University of Sussex
Browse

File(s) not publicly available

Prioritizing low-carbon energy sources to enhance China's energy security

journal contribution
posted on 2023-06-08, 23:31 authored by Jingzheng Ren, Benjamin SovacoolBenjamin Sovacool
This paper explores how low-carbon systems compare to each other in terms of their net effect on Chinese energy security, and how they ought to be ranked and strategized into an optimal and integrated resource plan. The paper utilizes Analytic Hierarchy Process (AHP) to first determine the relative performances of hydroelectricity, wind energy, solar energy, biomass energy, and nuclear power with respect to the energy security dimensions of availability, affordability, accessibility, and acceptability. Both qualitative and quantitative metrics are considered. It relies on AHP to calculate the relative weights of the qualitative metrics attached to these dimensions of energy security for each of our five low carbon energy sources. Then, energy security performance is determined by aggregating multiple, weighted metrics into a generic index based on the method of TOPSIS and then tweaked with a sensitivity analysis. Finally, an integrated method has been developed to rank the low-carbon energy systems from most to least important, with major implications for Chinese decision-makers and stakeholders. We conclude that hydroelectricity and wind power are the two low-carbon energy sources with the most potential to enhance China’s energy security. By contrast, nuclear and solar power have the least potential.

History

Publication status

  • Published

Journal

Energy Conversion and Management

ISSN

0196-8904

Publisher

Pergamon

Volume

92

Page range

129-136

Department affiliated with

  • SPRU - Science Policy Research Unit Publications

Full text available

  • No

Peer reviewed?

  • Yes

Legacy Posted Date

2016-01-28

Usage metrics

    University of Sussex (Publications)

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC