An integrated multi-modeling framework to estimate potential rice and energy production under an agrivoltaic system

Abstract

With the growth of renewable energy use, solar energy is becoming the most popular renewable energy source worldwide. Nevertheless, the construction of a solar power plant can be a burden to a small country with a land shortage problem, because it requires extensive land. To avoid the potential food security issue caused by solar energy production, an agrivoltaic system producing both crop and solar energy is devised. This study aims to develop an integrated multi-modeling framework for an agrivoltaic system used for rice production. The proposed framework consists of four modules: (1) An environmental database module involving soil, climate, and climate change scenarios; (2) a solar energy generation estimation module predicting electricity production quantity via polynomial regression technique; (3) a crop production estimation module simulating rice yield and its impact underneath Photovoltaic (PV) panels via the Agricultural Policy/Environmental eXtender (APEX) model; and (4) a What-if analysis module analyzing the economic and environmental feasibility of an Agrivoltaic system under a climate change scenario. For validation and calibration of the proposed framework, rice production field study data underneath an Agrivoltaic system with a capacity of 107 kW at the Jeollanamdo Agricultural Research and Extension Center in Naju-si (35.0272° N, 126.8247° E), Jeollanam-do, South Korea, is collected. The prediction accuracy of the proposed framework is approximately 88 % in terms of the coefficient of determination. The experimental results show that the bi-facial agrivoltaic system with shading ratio of 32 % tends to have the highest total profit of USD 3.65 $/m2/day. © 2023 Elsevier B.V.