage Stability Constrained Multi-objective Optimal Power Flow using Particle Swarm Optimization," 1st International Conference on Industrial and Information Systems, pp. 161 166, 8-11 August 2006. [14] Z. Haibo, Z. Lizi and M. Fanling, "Reactive power optimization based on genetic algorithm," International Power Conference on Power System Technology, pp.1448 1453, 18-21 August 1998. [15] K. Somsai, A. Oonsivilai, A. Srikaew, and T. Kulworawanichpong, "Optimal PI controller design and simulation of a static var compensator using MATLABs SIMULINK," The 7th WSEAS International Conference on POWER SYSTEMS, Beijing, China, pp. 30 35, September 2007. [16] The MathWorks Inc., Genetic Algorithms and Direct Search TOOLBOX, CD-ROM Manual, 2004. [17] J. Hazra1 and A. K. Sinha, "A Study on Real and Reactive Power Optimization using Particle Swarm Optimization," International Conference on Industrial and Information Systems, pp. 323-328, 9-11 August 2007. [18] N.T. Linh and N.Q. Anh, "Application of artificial beecolony algorithm (ABC) for reconfiguring distribution network," International Conference on Computer Modelling and Simulation, pp. 102-106. [19] N. Karaboga, "A new design method based on artificial bees colony algorithm for digital IRR fiters," Journal of the Franklin Institute, Vol. 346, pp.328348, 2009. [20] D. Karaboga and B. Busturk, "A powerful and e±cient algorithm for numerical function optimization: arti¯cial bee colony optimization," Journal of Global Optimization, VOl. 39, pp. 459- 471. [21] S.P. Karthikeyan, K. Palanisamy, L.J. Varghese, I.J. Raglend, and D.P. Kothari, "Comparison of Intelligent Techniques to Solve Economic Load Dispatch Problem with Line Flow Constraints," Advance Computing Conference, 2009. IACC 2009. IEEE International, pp. 446452, 6-7 March 2009. [22] M. Varadarajan, K. S. Swarup, "Solving multiobjective optimal power flow using differential evolution," Generation, Transmission & Distribution, IET, Vol 2, pp. 720730, 2008.
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