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Application Research of Inner-plant Economical Operation by Multi-colony Ant Optimization

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  • Xiaoyu Wang

    (Hohai University)

  • Kan Yang

    (Hohai University)

  • Liu Yang

    (Hohai University)

Abstract

A new multi-colony ant optimization (MCAO) combined with a dynamic economic distribution (DED) technique has been proposed for the economical operation of the inner-plant of a hydropower station. MCAO and DED are applied to solve the unit commitment (UC) sub-problem and the economic load distribution (ELD) sub-problem consolidating the ramp rate constraints for the entire schedule. Moreover, a patching mechanism is developed to converge quickly on the optimal solution in two respects: minimum up/down and spinning reserve. A mechanism mitigates the premature convergence by measuring the uncertainty of pheromone with information entropy. A local research technique enriches the diversity of solution space by selecting the derived solutions from the perturbation mechanism. In comparison with the genetic algorithm, the particle swarm optimization, and the ant colony optimization, the MCAO is significantly robust and provides better solutions to the economical operation problem of hydropower stations. Numerical simulations exhibit the superiority of the DED technique regarding stably and quickly consolidating the ramp rate constraints.

Suggested Citation

  • Xiaoyu Wang & Kan Yang & Liu Yang, 2018. "Application Research of Inner-plant Economical Operation by Multi-colony Ant Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(13), pages 4275-4295, October.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:13:d:10.1007_s11269-018-2048-8
    DOI: 10.1007/s11269-018-2048-8
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    References listed on IDEAS

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    1. Matthias Nowak & Werner Römisch, 2000. "Stochastic Lagrangian Relaxation Applied to Power Scheduling in a Hydro-Thermal System under Uncertainty," Annals of Operations Research, Springer, vol. 100(1), pages 251-272, December.
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    3. Omid Hoseynpour & Behnam Mohammadi-ivatloo & Morteza Nazari-Heris & Somayeh Asadi, 2017. "Application of Dynamic Non-Linear Programming Technique to Non-Convex Short-Term Hydrothermal Scheduling Problem," Energies, MDPI, vol. 10(9), pages 1-17, September.
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    Cited by:

    1. Wu, Xinyu & Wu, Yiyang & Cheng, Xilong & Cheng, Chuntian & Li, Zehong & Wu, Yongqi, 2023. "A mixed-integer linear programming model for hydro unit commitment considering operation constraint priorities," Renewable Energy, Elsevier, vol. 204(C), pages 507-520.

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