<scp>ICA</scp>
            ‐based solar photovoltaic fault diagnosis

Qureshi, Faheem A.; Uddin, Zahoor; Satti, Mohammed; Ali, Muhammad Umair

doi:10.1002/2050-7038.12456

Cited by 15 publications

(5 citation statements)

References 57 publications

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“…As a result of the decreasing costs and prices, the amount of electric energy generated from solar power has increased by 20% to 25% each year over the past 20 years [6]. This price decline has been induced by the increased efficiency and lifespan of solar cells, advancements in manufacturing techniques [7][8][9], and economies of scale. In the most recent decade, the global weighted average levelized cost of energy (LCOE) of utility-scale solar PVs decreased by 85%, while installed costs decreased by 81% [10].…”

Section: Introductionmentioning

confidence: 99%

Renewable Energy-Powered Traffic Signalization as a Step to Carbon-Neutral Cities (The Case of Western Balkans)

et al. 2023

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Global warming and its negative effect on the environment pose a great threat to the future of mankind. In order to overcome these challenges, EU countries have set the target of becoming climate neutral by 2050, a path defined through the policies of the European Green Deal. The Republic of Serbia and Bosnia and Herzegovina also agreed upon the same goal through the endorsement of the Green Agenda for the Western Balkans. One of the means to achieve this goal is by increasing the share of renewable energy sources. In this paper, we analyze the feasibility, challenges, and potential issues of substituting conventional traffic light signalization with signalization based on renewable energy sources on a national scale. An ad hoc questionnaire was used to collect data from representatives of most of the municipalities in the Republic of Srpska entity in Bosnia and Herzegovina and representatives of the city of Novi Sad in Serbia. In the city of Novi Sad, personal interviews were also carried out to collect additional information. The results of this research show that the implementation of solar-powered traffic lights is economically and environmentally viable. These results will provide the basis for understanding the benefits and challenges in the case of the application of traffic light signalization based on renewable energy sources.

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Section: Introductionmentioning

confidence: 99%

Renewable Energy-Powered Traffic Signalization as a Step to Carbon-Neutral Cities (The Case of Western Balkans)

et al. 2023

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“…Although the number of signal features can be ensured, if the original data is directly used to establish the defect detection model, the training efficiency of the model will be very low. To reduce data dimension and retain feature information simultaneously, some data dimensionality reduction algorithms have been proposed, such as wavelet algorithm, [ 25 ] principal component analysis, [ 26 ] independent component analysis, [ 27 ] factor analysis, [ 28 ] and linear discriminant analysis. [ 29 ] However, the performance of the model depends heavily on the setting parameters of the data dimensionality reduction algorithms.…”

Section: Resultsmentioning

confidence: 99%

Structure‐Crack Detection and Digital Twin Demonstration Based on Triboelectric Nanogenerator for Intelligent Maintenance

Xin

Xie

et al. 2023

Advanced Science

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The accomplishment of condition monitoring and intelligent maintenance for cantilever structure‐based energy harvesting devices remains a challenge. Here, to tackle the problems, a novel cantilever‐structure freestanding triboelectric nanogenerator (CSF‐TENG) is proposed, which can capture ambient energy or transmit sensory information. First, with and without a crack in cantilevers, the simulations are carried out. According to simulation results, the maximum change ratios of natural frequency and amplitude are 1.1% and 2.2%, causing difficulties in identifying defects by these variations. Thus, based on Gramian angular field and convolutional neural network, a defect detection model is established to achieve the condition monitoring of the CSF‐TENG, and the experimental result manifests that the accuracy of the model is 99.2%. Besides, the relation between the deflection of cantilevers and the output voltages of the CSF‐TENG is first built, and then the defect identification digital twin system is successfully created. Consequently, the system is capable of duplicating the operation of the CSF‐TENG in a real environment, and displaying defect recognition results, so the intelligent maintenance of the CSF‐TENG can be realized.

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“…42 An interesting approach for PV output energy modelling by combining a new data filtering procedure and a fast machine learning algorithm named light gradient boosting machine (LightGBM) was introduced in Ascencio-Vásquez et al 43 and can also be used for malfunction detection. Another fault diagnosis technique, based on independent component analysis (ICA), was proposed in Qureshi et al 44 Yet different approaches, based on malfunction forecasting, are introduced in Vergura 45 and He et al 46 In the first paper, authors detect low-intensity anomalies before they become failures, while the second is based on similarities of inverter clusters of a PV system. Finally, in 2021, several interesting papers in the field of PV systems monitoring based on data science have been published.…”

Section: Literature Reviewmentioning

confidence: 99%

A density‐based time‐series data analysis methodology for shadow detection in rooftop photovoltaic systems

Tsafarakis

Sark

2022

Progress in Photovoltaics

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The majority of photovoltaic (PV) systems in the Netherlands are small scale, installed on rooftops, where the lack of onsite global tilted irradiance (GTI) measurements and the frequent presence of shadow due to objects in the close vicinity oppose challenge in their monitoring process. In this study, a new algorithmic tool is introduced that creates a reference data‐set through the combination of data‐sets of the unshaded PV systems in the surrounding area. It subsequently compares the created reference data‐set with the one of the PV system of interest, detects any energy loss and clusters the distinctive loss due to shadow, created by the surrounding objects. The new algorithm is applied successfully to a number of different cases of shaded PV systems. Finally, suggestions on the unsupervised use of the algorithm by any monitoring platform are discussed, along with its limitations algorithm and suggestions for further research.

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ICA ‐based solar photovoltaic fault diagnosis

Cited by 15 publications

References 57 publications

Renewable Energy-Powered Traffic Signalization as a Step to Carbon-Neutral Cities (The Case of Western Balkans)

Renewable Energy-Powered Traffic Signalization as a Step to Carbon-Neutral Cities (The Case of Western Balkans)

Structure‐Crack Detection and Digital Twin Demonstration Based on Triboelectric Nanogenerator for Intelligent Maintenance

A density‐based time‐series data analysis methodology for shadow detection in rooftop photovoltaic systems

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