Identify and Locating the Faults in the Photovoltaic Array Using Neural Network
| Autor: | Gigih Surya Adi Pratama, Hendik Eko Hadi Suharyanto, Yahya Chusna Arif |
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| Jazyk: | English<br />Indonesian |
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Jurnal Nasional Teknik Elektro, Vol 10, Iss 2 (2021) |
| Druh dokumentu: | article |
| ISSN: | 2302-2949 2407-7267 |
| DOI: | 10.25077/jnte.v10n2.910.2021 |
| Popis: | In making the PV array system work optimally without a hitch, it is important to recognize and know where the fault occurs. The current and voltage represent the conditions of a PV array, so that, in this paper, the proposed method is based on the current and voltage values for each string, four identified conditions, namely free fault conditions, partial shading, short circuit and open circuit. Neural network is used as a tool for predicting the type and location of faults, fault samples are obtained from simulations through PSIM and the learning process is carried out through MATLAB/Simulink, the algorithms used in the learning process are also compared to see which are the best. As a result, neural network was able to identify the type and location of faults on the PV array. This proves that the condition of a PV array can be explained through its voltage and current values. Keyword:PV array, partial shading, short circuit, open circuit, neural network |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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