Assessment of large commercial rooftop photovoltaic system installations: Evidence from California. (15th February 2017)

• Record Type: Journal Article
• Authors: Wang, Derek D.; Sueyoshi, Toshiyuki
• Is Part Of: Applied energy. Volume 188(2017)
• Page Start: 45
• Page End: 55
• Publication Date: 2017-02-15
• Subjects: Renewable energy -- Photovoltaic -- Rooftop solar -- Data envelopment analysis; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2016.11.076
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: A DEA model is developed for assessing performance of PV installations. The model is applied to a large set of rooftop PV installations in California. A significant number of PV installations fail to achieve the best performance. There is a significant efficiency gain for installations in California from 2008 to 2012. We identify counties/cities in California with the best and worst PV installations. Abstract: In this paper we study the performance of 855 large (⩾10 kW) commercial rooftop photovoltaic (PV) system installations in California. Drawing on the nonparametric data envelopment analysis (DEA) method, our study takes the PV capacity, electricity generation, modules, system cost, solar irradiance, and ambient air temperature into account to provide a unified measure of the PV installation performance. This approach can overcome some of the limitations of simple output-to-input ratio analysis and allow us to assess whether solar capacity and electricity generation have been efficiently integrated into the grid in a holistic way. We find widespread inefficiencies in roughly 80–90% of the installations both within a specific year and across different years. There is a significant efficiency gain in solar installation from 2008 to 2012. Through regional analysis, we find high dispersions of performance across counties and cities, and identify locations where PV installations have achieved the best performance. The analysis also sheds lights on the magnitude of the gap between inefficient installations and efficient ones.