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http://dx.doi.org/10.5370/JEET.2007.2.3.312

A New Concept of Power Flow Analysis  

Kim, Hyung-Chul (Electrical & Research Department, Korean Railroad Research Institute)
Samann, Nader (Enernex corporation, Knoxville)
Shin, Dong-Geun (Department of Electrical Engineering, Korea University)
Ko, Byeong-Hun (Electrical & Research Department, Korean Railroad Research Institute)
Jang, Gil-Soo (Department of Electrical Engineering, Korea University)
Cha, Jun-Min (Department of Electrical Engineering, Daejin University)
Publication Information
Journal of Electrical Engineering and Technology / v.2, no.3, 2007 , pp. 312-319 More about this Journal
Abstract
The solution of the power flow is one of the most important problems in electrical power systems. These traditional methods such as Gauss-Seidel method and Newton-Raphson (NR) method have had drawbacks up to now such as initial values, abnormal operating solutions and divergences in heavy loads. In order to overcome theses problems, the power flow solution incorporating genetic algorithm (GA) is introduced in this paper. General operator of genetic algorithm, arithmetic crossover, and non-uniform mutation operator of GA are suggested to solve the power flow problem. While abnormal solution cannot be obtained by a NR method, multiple power flow solution can be obtained by a GA method. With a heavy load, both normal solution and abnormal solution can be obtained by a proposed method. In this paper, a floating number representation instead of the binary number representation is introduced for accuracy. Simulation results have been compared with traditional methods.
Keywords
Newton-Raphson method; Power Flow problem;
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  • Reference
1 R. N. Dhar, 'Computer Aided Power System Operation & Analysis', Tata McGraw-Hill Publishing Company Limited, 1982
2 Stagg and El-Abiad, 'Computer Method in Power System Analysis', McGraw-Hill Inc., 1968
3 Xiaodong Yin, 'Application of Genetic Algorithms to Multiple Load Flow Solution Problem in Electric Power Systems', Proceedings of the 32nd Conference on Decision and Control San Antonio, Texas, December 1993, pp. 3734-3739
4 Mitsuo Gen , Runwei Cheng, 'Genetic Algorithms & Engineering Optimization', John Wiley & Sons, New York 2000
5 F.M.A. Salam, L. Ni, S. Guo and X. Sun, 'Parallel Processing for the Load Flow of Power Systems: The Approach and Application', Proceedings of the 28th Conference on Decision and Control San Antonio, Texas, December 1989, pp. 2173-2178
6 Goldberg, David E, 'Genetic Algorithms in Search, Optimization, and Machine Learning', Addison-Wesley, 1989
7 Michalewicz, Zbigniew, 'Genetic Algorithms + Data Structures = Evolution Programs', Third edition, AI Series. Springer-Verlag, New York 1996
8 K.P. Wong, A.Li. and T.M.Y. Law, 'Advanced Constrained genetic algorithm load flow method', lEE Proc. - Gener. Transm. Distrib., Vol. 146, No. 6, pp. 609-616, November 1999   DOI   ScienceOn
9 Klos, A., and Kerner, A., 'The non-uniqueness of load flow solutions' Proceedings of 5th power system computation conference, Cambridge, UK, July 1975
10 K.P. Wong, A. Li. and T.M.Y. Law, 'Development of Constrained genetic algorithm load flow method', lEE Proc. - Gener. Transm. Distrib., Vol. 144, No. 2, pp. 91-99, March 1997   DOI   ScienceOn