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Fuel constrained combined heat and power dynamic dispatch using horse herd optimization algorithm

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  • Basu, M.

Abstract

Due to gradually reduction of fossil fuel, the cost-effective use of available fuel for electric power generation has turn out to be a very significant concern of electric power utilities. This work recommends horse herd optimization algorithm (HOA) to solve fuel constrained combined heat and power dynamic economic dispatch with demand side management integrating wind turbine generators, solar PV plants and pumped storage hydro plant for three different scenarios. The effectiveness of the recommended method is divulged on an archetypal system. Numerical results of archetypal system for three different scenarios are compared with those obtained from self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients, fast convergence evolutionary programming, differential evolution and real-coded genetic algorithm. It has been seen from numerical results, that the total cost with fuel constraints is more than the cost without fuel constraints. It has been also observed from the comparison that the recommended HOA has the capability to confer with superior-quality solution.

Suggested Citation

  • Basu, M., 2022. "Fuel constrained combined heat and power dynamic dispatch using horse herd optimization algorithm," Energy, Elsevier, vol. 246(C).
    • Handle: RePEc:eee:energy:v:246:y:2022:i:c:s0360544222002997
    DOI: 10.1016/j.energy.2022.123396
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    References listed on IDEAS

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    Cited by:

    1. Hou, Guolian & Huang, Ting & Huang, Congzhi, 2023. "Flexibility improvement of 1000 MW ultra-supercritical unit under full operating conditions by error-based ADRC and fast pigeon-inspired optimizer," Energy, Elsevier, vol. 270(C).
    2. Xu, Shengping & Xiong, Guojiang & Mohamed, Ali Wagdy & Bouchekara, Houssem R.E.H., 2022. "Forgetting velocity based improved comprehensive learning particle swarm optimization for non-convex economic dispatch problems with valve-point effects and multi-fuel options," Energy, Elsevier, vol. 256(C).

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