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HEURISTIC METHODS TO SOLVE OPTIMAL POWER FLOW PROBLEM

Year 2013, Volume: 13 Issue: 2, 1653 - 1659, 25.12.2013

Abstract

Optimal Power Flow (OPF) is one of the most effective tools for both analysis of current and planning of new power systems. The Manuscript is about an Artificial Intellicence (AI) application based on Heuristic methods can solve OPF problems with an more extreme accuracy compared to conventional methods. In this paper, the total hourly generation cost of generator units are minimized as an objective function to meet the load demand and system losses. Real Coded Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods developed using MATLAB are applied to IEEE 14 and IEEE 30 standart test systems to solve OPF problem. In consequence of the OPF carried with the use of PSO and GA, the optimum solutions were compared to similar studies in the literature. It was determined that the PSO algorithm developed within the scope of this paper provides lower-cost results than GA developed for this study and the GA studies that are  present in the literature.

References

  • Kaur H.,Brar Y.S. and Randhawa J.S., Optimal Power Flow Using Power World Simulator ,IEEE Electrical Power & Energy Conference , s. 1-2, 2010.
  • C. Sumpavakup, I. Srikun, and S. Chusanapiputt, “A Solution to the Optimal Power Flow Using Artificial Bee Colony Algorithm”, International Conference on Power System Technology, 978-J-4244-5940-7/10/, Tailand, 2011.
  • X. Tong and M. Lin, “Semismooth Newtontype Algorithms for Solving Optimal Power Flow Problems”, in Proc. Of IEEE/PES Transmission and Distribution Conference, Dalian, China, pp.l-7, 2005.
  • 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.
  • 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 19 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.
  • 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.
  • 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.
  • 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.
  • Abido M.A., “Optimal Power Flow Using Tabu Search Algorithm”, Electric Power Components and Systems, Taylor & Francis 30:469–483, 2002.
  • Rajasekar N., Soravana Ilango G., Edward Belwin J. and Rajendra K., “A Novel Approach Using Particle Swarm Optimization Technique for Optimum Power Flow Problem with Reduced Control Variables”, Proceedings of World Academy of Science, Engineering and Technology, Vol.37,ISSN 2070-3740, January 2009.
  • Geidl Martin and Anderson Göran, “Optimal Power Flow of Multiple Energy Carriers”, IEEE Trans. On Power Systems,Vol. 22, No.1,February 2007.
  • Abido M.A., “Multi Objective Particle Swarm Optimization for Optimal Power Flow Problem”, 12 th International Middle-East Power System Conference, pp. 392 – 396, 12-15 March 2008
  • E. Muneender and M. Vinod Kumar, “A Zonal Congestion Management Using PSO and Real Coded Genetic Algorithm”, Power Systems Conference and Exposition (PSCE’09. IEEE/PES), April, 2009.
  • Devaraj D. and Yegnanarayana B.,“Genetic-Algorithm-Based Optimal Power Flow for Security Enhancement”, IEEE Proc.Gener. Transm. Distrib., Vol. 152, No. 6, pp. 899-905, November 200 J. Kennedy and R. C. Eberhart, “Particle Swarm Optimization,” Proceedings of IEEE International Conference on Neural Networks (ICNN’95), Vol. IV, pp. 1942-1948, Perth, Australia, 1995.
  • J. Kennedy and R. C. Eberhart, “A New Optimizer Using Particle Swarm Theory,” 6th International Conference on Micro Machine and Human Science, pp. 39-43, Nagaya, Japan, 1995.
  • Park J-B., Jeong Y-W., Kim H-H. and Shin J-R., “An Improved Particle Swarm Optimization for Economic Dispatch with Valve-Point Effect “, International Journal of Innovations in Energy Systems and Power, Vol. 1, no. 1 , November 2006.
  • Soares J., Sousa T., Vale Z. A., Morais H. and Faria P., “Ant Colony Search Algorithm for the Optimal Power Flow Problem”, 978-1-4577-1002-5/11/, Porto, 2011.
  • Nidul Sinha, R. Chakrabarti and P. K. Chattopadhyay, “Evolutionary Programming Techniques for Economic Load Dispatch,” IEEE Transactions on Evolutionary Computation, Vol. 7 No.1, pp. 83-94, 2003.
  • Kwannetr U., Leeton U., Kulworawanichpong T., “Optimal Power Flow Using Artificial Bee Colony Algorithms”, International Review of Electrical Engineering (I.R.E.E.), Vol. 6, N.4, July-August 2011.
  • Malik T.N., Asar A., Wyne M.F., Akhtar S.A.,”A New Hybrid Approach for the Solution of Nonconvex Econimic Dispatch problems”,Electric Power Systems Research, 2008.
  • Yasar C., Ozyon S., “A New Hybrid Approach for Nonconvex Economic Dispatch Problem with Valve-Point Effect”, SciVerse Science Direct, Elsevier, Energy 36 58385845, September 2011.
  • Vu P.T., Le D.L. ve Tlusty J., “A Novel WeightImproved Particle Swarm Optimization Algorithm for Optimal Power Flow and Economic Load Dispatch Problems”, 978-1-4244-6547-7/10, IEEE Transactions on
  • Power Systems, 2010. Rengin Idil Cabadag received the B.Sc. degree in Electrical Engineering from Yildiz Technical University in 2009. Then she got her M.S. degree from Energy Institute of Istanbul Technical University in 2012. She is currently a Research Assistant at TU Dresden in Germany. Her research interests include Power
  • Systems and Impact of Renewable Energy Sources on Power Systems. Belgin Emre Turkay received the B.Sc, M.S. and Ph.D. degrees in Electrical Engineering from Istanbul Technical University, Turkey. She is currently working as a Professor at Istanbul Technical University and she is also Istanbul Technical University Electrical Engineering Program Coordinator since 2011. Her research areas consist of
  • Distribution Systems, Electric Power Generation, Power Quality, Automation and Control, Power System Operation, Control and Optimization, Renewable Energy Sources.
Year 2013, Volume: 13 Issue: 2, 1653 - 1659, 25.12.2013

