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A Framework for the Synthesis of Optimum Operating Profiles Based on Dynamic Simulation and a Micro Genetic Algorithm

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  • Erik Rosado-Tamariz

    (School of Engineering and Sciences, Tecnologico de Monterrey, Av. Eugenio Garza Sada Sur No. 2501, Col. Tecnologico, Monterrey 64849, Mexico
    Instituto Nacional de Electricidad y Energías Limpias (INEEL), Av. Reforma 113, Col. Palmira, Cuernavaca CP 62490, Mexico)

  • Miguel A. Zuniga-Garcia

    (School of Engineering and Sciences, Tecnologico de Monterrey, Av. Eugenio Garza Sada Sur No. 2501, Col. Tecnologico, Monterrey 64849, Mexico
    Instituto Nacional de Electricidad y Energías Limpias (INEEL), Av. Reforma 113, Col. Palmira, Cuernavaca CP 62490, Mexico)

  • Alfonso Campos-Amezcua

    (Instituto Nacional de Electricidad y Energías Limpias (INEEL), Av. Reforma 113, Col. Palmira, Cuernavaca CP 62490, Mexico)

  • Rafael Batres

    (School of Engineering and Sciences, Tecnologico de Monterrey, Av. Eugenio Garza Sada Sur No. 2501, Col. Tecnologico, Monterrey 64849, Mexico)

Abstract

This paper presents an approach to managing the thermal power plant’s flexible operation based on the steam generation process optimization. A strategy at the process level, as a first step in the operational optimization of the entire power plant, is proposed. The proposed approach focuses on minimizing the drum boiler startup time, since it is considered the most critical element in the steam generation process and in the thermal power plant’s efficient operation. An approach that addresses the problem to find the optimal sequences of control valves that minimize the drum boiler startup time as a dynamic optimization problem is proposed. To solve the optimization problem, a dynamic optimization framework based on a micro genetic algorithm (mGA) coupled with a dynamic simulation model is implemented. The dynamic simulation model is validated against data available in the literature, and the proposed optimization algorithm is characterized by the use of variable length chromosomes and the use of small population sizes. The results show that optimized operating profiles minimize the drum boiler startup time by at least 35 percent and generate control valve operating sequences that must be carried out to achieve the desired profile, while the structural integrity constraints are fulfilled at all times.

Suggested Citation

  • Erik Rosado-Tamariz & Miguel A. Zuniga-Garcia & Alfonso Campos-Amezcua & Rafael Batres, 2020. "A Framework for the Synthesis of Optimum Operating Profiles Based on Dynamic Simulation and a Micro Genetic Algorithm," Energies, MDPI, vol. 13(3), pages 1-23, February.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:3:p:677-:d:316528
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    References listed on IDEAS

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    1. Krüger, Klaus & Franke, Rüdiger & Rode, Manfred, 2004. "Optimization of boiler start-up using a nonlinear boiler model and hard constraints," Energy, Elsevier, vol. 29(12), pages 2239-2251.
    2. Mirandola, A. & Stoppato, A. & Lo Casto, E., 2010. "Evaluation of the effects of the operation strategy of a steam power plant on the residual life of its devices," Energy, Elsevier, vol. 35(2), pages 1024-1032.
    3. Rossi, Iacopo & Sorce, Alessandro & Traverso, Alberto, 2017. "Gas turbine combined cycle start-up and stress evaluation: A simplified dynamic approach," Applied Energy, Elsevier, vol. 190(C), pages 880-890.
    4. Taler, Jan & Dzierwa, Piotr & Taler, Dawid & Harchut, Piotr, 2015. "Optimization of the boiler start-up taking into account thermal stresses," Energy, Elsevier, vol. 92(P1), pages 160-170.
    5. Kubik, M.L. & Coker, P.J. & Barlow, J.F., 2015. "Increasing thermal plant flexibility in a high renewables power system," Applied Energy, Elsevier, vol. 154(C), pages 102-111.
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