Techno-economic assessment of wind and solar energy: Upgrading the LCOE model and enhancing geographical granularity

Wind and solar (W&S) energy are pivotal to China's energy transition, yet traditional models for calculating the Levelized Cost of Electricity (LCOE) inadequately account for regional and temporal variability. Enhancing the LCOE model will provide a more precise and reliable assessment of the economic costs of W&S resources, facilitating the transition to a more sustainable energy future. This study reviews existing LCOE methodologies, identifying critical limitations, and underscores the necessity for high-precision economic assessments. Results show that current LCOE models can be improved from five geographic perspectives, i.e. natural, transportation, social, policy and economic. Based on these factors, an advanced China-based LCOE model is proposed incorporating spatio-temporal granularity, significantly enhancing the accuracy of economic evaluations of W&S projects, offering a refined approach to assess economic costs and support detailed planning for renewable energy development. This paper highlights the need for refinement of LCOE models, with future research focusing on geographic heterogeneity, variability impacts, and the influence of dynamic pricing and policy variations. • Existing LCOE models are reviewed and critical limitations are identified. • LCOE model should incorporate geographical factors to enhance the accuracy. • An advanced China-based LCOE model is proposed incorporating spatio-temporal granularity.

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Publication Details

Journal
Energy Strategy Reviews
Published
2025-03-01
DOI
https://doi.org/10.1016/j.esr.2025.101686
Citations
9
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
6.57

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article

Techno-economic assessment of wind and solar energy: Upgrading the LCOE model and enhancing geographical granularity

Yuan Zeng, Bo Bai, Yuchu Huang, Kali Zhou et al.
9 citations
Energy Strategy Reviews
Integrated Energy Systems Optimization
6.57
article

Techno-economic assessment of wind and solar energy: Upgrading the LCOE model and enhancing geographical granularity

Yuan Zeng, Bo Bai, Yuchu Huang, Kali Zhou, Zheng Wang, Xiang Tang
article en
9 citations

Abstract

Wind and solar (W&S) energy are pivotal to China's energy transition, yet traditional models for calculating the Levelized Cost of Electricity (LCOE) inadequately account for regional and temporal variability. Enhancing the LCOE model will provide a more precise and reliable assessment of the economic costs of W&S resources, facilitating the transition to a more sustainable energy future. This study reviews existing LCOE methodologies, identifying critical limitations, and underscores the necessity for high-precision economic assessments. Results show that current LCOE models can be improved from five geographic perspectives, i.e. natural, transportation, social, policy and economic. Based on these factors, an advanced China-based LCOE model is proposed incorporating spatio-temporal granularity, significantly enhancing the accuracy of economic evaluations of W&S projects, offering a refined approach to assess economic costs and support detailed planning for renewable energy development. This paper highlights the need for refinement of LCOE models, with future research focusing on geographic heterogeneity, variability impacts, and the influence of dynamic pricing and policy variations. • Existing LCOE models are reviewed and critical limitations are identified. • LCOE model should incorporate geographical factors to enhance the accuracy. • An advanced China-based LCOE model is proposed incorporating spatio-temporal granularity.

Energy Strategy ReviewsVol. 58
Beijing Normal-Hong Kong Baptist University (CN), Harvard University (US), Beijing Normal University (CN)
National Natural Science Foundation of China, Beijing Normal University, Guangdong Office of Philosophy and Social Science, Humanities and Social Science Fund of Ministry of Education of China
Affordable and clean energy
Openalex Percentile: Top 3%
Integrated Energy Systems Optimization
6.57
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