Author
Listed:
- Grubbs, E.K.
- Gruss, S.M.
- Schull, V.Z.
- Gosney, M.J.
- Mickelbart, M.V.
- Brouder, S.
- Gitau, M.W.
- Bermel, P.
- Tuinstra, M.R.
- Agrawal, R.
Abstract
As the global population accelerates toward a full earth scenario, food, energy, and water demands will increase dramatically. The first order constraints that face resource generation technologies, such as static land availability, compound into second order challenges such as direct competition for the same land and solar photons. Within the contiguous United States, both agriculture and energy production such as solar have turned to densification schemes to increase yields and power per land area, respectively. These technologies coupled with water generation capabilities or management strategies, remain widely separated in their implementation or experience loss in combination. We propose an Agrivoltaic food and energy coproduction architecture to address these challenges, utilizing an Agrivoltaic Array, on-site micrometeorological condition analyses, on-site experimentally validated ray-tracing and irradiance modeling simulation software, as well as crop physiological stage, ear, and height data. Identification of critical time frames in which the relationship between irradiance and yield is highly significant (p less than 0.00005) enables implementation of ideal anti-tracking during those growth periods and solar tracking during all non-critical periods, collectively called critical-time anti-tracking. This reduces power generation to 13.68% during a six-week ideal anti-tracking time frame compared to solar tracking; still, this translates to 86.71% power generation over a year when compared to solar tracking. The reduction in power offsets yield loss, increasing land productivity. This research proposes a technology for near-neutral coproduction of food and energy leveraging already existing hardware for a viable pathway for widespread solar implementation throughout the contiguous United States.
Suggested Citation
Grubbs, E.K. & Gruss, S.M. & Schull, V.Z. & Gosney, M.J. & Mickelbart, M.V. & Brouder, S. & Gitau, M.W. & Bermel, P. & Tuinstra, M.R. & Agrawal, R., 2024.
"Optimized agrivoltaic tracking for nearly-full commodity crop and energy production,"
Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
Handle:
RePEc:eee:rensus:v:191:y:2024:i:c:s1364032123008766
DOI: 10.1016/j.rser.2023.114018
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