Towards more reliable photovoltaic energy conversion systems: A weakly-supervised learning perspective on anomaly detection

Energy Conversion and Management, Год журнала: 2024, Номер 316, С. 118845 - 118845

Опубликована: Июль 27, 2024

Язык: Английский

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An Enhanced Buck-Boost Converter for Photovoltaic Diagnosis application: Accurate MPP Tracker and I-V Tracer

Scientific African, Год журнала: 2025, Номер unknown, С. e02561 - e02561

Опубликована: Янв. 1, 2025

Язык: Английский

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Impacts of shadow conditions on solar PV array performance: a full-scale experimental and empirical study

Energy, Год журнала: 2025, Номер unknown, С. 135219 - 135219

Опубликована: Фев. 1, 2025

Язык: Английский

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Automatic fault detection in grid-connected photovoltaic systems via variational autoencoder-based monitoring

Energy Conversion and Management, Год журнала: 2024, Номер 314, С. 118665 - 118665

Опубликована: Июнь 21, 2024

Язык: Английский

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Accurate parameters extraction of photovoltaic models using Lambert W-function collaborated with AI-based Puma optimization method

Results in Engineering, Год журнала: 2025, Номер unknown, С. 104268 - 104268

Опубликована: Фев. 1, 2025

Язык: Английский

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Enhancing solar PV reliability with hybrid local features and infrared thermography

Energy Reports, Год журнала: 2024, Номер 13, С. 345 - 352

Опубликована: Дек. 13, 2024

Язык: Английский

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A hybrid spatiotemporal distribution forecast methodology for IES vulnerabilities under uncertain and imprecise space-air-ground monitoring data scenarios

Applied Energy, Год журнала: 2024, Номер 373, С. 123805 - 123805

Опубликована: Июль 10, 2024

Язык: Английский

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Time Frequency Analysis Based Fault Detection in PV Array Using Scaling Basis Chirplet Transform

Engineering Reports, Год журнала: 2024, Номер unknown

Опубликована: Окт. 9, 2024

ABSTRACT Photovoltaic (PV) arrays have gained significant attention in recent years due to their potential for sustainable energy generation. However, the reliable operation of PV is crucial optimal performance and long‐term durability. The early detection faults vital prevent further damage, improve maintenance strategies, ensure uninterrupted production. In this study, we propose a novel fault method based on Time Frequency Analysis (TFA) using Scaling Basis Chirplet Transform (SBCT). proposed method, array signal decomposed into set chirplets SBCT. represent localized time‐frequency components that can capture dynamic behavior signal. To evaluate effectiveness extensive simulations experiments are conducted real‐world data. SBCT with combination various machine learning algorithms detect array. Support Vector Machine, Decision Tree, Random Forest, ANN classifiers able 99%, 98.5%, 99.2%, 99.5% accuracies no shading condition 88%, 85%, 89%, 89.5% severe condition. achieves high accuracy robustness detecting types arrays, even presence noise uncertainties. TFA offers promising solution efficient arrays. It enables detection, facilitating timely minimizing losses. approach contribute enhancing overall performance, reliability, lifespan thereby advancing adoption renewable sources promoting development.

Язык: Английский

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A Novel Data-driven State Evaluation Approach for Photovoltaic Arrays in Uncertain Shading Scenarios

Energy, Год журнала: 2024, Номер unknown, С. 133533 - 133533

Опубликована: Окт. 1, 2024

Язык: Английский

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Multi-coupling fault detection and diagnosis of photovoltaic arrays with improved slime mould algorithm and PolyCatBoost

Process Safety and Environmental Protection, Год журнала: 2024, Номер unknown

Опубликована: Дек. 1, 2024

Язык: Английский

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