An accurate method for the PV model identification based on a genetic algorithm and the interior-point method
- Submitting institution
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University of Sussex
- Unit of assessment
- 12 - Engineering
- Output identifier
- 449994_82681
- Type
- D - Journal article
- DOI
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10.1016/j.renene.2014.07.014
- Title of journal
- Renewable Energy
- Article number
- -
- First page
- 212
- Volume
- 72
- Issue
- -
- ISSN
- 0960-1481
- Open access status
- Out of scope for open access requirements
- Month of publication
- August
- Year of publication
- 2014
- URL
-
http://dx.doi.org/10.1016/j.renene.2014.07.014
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Photovoltaic modules are with different technologies and it is difficult to develop a unified and parameterised model applicable to all of them. For the first time, the provided information by the manufacturers under both the standard test conditions and nominal operating cell temperature are combined to accurately and robustly model different modules regardless of their technologies. Such accuracy and robustness are crucial for the optimal-sizing of renewable-energy sites. The presented results in the paper were employed by the EPSRC project HEED (http://heed-refugee.coventry.ac.uk/, contact: jonathan.nixon@coventry.ac.uk) to provide PV-based solutions for energy access in refugee camps. The paper has received several citations.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
