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Levelised cost of energy: a theoretical justification and critical assessment.

Aldersey-Williams, J.; Rubert, T.

Authors

J. Aldersey-Williams

T. Rubert



Abstract

Although widely accepted as a measure of the comparative lifetime costs of electricity generation alternatives, levelised cost of energy (LCOE) lacks a theoretical foundation in the academic literature and encompasses a number of areas where caution is important. Therefore, this paper seeks to provide a theoretical foundation by comparing the metric with alternative LCOE metrics and by undertaking a brief literature review to describe its strengths and weaknesses. In comparison with other potential measures of unit cost of energy, LCOE is found to be the preferred choice, in large part because of its widespread adoption. The weaknesses of the LCOE are found to centre on discount rate, inflation effects and the sensitivity of results to uncertainty in future commodity costs. These weaknesses are explored in the context of comparing combined cycle gas fired generation and offshore wind in the UK, based on publicly available cost measures. It is found that with variability of future fuel gas prices, and a Monte Carlo approach to modelling LCOE, the range of LCOE for CCGT is much broader in comparison to the LCOE of offshore wind. It is urged that explicit account be taken of the areas of weakness in future use of LCOE.

Citation

ALDERSEY-WILLIAMS, J. and RUBERT, T. 2019. Levelised cost of energy: a theoretical justification and critical assessment. Energy policy [online], 124, pages 169-179. Available from: https://doi.org/10.1016/j.enpol.2018.10.004

Journal Article Type Article
Acceptance Date Oct 7, 2018
Online Publication Date Oct 15, 2018
Publication Date Jan 31, 2019
Deposit Date Oct 8, 2018
Publicly Available Date Oct 8, 2018
Journal Energy policy
Print ISSN 0301-4215
Electronic ISSN 1873-6777
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 124
Pages 169-179
DOI https://doi.org/10.1016/j.enpol.2018.10.004
Keywords Levelised cost of energy; Offshore wind energy; Monte Carlo; Uncertainty
Public URL http://hdl.handle.net/10059/3166