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Records with Subject: System Identification
Showing records 176 to 200 of 536. [First] Page: 4 5 6 7 8 9 10 11 12 Last
Locked Deduplication of Encrypted Data to Counter Identification Attacks in Cloud Storage Platforms
Taek-Young Youn, Nam-Su Jho, Keonwoo Kim, Ku-Young Chang, Ki-Woong Park
March 27, 2023 (v1)
Keywords: data storage systems, encrypted storage, encryption, identification attack, privacy
Deduplication of encrypted data is a significant function for both the privacy of stored data and efficient storage management. Several deduplication techniques have been designed to provide improved security or efficiency. In this study, we focus on the client-side deduplication technique, which has more advantages than the server-side deduplication technique, particularly in communication overhead, owing to conditional data transmissions. From a security perspective, poison, dictionary, and identification attacks are considered as threats against client-side deduplication. Unfortunately, in contrast to other attacks, identification attacks and the corresponding countermeasures have not been studied in depth. In identification attacks, an adversary tries to identify the existence of a specific file. Identification attacks should be countered because adversaries can use the attacks to break the privacy of the data owner. Therefore, in the literature, some counter-based countermeasures... [more]
Methods for the Separation of Failure Modes in Power-Cycling Tests of High-Power Transistor Modules Using Accurate Voltage Monitoring
Zoltan Sarkany, Marta Rencz
March 27, 2023 (v1)
Keywords: bond-wire degradation, die-attach degradation, power cycling, thermal transient testing
The accurate measurement of on-state device voltage during power-cycling tests can deliver important information about the health of the tested power electronics components. In this article, we present the major aspects of how a power-cycling test can be set up to enable high-resolution device voltage monitoring, during both heating and cooling stages, and discuss the effect of some important parameters on the arising failure modes. The thermal transient of the component can also be captured in these setups. We show how the structure functions calculated from the captured thermal transients can be used to reveal the location of degradation in the module structure. Finally, the method for identification of bond-wire cracking and lift-off using only the measured voltage curves, is shown.
Identification of Suitable Areas for Biomass Power Plant Construction through Environmental Impact Assessment of Forest Harvesting Residues Transportation
Maria Pergola, Angelo Rita, Alfonso Tortora, Maria Castellaneta, Marco Borghetti, Antonio Sergio De Franchi, Antonio Lapolla, Nicola Moretti, Giovanni Pecora, Domenico Pierangeli, Luigi Todaro, Francesco Ripullone
March 27, 2023 (v1)
Keywords: bioenergy, geographic information system (GIS), harvesting residues, life cycle assessment
In accordance with European objectives, the Basilicata region intends to promote the use of energy systems and heat generators powered by lignocellulosic biomass, so the present study aimed to investigate the availability of logging residues and most suitable areas for the construction of bioenergy production plants. The life cycle assessment (LCA) methodology was employed to conduct an environmental impact assessment of the biomass distribution and its transport, and spatial LCA was used to evaluate the impact of regional transport. One cubic meter kilometer (m3 km−1) was used as the functional unit and a small lorry was considered for the transport. The results showed that the available harvesting residues amounted to 36,000 m3 and their loading environmental impact accounted for 349 mPt m−3. The impacts of transport (4.01 mPt m−3) ranged from 3.4 to 144,400 mPt km−1 forest parcel−1, mainly affecting human health (95%) and, second, the ecosystem quality (5%). Three possible sites for... [more]
Cloud Based IoT Solution for Fault Detection and Localization in Power Distribution Systems
Mussawir Ul Mehmood, Abasin Ulasyar, Abraiz Khattak, Kashif Imran, Haris Sheh Zad, Shibli Nisar
March 27, 2023 (v1)
Keywords: cloud computing, edge intelligence, fault identification, fault localization, IoT, MQTT, power distribution systems
