World estimates of PV optimal tilt angles and ratios of sunlight incident upon tilted and tracked PV panels relative to horizontal panels
By Mark Z. Jacobson, Vijaysinh Jadhav. Solar Energy, 2018
452 citations recorded by the source corpus.
Abstract This study provides estimates of photovoltaic (PV) panel optimal tilt angles for all countries worldwide. It then estimates the incident solar radiation normal to either tracked or optimally tilted panels relative to horizontal panels globally. Optimal tilts are derived from the National Renewable Energy Laboratory’s PVWatts program. A simple 3rd-order polynomial fit of optimal tilt versus latitude is derived. The fit matches data better above 40° N latitude than do previous linear fits. Optimal tilts are then used in the global 3-D GATOR-GCMOM model to estimate annual ratios of incident radiation normal to optimally tilted, 1-axis vertically tracked (swiveling vertically around a horizontal axis), 1-axis horizontally tracked (at optimal tilt and swiveling horizontally around a vertical axis), and 2-axis tracked panels relative to horizontal panels in 2050. Globally- and annually-averaged, these ratios are ∼1.19, ∼1.22, ∼1.35, and ∼1.39, respectively. 1-axis horizontal tracking differs from 2-axis tracking, annually averaged, by only 1–3% at most all latitudes. 1-axis horizontal tracking provides much more output than 1-axis vertical tracking below 65° N and S, whereas output is similar elsewhere. Tracking provides little benefit over optimal tilting above 75° N and 60° S. Tilting and tracking benefits generally increase with increasing latitude. In fact, annually averaged, more sunlight reach tilted or tracked panels from 80 to 90° S than any other latitude. Tilting and tracking benefit cities of the same latitude with lesser aerosol and cloud cover. In sum, for optimal utility PV output, 1-axis horizontal tracking is recommended, except for the highest latitudes, where optimal tilting is sufficient. However, decisions about panel configuration also require knowing tracking equipment and land costs, which are not evaluated here. Installers should also calculate optimal tilt angles for their location for more accuracy. Models that ignore optimal tilting for rooftop PV and utility PV tracking may underestimate significantly country or world PV potential.
Subfields: Artificial Intelligence, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/90e766b74eb4b473f6e1fa8aefd66aa0eccf3294
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Citations in the corpus
- 100% clean and renewable Wind, Water, and Sunlight (WWS) all-sector energy roadmaps for 53 towns and cities in North America (2018, background): “The capacity factors, provided in Jacobson et al. (2018b), are based on state data or country data that the town or city resides in, and account for competition among wind turbines for limited kinetic energy (array losses).”
- Accelerating the energy transition towards photovoltaic and wind in China (2023, unknown): “The coefficients a 0 (1.3793), a 1 (1.2011), a 2 (–0.0144) and a 3 (8.051 10 -5 ) were estimated in a previous study (Jacobson and Jadhav, 2018), while the coefficients b 0 (0.00692), b 1 (–0.400), c 1 (0.0703), b 2 (–0.006768), c 2 (0.000907), b 3 (–0.00270) and c 3 (0.00148) were estimated in a…”
- Recent Progresses of Superhydrophobic Coatings in Different Application Fields: An Overview (2021, background): “solar energy modules are installed at a tilt angle greater than 10◦ [26,27], and this angle is generally higher than the maximal sliding angle of superhydrophobic coatings.”