Abstract

References

  • Kaur H.,Brar Y.S. and Randhawa J.S., Optimal Power Flow Using Power World Simulator ,IEEE Electrical Power & Energy Conference , s. 1-2, 2010.
  • C. Sumpavakup, I. Srikun, and S. Chusanapiputt, “A Solution to the Optimal Power Flow Using Artificial Bee Colony Algorithm”, International Conference on Power System Technology, 978-J-4244-5940-7/10/, Tailand, 2011.
  • X. Tong and M. Lin, “Semismooth Newtontype Algorithms for Solving Optimal Power Flow Problems”, in Proc. Of IEEE/PES Transmission and Distribution Conference, Dalian, China, pp.l-7, 2005.
  • 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.
  • 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 19 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.
  • 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.
  • 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.
  • 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.
  • Abido M.A., “Optimal Power Flow Using Tabu Search Algorithm”, Electric Power Components and Systems, Taylor & Francis 30:469–483, 2002.
  • Rajasekar N., Soravana Ilango G., Edward Belwin J. and Rajendra K., “A Novel Approach Using Particle Swarm Optimization Technique for Optimum Power Flow Problem with Reduced Control Variables”, Proceedings of World Academy of Science, Engineering and Technology, Vol.37,ISSN 2070-3740, January 2009.
  • Geidl Martin and Anderson Göran, “Optimal Power Flow of Multiple Energy Carriers”, IEEE Trans. On Power Systems,Vol. 22, No.1,February 2007.
  • Abido M.A., “Multi Objective Particle Swarm Optimization for Optimal Power Flow Problem”, 12 th International Middle-East Power System Conference, pp. 392 – 396, 12-15 March 2008
  • E. Muneender and M. Vinod Kumar, “A Zonal Congestion Management Using PSO and Real Coded Genetic Algorithm”, Power Systems Conference and Exposition (PSCE’09. IEEE/PES), April, 2009.
  • Devaraj D. and Yegnanarayana B.,“Genetic-Algorithm-Based Optimal Power Flow for Security Enhancement”, IEEE Proc.Gener. Transm. Distrib., Vol. 152, No. 6, pp. 899-905, November 200 J. Kennedy and R. C. Eberhart, “Particle Swarm Optimization,” Proceedings of IEEE International Conference on Neural Networks (ICNN’95), Vol. IV, pp. 1942-1948, Perth, Australia, 1995.
  • J. Kennedy and R. C. Eberhart, “A New Optimizer Using Particle Swarm Theory,” 6th International Conference on Micro Machine and Human Science, pp. 39-43, Nagaya, Japan, 1995.
  • Park J-B., Jeong Y-W., Kim H-H. and Shin J-R., “An Improved Particle Swarm Optimization for Economic Dispatch with Valve-Point Effect “, International Journal of Innovations in Energy Systems and Power, Vol. 1, no. 1 , November 2006.
  • Soares J., Sousa T., Vale Z. A., Morais H. and Faria P., “Ant Colony Search Algorithm for the Optimal Power Flow Problem”, 978-1-4577-1002-5/11/, Porto, 2011.
  • Nidul Sinha, R. Chakrabarti and P. K. Chattopadhyay, “Evolutionary Programming Techniques for Economic Load Dispatch,” IEEE Transactions on Evolutionary Computation, Vol. 7 No.1, pp. 83-94, 2003.
  • Kwannetr U., Leeton U., Kulworawanichpong T., “Optimal Power Flow Using Artificial Bee Colony Algorithms”, International Review of Electrical Engineering (I.R.E.E.), Vol. 6, N.4, July-August 2011.
  • Malik T.N., Asar A., Wyne M.F., Akhtar S.A.,”A New Hybrid Approach for the Solution of Nonconvex Econimic Dispatch problems”,Electric Power Systems Research, 2008.
  • Yasar C., Ozyon S., “A New Hybrid Approach for Nonconvex Economic Dispatch Problem with Valve-Point Effect”, SciVerse Science Direct, Elsevier, Energy 36 58385845, September 2011.
  • Vu P.T., Le D.L. ve Tlusty J., “A Novel WeightImproved Particle Swarm Optimization Algorithm for Optimal Power Flow and Economic Load Dispatch Problems”, 978-1-4244-6547-7/10, IEEE Transactions on
  • Power Systems, 2010. Rengin Idil Cabadag received the B.Sc. degree in Electrical Engineering from Yildiz Technical University in 2009. Then she got her M.S. degree from Energy Institute of Istanbul Technical University in 2012. She is currently a Research Assistant at TU Dresden in Germany. Her research interests include Power
  • Systems and Impact of Renewable Energy Sources on Power Systems. Belgin Emre Turkay received the B.Sc, M.S. and Ph.D. degrees in Electrical Engineering from Istanbul Technical University, Turkey. She is currently working as a Professor at Istanbul Technical University and she is also Istanbul Technical University Electrical Engineering Program Coordinator since 2011. Her research areas consist of
  • Distribution Systems, Electric Power Generation, Power Quality, Automation and Control, Power System Operation, Control and Optimization, Renewable Energy Sources.
There are 25 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Rengin Cabadag

