4.6 Article

A compound fault diagnosis model for photovoltaic array based on 1D VoVNet-SVDD by considering unknown faults

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Energy & Fuels

Intelligent fault identification strategy of photovoltaic array based on ensemble self-training learning

Mohamed M. Badr et al.

Summary: This paper introduces a novel strategy that combines ensemble learning and semi-supervised learning methods to realize fault diagnosis in photovoltaic arrays. The strategy uses multiple merged machine learning models to enhance overall diagnostics performance and overcome limitations of standard supervised learning algorithms. The proposed strategy is validated through simulation and experimental case studies.

SOLAR ENERGY (2023)

Article Green & Sustainable Science & Technology

An embedded system for remote monitoring and fault diagnosis of photovoltaic arrays using machine learning and the internet of things

A. Mellit et al.

Summary: In this paper, a novel embedded system is introduced for remote monitoring and fault diagnosis of photovoltaic systems. The system utilizes machine learning algorithms on a low-cost edge device for real-time deployment. An artificial neural network is developed to detect faults, and an effective stacking ensemble learning algorithm is used to classify the nature of the faults. The performance of the method is evaluated using common error metrics, and additional algorithms are embedded into the edge device to remotely control the photovoltaic array parameters.

RENEWABLE ENERGY (2023)

Article Energy & Fuels

Real-time monitoring of partial shading in large PV plants using Convolutional Neural Network

Abdelhakim Latoui et al.

Summary: A low-cost solution for real-time monitoring and diagnosis of PV plants is proposed in this study. It utilizes a pre-trained AlexNet CNN to predict whether a PV panel is under partial shading conditions (PSC) or not, based on features extracted from real-time generated 2-D scalograms. The system includes four sensors and an Adafruit PyBadge MCU, enabling automatic disconnection of partially shaded PV panels and removal of undesired objects on their surface by actioning a servo motor.

SOLAR ENERGY (2023)

Review Thermodynamics

Characteristics and cleaning methods of dust deposition on solar photovoltaic modules-A review

Beihua He et al.

Summary: Carbon neutrality is a global consensus for green development, and solar photovoltaic power generation is increasingly one of the key technologies for carbon reduction. Dust deposition on photovoltaic modules in large-scale solar power plants in arid and sandy areas significantly affects their efficiency and service life. This paper summarizes relevant research worldwide, the mechanism and influencing factors of dust deposition on photovoltaic modules, current cleaning methods, and the development of self-cleaning coatings. It also highlights the importance of further research on particle deposition and cleaning methods on photovoltaic modules.

ENERGY (2023)

Article Automation & Control Systems

Deep-Learning-Based Open Set Fault Diagnosis by Extreme Value Theory

Xiaolei Yu et al.

Summary: Existing fault diagnosis methods assume consistent label sets for training and test data, which is not applicable for real applications. This article proposes open set fault diagnosis (OSFD) to address this problem, where the test label set includes a portion of the training label set and unknown classes. The article further divides OSFD into shared-domain and cross-domain cases, and proposes different solutions for each case.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2022)

Review Energy & Fuels

Failures of Photovoltaic modules and their Detection: A Review

M. Waqar Akram et al.

Summary: Photovoltaic (PV) has grown rapidly as a promising renewable energy technology, but there have been numerous cases of early failure and degradation, as well as increasing fire risks associated with PV modules. Timely, fast and accurate detection of failures is crucial for producing efficient and durable modules. However, the current visual monitoring and assessment methods in the field are dependent on human abilities and prone to human error, making them impractical for large-scale applications. Therefore, the automation of PV monitoring and assessment methods is becoming increasingly important.

APPLIED ENERGY (2022)

Article Computer Science, Information Systems

Stereo VoVNet-CNN for 3D object detection

Kaiqi Su et al.

Summary: The paper introduces stereo VoVNet-CNN for 3D object detection, which extracts 3D boxes by stereo regression with 3D constraint, providing high accuracy for feature extraction. Experimental results prove the effectiveness of the proposed network when compared with other state-of-the-art methods on the KITTI dataset.

MULTIMEDIA TOOLS AND APPLICATIONS (2022)

Article Thermodynamics

Fault diagnosis of photovoltaic panels using full I-V characteristics and machine learning techniques

Baojie Li et al.

