Renewable energies in the context of the water–food–energy nexus

Campana, Pietro Elia; Lawford, R. G.

doi:10.1016/b978-0-323-85527-3.00010-8

Cited by 2 publications

(1 citation statement)

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“…Frequently this land is, or could potentially become, agricultural land, because the exact requirements apply for both lands uses. The permitting process for installing PV plants on (actual or potential) agricultural land is a significant challenge due to the so-called "food-versus-fuel (electricity)" debate (Tomei and Helliwell, 2016;Ketzer et al, 2020;Campana and Lawford, 2022). This ethical debate concerns whether the land must be used for energy conversion or food production.…”

Section: Introductionmentioning

confidence: 99%

Solar irradiance distribution under vertically mounted agrivoltaic systems – Model development, validation, and applications for microclimate assessment

Campana¹,

Scragg²,

Lu³

et al. 2022

Preprint

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ccurate assessment of the Photosynthetically Active Radiation (PAR) and Global Horizontal Irradiance (GHI) at the crop level is paramount for accurately assessing the energy balances and the crop yield under agrivoltaic systems. The shadings produced by the photovoltaic modules and structures of the agrivoltaic systems cause a non-homogeneous distribution of PAR and GHI at the crop level. It is thus essential to calculate their distribution at a high spatial resolution within the agrivoltaic field. Using field data and commercial software, we have validated a high spatial resolution model (i.e., 25 cm × 25 cm) for PAR and GHI distribution within a vertical agrivoltaic system. The results show good model accuracy with coefficients of determination higher than 0.98 when comparing GHI from the model developed in this study and commercial software based on ray tracing. Model applications are presented with consideration to the computation of surface temperature, evapotranspiration, crop yield, and soil moisture. The model developed in this study shows good agreement in terms of crop yield computations as compared to a previously published model for agrivoltaic systems simulations and optimization (Campana et al., 2021). The added value of the model presented in this study consists in performing high spatial resolution computations of microclimatic parameters and crop yield within the agrivoltaic field.

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Section: Introductionmentioning

confidence: 99%