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A dynamic model to optimize a regional energy system with waste and crops as energy resources for greenhouse gases mitigation

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  • Song, Han
  • Dotzauer, Erik
  • Thorin, Eva
  • Guziana, Bozena
  • Huopana, Tuomas
  • Yan, Jinyue

Abstract

A dynamic model of a regional energy system has been developed to support sustainable waste treatment with greenhouse gases (GHG) mitigation, addressing the possibility for development towards a regional fossil fuel-free society between 2011 and 2030. The model is based on conventional mixed integer linear programming (MILP) techniques to minimize the total cost of regional energy systems. The CO2 emission component in the developed model includes both fossil and biogenic origins when considering waste, fossil fuels and other renewable sources for energy production. A case study for the county of Västmanland in central Sweden is performed to demonstrate the applicability of the developed MILP model in five distinct scenarios. The results show significant potential for mitigating CO2 emission by gradually replacing fossil fuels with different renewable energy sources. The MILP model can be useful for providing strategies for treating wastes sustainably and mitigating GHG emissions in a regional energy system, which can function as decision bases for formulating GHG reduction policies and assessing the associated economic implications.

Suggested Citation

  • Song, Han & Dotzauer, Erik & Thorin, Eva & Guziana, Bozena & Huopana, Tuomas & Yan, Jinyue, 2012. "A dynamic model to optimize a regional energy system with waste and crops as energy resources for greenhouse gases mitigation," Energy, Elsevier, vol. 46(1), pages 522-532.
  • Handle: RePEc:eee:energy:v:46:y:2012:i:1:p:522-532
    DOI: 10.1016/j.energy.2012.07.060
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    10. Pierie, F. & Bekkering, J. & Benders, R.M.J. & van Gemert, W.J.Th. & Moll, H.C., 2016. "A new approach for measuring the environmental sustainability of renewable energy production systems: Focused on the modelling of green gas production pathways," Applied Energy, Elsevier, vol. 162(C), pages 131-138.
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