Risk-based methods for sustainable energy system planning: a review

Anastasia Ioannou, Andrew Angus, Feargal Brennan

Research output: Contribution to journalReview article

47 Citations (Scopus)
44 Downloads (Pure)

Abstract

The value of investments in renewable energy (RE) technologies has increased rapidly over the last decade as a result of political pressures to reduce carbon dioxide emissions and the policy incentives to increase the share of RE in the energy mix. As the number of RE investments increases, so does the need to measure the associated risks throughout planning, constructing and operating these technologies. This paper provides a state-of-the-art literature review of the quantitative and semi-quantitative methods that have been used to model risks and uncertainties in sustainable energy system planning and feasibility studies, including the derivation of optimal energy technology portfolios. The review finds that in quantitative methods, risks are mainly measured by means of the variance or probability density distributions of technical and economical parameters; while semi-quantitative methods such as scenario analysis and multi-criteria decision analysis (MCDA) can also address non-statistical parameters such as socio-economic factors (e.g. macro-economic trends, lack of public acceptance). Finally, untapped issues recognised in recent research approaches are discussed along with suggestions for future research.

Original languageEnglish
Pages (from-to)602-615
Number of pages14
JournalRenewable and Sustainable Energy Reviews
Volume74
Early online date2 Mar 2017
DOIs
Publication statusPublished - 31 Jul 2017

Keywords

  • energy system planning and feasibility
  • mean variance portfolio
  • Monte Carlo simulation
  • multi-criteria decision analysis
  • sustainable power generation
  • risk
  • risk-based methods
  • scenario analysis
  • stochastic optimisation

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