Solving Practical Economic Dispatch Problems Using Improved Artificial Bee Colony Method

Solving Practical Economic Dispatch Problems Using Improved Artificial Bee Colony Method

Автор: Belkacem MAHDAD, Kamel Srairi

Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa

Статья в выпуске: 7 vol.6, 2014 года.

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This paper presents an improved artificial bee colony (IABC) optimization method to solving practical economic dispatch taking into account the nonlinear generator characteristics such as valve-point loading effects. In order to exploit the performance of this new variant based ABC method to solving practical economic dispatch, a new local search mechanism (LSM) associated to the original ABC algorithm; it allows exploiting effectively the promising region to locate the best solution. The proposed approach has been examined and applied to many practical electrical power systems, the 13 generating units, and to the large electrical system with 40 generating units considering valve point loading effects. From the different case studies, it is observed that the results compared with the other recent techniques demonstrate the potential of the proposed approach and show clearly its effectiveness to solve practical and large ED.

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Global optimization, Artificial bee colony, Economic dispatch, Optimal power flow, Valve point effect, Prohibited zones, Local search

Короткий адрес: https://sciup.org/15010580

IDR: 15010580

Список литературы Solving Practical Economic Dispatch Problems Using Improved Artificial Bee Colony Method

  • S. Frank, I. Steponavice, and S. Rebennak, "Optimal power flow: a bibliographic survey I, formulations and deterministic methods," Int. J. Energy.System (Springer-Verlag), 2012.
  • J. Wood and B. F. Wollenberg, Power Generation, Operation, and Control, 2nd ed. New York: Wiley, 1984.
  • J. A. Momoh and J. Z. Zhu, “Improved interior point method for OPF problems,” IEEE Trans. Power Syst. , vol. 14, pp. 1114-1120, Aug. 1999.
  • M. Huneault, and F. D. Galiana, “A survey of the optimal power flow literature,” IEEE Trans. Power Systems, vol. 6, no. 2, pp. 762-770, May 1991.
  • C.-L. Chiang, “Improved genetic algorithm for power economic dispatch of units with valve-point effects and multiple fuels,” IEEE Trans. Power Syst., vol. 20, no. 4, pp. 1690–1699, Nov. 2005.
  • Z. L. Gaing, “Particle swarm optimization to solving the economic dispatch considering the generator constraints,” IEEE Trans. Power Systems, vol. 18, no. 3, pp. 1187-1195, 2003.
  • S.Hui, “Multi-objective optimization for hydraulic hybrid vehicle based on adaptive simulated annealing genetic algorithm,” Engineering Applications of Artificial Intelligence 2010; 23(1):27e33.B.
  • W. M, Lin, F. S., Cheng, and M. T. Tsay, “An improved tabu search for economic dispatch with multiple minima,” IEEE Trans. Power Systems, vol. 17, no. 1, pp. 108-112, 2002.
  • M. F. Mustafar, I. Musirin, M. R. Kalil, M. K. Idris, ”Ant colony optimization (aco) based technique for voltage control and loss minimization using transformer tap setting,” In: Proc. 5th student conference on research and development SCOReD 2007. 2007. p. 1–6.
  • K. Price, R. Storn, and J. Lampinen, Differential Evolution: A Practical Approach to Global Optimization. Berlin, Germany: Springer- Verlag, 2005.
  • S. Frank, I. Steponavice, and S. Rebennak, "Optimal power flow: a bibliographic survey II, non-deterministic and hybrid methods," Int. J. Energy.System (Springer-Verlag), 2012.
  • T. Niknam, M. R. Narimani, Rasoul.A. Abarghooee “A new hybrid algorithm for optimal power flow considering prohibited zones and valve point effect,” Energy Conversion and Management, vol. 53, pp. 197-206, 2012.
  • S. Sivasubramani, K. S., Swarup, “Environmental economic dispatch using multi-objective harmony search algorithm,” Int. J. Electr. Power System Res, vol. 81, pp. 1778-1785, 2011.
  • A. Bhattacharya, and P. k, Chattopadhyay “Solving complex economic load dispatch problems using biogeography-based optimization,” International Journal of Expert Systems with Apllications, Vol. 37, pp. 3605-3615, 2010.
  • T. Niknam, H. D. Mojarrad, H. Z. Meymand, B. B. Firouzi, “A new honey bee mating optimization algorithm for non-smooth economic dispatch,” International Journal of Energy, Vol. 36, pp. 896-908, 2011.
  • Mandal B, Roy PK. “Optimal reactive power dispatch using quasi-oppositional teaching learning based optimization,” Int J Electric Power Energy Syst, ;53:123–34. 2013
  • Ahmad Moghadam, Ali Reza Seifi, “Fuzzy-TLBO optimal reactive power control variables planning for energy loss minimization,” Energy Conversion and Management, vol. 77, pp. 208-215, 2014.
  • D. Karaboga, “An idea based on honey bee swarm for numerical optimization,” Technical Report-TR06, Erciyes University of Engineering, Faculty of Computer Engineering Department, 2005
  • D. Karaboga, B. Basturk, “A powerful and efficient algorithm for numeric optimization: artificial bee colony (ABC) algorithm,” J. Global Optim. 39 (3) (2007) 459–471.
  • B. Akay , D. Karaboga, “A modified Artificial Bee Colony algorithm for real-parameter optimization,” Journal of Information Sciences, 2010.
  • B. Mahdad, T. Bouktir, K. Srairi, “OPF with Environmental Constraints with SVC Controller using Decomposed Parallel GA: Application to the Algerian Network,” Journal of Electrical Engineering & Technology, Korea, Vol. 4, No.1, pp. 55~65, March 2009.
  • B. Mahdad, K. Srairi “Differential evolution based dynamic decomposed strategy for solution of large practical economic dispatch,” 10th EEEIC International Conference on Environment and Electrical Engineering, Italy, 2011.
  • J. G. Vlachogiannis, and K. Y. Lee, “Economic dispatch-A comparative study on heuristic optimization techniques with an improved coordinated aggregation-based PSO,” IEEE Trans. Power Systems, vol. 24, no. 2, pp. 991-1001, 2009.
  • J. S. Al-Sumait, J. K. Sykulski, A. K. Al-Othman, “Solution of different types of economic load dispatch problems using a pattern search method ,” Int. J. Electr. Power Components and Systems, vol. 36, no. 3, pp. 250-265, 2008.
  • Ke. Meng, H. G. Wang, Z. Y. Dong, and K. P. Wong, “ Quantum-inspired particle swarm optimization for valve-point economic load dispatch,“ IEEE Trans. Power Systems, vol. 25, no. 1, pp. 215-222, 2010.
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