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An integrated approach for climate-change impact analysis and adaptation planning under multi-level uncertainties. Part I: Methodology

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  • Cai, Y.P.
  • Huang, G.H.
  • Tan, Q.
  • Yang, Z.F.

Abstract

In this study, a large-scale integrated modeling system (IMS) was developed for supporting climate-change impact analysis and adaptation planning under multi-level uncertainties. A number of methodologies were seamlessly incorporated within IMS, including fuzzy-interval inference method (FIIM), inexact energy model (IEM), and uncertainty analysis. The system could (i) encompass multiple technologies, energy resources, and sub-sectors, and climate change impact analysis into a general modeling framework, (ii) address interactions of climate change impacts on multiple energy sub-sectors and resources within an EMS, (iii) identify optimal adaptation strategies of an EMS to climate change impact through a two-step procedure, (iv) deal with multiple levels of uncertain information associated with processes of climate change impact analysis and adaptation planning, and (v) seamlessly combine climate change impact analysis results with inexact adaptation planning. It could provide decision makers a comprehensive view on the EMS as well as the corresponding adaptation schemes under climate change, greatly improving the robustness and completeness of the decision-making processes. The generated solutions can provide desired energy resource/service allocation with a minimized system cost, a maximized system reliability and a maximized energy security under varied climate change impact levels, as well as multiple levels of uncertainties. In a companion paper, the developed method is applied to a real case for the long-term planning of waste management in the Province of Manitoba, Canada.

Suggested Citation

  • Cai, Y.P. & Huang, G.H. & Tan, Q. & Yang, Z.F., 2011. "An integrated approach for climate-change impact analysis and adaptation planning under multi-level uncertainties. Part I: Methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 2779-2790, August.
    • Handle: RePEc:eee:rensus:v:15:y:2011:i:6:p:2779-2790
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