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Effects of Irradiance and Ambient Temperature on a Decision-Making Tool for Rooftop PV Array Sizing for Commercial Buildings

[+] Author Affiliations
Carlo Bianchi, Amanda D. Smith

University of Utah, Salt Lake City, UT

Paper No. ES2016-59391, pp. V001T11A012; 8 pages
  • ASME 2016 10th International Conference on Energy Sustainability collocated with the ASME 2016 Power Conference and the ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology
  • Volume 1: Biofuels, Hydrogen, Syngas, and Alternate Fuels; CHP and Hybrid Power and Energy Systems; Concentrating Solar Power; Energy Storage; Environmental, Economic, and Policy Considerations of Advanced Energy Systems; Geothermal, Ocean, and Emerging Energy Technologies; Photovoltaics; Posters; Solar Chemistry; Sustainable Building Energy Systems; Sustainable Infrastructure and Transportation; Thermodynamic Analysis of Energy Systems; Wind Energy Systems and Technologies
  • Charlotte, North Carolina, USA, June 26–30, 2016
  • Conference Sponsors: Advanced Energy Systems Division, Solar Energy Division
  • ISBN: 978-0-7918-5022-0
  • Copyright © 2016 by ASME


Reducing global emissions and meeting the electricity generation needs of urban areas are compelling energy issues. Rooftop and small-scale photovoltaic (PV) technology is a quickly growing sector of the distributed generation market. The array size chosen for a PV installation is one of the main factors affecting its ability to meet a building’s electrical needs and reduce its operational emissions.

The rooftop area available for placement of PV can be a constraint on the optimization of PV array size. If the optimal array area for a specific building is larger than the area available on the rooftop, optimization using demand-matching methods is not necessary.

A new parameter EUI-R has been introduced to describe the building’s annual electrical demand with respect to the building rooftop area. It is a decision-making tool presented to help a system designer choose whether to employ an optimization method or not in selecting a PV system. The EUI-R depends on 2 general parameters, building electric demand and building rooftop area, that should be easily accessible for any system designer. This paper presents an extended study of EUI-R applied to 10 commercial building types in 3 different climate zones throughout the U.S. These cities are characterized by different latitudes and varying amounts of available solar radiation. The results show a linear dependency between optimal PV size obtained with a simple demand-matching algorithm, and building rooftop area, applicable to any building type. Any distributed energy technology serving a single building should be sized based on the specific conditions unique to the building, including electric demand and physical space available.

Copyright © 2016 by ASME



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