Abstract
A hybrid framework is proposed to identify the optimal design of agrophotovoltaic (APV) system that can be a promising alternative to resolve the food security issue by producing both solar energy and crops. It consists of four components: (1) Environmental database involving historical climate and soil data, (2) Solar energy module estimating energy quantity via polynomial regression (PR), (3) ALMANAC simulation that estimates crop parameters and yields; and (4) Analysis module identifying the optimum operational plan under climate change scenarios. The framework is calibrated with historical data collected from the APV system at the Jeollanamdo Agricultural Research and Extension Services (35.0161° N, 126.7108° E) in South Korea. Five crops of sesame, mungbean, red bean, corn, and soybean are considered under four climate change scenarios (i.e., SSP126, SSP245, SSP370, and SSP585) with two different time horizons (i.e., 2021–2050 and 2051–2080). According to the experiment, the APV system with mungbean is the most profitable with the unit profit of $ 77.44/m2 under 25.6% shading ratio from 2021 to 2050. The novel framework for the optimal design of the APV system enables to increase the income of a famer and resolve the food security under climate change environment in future.
Original language | English |
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Pages (from-to) | 928-938 |
Number of pages | 11 |
Journal | Renewable Energy |
Volume | 206 |
DOIs | |
State | Published - Apr 2023 |
Keywords
- Agrophotovoltaic system
- Crop growth model
- Renewable energy
- Simulation
- Solar energy