Power restoring time in power distribution systems (PDS) can be minimized by using efficient fault localization techniques. This paper proposes a novel, robust and scalable cloud based internet of things (IoT) solution for identification and localization of faults in PDS. For this purpose, a new algorithm is developed that can detect single and multiple simultaneous faults in the presence of single and multiple device or sensor failures. The algorithm has utilized a zone based approach that divides a PDS into different zones. A current sensing device (CSD) was deployed at the boundary of a zone. The function of CSD is to provide time synchronized current measurements and communicate with a cloud server through an edge device (ED). Another contribution of this research work is the unique implementation of context aware policy (CAP) in ED. Due to CAP, only those measurements are transmitted to cloud server that differ from the previously transmitted measurements. The cloud server perform... [more]
Assessment of Offshore Wind Power Potential along the Brazilian Coast
Sylvester Stallone Pereira de Azevedo, Amaro Olimpio Pereira Junior, Neilton Fidelis da Silva, Renato Samuel Barbosa de Araújo, Antonio Aldísio Carlos Júnior
March 27, 2023 (v1)
Keywords: Brazilian coast, geographic information system, multicriteria analysis, wind power potential offshore
Brazilian offshore potential exploration is still in its early stages, with no single offshore park in operation or being implemented. Unlike the already identified onshore wind potential—with over 14 GW installed in the form of onshore wind turbines—offshore wind potential research is absent and restricted to limited areas. In this context, this study aims to identify offshore wind potential throughout the Brazilian coast for electricity generation. The research method took into account the average annual wind velocity records as 100 m/s, as well as bathymetry and the distance from the coast baseline, to classify areas displaying the greatest potential, applying an analytic hierarchy process (AHP) to the geographic information system for the identification of potential offshore wind energy exploration sites. Environmental conservation units were considered exclusion areas. The installable capacity using aerogenerators was estimated at 3 TW, while an annual average power production of... [more]
Identification of the Building Envelope Performance of a Residential Building: A Case Study
Evi Lambie, Dirk Saelens
March 27, 2023 (v1)
Keywords: building envelope performance, energy performance gap, experimental analysis, overall heat loss coefficient, residential buildings, retrofit, thermal resistance
Since households are one of the most energy-intensive sectors in Europe, retrofit of dwellings is promoted to increase energy efficiency. Recent research, however, shows that the energy performance after retrofit does not always meet the target values, which can be caused by amongst other things, a deviating building envelope performance. This paper compares the theoretical and measured building envelope performance for a real-life case study in post-retrofit state, in order to illustrate the limitations of calculation methods and characterization models. First, the performance is evaluated on building scale by verifying the correspondence between the default theoretical heat loss coefficient (HLC) and the measured HLC, which was determined by following the guidelines formulated within IEA EBC Annex 58 and Annex 71. In order to illustrate the limitations of the standard calculation method in real-life conditions, the theoretical variability of the HLC is evaluated, generated by variati... [more]
Boundary Identification for Traction Energy Conservation Capability of Urban Rail Timetables: A Case Study of the Beijing Batong Line
Jiang Liu, Tian-tian Li, Bai-gen Cai, Jiao Zhang
March 24, 2023 (v1)
Keywords: bacterial foraging optimization, boundary identification, case study, energy conservation, timetable, train driving control, urban transit
Energy conservation is attracting more attention to achieve a reduced lifecycle system cost level while enabling environmentally friendly characteristics. Conventional research mainly concentrates on energy-saving speed profiles, where the energy level evaluation of the timetable is usually considered separately. This paper integrates the train driving control optimization and the timetable characteristics by analyzing the achievable tractive energy conservation performance and the corresponding boundaries. A calculation method for energy efficient driving control solution is proposed based on the Bacterial Foraging Optimization (BFO) strategy, which is utilized to carry out batch processing with timetable. A boundary identification solution is proposed to detect the range of energy conservation capability by considering the relationships with average interstation speed and the passenger volume condition. A case study is presented using practical data of Beijing Metro Batong Line and t... [more]
Impedance-Based Stability Analysis of Paralleled Grid-Connected Rectifiers: Experimental Case Study in a Data Center
