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Reactive Power Optimization Using Hybrid Cultural Algorithm

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Swarm, Evolutionary, and Memetic Computing (SEMCCO 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7677))

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Abstract

Optimal reactive power dispatch is an important task to achieve secure and economic operation of power systems. A well-organized allocation of reactive power in an electric network can minimize the system losses. This paper presents a Cultural Algorithm (CA) with a single point crossover to minimize the real power loss subjected to limits on generator real and reactive power outputs. In this hybrid approach, CA is used to give a good direction to the optimal global region, and a domain knowledge is used as a fine tuning to determine the optimal solution at the final for better convergence. The solution can be achieved by varying the bus voltages, the on-load tap changer positions of transformers and by switching of shunt capacitors. The performance of the proposed method is demonstrated on IEEE 14-bus system to find the optimal reactive power control variables subjected to various equality and inequality constraints. It is found that the results obtained by the proposed method are comparable in terms real power losses.

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References

  1. Bansal, R., Bhatti, T., Kothari, D.: Artificial intelligence techniques for reactive power/voltage control in power systems: A review. International Journal of Power and Energy Systems 23, 81–89 (2003)

    Google Scholar 

  2. Dommel, H.W., Tinney, W.F.: Optimal Power Flow Solutions. IEEE Trans. Power App. Syst.  PAS-87(10), 1866–1876 (1968)

    Google Scholar 

  3. Lee, K.Y., Park, Y.M., Ortiz, J.L.: A United Approach to Optimal Real and Reactive Power Dispatch. IEEE Trans. on Power Apparatus and Systems PAS-104(5), 1147–1153 (1985)

    Google Scholar 

  4. Granville, S.: Optimal Reactive Power Dispatch Through Interior Point Methods. IEEE Trans. on Power Systems 9(1), 98–105 (1994)

    Article  Google Scholar 

  5. Momoh, J.A., El-Hawary, M.E., Adapa, R.: A review of selected optimal power flow literature to 1993 part I & II. IEEE Trans. Power Syst. 14(1), 96–111 (1999)

    Article  Google Scholar 

  6. Ramos, J.L.M., Exposito, A.G., Quintana, V.H.: Transmission power loss reduction by interior-point methods: implementation issues and practical experience. IEE Proc. Gener. Trans. Distrib. 152(1), 90–98 (2005)

    Article  Google Scholar 

  7. Quintana, V.H., Santos-Nieto, M.: Reactive power-dispatch by successive quadratic programming. IEEE Trans. Energy Convers. 4(3), 425–435 (1989)

    Article  Google Scholar 

  8. Bakare, G.A., Venayagamoorthy, G.K., Aliyu, U.O.: Reactive Power and Voltage Control of the Nigerian Grid System Using Micro-Genetic Algorithm. In: Proceedings of IEEE Power Engineering Society General Meeting (2005)

    Google Scholar 

  9. El-Sayeed, M.A.H.: Ruled Based Approach for Real Time Reactive Power Control in Interconnected Power System. Expert System with Applications 14, 335–360 (1998)

    Google Scholar 

  10. Miranda, V., Srinivasan, D., Proenca, L.: Evolutionary Computation in Power Systems. Electrical Power and Energy Systems 20(2), 89–98 (1998)

    Article  Google Scholar 

  11. Yoshida, H., Kawata, K., Fukuyama, Y., Nakanishi, Y.: A Particle Swarm Optimization for Reactive Power and Voltage Control Considering Voltage Stability Assessment. IEEE Transactions on Power Systems 15(4), 1232–1241 (2000)

    Article  Google Scholar 

  12. Krost, G., Bakare, G.A.: A Genetic Algorithm Based Approach for Improvement in Voltage Profile and Real Power Loss Minimization. In: Proceedings of the IEEE Power Tech 1999 Conference, Budapest, Hungary, August 29-September 2, Section 24, paper BP99-293-23 (1999)

    Google Scholar 

  13. Bakare, G.: Removal of Overload and Voltage Problems using Genetic Algorithm and Expert Systems, Dissertation Gerhard Mercator University, Duisburg, Germany (2001)

