An integrated agent-based simulation modeling framework for sustainable production of an Agrophotovoltaic system
The Agrophtovoltaic (APV) system is an alternative for sustainable crop production, where solar power is generated via Photovoltaic (PV) modules. Since both crop production and solar power generation activities are heavily dependent on dynamic environmental conditions, it is challenging to design an...
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Veröffentlicht in: | Journal of cleaner production 2023-09, Vol.420, p.138307, Article 138307 |
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Sprache: | eng |
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Zusammenfassung: | The Agrophtovoltaic (APV) system is an alternative for sustainable crop production, where solar power is generated via Photovoltaic (PV) modules. Since both crop production and solar power generation activities are heavily dependent on dynamic environmental conditions, it is challenging to design an APV system based on accurate estimation of its performance. To this end, this study aims to introduce an agent-based simulation (ABS) framework integrated with polynomial regression and ridge regression. In particular, two agent types are devised, as follow: (1) The photovoltaic agent calculates electricity produced via PV modules, and estimates its profits; and (2) the crop production agent calculates crop harvests underneath the PV modules, and estimates their profits. To validate the proposed framework, field experiment data with five types of crops (i.e., corn, sesame, soybean, mung bean, and red bean) at the APV system at Jeollanam-do Agricultural Research and Extension Services in South Korea with three different shading ratios of 21.3%, 25.6%, and 32.0% have been used. In addition, for the sustainable operation of an APV system in terms of electricity generation as well as crop production, three climate change scenarios based on the shared socioeconomic pathway (SSP) are considered. The proposed framework identifies that the agrophotovoltaic system with 32% sharing ratio increases up to 20% of the total profit of normal farmland. As a result, the proposed framework enables the performance of an APV system under dynamic climate conditions to be accurately estimated, so that APV system designers can utilize it to identify a profitable long-term APV system.
•Crop and energy production activities were modelled via the hybrid framework.•An agent-based simulation (ABS) was integrated with machine learning algorithms.•The shared socioeconomic pathway (SSP) climate change scenarios were considered.•Validation result of the framework with a field study data was R2 of 83%.•The Agrophotovoltaic system increased up to 20% of the profit of normal farmland. |
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ISSN: | 0959-6526 1879-1786 |
DOI: | 10.1016/j.jclepro.2023.138307 |