Summary: The study developed a method to fully utilize I-V curves for PV fault diagnosis, extracting fault features and evaluating classification with six machine learning techniques, achieving 100% classification accuracy with the best classifier in both simulation and field data.

ENERGY CONVERSION AND MANAGEMENT (2021)

Article Energy & Fuels

Fault Detection, Classification and Localization Algorithm for Photovoltaic Array

Ahsan Mehmood et al.

Summary: This study develops an algorithm that can detect, classify, and localize different types of faults in a PV array, and it can accurately work with faults of varying levels of mismatch and size.

IEEE TRANSACTIONS ON ENERGY CONVERSION (2021)

Review Green & Sustainable Science & Technology

Solar photovoltaic energy optimization methods, challenges and issues: A comprehensive review

Omar A. Al-Shahri et al.

Summary: The implementation of renewable energy systems, such as solar energy systems, aims to reduce investment, operation, and maintenance costs, as well as emissions to enhance system reliability. However, developing optimal methods under the intermittent nature of solar energy resources remains a key issue to be explored.

JOURNAL OF CLEANER PRODUCTION (2021)

Article Engineering, Mechanical

A hybrid classification autoencoder for semi-supervised fault diagnosis in rotating machinery

Xinya Wu et al.

Summary: Accurate fault diagnosis is crucial for the safe operation of rotating machinery. The proposed method, hybrid classification autoencoder, utilizes both labeled and unlabeled data for training and achieved high diagnostic accuracies in experiments with minimal labeled data. This approach shows potential for more efficient fault diagnosis in the future.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2021)

Review Green & Sustainable Science & Technology

Application of Artificial Neural Networks to photovoltaic fault detection and diagnosis: A review

B. Li et al.

Summary: This review systematically studies the application of Artificial Neural Network (ANN) and hybridized ANN models for PV fault detection and diagnosis, extracting and analyzing the targeted PV faults, detectable faults, data types and amounts, model configurations, and FDD performance for each application. The main trends, challenges, and prospects for the application of ANN for PV FDD are identified and presented.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2021)

Article Thermodynamics

A fast MPPT-based anomaly detection and accurate fault diagnosis technique for PV arrays

Chenxi Li et al.

Summary: This paper proposes a sensorless fault detection technique based on instantaneous current reduction, which can effectively identify anomalies in photovoltaic arrays and perform well in different environments. Furthermore, by utilizing an inflection point on the I-V curve, it can accurately distinguish partial shading conditions and evaluate the level of faults.

ENERGY CONVERSION AND MANAGEMENT (2021)

Letter Thermodynamics

The impact of the ANN's choice on PV systems diagnosis quality

Cherifa Kara Mostefa Khelil et al.

Summary: This study examines the impact of different Artificial Neural Networks on fault diagnosis in PV installations. It shows that RBF ANNs affect the algorithm's reaction rate, while BPNNs and GRNN present the best results in terms of speed, high precision, and classification efficiency. PNN also stands out for achieving 100% accuracy in key statistical concepts.

ENERGY CONVERSION AND MANAGEMENT (2021)

Article Energy & Fuels

A fault diagnosis method for photovoltaic module current mismatch based on numerical analysis and statistics

Zhixiang Zhang et al.

Summary: This paper investigates current mismatch faults in PV modules caused by partial shading, hot spots, and cracks, proposing a fault diagnostic method that can effectively identify the fault types, with demonstrated strong discriminating power and adaptability in actual case studies.

SOLAR ENERGY (2021)

Article Computer Science, Information Systems

Diverse Temporal Aggregation and Depthwise Spatiotemporal Factorization for Efficient Video Classification

Youngwan Lee et al.

Summary: Video classification researches have recently focused on temporal modeling and efficient 3D convolutional architectures. The proposed VoV3D network, featuring a T-OSA module and a D(2+1)D depthwise factorized component, offers efficient and effective temporal modeling. VoV3D-L, with fewer parameters and less computation, outperforms the state-of-the-art TEA model on Something-Something and Kinetics-400 datasets.

