DC energy yield prediction in large monocrystalline and polycrystalline PV plants: Time-domain integration of Osterwald's model. (1st November 2016)
- Record Type:
- Journal Article
- Title:
- DC energy yield prediction in large monocrystalline and polycrystalline PV plants: Time-domain integration of Osterwald's model. (1st November 2016)
- Main Title:
- DC energy yield prediction in large monocrystalline and polycrystalline PV plants: Time-domain integration of Osterwald's model
- Authors:
- Muñoz, J.V.
Nofuentes, G.
Fuentes, M.
de la Casa, J.
Aguilera, J. - Abstract:
- Abstract: The energy produced by a large PV plant is a paramount parameter for predicting the profitability of the PV system. This prediction generally consists of first estimating the DC energy and then estimating the AC energy. At present, the well-known behavior and reliability of the inverters available on the market make the estimation of the DC energy the most important source of uncertainty in the prediction of the energy produced by a PV installation. This paper presents an experimental validation of a method based on a time-domain integration of Osterwald's model for predicting the DC energy produced by a large PV system. The statistical error indicators RMSE E and MBE E, as well as a study based on scatter plots and best-fit lines, were used to validate the method. Ten large PV systems under operation in Spain were tested. Some of the PV generators exhibited hot spots, snail tracks, blown fuses and, as a result, remarkable drops in their nominal power. Despite such remarkable power decreases, the validated method was demonstrated to perform remarkably well, particularly when the systems operate under high irradiances, displaying values of RMSE E, MBE E and R 2 of up to 0.56 %, 0.30 % and 0.999974, respectively. Highlights: The DC energy was estimated by a time-domain integration of Osterwald's model. Ten large PV systems under operation in Spain were tested. Some PV generators exhibited problems and remarkable drops in their nominal power. The method demonstratedAbstract: The energy produced by a large PV plant is a paramount parameter for predicting the profitability of the PV system. This prediction generally consists of first estimating the DC energy and then estimating the AC energy. At present, the well-known behavior and reliability of the inverters available on the market make the estimation of the DC energy the most important source of uncertainty in the prediction of the energy produced by a PV installation. This paper presents an experimental validation of a method based on a time-domain integration of Osterwald's model for predicting the DC energy produced by a large PV system. The statistical error indicators RMSE E and MBE E, as well as a study based on scatter plots and best-fit lines, were used to validate the method. Ten large PV systems under operation in Spain were tested. Some of the PV generators exhibited hot spots, snail tracks, blown fuses and, as a result, remarkable drops in their nominal power. Despite such remarkable power decreases, the validated method was demonstrated to perform remarkably well, particularly when the systems operate under high irradiances, displaying values of RMSE E, MBE E and R 2 of up to 0.56 %, 0.30 % and 0.999974, respectively. Highlights: The DC energy was estimated by a time-domain integration of Osterwald's model. Ten large PV systems under operation in Spain were tested. Some PV generators exhibited problems and remarkable drops in their nominal power. The method demonstrated to perform remarkably well, particularly for high irradiances. … (more)
- Is Part Of:
- Energy. Volume 114(2016)
- Journal:
- Energy
- Issue:
- Volume 114(2016)
- Issue Display:
- Volume 114, Issue 2016 (2016)
- Year:
- 2016
- Volume:
- 114
- Issue:
- 2016
- Issue Sort Value:
- 2016-0114-2016-0000
- Page Start:
- 951
- Page End:
- 960
- Publication Date:
- 2016-11-01
- Subjects:
- Large grid-connected systems -- DC energy estimation -- Measurement and validation -- Osterwald's model -- Outdoor measurements
Power resources -- Periodicals
Power (Mechanics) -- Periodicals
Energy consumption -- Periodicals
333.7905 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.energy.2016.07.064 ↗
- Languages:
- English
- ISSNs:
- 0360-5442
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.445000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 2366.xml