Estimating the Deterministic and Stochastic Levelized Cost of the Energy of Fence-Type Agrivoltaics
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Title
- Estimating the Deterministic and Stochastic Levelized Cost of the Energy of Fence-Type Agrivoltaics
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Author(s)
- Hwang, Kyu Won; Lee, Chul-Yong
- KIOST Author(s)
- Hwang, Kyu Won(황규원)
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Alternative Author(s)
- 황규원
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Publication Year
- 2024-04
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Abstract
- Agrivoltaics can be used to supply energy and produce agricultural products in order to meet the growing demand for energy and food. The amount of power generation is affected by the solar panel direction, spacing, tilt, and panel technology; however, there is insufficient empirical data-based research on the operation of agrivoltaics. This study estimates the levelized cost of energy (LCOE) for a fence-based agrivoltaics system using bifacial modules. This study installed and operated photovoltaic (PV) systems on a rice paddy and saltern in South Korea to estimate the input variables that could affect their economic efficiency and LCOE. For the research methods, this study used Monte Carlo simulation (a stochastic analysis method that reflects the uncertainty of the input variables), a deterministic LCOE analysis, and a sensitivity analysis of the input variables. In terms of space utilization, the LCOE of the paddy system (139.07~141.19 KRW/kWh) was found to be relatively lower than that of the saltern system (145.43~146.18 KRW/kWh), implying that the PV system on the paddy was economically favorable. In terms of installation direction, it was more economical to operate the southwest-facing panels (139.07~145.43 KRW/kWh) than the southeast-facing panels (141.19~146.18 KRW/kWh). This study provides foundational policy data for the adoption of fence-based agrivoltaics and contributes to the widespread and active use of agrivoltaics.
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ISSN
- 1996-1073
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URI
- https://sciwatch.kiost.ac.kr/handle/2020.kiost/45531
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DOI
- 10.3390/en17081932
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Bibliographic Citation
- Energies, v.17, no.8, 2024
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Publisher
- Multidisciplinary Digital Publishing Institute (MDPI)
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Keywords
- solar PV; renewable energy; LCOE; agrivoltaics; stochastic
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Type
- Article
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