A method to estimate the location and orientation of distributed photovoltaic systems from their generation output data. (August 2017)
- Record Type:
- Journal Article
- Title:
- A method to estimate the location and orientation of distributed photovoltaic systems from their generation output data. (August 2017)
- Main Title:
- A method to estimate the location and orientation of distributed photovoltaic systems from their generation output data
- Authors:
- Haghdadi, Navid
Copper, Jessie
Bruce, Anna
MacGill, Iain - Abstract:
- Abstract: Distributed PV systems, mostly on household, commercial and industrial rooftops, represent around half of global PV capacity. Their orientation (tilt and azimuth) often depends on the particular rooftop on which they are installed, rather than being designed for optimal performance. Furthermore, data collection, and particularly validation, of their configurations is often lacking. However, their generation output is usually well monitored given this determines cashflows. Rooftop PV systems therefore pose important performance assessment challenges. Large databases of distributed PV generation performance now exist. However, there is often little information on the actual system installation, or quality checks on provided information, which is a major problem for performance assessment. We therefore present a method for estimating tilt, azimuth, and even location for PV plants by fitting a model to their time-series generation. The method is tested for three case studies: (1) simulated generation of a theoretical PV system using weather data; (2) measured generation of PV systems with validated location and orientation; and (3) measured generation from PV systems with self-reported information. Results suggest that the proposed method can estimate array tilt, azimuth, longitude, and latitude with Mean Absolute Deviations of 2.75°, 5.85°, 0.2°, and 4.08° respectively, for a typical PV system. Highlights: A method is presented to estimate the location, tilt andAbstract: Distributed PV systems, mostly on household, commercial and industrial rooftops, represent around half of global PV capacity. Their orientation (tilt and azimuth) often depends on the particular rooftop on which they are installed, rather than being designed for optimal performance. Furthermore, data collection, and particularly validation, of their configurations is often lacking. However, their generation output is usually well monitored given this determines cashflows. Rooftop PV systems therefore pose important performance assessment challenges. Large databases of distributed PV generation performance now exist. However, there is often little information on the actual system installation, or quality checks on provided information, which is a major problem for performance assessment. We therefore present a method for estimating tilt, azimuth, and even location for PV plants by fitting a model to their time-series generation. The method is tested for three case studies: (1) simulated generation of a theoretical PV system using weather data; (2) measured generation of PV systems with validated location and orientation; and (3) measured generation from PV systems with self-reported information. Results suggest that the proposed method can estimate array tilt, azimuth, longitude, and latitude with Mean Absolute Deviations of 2.75°, 5.85°, 0.2°, and 4.08° respectively, for a typical PV system. Highlights: A method is presented to estimate the location, tilt and azimuth of PV systems. Self-reported PV system specifications are often not reliable. The proposed method only requires PV generation data. The method is assessed through application to three case studies. The error is low within a typical range of tilt and azimuth angles. … (more)
- Is Part Of:
- Renewable energy. Volume 108(2017)
- Journal:
- Renewable energy
- Issue:
- Volume 108(2017)
- Issue Display:
- Volume 108, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 108
- Issue:
- 2017
- Issue Sort Value:
- 2017-0108-2017-0000
- Page Start:
- 390
- Page End:
- 400
- Publication Date:
- 2017-08
- Subjects:
- PV orientation -- PV location estimation -- PV performance analysis
Renewable energy sources -- Periodicals
Power resources -- Periodicals
Énergies renouvelables -- Périodiques
Ressources énergétiques -- Périodiques
333.794 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09601481 ↗
http://www.elsevier.com/journals ↗
http://www.journals.elsevier.com/renewable-energy/ ↗ - DOI:
- 10.1016/j.renene.2017.02.080 ↗
- Languages:
- English
- ISSNs:
- 0960-1481
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7364.187000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 27.xml