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Chaotic artificial immune approach applied to economic dispatch of electric energy using thermal units

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  • Coelho, Leandro dos Santos
  • Mariani, Viviana Cocco

Abstract

The economic dispatch problem (EDP) is an optimization problem useful in power systems operation. The objective of the EDP of electric power generation, whose characteristics are complex and highly non-linear, is to schedule the committed generating unit outputs so as to meet the required load demand at minimum operating cost while satisfying system constraints. Recently, as an alternative to the conventional mathematical approaches, modern heuristic optimization techniques have been given much attention by many researchers due to their ability to find an almost global optimal solution in EDPs. As special mechanism to avoid being trapped in local minimum, the ergodicity property of chaotic sequences has been used as optimization technique in EDPs. Based on the chaos theory, this paper discusses the design and validation of an optimization procedure based on a chaotic artificial immune network approach based on Zaslavsky’s map. The optimization approach based on chaotic artificial immune network is validated for a test system consisting of 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects. Simulation results and comparisons show that the chaotic artificial immune network approach is competitive in performance with other optimization approaches presented in literature and is also an attractive tool to be used on applications in the power systems field.

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  • Coelho, Leandro dos Santos & Mariani, Viviana Cocco, 2009. "Chaotic artificial immune approach applied to economic dispatch of electric energy using thermal units," Chaos, Solitons & Fractals, Elsevier, vol. 40(5), pages 2376-2383.
    • Handle: RePEc:eee:chsofr:v:40:y:2009:i:5:p:2376-2383
    DOI: 10.1016/j.chaos.2007.10.032
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    References listed on IDEAS

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    1. Pan, Hui & Wang, Ling & Liu, Bo, 2008. "Chaotic annealing with hypothesis test for function optimization in noisy environments," Chaos, Solitons & Fractals, Elsevier, vol. 35(5), pages 888-894.
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    6. Coelho, Leandro dos Santos & Mariani, Viviana Cocco, 2009. "A novel chaotic particle swarm optimization approach using Hénon map and implicit filtering local search for economic load dispatch," Chaos, Solitons & Fractals, Elsevier, vol. 39(2), pages 510-518.
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    Cited by:

    1. de Athayde Costa e Silva, Marsil & Klein, Carlos Eduardo & Mariani, Viviana Cocco & dos Santos Coelho, Leandro, 2013. "Multiobjective scatter search approach with new combination scheme applied to solve environmental/economic dispatch problem," Energy, Elsevier, vol. 53(C), pages 14-21.
    2. Liao, Gwo-Ching, 2011. "A novel evolutionary algorithm for dynamic economic dispatch with energy saving and emission reduction in power system integrated wind power," Energy, Elsevier, vol. 36(2), pages 1018-1029.
    3. Wei-Chiang Hong & Yucheng Dong & Chien-Yuan Lai & Li-Yueh Chen & Shih-Yung Wei, 2011. "SVR with Hybrid Chaotic Immune Algorithm for Seasonal Load Demand Forecasting," Energies, MDPI, vol. 4(6), pages 1-18, June.
    4. Wang, Deyun & Yue, Chenqiang & ElAmraoui, Adnen, 2021. "Multi-step-ahead electricity load forecasting using a novel hybrid architecture with decomposition-based error correction strategy," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).

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