Estimating levelized cost of electricity for solar PV and wind power

Amid growing concerns over global supply chain disruptions, the imperative to achieve carbon neutrality, and increasing demands for energy security, this study proposes a systematic and comprehensive framework for analyzing the Levelized Cost of Electricity (LCOE) for renewable energy in South Korea, with a particular focus on solar and wind power. Recognizing the urgency of transitioning to clean energy, the study develops a standardized classification system that disaggregates key cost components, including capital equipment, operation, maintenance, and land acquisition. A refined LCOE calculation methodology is introduced to reflect the unique economic and technical characteristics of renewable energy systems in Korea. Using the latest available cost data, the study derives national-level LCOE estimates and constructs a database to support ongoing cost tracking and policy evaluation. The sensitivity analysis reveals that LCOE responsiveness varies considerably with changes in input parameters, providing a quantitative basis for evaluating the relative influence of each factor. Specifically, for solar PV and onshore wind technologies, economic lifetime, capital expenditures (CAPEX), and the discount rate are identified as the most influential variables. Among these, variations in economic lifetime exert the greatest impact on LCOE due to their direct effects on investment payback periods and the distribution of fixed costs. Based on these findings, the study presents policy recommendations aimed at reducing renewable energy generation costs, improving investment efficiency, and enhancing the overall competitiveness of South Korea’s renewable energy sector.

Authors

Publication Details

Journal
Journal of Climate Change Research
Published
2025-08-31
DOI
https://doi.org/10.15531/ksccr.2025.16.4.633
Primary Topic
Electric Power System Optimization
Type
article
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article

Estimating levelized cost of electricity for solar PV and wind power

Eun-Geun Lee, Young-Hwan Ahn, Chul-Yong Lee, Deokoh Lim
Journal of Climate Change Research
Electric Power System Optimization
article

Estimating levelized cost of electricity for solar PV and wind power

Eun-Geun Lee, Young-Hwan Ahn, Chul-Yong Lee, Deokoh Lim
article en

Abstract

Amid growing concerns over global supply chain disruptions, the imperative to achieve carbon neutrality, and increasing demands for energy security, this study proposes a systematic and comprehensive framework for analyzing the Levelized Cost of Electricity (LCOE) for renewable energy in South Korea, with a particular focus on solar and wind power. Recognizing the urgency of transitioning to clean energy, the study develops a standardized classification system that disaggregates key cost components, including capital equipment, operation, maintenance, and land acquisition. A refined LCOE calculation methodology is introduced to reflect the unique economic and technical characteristics of renewable energy systems in Korea. Using the latest available cost data, the study derives national-level LCOE estimates and constructs a database to support ongoing cost tracking and policy evaluation. The sensitivity analysis reveals that LCOE responsiveness varies considerably with changes in input parameters, providing a quantitative basis for evaluating the relative influence of each factor. Specifically, for solar PV and onshore wind technologies, economic lifetime, capital expenditures (CAPEX), and the discount rate are identified as the most influential variables. Among these, variations in economic lifetime exert the greatest impact on LCOE due to their direct effects on investment payback periods and the distribution of fixed costs. Based on these findings, the study presents policy recommendations aimed at reducing renewable energy generation costs, improving investment efficiency, and enhancing the overall competitiveness of South Korea’s renewable energy sector.

Journal of Climate Change ResearchVol. 16(4)
Openalex Percentile: Top 76%
Electric Power System Optimization
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