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

Aldersey-Williams, J.; Rubert, T.

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
• Contract Date: Oct 8, 2018