- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
Determination of Technological Features of a Solar Photovoltaic Cell Made of Monocrystalline Silicon P <sup>+</sup> PNN <sup>+</sup>
摘要： The development in the field of semiconductor materials and electronic devices has a great impact on systems with renewable energy sources. Determination of the functional parameters of photovoltaic solar cells is essential for the subsequent usage of these semiconductor devices. Research was made on type P+PNN+ monocrystalline silicon wafers. Crystallographic measurements of the photovoltaic solar cell were made by means of FESEM-FIB Auriga Workstation. Initial data were selected from the study of models found in the specialized literature. The experimental results were compared to classical mathematical models. Measurements made on the photovoltaic solar cell were realised in laboratory conditions on the NI-ELVIS platform produced by National Instruments.
关键词： P+PNN+,NI-ELVIS platform,monocrystalline silicon,FESEM-FIB Auriga Workstation,photovoltaic solar cells
更新于2025-09-12 10:27:22
-
[IEEE 2019 Chinese Control And Decision Conference (CCDC) - Nanchang, China (2019.6.3-2019.6.5)] 2019 Chinese Control And Decision Conference (CCDC) - A Fault Classification Method of Photovoltaic Array Based on Probabilistic Neural Network
摘要： The energy crisis has promoted the development of solar photovoltaic power generation systems, but during the operation of solar panels, there will be hidden troubles such as ground fault, line-to-line fault, open-circuit fault, short-circuits fault and the hot spots. This will cause serious obstacles to the power generation of photovoltaic systems. Therefore, the immediate diagnosis and elimination of the fault of the photovoltaic system is the guarantee for the stable operation of the photovoltaic system. To address these issues, this paper makes contribution in the following Three aspects: (1) Building a 4 3× PV array model based on the key points and model parameters extracted from PV array by using Matlab, an efficient feature vector of five dimensions is proposed as the input of the fault diagnosis model; (2) The probabilistic neural network (PNN) is proposed as the fault classification tools, and achieving a good classification effect by using the simulated data after normalization to classify; (3) Performing the field test and inputting the experimental data into PNN for classification, with an accuracy of 97%. Both the simulation and experimental results show that the PNN can achieve high accuracy classification, provide a more favorable premise basis for the intelligent classification of faults in photovoltaic arrays.
关键词： PV array,Fault Diagnosis,PNN,Fault classification
更新于2025-09-11 14:15:04