Full life-cycle cost model for practical application of solar energy system

Q2 Energy Energy Informatics Pub Date : 2025-03-20 DOI:10.1186/s42162-025-00505-9
Ang Sha, Zhen Xiong, Xiaolin Zang, Wei Zhao, Ruibang Ge, Wanxiang Yao, Marco Aiello
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Abstract

In pursuit of carbon neutrality, a swift transformation is underway in the global energy structure, marked by a consistent rise in the installed capacity of solar energy systems. Meanwhile, the substantial reduction of government subsidies in the solar industry intensifies focus on the economic viability of solar energy installations. In this study, we propose a full life-cycle cost model, named the F-LCC model, for calculating the cost of the solar energy system on the long term, e.g., 20–30 years. This model integrates replacement costs, residual value calculation, interest rate, and inflation impacts while supporting market price estimation for individual components, thereby aiding feasibility analysis in the early project phase. We design an investment cost recovery algorithm based on the F-LCC model to calculate the break-even electricity price for solar energy system. Moreover, we analyze component cost distributions, Net Present Value (NPV), and Discounted Payback Period (DPP) for grid-connected and off-grid solar energy systems with capacities of 10 kWp and 100 kWp in the Chinese market. The results show that the proposed model, compared to other models, captures the fact that payback times are longer. In a solar energy system without storage, solar panels have the highest component cost share at 28.8%. With battery storage, batteries dominate the total cost, reaching up to 74.6%. And the the grid-connected systems DPP ranging from a minimum of 5.5 to a maximum of 7.0 years by grid-connected electricity price, while off-grid systems require at least 19.9 years. The 10 kWp off-grid fixed mounting system’s break-even price being 137.1% higher than its grid-connected counterpart. In addition, tracking-mount systems offer greater cost-reduction potential than fixed installations, with the payback period reduced by 20% for 100 kWp grid-connected systems and 15% for off-grid systems. Finally, we develop a plugin based on the F-LCC model. These findings deepen understanding of solar energy economics and inform policy and investment.

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来源期刊
Energy Informatics
Energy Informatics Computer Science-Computer Networks and Communications
CiteScore
5.50
自引率
0.00%
发文量
34
审稿时长
5 weeks
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