Articles producció científica> Enginyeria Química

Scheduling optimization and risk analysis for energy-intensive industries under uncertain electricity market to facilitate financial planning

  • Datos identificativos

    Identificador: imarina:9295596
    Autores:
    Gangwar, SFernández, DPozo, CFolgado, RJiménez, LBoer, D
    Resumen:
    The planning of energy-intensive processes is intrinsically uncertain due to their dependence on the volatile energy market, with scheduling having a vast impact on the final production cost of these plants. Traditional stochastic methods are mathematically very complex, which translates into a significant computational effort that might prevent a timely response to varying electricity prices. To encounter this uncertainty, we develop a reliable hybrid simulation-optimization approach for optimizing the production plant scheduling, combining scenario analysis with risk analysis. The proposed methodology is demonstrated with real data from a cryogenic air separation plant in Tarragona (Spain). This approach also informs decision-makers about risk or expected shortfall associated with the implied scenario. The generic methodology used here can be easily adapted to schedule facilities in other energy-intensive sectors such as cement, metallurgy or pulp and paper.
  • Otros:

    Autor según el artículo: Gangwar, S; Fernández, D; Pozo, C; Folgado, R; Jiménez, L; Boer, D
    Departamento: Enginyeria Química Enginyeria Mecànica
    Autor/es de la URV: Boer, Dieter-Thomas / Gangwar, Sachin / Jiménez Esteller, Laureano / Pozo Fernández, Carlos
    Palabras clave: Uncertainty Spot market forecast Scheduling Risk analysis, energy-intensive industry Optimization
    Resumen: The planning of energy-intensive processes is intrinsically uncertain due to their dependence on the volatile energy market, with scheduling having a vast impact on the final production cost of these plants. Traditional stochastic methods are mathematically very complex, which translates into a significant computational effort that might prevent a timely response to varying electricity prices. To encounter this uncertainty, we develop a reliable hybrid simulation-optimization approach for optimizing the production plant scheduling, combining scenario analysis with risk analysis. The proposed methodology is demonstrated with real data from a cryogenic air separation plant in Tarragona (Spain). This approach also informs decision-makers about risk or expected shortfall associated with the implied scenario. The generic methodology used here can be easily adapted to schedule facilities in other energy-intensive sectors such as cement, metallurgy or pulp and paper.
    Áreas temáticas: Saúde coletiva Química Nutrição Medicina ii Matemática / probabilidade e estatística Linguística e literatura Interdisciplinar General chemical engineering Engineering, chemical Engenharias iv Engenharias iii Engenharias ii Computer science, interdisciplinary applications Computer science applications Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciência de alimentos Ciência da computação Chemical engineering (miscellaneous) Chemical engineering (all) Biotecnología
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: carlos.pozo@urv.cat sachin.gangwar@estudiants.urv.cat sachin.gangwar@estudiants.urv.cat dieter.boer@urv.cat laureano.jimenez@urv.cat
    Identificador del autor: 0000-0002-5532-6409 0000-0002-3186-7235
    Fecha de alta del registro: 2024-08-03
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://www.sciencedirect.com/science/article/pii/S0098135423001047
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Computers & Chemical Engineering. 174
    Referencia de l'ítem segons les normes APA: Gangwar, S; Fernández, D; Pozo, C; Folgado, R; Jiménez, L; Boer, D (2023). Scheduling optimization and risk analysis for energy-intensive industries under uncertain electricity market to facilitate financial planning. Computers & Chemical Engineering, 174(), -. DOI: 10.1016/j.compchemeng.2023.108234
    DOI del artículo: 10.1016/j.compchemeng.2023.108234
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2023
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Chemical Engineering (Miscellaneous),Computer Science Applications,Computer Science, Interdisciplinary Applications,Engineering, Chemical
    Uncertainty
    Spot market forecast
    Scheduling
    Risk analysis, energy-intensive industry
    Optimization
    Saúde coletiva
    Química
    Nutrição
    Medicina ii
    Matemática / probabilidade e estatística
    Linguística e literatura
    Interdisciplinar
    General chemical engineering
    Engineering, chemical
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Computer science, interdisciplinary applications
    Computer science applications
    Ciências biológicas ii
    Ciências biológicas i
    Ciências ambientais
    Ciência de alimentos
    Ciência da computação
    Chemical engineering (miscellaneous)
    Chemical engineering (all)
    Biotecnología
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