Author
Listed:
- Bellone, Yuri
- Croci, Michele
- Impollonia, Giorgio
- Nik Zad, Amirhossein
- Colauzzi, Michele
- Campana, Pietro Elia
- Amaducci, Stefano
Abstract
In this study, a framework to compare the performances of different agrivoltaic systems, or agriphotovoltaic systems, in a range of environments was developed and tested. A set of key performance indicators derived from simulations was combined in a multi criteria decision analysis approach. The agriphotovoltaic systems were then ranked based on their similarity to the optimal solution for a specific environment. Main key performance indicators were crop ratio, energy conversion per hectare, specific energy yield, water use efficiency, and initial capital expenditure. Four agriphotovoltaics, namely vertical, interspace mono-axial, overhead mono-axial, and an overhead bi-axial, with five pitch width for each agriphotovoltaic and cultivated with processing tomato, were modelled across five sites (from the North to the South of Italy) during a ten-year period. The different scenarios were simulated in Scilab, in which a radiation model and GECROS crop model were coded. Global irradiation distribution beneath modules, and thus crop yield, were more homogeneous in vertical and overhead mono-axial than in the other agriphotovoltaic. Processing tomato demonstrated high adaptability to shading and yield was marginally affected in most of the agriphotovoltaic system alternatives. Vertical and overhead mono-axial accounted for the least yield reduction when the same pitch is compared. Overall, overhead mono-axial APV with 6 m pitch ranked first in each site when a 0.7 crop ratio threshold was considered. This framework could serve as a valuable tool for assessing the performance of different solution of agriphotovoltaics systems and their compliance with national regulation, and economic and technical targets.
Suggested Citation
Bellone, Yuri & Croci, Michele & Impollonia, Giorgio & Nik Zad, Amirhossein & Colauzzi, Michele & Campana, Pietro Elia & Amaducci, Stefano, 2024.
"Simulation-Based Decision Support for Agrivoltaic Systems,"
Applied Energy, Elsevier, vol. 369(C).
Handle:
RePEc:eee:appene:v:369:y:2024:i:c:s0306261924008730
DOI: 10.1016/j.apenergy.2024.123490
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