Optimizing the supply chain of biomass and biogas for a single plant considering mass and energy losses

    Research output: Contribution to journalJournal articleResearchpeer-review

    61 Downloads (Pure)

    Abstract

    The share of renewable energy in the Danish energy sector is increasing and the goal is that biogas production should reach a production level of 17 petajoules (PJ) in 2020 according to the Danish Energy Agency. However, this goal is currently not reachable due to lack of investments in biogas plants. In this paper, a mixed integer programming (MIP) model for finding the optimal production and investment plan for a biogas supply chain is presented to ensure better economy for the full chain hopefully stimulating future investments in biogas. The model makes use of step-wise linear functions to represent capital and operational expenditures at the biogas plant; considers the chain from the farmer to the end market; and includes changes of mass and energy content along the chain by modeling the losses and gains for all processes in the chain. Biomass inputs are scheduled on a weekly basis whereas energy outputs are scheduled on an hourly basis to better capture the changes of energy prices and potentially take advantage of these changes. The model is tested on a case study with co-digestion of straw, sugar beet and manure, considering natural gas, heat, and electricity as end products. The model finds a production and investment plan for a predefined location of the plant within half an hour of central processing unit (CPU) time. The resulting project turns out to be profitable and gives a production plan for each process, which underlines the possibilities of optimizing the processes in a biogas project.
    Original languageEnglish
    JournalEuropean Journal of Operational Research
    Volume262
    Issue number2
    Pages (from-to)744-758
    Number of pages15
    ISSN0377-2217
    DOIs
    Publication statusPublished - 2017

    Keywords

    • OR in energy
    • Supply chain optimization
    • Biomass and bioenergy supply chains
    • Network flow optimization

    Cite this

    @article{7814c588bf0f4945b88d622a4b6ac8c7,
    title = "Optimizing the supply chain of biomass and biogas for a single plant considering mass and energy losses",
    abstract = "The share of renewable energy in the Danish energy sector is increasing and the goal is that biogas production should reach a production level of 17 petajoules (PJ) in 2020 according to the Danish Energy Agency. However, this goal is currently not reachable due to lack of investments in biogas plants. In this paper, a mixed integer programming (MIP) model for finding the optimal production and investment plan for a biogas supply chain is presented to ensure better economy for the full chain hopefully stimulating future investments in biogas. The model makes use of step-wise linear functions to represent capital and operational expenditures at the biogas plant; considers the chain from the farmer to the end market; and includes changes of mass and energy content along the chain by modeling the losses and gains for all processes in the chain. Biomass inputs are scheduled on a weekly basis whereas energy outputs are scheduled on an hourly basis to better capture the changes of energy prices and potentially take advantage of these changes. The model is tested on a case study with co-digestion of straw, sugar beet and manure, considering natural gas, heat, and electricity as end products. The model finds a production and investment plan for a predefined location of the plant within half an hour of central processing unit (CPU) time. The resulting project turns out to be profitable and gives a production plan for each process, which underlines the possibilities of optimizing the processes in a biogas project.",
    keywords = "OR in energy, Supply chain optimization, Biomass and bioenergy supply chains, Network flow optimization",
    author = "Jensen, {Ida Gr{\ae}sted} and Marie M{\"u}nster and David Pisinger",
    year = "2017",
    doi = "10.1016/j.ejor.2017.03.071",
    language = "English",
    volume = "262",
    pages = "744--758",
    journal = "European Journal of Operational Research",
    issn = "0377-2217",
    publisher = "Elsevier",
    number = "2",

    }

    Optimizing the supply chain of biomass and biogas for a single plant considering mass and energy losses. / Jensen, Ida Græsted; Münster, Marie; Pisinger, David.

    In: European Journal of Operational Research, Vol. 262, No. 2, 2017, p. 744-758.

    Research output: Contribution to journalJournal articleResearchpeer-review

    TY - JOUR

    T1 - Optimizing the supply chain of biomass and biogas for a single plant considering mass and energy losses

    AU - Jensen, Ida Græsted

    AU - Münster, Marie

    AU - Pisinger, David

    PY - 2017

    Y1 - 2017

    N2 - The share of renewable energy in the Danish energy sector is increasing and the goal is that biogas production should reach a production level of 17 petajoules (PJ) in 2020 according to the Danish Energy Agency. However, this goal is currently not reachable due to lack of investments in biogas plants. In this paper, a mixed integer programming (MIP) model for finding the optimal production and investment plan for a biogas supply chain is presented to ensure better economy for the full chain hopefully stimulating future investments in biogas. The model makes use of step-wise linear functions to represent capital and operational expenditures at the biogas plant; considers the chain from the farmer to the end market; and includes changes of mass and energy content along the chain by modeling the losses and gains for all processes in the chain. Biomass inputs are scheduled on a weekly basis whereas energy outputs are scheduled on an hourly basis to better capture the changes of energy prices and potentially take advantage of these changes. The model is tested on a case study with co-digestion of straw, sugar beet and manure, considering natural gas, heat, and electricity as end products. The model finds a production and investment plan for a predefined location of the plant within half an hour of central processing unit (CPU) time. The resulting project turns out to be profitable and gives a production plan for each process, which underlines the possibilities of optimizing the processes in a biogas project.

    AB - The share of renewable energy in the Danish energy sector is increasing and the goal is that biogas production should reach a production level of 17 petajoules (PJ) in 2020 according to the Danish Energy Agency. However, this goal is currently not reachable due to lack of investments in biogas plants. In this paper, a mixed integer programming (MIP) model for finding the optimal production and investment plan for a biogas supply chain is presented to ensure better economy for the full chain hopefully stimulating future investments in biogas. The model makes use of step-wise linear functions to represent capital and operational expenditures at the biogas plant; considers the chain from the farmer to the end market; and includes changes of mass and energy content along the chain by modeling the losses and gains for all processes in the chain. Biomass inputs are scheduled on a weekly basis whereas energy outputs are scheduled on an hourly basis to better capture the changes of energy prices and potentially take advantage of these changes. The model is tested on a case study with co-digestion of straw, sugar beet and manure, considering natural gas, heat, and electricity as end products. The model finds a production and investment plan for a predefined location of the plant within half an hour of central processing unit (CPU) time. The resulting project turns out to be profitable and gives a production plan for each process, which underlines the possibilities of optimizing the processes in a biogas project.

    KW - OR in energy

    KW - Supply chain optimization

    KW - Biomass and bioenergy supply chains

    KW - Network flow optimization

    U2 - 10.1016/j.ejor.2017.03.071

    DO - 10.1016/j.ejor.2017.03.071

    M3 - Journal article

    VL - 262

    SP - 744

    EP - 758

    JO - European Journal of Operational Research

    JF - European Journal of Operational Research

    SN - 0377-2217

    IS - 2

    ER -