IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v34y2012i1p78-81.html
   My bibliography  Save this article

A simple dynamic energy capacity model

Author

Listed:
  • Gander, James P.

Abstract

I develop a simple dynamic model showing how total energy capacity is allocated to two different uses and how these uses and their corresponding energy flows are related and behave through time. The control variable of the model determines the allocation. All the variables of the model are in terms of a composite energy equivalent measured in BTU's. A key focus is on the shadow price of energy capacity and its behavior through time. Another key focus is on the behavior of the control variable that determines the allocation of overall energy capacity. The matching or linking of the model's variables to real world U.S. energy data is undertaken. In spite of some limitations of the data, the model and its behavior fit the data fairly well. Some energy policy implications are discussed.

Suggested Citation

  • Gander, James P., 2012. "A simple dynamic energy capacity model," Energy Economics, Elsevier, vol. 34(1), pages 78-81.
  • Handle: RePEc:eee:eneeco:v:34:y:2012:i:1:p:78-81
    DOI: 10.1016/j.eneco.2011.08.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S014098831100171X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2011.08.011?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chung, W. & Wu, Y. June & Fuller, J. David, 1997. "Dynamic energy and environment equilibrium model for the assessment of CO2 emission control in Canada and the USA," Energy Economics, Elsevier, vol. 19(1), pages 103-124, March.
    2. Greening, Lorna A. & Boyd, Gale & Roop, Joseph M., 2007. "Modeling of industrial energy consumption: An introduction and context," Energy Economics, Elsevier, vol. 29(4), pages 599-608, July.
    3. Beladi, Hamid & Zuberi, Habib A., 1988. "Environmental constraints and a dynamic model for energy development," Energy Economics, Elsevier, vol. 10(1), pages 18-28, January.
    4. Nissan Levin & Asher Tishler & Jacob Zahavi, 1983. "Time Step vs. Dynamic Optimization of Generation-Capacity-Expansion Programs of Power Systems," Operations Research, INFORMS, vol. 31(5), pages 891-914, October.
    5. Lee, Chien-Chiang & Chien, Mei-Se, 2010. "Dynamic modelling of energy consumption, capital stock, and real income in G-7 countries," Energy Economics, Elsevier, vol. 32(3), pages 564-581, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yuo-Hsien Shiau & Su-Fen Yang & Rishan Adha & Syamsiyatul Muzayyanah, 2022. "Modeling Industrial Energy Demand in Relation to Subsector Manufacturing Output and Climate Change: Artificial Neural Network Insights," Sustainability, MDPI, vol. 14(5), pages 1-18, March.
    2. Berna Tektaş & Hasan Hüseyin Turan & Nihat Kasap & Ferhan Çebi & Dursun Delen, 2022. "A Fuzzy Prescriptive Analytics Approach to Power Generation Capacity Planning," Energies, MDPI, vol. 15(9), pages 1-26, April.
    3. Fakhri J. Hasanov & Jeyhun I. Mikayilov, 2020. "Revisiting Energy Demand Relationship: Theory and Empirical Application," Sustainability, MDPI, vol. 12(7), pages 1-15, April.
    4. W. Chung & J. Fuller & Y. Wu, 2003. "A New Demand-Supply Decomposition Method for a Class of Economic Equilibrium Models," Computational Economics, Springer;Society for Computational Economics, vol. 21(3), pages 231-243, June.
    5. Rahman, Mohammad Mafizur & Mamun, Shamsul Arifeen Khan, 2016. "Energy use, international trade and economic growth nexus in Australia: New evidence from an extended growth model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 806-816.
    6. Brini, Riadh & Amara, Mohamed & Jemmali, Hatem, 2017. "Renewable energy consumption, International trade, oil price and economic growth inter-linkages: The case of Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 620-627.
    7. Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    8. Salmanzadeh-Meydani, N. & Fatemi Ghomi, S.M.T., 2019. "The causal relationship among electricity consumption, economic growth and capital stock in Iran," Journal of Policy Modeling, Elsevier, vol. 41(6), pages 1230-1256.
    9. Mazzanti, Massimiliano & Montini, Anna, 2010. "Embedding the drivers of emission efficiency at regional level -- Analyses of NAMEA data," Ecological Economics, Elsevier, vol. 69(12), pages 2457-2467, October.
    10. Yanli Ji & Jie Xue & Zitian Fu, 2022. "Sustainable Development of Economic Growth, Energy-Intensive Industries and Energy Consumption: Empirical Evidence from China’s Provinces," Sustainability, MDPI, vol. 14(12), pages 1-20, June.
    11. Cosimo Magazzino, 2012. "On the Relationship between Disaggregated Energy Production and GDP in Italy," Energy & Environment, , vol. 23(8), pages 1191-1207, December.
    12. Lin, Boqiang & Ouyang, Xiaoling, 2014. "Electricity demand and conservation potential in the Chinese nonmetallic mineral products industry," Energy Policy, Elsevier, vol. 68(C), pages 243-253.
    13. Svensson, Elin & Berntsson, Thore, 2011. "Planning future investments in emerging energy technologies for pulp mills considering different scenarios for their investment cost development," Energy, Elsevier, vol. 36(11), pages 6508-6519.
    14. Sarid, A. & Tzur, M., 2018. "The multi-scale generation and transmission expansion model," Energy, Elsevier, vol. 148(C), pages 977-991.
    15. Abarahan, Amnisuhailah Binti & Masih, Mansur, 2016. "Is energy a stimulus for economic growth? A focused study on Malaysia using the auto regressive distributed lag technique," MPRA Paper 69765, University Library of Munich, Germany.
    16. Lucio, Nilson Rogerio & Lamas, Wendell de Queiroz & de Camargo, Jose Rubens, 2013. "Strategic energy management in the primary aluminium industry: Self-generation as a competitive factor," Energy Policy, Elsevier, vol. 59(C), pages 182-188.
    17. Nicholas Lee & Hsiang-Jane Su & Ming-Chin Lin, 2018. "Electricity Consumption and Green Mortgage: New Insights into the Threshold Cointegration Relationship," International Journal of Energy Economics and Policy, Econjournals, vol. 8(2), pages 39-46.
    18. Cansino, José M. & Sánchez-Braza, Antonio & Rodríguez-Arévalo, María L., 2018. "How can Chile move away from a high carbon economy?," Energy Economics, Elsevier, vol. 69(C), pages 350-366.
    19. Bahman Huseynli, 2023. "Effect of Exports of Goods and Services and Energy Consumption in Italy`s Service Sector," International Journal of Energy Economics and Policy, Econjournals, vol. 13(3), pages 254-261, May.
    20. Csereklyei, Zsuzsanna & Humer, Stefan, 2012. "Modelling Primary Energy Consumption under Model Uncertainty," Department of Economics Working Paper Series 147, WU Vienna University of Economics and Business.

    More about this item

    Keywords

    Dynamic energy capacity model; Allocation of energy capacity; Shadow price of energy capacity; Energy data correspondence;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:34:y:2012:i:1:p:78-81. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.