Henrik Alenius, Tomi Roinila
March 24, 2023 (v1)
Keywords: case study, grid-connected power electronics, impedance-based stability criterion, stability analysis, system instability
Grid-connected systems often consist of several feedback-controlled power-electronics converters that are connected in parallel. Consequently, a number of stability issues arise due to interactions among multiple converter subsystems. Recent studies have presented impedance-based methods to assess the stability of such large systems. However, only few real-life experiences have been previously presented, and practical implementations of impedance-based analysis are rare for large-scale systems that consist of multiple parallel-connected devices. This work presents a case study in which an unstable high-frequency operation, caused by multiple paralleled grid-connected rectifiers, of a 250 kW data center in southern Finland is reported and studied. In addition, the work presents an experimental approach for characterizing and assessing the system stability by using impedance measurements and an aggregated impedance-based analysis. Recently proposed wideband-identification techniques base... [more]
An Accurate Time Constant Parameter Determination Method for the Varying Condition Equivalent Circuit Model of Lithium Batteries
Liang Zhang, Shunli Wang, Daniel-Ioan Stroe, Chuanyun Zou, Carlos Fernandez, Chunmei Yu
March 24, 2023 (v1)
Keywords: lithium battery, parameter identification, resistance capacitance time constant, Thevenin model
An accurate estimation of the state of charge for lithium battery depends on an accurate identification of the battery model parameters. In order to identify the polarization resistance and polarization capacitance in a Thevenin equivalent circuit model of lithium battery, the discharge and shelved states of a Thevenin circuit model were analyzed in this paper, together with the basic reasons for the difference in the resistance capacitance time constant and the accurate characterization of the resistance capacitance time constant in detail. The exact mathematical expression of the working characteristics of the circuit in two states were deduced thereafter. Moreover, based on the data of various working conditions, the parameters of the Thevenin circuit model through hybrid pulse power characterization experiment was identified, the simulation model was built, and a performance analysis was carried out. The experiments showed that the accuracy of the Thevenin circuit model can become... [more]
Identification of Promising Alternative Mono-Alcohol Fuel Blend Components for Spark Ignition Engines
Saeid Aghahossein Shirazi, Thomas D. Foust, Kenneth F. Reardon
March 24, 2023 (v1)
Keywords: advantaged gasoline blends, alcohols, biofuel, fuel properties, spark ignition engine
Alcohols are attractive fuel blendstocks for spark ignition engines due to their high octane values and potentially positive influence on performance and emission. Although methanol, ethanol, and butanol have been widely studied, other biomass-derived alcohols may have similar or better properties. However, it is not feasible to experimentally investigate the fuel potential of every molecule. The goals of this study were to develop a methodology for rapid screening of a fuel property database for mono-alcohols and to identify alcohols with the potential of blending to produce advantaged motor gasolines. A database was developed with 13 fuel properties of all saturated C1−C10 mono-alcohols. A decision framework was used to evaluate alcohols suitable for blending in gasoline for spark ignition engines in two scenarios: low-range (up to 15 vol%) blends and high-range (greater than 40 vol%) blends. The low-range blend cases resulted in the identification of 48 alcohols. In the case of high... [more]
A Harmonic Impedance Identification Method of Traction Network Based on Data Evolution Mechanism
Ruixuan Yang, Fulin Zhou, Kai Zhong
March 24, 2023 (v1)
Keywords: data evolution mechanism, harmonic impedance, harmonic impedance identification, linear regression model, traction network
In railway electrification systems, the harmonic impedance of the traction network is of great value for avoiding harmonic resonance and electrical matching of impedance parameters between trains and traction networks. Therefore, harmonic impedance identification is beneficial to suppress harmonics and improve the power quality of the traction network. As a result of the coupling characteristics of the traction power supply system, the identification results of harmonic impedance may be inaccurate and controversial. In this context, an identification method based on a data evolution mechanism is proposed. At first, a harmonic impedance model is established and the equivalent circuit of the traction network is established. According to the harmonic impedance model, the proposed method eliminates the outliers of the measured data from trains by the Grubbs criterion and calculates the harmonic impedance by partial least squares regression. Then, the data evolution mechanism based on the s... [more]
