Output Energy and Efficiency of a PV Module as Influenced by Stochastic Variation of the Incident Solar Irradiation
This paper is aimed at evaluating the output energy and efficiency of a PV module as influenced by the stochastic variation of the incident solar radiation. A method is proposed for fitting the measured solar radiation from sunrise to sunset with different probability density function (PDF) models. The recorded data of solar radiation is arranged in an ascending order. Two indicators were adopted for checking the accuracy of fitting process. The first indicator is concerned with the equality of the sum of calculated PDF values over the sunrise hours to unity. The second indicator is concerned with the evaluation of the average of solar radiation as determined by the sum of the product of arranged values of solar radiation times their corresponding PDF value. It is concluded that Beta PDF is the best to fit the measured solar radiation values when compared with other PDFs. Following Beta PDF values, the number of hours corresponding to each value of the arranged solar radiation is evaluated. This makes it possible to calculate the input solar energy to the module. Assuming that the module is provided with a maximum power point tracker, the module output energy can be also evaluated with a subsequent determination of the energy efficiency of the module. For comparison purpose, the output energy and efficiency of the module is also calculated based on the average of the arranged solar radiation values. The comparison is also extended to compare against the efficiency of the module based on datasheet.
Authors
- Reham Kamal (ORCID: https://orcid.org/0000-0002-9005-5085)
- Mazen Abdel‐Salam
- Mohamed Nayel (ORCID: https://orcid.org/0000-0002-1691-3352)
Institutions
- Assiut University (EG)
Publication Details
- Published
- 2024-12-17
- DOI
- https://doi.org/10.1109/mepcon63025.2024.10850215
- Citations
- 1
- Primary Topic
- Solar Radiation and Photovoltaics
- Type
- article
- Field-Weighted Citation Impact
- 0.35
Funders
- Innovation Fund