Failure Analysis in Photovoltaic Power Systems Using an Artificial Neural Network | ||||
| Journal of Advanced Engineering Trends | ||||
| Article 16, Volume 41, Issue 2, July 2021, Page 205-218 PDF (928.6 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/jaet.2021.49408.1069 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
mohamed ragab aboelmagd  1; Ahmed Abdelhamid Zaki Diab 2; Gamal M. Dousoky 3
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| 1electrical power | ||||
| 2Faculty of Engineering Minia University | ||||
| 3Electrical Engineering Department, Faculty of Engineering, Minia University, Minia, Egypt. | ||||
| Abstract | ||||
| As a result of the rapid expansion of photovoltaic systems, raising efficiency and managing maintenance became the PV systems' main factors. After that comes the cost and the time of repair immediately. This research provides an artificial neural network (ANN) to classify the system's type of failure. Three types of failure have been studied: line-to-line fault with a small voltage difference, a line-to-line fault with a large voltage difference, and ground fault. In addition to the fourth normal operation case, no failure is applied. The ANN employs five input data: power, voltage, current, temperature, and solar radiation. The output is a number from (0 to 3), each number denotes a specific type of failure: number '0' denotes the normal operation, number '1' denotes a line to line fault with a small voltage difference, number '2' denotes a ground fault, and number '3' denotes a line to line fault with a large voltage difference. Samples of collected data are used to train the ANN, with MATLAB Software Package, to model and simulate the system. Then, the proposed ANN is tested. Its ability to detect and classify the type of failure in the system is validated at a satisfactory success rate. The research's focus was on the discovery of a failure in the PV system, Not only the existence of a failure but also the discovery of the type of failure that occurred; this helps in speeding up the solution of the problem, speeding maintenance, and reducing the loss of power. | ||||
| Keywords | ||||
| Photovoltaic system; PV fault; line to line fault; ground fault; PV faults simulation | ||||
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