Belgin Turkay

Publication Date December 25, 2013
Published in Issue Year 2013 Volume: 13 Issue: 2

Cite

APA Cabadag, R., & Turkay, B. (2013). HEURISTIC METHODS TO SOLVE OPTIMAL POWER FLOW PROBLEM. IU-Journal of Electrical & Electronics Engineering, 13(2), 1653-1659.
AMA Cabadag R, Turkay B. HEURISTIC METHODS TO SOLVE OPTIMAL POWER FLOW PROBLEM. IU-Journal of Electrical & Electronics Engineering. December 2013;13(2):1653-1659.
Chicago Cabadag, Rengin, and Belgin Turkay. “HEURISTIC METHODS TO SOLVE OPTIMAL POWER FLOW PROBLEM”. IU-Journal of Electrical & Electronics Engineering 13, no. 2 (December 2013): 1653-59.
EndNote Cabadag R, Turkay B (December 1, 2013) HEURISTIC METHODS TO SOLVE OPTIMAL POWER FLOW PROBLEM. IU-Journal of Electrical & Electronics Engineering 13 2 1653–1659.
IEEE R. Cabadag and B. Turkay, “HEURISTIC METHODS TO SOLVE OPTIMAL POWER FLOW PROBLEM”, IU-Journal of Electrical & Electronics Engineering, vol. 13, no. 2, pp. 1653–1659, 2013.
ISNAD Cabadag, Rengin - Turkay, Belgin. “HEURISTIC METHODS TO SOLVE OPTIMAL POWER FLOW PROBLEM”. IU-Journal of Electrical & Electronics Engineering 13/2 (December 2013), 1653-1659.
JAMA Cabadag R, Turkay B. HEURISTIC METHODS TO SOLVE OPTIMAL POWER FLOW PROBLEM. IU-Journal of Electrical & Electronics Engineering. 2013;13:1653–1659.
MLA Cabadag, Rengin and Belgin Turkay. “HEURISTIC METHODS TO SOLVE OPTIMAL POWER FLOW PROBLEM”. IU-Journal of Electrical & Electronics Engineering, vol. 13, no. 2, 2013, pp. 1653-9.
Vancouver Cabadag R, Turkay B. HEURISTIC METHODS TO SOLVE OPTIMAL POWER FLOW PROBLEM. IU-Journal of Electrical & Electronics Engineering. 2013;13(2):1653-9.