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Interaction effects in optimising a municipal energy system

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  • Sundberg, G
  • Karlsson, B.G

Abstract

A study is presented where factorial design is used to find how some selected economic and technical factors affect the profitability of an investment in a combined heat and power plant. The study is performed on a Swedish district heating system. The minimal cost for supplying the demanded heat is calculated with a developed energy system optimisation model, MODEST. The effects on the resulting parameters, such as system cost and optimal size of steam cycle, are calculated from a series of experiments performed using high and low levels of the most relevant factors. The conclusion of the study is that both the main factors and the interactions between them have to be analysed to establish an accurate ranking of the technical and economic factors.

Suggested Citation

  • Sundberg, G & Karlsson, B.G, 2000. "Interaction effects in optimising a municipal energy system," Energy, Elsevier, vol. 25(9), pages 877-891.
    • Handle: RePEc:eee:energy:v:25:y:2000:i:9:p:877-891
    DOI: 10.1016/S0360-5442(00)00022-0
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    References listed on IDEAS

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    1. Henning, Dag, 1997. "MODEST—An energy-system optimisation model applicable to local utilities and countries," Energy, Elsevier, vol. 22(12), pages 1135-1150.
    2. Gustafsson, Stig-Inge & Andersson, Susanne & Karlsson, Björn G., 1994. "Factorial design for energy-system models," Energy, Elsevier, vol. 19(8), pages 905-910.
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    Cited by:

    1. Gustavsson, L & Karlsson, Å, 2003. "Heating detached houses in urban areas," Energy, Elsevier, vol. 28(8), pages 851-875.
    2. Keirstead, James & Jennings, Mark & Sivakumar, Aruna, 2012. "A review of urban energy system models: Approaches, challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3847-3866.
    3. Weinberger, Gottfried & Moshfegh, Bahram, 2018. "Investigating influential techno-economic factors for combined heat and power production using optimization and metamodeling," Applied Energy, Elsevier, vol. 232(C), pages 555-571.
    4. Dong, Cong & Huang, Guohe & Cai, Yanpeng & Cheng, Guanhui & Tan, Qian, 2016. "Bayesian interval robust optimization for sustainable energy system planning in Qiqihar City, China," Energy Economics, Elsevier, vol. 60(C), pages 357-376.
    5. Patrizio, P. & Chinese, D., 2016. "The impact of regional factors and new bio-methane incentive schemes on the structure, profitability and CO2 balance of biogas plants in Italy," Renewable Energy, Elsevier, vol. 99(C), pages 573-583.
    6. Chinese, Damiana & Meneghetti, Antonella, 2005. "Optimisation models for decision support in the development of biomass-based industrial district-heating networks in Italy," Applied Energy, Elsevier, vol. 82(3), pages 228-254, November.
    7. Karlsson, Magnus, 2004. "A systems approach to the reduction of oil demand in a Swedish board mill," Energy, Elsevier, vol. 29(1), pages 103-124.
    8. Eriksson, Marcus & Vamling, Lennart, 2007. "Future use of heat pumps in Swedish district heating systems: Short- and long-term impact of policy instruments and planned investments," Applied Energy, Elsevier, vol. 84(12), pages 1240-1257, December.
    9. Brkić, Dejan & Tanasković, Toma I., 2008. "Systematic approach to natural gas usage for domestic heating in urban areas," Energy, Elsevier, vol. 33(12), pages 1738-1753.

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