Reference health
Machine Learning Schemes for Anomaly Detection in Solar Power Plants
37/37 checkable references clean · checked 2026-08-02
Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.
8 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.
The 37 checked references that resolve
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Classification model for accuracy and intrusion detection using machine learning approach
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A fast MPPT-based anomaly detection and accurate fault diagnosis technique for PV arrays
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A simple model of PV system performance and its use in fault detection
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Modeling of solar energy systems using artificial neural network: A comprehensive review
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Utilization of LSTM neural network for water production forecasting of a stepped solar still with a corrugated absorber plate
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Productivity forecasting of solar distiller integrated with evacuated tubes and external condenser using artificial intelligence model and moth-flame optimizer
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Short-Time Wind Speed Forecast Using Artificial Learning-Based Algorithms
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A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids
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Anomaly detection and predictive maintenance for photovoltaic systems
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An unsupervised monitoring procedure for detecting anomalies in photovoltaic systems using a one-class Support Vector Machine
resolves10.1088/1742-6596/364/1/012119
Intelligent system for a remote diagnosis of a photovoltaic solar power plant
resolves10.1109/TSTE.2018.2867009
Hierarchical Anomaly Detection and Multimodal Classification in Large-Scale Photovoltaic Systems
resolves10.1080/08839514.2019.1691839
Anomaly Detection in Power Generation Plants Using Machine Learning and Neural Networks
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Anomaly Detection and Automatic Labeling for Solar Cell Quality Inspection Based on Generative Adversarial Network
resolves10.1080/00224065.2021.1948372
Online automatic anomaly detection for photovoltaic systems using thermography imaging and low rank matrix decomposition
resolves10.1109/PVSC45281.2020.9300481
Evaluation of unsupervised anomaly detection approaches on photovoltaic monitoring data
resolves10.1109/Indo-TaiwanICAN48429.2020.9181310
Anomaly Detection Mechanism for Solar Generation using Semi-supervision Learning Model
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Unsupervised Anomaly Detection in Energy Time Series Data Using Variational Recurrent Autoencoders with Attention
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Ensemble regression model-based anomaly detection for cyber-physical intrusion detection in smart grids
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Overview of Anomaly Detection techniques in Machine Learning
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Anomaly Detection of Power Plant Equipment Using Long Short-Term Memory Based Autoencoder Neural Network
resolves10.1109/ICFPT47387.2019.00072
Real-Time Anomaly Detection for Flight Testing Using AutoEncoder and LSTM
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The 8 references without a DOI — listed, not checked
no DOI — not checkedBenninger, M., Hofmann, M., and Liebschner, M. (2019, January 19–20). Online Monitoring System for Photovoltaic Systems Using Anomaly Detection with Machine Learning. Proceedings of the NEIS 2019, Conference on Sustainable Energy Supply and Energy Storage Systems, Hamburg, Germany.
no DOI — not checkedHu, B. (2012). Solar Panel Anomaly Detection and Classification. [Master’s Thesis, University of Waterloo].
no DOI — not checkedFault Detection of Solar PV System Using SVM and Thermal Image Processing
no DOI — not checkedBenninger, M., Hofmann, M., and Liebschner, M. (2020, January 14–15). Anomaly detection by comparing photovoltaic systems with machine learning methods. Proceedings of the NEIS 2020, Conference on Sustainable Energy Supply and Energy Storage Systems, Hamburg, Germany.
no DOI — not checkedSrivastava, S. (2019). Benchmarking Facebook’s Prophet, PELT and Twitter’s Anomaly Detection and Automated de Ployment to Cloud. [Master’s Thesis, University of Twente].
no DOI — not checkedKannal, A. (2022, January 25). Solar Power Generation Data. Kaggle.com. Available online: https://www.kaggle.com/anikannal/solar-power-generation-data.
no DOI — not checkedCorder, G.W., and Foreman, D.I. (2014). Nonparametric Statistics: A Step-by-Step Approach, John Wiley & Sons.
no DOI — not checked(2022, January 25). ParameterGrid. Available online: https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.ParameterGrid.html.
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