Zero-Sequence Differential Current Protection Scheme for Converter Transformer Based on Waveform Correlation Analysis
Tao Zheng, Xinhui Yang, Xingchao Guo, Xingguo Wang, Chengqi Zhang
March 24, 2023 (v1)
Keywords: Converter transformer, correlation analysis, CT saturation, zero-sequence differential current protection
Through the analysis of the recovery inrush current generated by the external fault removal of the converter transformer, it is pointed out that the zero-sequence current caused by the recovery inrush may result in the saturation of the neutral current transformer (CT), whose measurement distortion contributes to the mis-operation of zero-sequence differential current protection. In this paper, a new scheme of zero-sequence differential current protection based on waveform correlation is proposed. By analyzing the characteristics of zero-sequence current under internal fault, external fault and external fault removal, the waveform correlation of the zero-sequence current measured at the terminal of the transformer and the zero-sequence current measured at the neutral point of the transformer is used for identification. The polarity of the CT is selected to guarantee the zero-sequence currents at the terminal and neutral point of the transformer exhibit a "ride through" characteristic u... [more]
Research on Parameter Self-Learning Unscented Kalman Filtering Algorithm and Its Application in Battery Charge of State Estimation
Fang Liu, Jie Ma, Weixing Su, Hanning Chen, Maowei He
March 24, 2023 (v1)
Keywords: battery management system, parameter identification, state of charge, unscented Kalman filter
A novel state estimation algorithm based on the parameters of a self-learning unscented Kalman filter (UKF) with a model parameter identification method based on a collaborative optimization mechanism is proposed in this paper. This algorithm can realize the dynamic self-learning and self-adjustment of the parameters in the UKF algorithm and the automatic optimization setting Sigma points without human participation. In addition, the multi-algorithm collaborative optimization mechanism unifies a variety of algorithms, so that the identification method has the advantages of member algorithms while avoiding the disadvantages of them. We apply the combination algorithm proposed in this paper for state of charge (SoC) estimation of power batteries and compare it with other model parameter identification algorithms and SoC estimation methods. The results showed that the proposed algorithm outperformed the other model parameter identification algorithms in terms of estimation accuracy and ro... [more]
Low Frequency Magnetic Fields Emitted by High-Power Charging Systems
Germana Trentadue, Rosanna Pinto, Marco Zanni, Harald Scholz, Konstantinos Pliakostathis, Giorgio Martini
March 24, 2023 (v1)
Keywords: electro-mobility, high-power charging, magnetic flux density
The new generation of fast charging systems faces a formidable technological challenge, aiming to drastically reduce the time needed to recharge an electric vehicle as a way to tackle the range anxiety issue. To achieve this, high power (up to 350 kW) is transferred from the grid to the vehicle, leading to potentially high values of low frequency magnetic fields. This study presents the results of measurements of magnetic flux density (B-field) emitted by two different high power charging systems. The electric vehicle used for the recharge was able to digest up to 83 kW of delivered power. The test procedure was designed to identify the locations where the maximum B-field levels were recorded and to measure the exposure indices according to reference levels for general public exposure defined in the Council Recommendation 1999/519/EC. Measurements in close proximity to the power cabinets during the recharge revealed that, at some points, exposure indices were higher than 100%, leading... [more]
Fault Model and Travelling Wave Matching Based Single Terminal Fault Location Algorithm for T-Connection Transmission Line: A Yunnan Power Grid Study
Hongchun Shu, Yiming Han, Ran Huang, Yutao Tang, Pulin Cao, Bo Yang, Yu Zhang
March 23, 2023 (v1)
Keywords: Single-terminal fault location, T-connection transmission line, travelling wave arrival time, travelling wave reflection
