Measurement-Based Modeling of a Semitransparent CdTe Thin-Film PV Module Based on a Custom Neural Network
Semitransparent photovoltaic (STPV) can be employed in a wide application range to provide sunlight permeability for supplying solar electrical energy with some shading, which is preferable in hot areas. To predict the output power and formulate the performance of this type of photovoltaic (PV) syst...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2018-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8388207/ |
| _version_ | 1818331735979458560 |
|---|---|
| author | Yasmeen Hussein Sabry W. Z. W. Hasan A. H. Sabry Mohd Zainal Abidin Ab Kadir M. A. M. Radzi S. Shafie |
| author_facet | Yasmeen Hussein Sabry W. Z. W. Hasan A. H. Sabry Mohd Zainal Abidin Ab Kadir M. A. M. Radzi S. Shafie |
| author_sort | Yasmeen Hussein Sabry |
| collection | DOAJ |
| description | Semitransparent photovoltaic (STPV) can be employed in a wide application range to provide sunlight permeability for supplying solar electrical energy with some shading, which is preferable in hot areas. To predict the output power and formulate the performance of this type of photovoltaic (PV) system, the proposed approach analyzes a Thin-Film solar cadmium telluride-type module and develops a custom neural network (CNN) for modeling its generated power expressed by its mathematical formula. Experiments for single and multilayer installation topologies are conducted for performance analysis. The coefficients of the model equation are investigated based on a set of power-current curves. The developed model adopts three factors: a minimum number of hidden neurons, the use of all measured data to train the network weights, and a linear output activation function to reduce the complexity of solving the network equations. The results specify the limit at which this type of PV starts generating power from the experimental measurements and the comparison with its equivalent normal PV module. The CNN-based STPV module is verified by comparing with the experimental measurements results, which shows a reasonable R-square, while its performance is evaluated on the silicon-based PV by comparing its behavior with the two-diode model PV in the MATLAB-based simulation. |
| first_indexed | 2024-12-13T13:24:35Z |
| format | Article |
| id | doaj.art-ceefca28827c47ad9e56caf6e37e99a7 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T13:24:35Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-ceefca28827c47ad9e56caf6e37e99a72022-12-21T23:44:20ZengIEEEIEEE Access2169-35362018-01-016349343494710.1109/ACCESS.2018.28489038388207Measurement-Based Modeling of a Semitransparent CdTe Thin-Film PV Module Based on a Custom Neural NetworkYasmeen Hussein Sabry0W. Z. W. Hasan1A. H. Sabry2https://orcid.org/0000-0002-2736-5582Mohd Zainal Abidin Ab Kadir3M. A. M. Radzi4S. Shafie5Department of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, MalaysiaDepartment of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, MalaysiaDepartment of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, MalaysiaDepartment of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, MalaysiaDepartment of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, MalaysiaDepartment of Electrical and Electronics Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, MalaysiaSemitransparent photovoltaic (STPV) can be employed in a wide application range to provide sunlight permeability for supplying solar electrical energy with some shading, which is preferable in hot areas. To predict the output power and formulate the performance of this type of photovoltaic (PV) system, the proposed approach analyzes a Thin-Film solar cadmium telluride-type module and develops a custom neural network (CNN) for modeling its generated power expressed by its mathematical formula. Experiments for single and multilayer installation topologies are conducted for performance analysis. The coefficients of the model equation are investigated based on a set of power-current curves. The developed model adopts three factors: a minimum number of hidden neurons, the use of all measured data to train the network weights, and a linear output activation function to reduce the complexity of solving the network equations. The results specify the limit at which this type of PV starts generating power from the experimental measurements and the comparison with its equivalent normal PV module. The CNN-based STPV module is verified by comparing with the experimental measurements results, which shows a reasonable R-square, while its performance is evaluated on the silicon-based PV by comparing its behavior with the two-diode model PV in the MATLAB-based simulation.https://ieeexplore.ieee.org/document/8388207/Artificial neural networkmodelingmeasurementssemitransparent PV |
| spellingShingle | Yasmeen Hussein Sabry W. Z. W. Hasan A. H. Sabry Mohd Zainal Abidin Ab Kadir M. A. M. Radzi S. Shafie Measurement-Based Modeling of a Semitransparent CdTe Thin-Film PV Module Based on a Custom Neural Network IEEE Access Artificial neural network modeling measurements semitransparent PV |
| title | Measurement-Based Modeling of a Semitransparent CdTe Thin-Film PV Module Based on a Custom Neural Network |
| title_full | Measurement-Based Modeling of a Semitransparent CdTe Thin-Film PV Module Based on a Custom Neural Network |
| title_fullStr | Measurement-Based Modeling of a Semitransparent CdTe Thin-Film PV Module Based on a Custom Neural Network |
| title_full_unstemmed | Measurement-Based Modeling of a Semitransparent CdTe Thin-Film PV Module Based on a Custom Neural Network |
| title_short | Measurement-Based Modeling of a Semitransparent CdTe Thin-Film PV Module Based on a Custom Neural Network |
| title_sort | measurement based modeling of a semitransparent cdte thin film pv module based on a custom neural network |
| topic | Artificial neural network modeling measurements semitransparent PV |
| url | https://ieeexplore.ieee.org/document/8388207/ |
| work_keys_str_mv | AT yasmeenhusseinsabry measurementbasedmodelingofasemitransparentcdtethinfilmpvmodulebasedonacustomneuralnetwork AT wzwhasan measurementbasedmodelingofasemitransparentcdtethinfilmpvmodulebasedonacustomneuralnetwork AT ahsabry measurementbasedmodelingofasemitransparentcdtethinfilmpvmodulebasedonacustomneuralnetwork AT mohdzainalabidinabkadir measurementbasedmodelingofasemitransparentcdtethinfilmpvmodulebasedonacustomneuralnetwork AT mamradzi measurementbasedmodelingofasemitransparentcdtethinfilmpvmodulebasedonacustomneuralnetwork AT sshafie measurementbasedmodelingofasemitransparentcdtethinfilmpvmodulebasedonacustomneuralnetwork |