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

Research output: Contribution to journalReview article

28 Citations (Scopus)

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.

LanguageEnglish
Pages602-615
Number of pages14
JournalRenewable and Sustainable Energy Reviews
Volume74
Early online date2 Mar 2017
DOIs
Publication statusPublished - 31 Jul 2017

Fingerprint

Planning
Economics
Decision theory
Macros
Carbon dioxide
Uncertainty

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

Cite this

@article{61bbe9991ef84ef6b3e122581e624caa,
title = "Risk-based methods for sustainable energy system planning: a review",
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.",
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",
author = "Anastasia Ioannou and Andrew Angus and Feargal Brennan",
year = "2017",
month = "7",
day = "31",
doi = "10.1016/j.rser.2017.02.082",
language = "English",
volume = "74",
pages = "602--615",
journal = "Renewable and Sustainable Energy Reviews",
issn = "1364-0321",

}

Risk-based methods for sustainable energy system planning : a review. / Ioannou, Anastasia; Angus, Andrew; Brennan, Feargal.

In: Renewable and Sustainable Energy Reviews, Vol. 74, 31.07.2017, p. 602-615.

Research output: Contribution to journalReview article

TY - JOUR

T1 - Risk-based methods for sustainable energy system planning

T2 - Renewable and Sustainable Energy Reviews

AU - Ioannou, Anastasia

AU - Angus, Andrew

AU - Brennan, Feargal

PY - 2017/7/31

Y1 - 2017/7/31

N2 - 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.

AB - 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.

KW - energy system planning and feasibility

KW - mean variance portfolio

KW - Monte Carlo simulation

KW - multi-criteria decision analysis

KW - sustainable power generation

KW - risk

KW - risk-based methods

KW - scenario analysis

KW - stochastic optimisation

UR - http://www.scopus.com/inward/record.url?scp=85014304489&partnerID=8YFLogxK

U2 - 10.1016/j.rser.2017.02.082

DO - 10.1016/j.rser.2017.02.082

M3 - Review article

VL - 74

SP - 602

EP - 615

JO - Renewable and Sustainable Energy Reviews

JF - Renewable and Sustainable Energy Reviews

SN - 1364-0321

ER -