Due to the complex structure of the T-connection transmission lines, it is extremely difficult to identify the reflected travelling wave from the fault point and that from the connection point by the measurement from only one terminal. According to the characteristics of the structure of the T-connection transmission line, the reflection of the travelling wave within the line after the failure of different sections in T-connection transmission line are analyzed. Based on the lattice diagram of the travelling wave, the sequence of travelling waves detected at the measuring terminal varies with the fault distance and the faulty section. Moreover, the sequence of travelling waves detected in one terminal is unique at each faulty section. This article calculates the arrival time of travelling waves of fault points at different locations in different sections to form the collection of the travelling wave arrival time sequence. Then the sequence of travelling waves of the new added fault wav... [more]
Distortion Load Identification Based on the Application of Compensating Devices
Yaroslav Shklyarskiy, Aleksandr Skamyin, Iaroslav Vladimirov, Farit Gazizov
March 23, 2023 (v1)
Keywords: capacitor banks, distortion source, external load, high harmonics, internal load, linear load, nonlinear load, passive harmonic filter, power system
The article provides an analysis of the existing methods of identifying the consumer’s contribution to voltage distortion at a point of common coupling. The considered methods do not allow correctly and fairly determining the source of harmonic distortions, or they have limited application and difficulties in implementation. The paper proposes new methods for determining the source of high harmonics. The developed methods and techniques are based on the analysis of the grid operation modes with two connected consumers using compensating devices, such as reactive power compensation devices and passive harmonic filters. It is shown that the most promising method is the application of harmonic filters, which allows determining the share of the consumer’s contribution to the voltage distortion. The present research is carried out using a computer simulation of the existing electrical grid, to which consumers with nonlinear electric load are connected. These methods can be implemented to as... [more]
Synthesis and Verification of Finite-Time Rudder Control with GA Identification for Electric Rudder System
Zhihong Wu, Ruifeng Yang, Chenxia Guo, Shuangchao Ge, Xiaole Chen
March 23, 2023 (v1)
Keywords: electric rudder system, finite time rudder control, Genetic Algorithm, parameter identification
The electric rudder system (ERS) is the executive mechanism of the flight control system, which can make the missile complete the route correction according to the control command. The performance and quality of the ERS directly determine the dynamic quality of the flight control system. However, the transient and static characteristic of ERS is affected by the uncertainty of physical parameters caused by nonlinear factors. Therefore, the control strategy based on genetic algorithm (GA) identification method and finite-time rudder control (FTRC) theory is studied to improve the control accuracy and speed of the system. Differently from the existing methods, in this method, the difficulty of parameter uncertainty in the controller design is solved based on the ERS mathematical model parameter identification strategy. Besides, in this way, the performance of the FTRC controller was verified by cosimulation experiments based on automatic dynamic analysis of mechanical systems (ADAMS) (MSC... [more]
High-Order AVO Inversion for Effective Pore-Fluid Bulk Modulus Based on Series Reversion and Bayesian Theory
Lei Shi, Yuhang Sun, Yang Liu, David Cova, Junzhou Liu
March 23, 2023 (v1)
Keywords: Bayesian theory, high order AVO equation, series reversion, the effective pore-fluid bulk modulus
Pore-fluid identification is one of the key technologies in seismic exploration. Fluid indicators play important roles in pore-fluid identification. For sandstone reservoirs, the effective pore-fluid bulk modulus is more susceptible to pore-fluid than other fluid indicators. AVO (amplitude variation with offset) inversion is an effective way to obtain fluid indicators from seismic data directly. Nevertheless, current methods lack a high-order AVO equation for a direct, effective pore-fluid bulk modulus inversion. Therefore, based on the Zoeppritz equations and Biot−Gassmann theory, we derived a high-order P-wave AVO approximation for an effective pore-fluid bulk modulus. Series reversion and Bayesian theory were introduced to establish a direct non-linear P-wave AVO inversion method. By adopting this method, the effective pore-fluid bulk modulus, porosity, and density can be inverted directly from seismic data. Numerical simulation results demonstrate the precision of our proposed meth... [more]