    Google Scholar 

  14. del Valle, Y., Venayagamoorthy, G.K., Mohagheghi, S., Hernandez, J.C., Harley, R.G.: Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems. IEEE Transactions on Evolutionary Computation (in press)

    Google Scholar 

  15. Liang, C.H., Chung, C.Y., Wong, K.P., Duan, X.Z., Tse, C.T.: Study of differential evolution for optimal reactive power flow. IEE Proc. Gener. Trans. Distrib. 1(2), 253–260 (2007)

    Article  Google Scholar 

  16. Varadarajan, M., Swarup, K.S.: Network loss minimization with voltage security using differential evolution. Elec. Power Syst. Research 78, 815–823 (2008)

    Article  Google Scholar 

  17. Wu, Q.H., Ma, J.T.: Power system optimal reactive power dispatch using evolutionary programming. IEEE Trans. Power Syst. 10(3), 1243–1249 (1995)

    Article  MathSciNet  Google Scholar 

  18. Tripathy, M., Mishra, S.: Bacteria Foraging-Based Solution to Optimize Both Real Power Loss and Voltage Stability Limit. IEEE Trans. Power Syst. 22(1), 240–248 (2007)

    Article  Google Scholar 

  19. Reynolds, R.G.: An Adaptive Computer Model of the Evolution of Agriculture for Hunter-Gatherers in the Valley of Oaxaca Mexico. Ph.D. Dissertation, Department of Computer Science, University of Michigan (1979)

    Google Scholar 

  20. Reynolds, R.G.: An Introduction to Cultural Algorithms. In: Proceedings of the 3rd Annual Conference on Evolutionary Programming, pp. 131–139. World Scientific Publishing (1994)

    Google Scholar 

  21. Liu, J., Gao, H., Zhang, J., Dai, B.: Urban power network substation optimal planning based on Geographic Cultural Algorithm. In: The 8th Int. Conf. Power Engineering, pp. 500–504 (2007)

    Google Scholar 

  22. Yuan, X., Yuan, Y.: Application of Cultural Algorithm to generation scheduling of hydrothermal systems. Energy Conversion and Management 47(15-28), 2192–2201 (2006)

    Google Scholar 

  23. Seifi, A.R.: A new Hybrid Optimization method for optimum distribution capacitor planning. Modern Applied Science, CCSE 3(4), 196–202 (2009)

    MATH  Google Scholar 

  24. Chung, C.-J., Reynolds, R.G.: CAEP: An Evolution-based Tool for real valued Function Optimization using Cultural algorithms. International Journal on Artificial Intelligence Tools 7(3) (1998)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Electrical Engineering Dept., Techno India, Saltlake, India

    Bidishna Bhattacharya

  2. Department of Power Engineering, Jadavpur University, India

    Kamal Krishna Mandal & Niladri Chakraborty

Authors
  1. Bidishna Bhattacharya
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  2. Kamal Krishna Mandal
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  3. Niladri Chakraborty
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Indian Institute of Technology, 110016, Delhi, India

    Bijaya Ketan Panigrahi

  2. Electronics and Communication Sciences Unit, Indian Statistical Institute, 700108, Kolkata, India

    Swagatam Das

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, Block N4, 2b-39, Nanyang Avenue, 639798, Singapore, Singapore

    Ponnuthurai Nagaratnam Suganthan

  4. Department of Electronics and Telecom. Engineering, Institute of Technical Education & Research, Siksha ’O’ Anusandhan University, 751030, Bhubaneswar, Odisha, India

    Pradipta Kumar Nanda

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© 2012 Springer-Verlag Berlin Heidelberg

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Bhattacharya, B., Mandal, K.K., Chakraborty, N. (2012). Reactive Power Optimization Using Hybrid Cultural Algorithm. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Nanda, P.K. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2012. Lecture Notes in Computer Science, vol 7677. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35380-2_14

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  • DOI: https://doi.org/10.1007/978-3-642-35380-2_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35379-6

  • Online ISBN: 978-3-642-35380-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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