A visual-inertial system to determine accurate solar insolation and optimal PV panel orientation at a point and over an area
Sarvesh Kumar Singh,
Bharat Lohani,
Lavish Arora,
Devendra Choudhary and
Balasubramanian Nagarajan
Renewable Energy, 2020, vol. 154, issue C, 223-238
Abstract:
To provide the best return on investments it is often required to assess the suitability of a site for installation of solar photovoltaic panel and quantify shading and atmospheric losses. The shading analysis is generally done using light detection and ranging or 3D geographic information system-based approaches which are cost-effective only for large-scale analysis. In several cases, particularly in developing countries, LiDAR data or 3D GIS are not available. In this study, a terrestrial image-based system is developed to accurately estimate solar insolation at a place. The positions of obstructions obtained using captured images are integrated with sun position model to provide solar insolation and optimal solar panel orientation. To further refine the result, the effect of sky conditions on the obtained solar insolation is also considered at monthly and yearly scale. About 40% reduction in solar insolation is observed due to shading which rose to 51% when the atmospheric conditions were included in the analysis of the selected sites. Further, an approach to estimate solar insolation over an area using some discrete point location is also presented and demonstrated. Results from 30 sites show that the obtained error in insolation estimate over an area is within 4%.
Keywords: Solar insolation; Viewshed; Shading loss; Atmospheric loss (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148120303025
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:154:y:2020:i:c:p:223-238
DOI: 10.1016/j.renene.2020.02.107
Access Statistics for this article
Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides
More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().