Practical Implementation of Adaptive SRF-PLL for Three-Phase Inverters Based on Sensitivity Function and Real-Time Grid-Impedance Measurements
Roni Luhtala, Henrik Alenius, Tomi Roinila
March 23, 2023 (v1)
Keywords: control systems, impedance measurement, phase locked loops, power electronics, stability analysis, system identification
Rapidly increasing demand for renewable energy has created a need for the photovoltaic and wind farms to be placed in various locations that have diverse and possibly time-variant grid conditions. A mismatch between the grid impedance and output admittance of an inverter causes impedance-based stability issues, which appear as power quality problems and poor transient performance. Grid synchronization with phase-locked loop (PLL) introduces a negative-resistance-like behavior to inverter output admittance. High control bandwidth of the PLL makes the system sensitive to impedance-based stability issues when the inverter is connected to a weak grid that has high impedance. However, very conservative tunings lead to overly damped dynamic responses in strong grids, where the control performance and power quality can be improved by applying higher PLL control bandwidths. Continuous evaluation of grid conditions makes it possible to avoid the risk of instability and poor dynamic responses, a... [more]
An Interval-Arithmetic-Based Approach to the Parametric Identification of the Single-Diode Model of Photovoltaic Generators
Martha Lucia Orozco-Gutierrez
March 22, 2023 (v1)
Keywords: interval arithmetic, parametric identification, photovoltaic systems, single-diode model
Parametric identification of the single diode model of a photovoltaic generator is a key element in simulation and diagnosis. Parameters’ values are often determined by using experimental data the modules manufacturers provide in the data sheets. In outdoor applications, the parametric identification is instead performed by starting from the current vs. voltage curve acquired in non-standard operating conditions. This paper refers to this latter case and introduces an approach based on the use of interval arithmetic. Photovoltaic generators based on crystalline silicon cells are considered: they are modeled by using the single diode model, and a divide-and-conquer algorithm is used to contract the initial search space up to a small hyper-rectangle including the identified set of parameters. The proposed approach is validated by using experimental data measured in outdoor conditions. The information provided by the approach, in terms of parametric sensitivity and of correlation between... [more]
A New Method of Lithology Classification Based on Convolutional Neural Network Algorithm by Utilizing Drilling String Vibration Data
Gang Chen, Mian Chen, Guobin Hong, Yunhu Lu, Bo Zhou, Yanfang Gao
March 22, 2023 (v1)
Keywords: class activation heatmap, convolutional neural network, drill string vibration data, lithology identification model
Formation lithology identification is of great importance for reservoir characterization and petroleum exploration. Previous methods are based on cutting logging and well-logging data and have a significant time lag. In recent years, many machine learning methods have been applied to lithology identification by utilizing well-logging data, which may be affected by drilling fluid. Drilling string vibration data is a high-density ancillary data, and it has the advantages of low-latency, which can be acquired in real-time. Drilling string vibration data is more accessible and available compared to well-logging data in ultra-deep well drilling. Machine learning algorithms enable us to develop new lithology identification models based on these vibration data. In this study, a vibration dataset is used as the signal source, and the original vibration signal is filtered by Butterworth (BHPF). Vibration time−frequency characteristics were extracted into time−frequency images with the applicati... [more]
Multi-State Household Appliance Identification Based on Convolutional Neural Networks and Clustering
Ying Zhang, Bo Yin, Yanping Cong, Zehua Du
March 22, 2023 (v1)
Keywords: non-intrusive load monitoring, the identification of appliances states, the identification of appliances types
