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The environmental impact of decentralised generation in an overall system context

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  • Haeseldonckx, Dries
  • D'haeseleer, William

Abstract

Decentralised-generation technologies are very likely to play an important role in our future energy supply. The operational behaviour of several decentralised-generation technologies, as well as their interaction with the central power system, are being discussed and reviewed. The outcome of this analysis is then used to make correct judgements on the global environmental performance of the concept of embedded generation. In order to assess the environmental impact of a massive installation of decentralised-generation units, simulations are being performed using the code PROMIX, a very accurate model of the generation units presently existing (and anticipating those planned in the future) in Belgium. Finally, the simulation results are being discussed and some important conclusions about the environmental impact of decentralised generation can be drawn.

Suggested Citation

  • Haeseldonckx, Dries & D'haeseleer, William, 2008. "The environmental impact of decentralised generation in an overall system context," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(2), pages 437-454, February.
  • Handle: RePEc:eee:rensus:v:12:y:2008:i:2:p:437-454
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    References listed on IDEAS

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    1. Voorspools, Kris R. & D'haeseleer, William D., 2006. "An analytical formula for the capacity credit of wind power," Renewable Energy, Elsevier, vol. 31(1), pages 45-54.
    2. Pepermans, G. & Driesen, J. & Haeseldonckx, D. & Belmans, R. & D'haeseleer, W., 2005. "Distributed generation: definition, benefits and issues," Energy Policy, Elsevier, vol. 33(6), pages 787-798, April.
    3. Voorspools, Kris R. & D'haeseleer, William D., 2007. "Critical evaluation of methods for wind-power appraisal," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(1), pages 78-97, January.
    4. Voorspools, Kris R & D'haeseleer, William D, 2000. "The influence of the instantaneous fuel mix for electricity generation on the corresponding emissions," Energy, Elsevier, vol. 25(11), pages 1119-1138.
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    2. Bracco, Stefano & Dentici, Gabriele & Siri, Silvia, 2016. "DESOD: a mathematical programming tool to optimally design a distributed energy system," Energy, Elsevier, vol. 100(C), pages 298-309.

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