IEEE ACCESS (2021)

Article Green & Sustainable Science & Technology

Output power loss of crystalline silicon photovoltaic modules due to dust accumulation in Saharan environment

Mustapha Dida et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2020)

Article Automation & Control Systems

Deep Residual Shrinkage Networks for Fault Diagnosis

Minghang Zhao et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2020)

Article Computer Science, Information Systems

Study on fault diagnosis algorithm in WSN nodes based on RPCA model and SVDD for multi-class classification

Qiao-yan Sun et al.

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS (2019)

Article Automation & Control Systems

Supervised process monitoring and fault diagnosis based on machine learning methods

Hajer Lahdhiri et al.

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY (2019)

Review Green & Sustainable Science & Technology

Recent advances in failure diagnosis techniques based on performance data analysis for grid-connected photovoltaic systems

Andreas Livera et al.

RENEWABLE ENERGY (2019)

Article Green & Sustainable Science & Technology

Cleaning cycle optimization and cost evaluation of module dust for photovoltaic power plants in China

Bo Zhao et al.

CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY (2019)

Article Green & Sustainable Science & Technology

The effect of dust with different morphologies on the performance degradation of photovoltaic modules

Julius Tanesab et al.

SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS (2019)

Article Thermodynamics

Simulation study on the degradation process of photovoltaic modules

Chao Huang et al.

ENERGY CONVERSION AND MANAGEMENT (2018)

Article Thermodynamics

Effect of soiling in bifacial EPV modules and cleaning schedule optimization

Enric Grau Luque et al.

ENERGY CONVERSION AND MANAGEMENT (2018)

Article Computer Science, Artificial Intelligence

Fault diagnosis of rolling bearing based on feature reduction with global-local margin Fisher analysis

Xiaoli Zhao et al.

NEUROCOMPUTING (2018)

Article Thermodynamics

Random forest based intelligent fault diagnosis for PV arrays using array voltage and string currents

Zhicong Chen et al.

ENERGY CONVERSION AND MANAGEMENT (2018)

Article Chemistry, Physical

A Density Peak-Based Clustering Approach for Fault Diagnosis of Photovoltaic Arrays

Peijie Lin et al.

INTERNATIONAL JOURNAL OF PHOTOENERGY (2017)

Article Engineering, Electrical & Electronic

Fault Detection for Photovoltaic Systems Based on Multi-Resolution Signal Decomposition and Fuzzy Inference Systems

Zhehan Yi et al.

IEEE TRANSACTIONS ON SMART GRID (2017)

Article Energy & Fuels

Pattern Effects of Soil on Photovoltaic Surfaces

Patrick D. Burton et al.

IEEE JOURNAL OF PHOTOVOLTAICS (2016)

Article Automation & Control Systems

Model-Based Degradation Analysis of Photovoltaic Modules Through Series Resistance Estimation

Juan David Bastidas-Rodriguez et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2015)

Article Computer Science, Hardware & Architecture

Probabilistic Novelty Detection With Support Vector Machines

Lei Clifton et al.

IEEE TRANSACTIONS ON RELIABILITY (2014)

Article Engineering, Mechanical

Semi-supervised learning and condition fusion for fault diagnosis

Jin Yuan et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2013)

Review Green & Sustainable Science & Technology

Energy policy to promote photovoltaic generation

S. M. Moosavian et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2013)

Proceedings Paper Biophysics

A Study of SVDD-based Algorithm to the Fault Diagnosis of Mechanical Equipment System

Zhiqiang Jiang et al.

2012 INTERNATIONAL CONFERENCE ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING (ICMPBE2012) (2012)

Article Geochemistry & Geophysics

Anomaly Detection in Hyperspectral Images Based on an Adaptive Support Vector Method

Safa Khazai et al.

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2011)

Review Green & Sustainable Science & Technology

Role of renewable energy sources in environmental protection: A review

N. L. Panwar et al.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2011)

Article Geochemistry & Geophysics

A support vector method for anomaly detection in hyperspectral imagery

Amit Banerjee et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2006)

Review Engineering, Electrical & Electronic

Novelty detection: a review - part 1: statistical approaches

M Markou et al.

SIGNAL PROCESSING (2003)