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Title: A data mining approach to estimating rooftop photovoltaic potential in the US

Journal Article · · Journal of Applied Statistics
 [1];  [2];  [1];  [1];  [1]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  2. Univ. of Denver, Denver, CO (United States)

This paper aims to quantify the amount of suitable rooftop area for photovoltaic (PV) energy generation in the continental United States (US). The approach is data-driven, combining Geographic Information Systems analysis of an extensive dataset of Light Detection and Ranging (LiDAR) measurements collected by the Department of Homeland Security with a statistical model trained on these same data. The model developed herein can predict the quantity of suitable roof area where LiDAR data is not available. This analysis focuses on small buildings (1000 to 5000 square feet) which account for more than half of the total available rooftop space in these data (58%) and demonstrate a greater variability in suitability compared to larger buildings which are nearly all suitable for PV installations. This paper presents new results characterizing the size, shape and suitability of US rooftops with respect to PV installations. Overall 28% of small building roofs appear suitable in the continental United States for rooftop solar. Nationally, small building rooftops could accommodate an expected 731 GW of PV capacity and generate 926 TWh/year of PV energy on 4920 km2 of suitable rooftop space which equates to 25% the current US electricity sales.

Research Organization:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Policy and Systems Analysis (EPSA)
Grant/Contract Number:
AC36-08GO28308
OSTI ID:
1462462
Report Number(s):
NREL/JA-2C00-66550
Journal Information:
Journal of Applied Statistics, Vol. 46, Issue 3; ISSN 0266-4763
Publisher:
Taylor & FrancisCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 7 works
Citation information provided by
Web of Science

References (2)

Estimating rooftop solar technical potential across the US using a combination of GIS-based methods, lidar data, and statistical modeling journal February 2018
Using GIS-based methods and lidar data to estimate rooftop solar technical potential in US cities journal July 2017

Cited By (1)

Solar PV as a mitigation strategy for the US education sector journal March 2019


Figures / Tables (5)