Non-intrusive load monitoring, a convenient way to discern the energy consumption of a house, has been studied extensively. However, most research works have been carried out based on a hypothetical condition that each electric appliance has only one running state. This leads to low identification accuracy for multi-state electric appliances. To deal with this problem, a method for identifying the type and state of electric appliances based on a power time series is proposed in this paper. First, to identify the type of appliance, a convolutional neural network model was constructed that incorporated residual modules. Then, a k-means clustering algorithm was applied to calculate the number of states of the appliance. Finally, in order to identify the states of the appliances, different k-means clustering models were established for different multi-state electric appliances. Experimental results show effectiveness of the proposed method in identifying both the type and the running state... [more]
The Senescence (Stay-Green)—An Important Trait to Exploit Crop Residuals for Bioenergy
Eduardo D. Munaiz, Susana Martínez, Arun Kumar, Marlon Caicedo, Bernardo Ordás
March 22, 2023 (v1)
Keywords: bioenergy, breeding, chlorophyll, genetics, high-throughput phenotyping, maize and rice, quantitative genetics, senescence, stay-green
In this review, we present a comprehensive revisit of past research and advances developed on the stay-green (SG) paradigm. The study aims to provide an application-focused review of the SG phenotypes as crop residuals for bioenergy. Little is known about the SG trait as a germplasm enhancer resource for energy storage as a system for alternative energy. Initially described as a single locus recessive trait, SG was shortly after reported as a quantitative trait governed by complex physiological and metabolic networks including chlorophyll efficiency, nitrogen contents, nutrient remobilization and source-sink balance. Together with the fact that phenotyping efforts have improved rapidly in the last decade, new approaches based on sensing technologies have had an impact in SG identification. Since SG is linked to delayed senescence, we present a review of the term senescence applied to crop residuals and bioenergy. Firstly, we discuss the idiosyncrasy of senescence. Secondly, we present... [more]
Identification Method for Series Arc Faults Based on Wavelet Transform and Deep Neural Network
Qiongfang Yu, Yaqian Hu, Yi Yang
March 22, 2023 (v1)
Keywords: deep neural network, low-voltage system, series arc faults, wavelet transform
The power supply quality and power supply safety of a low-voltage residential power distribution system is seriously affected by the occurrence of series arc faults. It is difficult to detect and extinguish them due to the characteristics of small current, high stochasticity, and strong concealment. In order to improve the overall safety of residential distribution systems, a novel method based on discrete wavelet transform (DWT) and deep neural network (DNN) is proposed to detect series arc faults in this paper. An experimental bed is built to obtain current signals under two states, normal and arcing. The collected signals are discomposed in different scales applying the DWT. The wavelet coefficient sequences are used for forming training set and test set. The deep neural network trained by training set under 4 different loads adaptively learn the feature of arc faults. The accuracy of arc faults recognition is sent through feeding test set into the model, about 97.75%. The experimen... [more]
Analysis of Photovoltaic String Failure and Health Monitoring with Module Fault Identification
Ahmad Rivai, Nasrudin Abd Rahim, Mohamad Fathi Mohamad Elias, Jafferi Jamaludin
March 22, 2023 (v1)
Keywords: graphical user interface, health monitoring, Internet of Things, photovoltaic module fault detection, photovoltaic string, self-powered wireless sensor network
In this paper, photovoltaic (PV) string failure analysis and health monitoring of PV modules based on a low-cost self-powered wireless sensor network (WSN) are presented. Simple and effective fault detection and diagnosis method based on the real-time operating voltage of PV modules is proposed. The proposed method is verified using the developed health monitoring system which is installed in a grid-connected PV system. Each of the PV modules is monitored via WSN to detect any individual faulty module. The analysis of PV string failure includes several electrical fault scenarios and their impact on the PV string characteristics. The results show that a degraded or faulty module exhibits low operating voltage as compared to the normal module. The developed health monitoring system also includes a graphical user interface (GUI) program which graphically displays the real-time operating voltage of each module with colors and thus helping users to identify the faulty modules easily. The fa... [more]
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