• Korean Journal of Agricultural Science
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• v.50 no.4
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• pp.953-966
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• 2023

As the importance of renewable energy diffusion spreads, promotion of sustainable renewable energy projects such as agrivoltaics is expected to accelerate. Furthermore, to promote agrivoltaics projects, it must be considered the legislation related to agrivoltaics and Chungnam Province's local policy. This research focuses on the selection of the most suitable sites for agrivoltaics installations in Chungnam Province in South Korea. Therefore, the process of this research was as follows. First, the legislation related to agrivoltaics and local policy in Chungnam Province were identified. Second, it employs an analytic hierarchy process (AHP) to consider important criteria and their weights for site selection. Third, based on the weights calculated AHP, geographic information system (GIS) was performed to select most suitable location selection of agrivoltaics installations in Chungnam Province. The analysis identified approximately 60 promising most suitable location for agrivoltaics installations in Chungnam Province, primarily in the northern part of Chungnam Province. These areas are expected to meet electricity demands in nearby regions since these are relatively adjacent to Gyeonggi Province. According to the results of research, policy suggestions related to agrivoltaics were presented separately into the agricultural sector and the electricity power sector. The study's results serve as a valuable resource for future national-level candidate site selection for agrivoltaics projects.

• New & Renewable Energy
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• v.20 no.1
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• pp.15-25
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• 2024

This study analyzes the economic feasibility of agrivoltaics in South Korea. The key findings are as follows. It was ascertained that an amendment to the Farmland Act, which currently has an 8-year permit period, is necessary to ensure the economic feasibility of agrivoltaic projects. Furthermore, economic feasibility improves when agrivoltaic projects are financed, as against cases without financing. Furthermore, the availability of low-interest loans through financial support programs significantly enhances economic feasibility. Scaling up projects leads to cost savings due to economies of scale, while community-based agrivoltaic initiatives generate higher revenue through the acquisition of additional Renewable Energy Certificates. These factors can help improve the economic feasibility of agrivoltaic projects. These incentives are emphasized as they can serve as a source of funding to foster community acceptance of agrivoltaic projects.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.258-267
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• 2020

The agrivoltaic can produce electricity and grow crops on fields at the same time. It is necessary to analyze the cultivation environment and evaluate the crop productivity under agrivoltaic because the shading point changes according to structure of agrivoltaic and sun's position. Two types of "fixing" and "tracing" agrivoltaic were installed, and a rice cultivation experiment was conducted in the fields under each agrivoltaic and without shading (control). "Hyunpoombyeo" was transplanted on June 7, 2019, and grown with fertilization of 9.0-4.5-5.7 kg/10a (N-P-K). Fifteen weather stations were installed under each agrivoltaic to measure solar radiation and temperature, and yield and yield-related elements were investigated by points. The accumulated solar radiation during the rice growing season in fixing was no much difference between points, and that in tracing was much difference between points. However, the average solar radiations of two agrivoltaics were similar. The mean temperature, yield, and yield-related elements showed a significant difference for the shading rate, and decreased with increasing the shading rate except ripening grain rate and 1000 grain weight of fixing agrivoltaic. In the relationship between shading rate and yield, fixing and tracing were fitted to a logistic equation and a simple linear equation, respectively, and showed a high correlation (tracing: R2 = 0.62, fixing: R2 = 0.73). The shading rate variation by point for two types was large despite similar yield variation. Thus, it needs to be more closely examined the relationship of the shading rate for a specific period rather than the shading rate during the whole growing season.