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Records with Subject: Process Monitoring
Showing records 1 to 25 of 41. [First] Page: 1 2 Last
State Estimation of Permanent Magnet Synchronous Motor Using Improved Square Root UKF
Bo Xu, Fangqiang Mu, Guoding Shi, Wei Ji, Huangqiu Zhu
December 3, 2018 (v1)
Keywords: permanent magnet synchronous motor, square root unscented Kalman filter, state estimation
This paper focuses on an improved square root unscented Kalman filter (SRUKF) and its application for rotor speed and position estimation of permanent magnet synchronous motor (PMSM). The approach, which combines the SRUKF and strong tracking filter, uses the minimal skew simplex transformation to reduce the number of the sigma points, and utilizes the square root filtering to reduce computational errors. The time-varying fading factor and softening factor are introduced to self-adjust the gain matrices and the state forecast covariance square root matrix, which can realize the residuals orthogonality and force the SRUKF to track the real state rapidly. The theoretical analysis of the improved SRUKF and implementation details for PMSM state estimation are examined. The simulation results show that the improved SRUKF has higher nonlinear approximation accuracy, stronger numerical stability and computational efficiency, and it is an effective and powerful tool for PMSM state estimation u... [more]
Online Identification with Reliability Criterion and State of Charge Estimation Based on a Fuzzy Adaptive Extended Kalman Filter for Lithium-Ion Batteries
Zhongwei Deng, Lin Yang, Yishan Cai, Hao Deng
November 28, 2018 (v1)
Keywords: battery management system, fuzzy adaptive extended Kalman filter, intrinsic model error, parameter reliability criterion, state of charge
In the field of state of charge (SOC) estimation, the Kalman filter has been widely used for many years, although its performance strongly depends on the accuracy of the battery model as well as the noise covariance. The Kalman gain determines the confidence coefficient of the battery model by adjusting the weight of open circuit voltage (OCV) correction, and has a strong correlation with the measurement noise covariance (R). In this paper, the online identification method is applied to acquire the real model parameters under different operation conditions. A criterion based on the OCV error is proposed to evaluate the reliability of online parameters. Besides, the equivalent circuit model produces an intrinsic model error which is dependent on the load current, and the property that a high battery current or a large current change induces a large model error can be observed. Based on the above prior knowledge, a fuzzy model is established to compensate the model error through updating... [more]
Application of a Heat Flux Sensor in Wind Power Electronics
Elvira Baygildina, Liudmila Smirnova, Kirill Murashko, Raimo Juntunen, Andrey Mityakov, Mikko Kuisma, Olli Pyrhönen, Pasi Peltoniemi, Katja Hynynen, Vladimir Mityakov, Sergey Sapozhnikov
November 28, 2018 (v1)
Keywords: heat flux sensor, measurement, power electronics, reliability, wind turbine
This paper proposes and investigates the application of the gradient heat flux sensor (GHFS) for measuring the local heat flux in power electronics. Thanks to its thinness, the sensor can be placed between the semiconductor module and the heat sink. The GHFS has high sensitivity and yields direct measurements without an interruption to the normal power device operation, which makes it attractive for power electronics applications. The development of systems for monitoring thermal loading and methods for online detection of degradation and failure of power electronic devices is a topical and crucial task. However, online condition monitoring (CM) methods, which include heat flux sensors, have received little research attention so far. In the current research, an insulated-gate bipolar transistor (IGBT) module-based test setup with the GHFS implemented on the base plate of one of the IGBTs is introduced. The heat flux experiments and the IGBT power losses obtained by simulations show sim... [more]
Representational Learning for Fault Diagnosis of Wind Turbine Equipment: A Multi-Layered Extreme Learning Machines Approach
Zhi-Xin Yang, Xian-Bo Wang, Jian-Hua Zhong
November 28, 2018 (v1)
Keywords: autoencoder (AE), classification, extreme learning machines (ELM), fault diagnosis, wind turbine
Reliable and quick response fault diagnosis is crucial for the wind turbine generator system (WTGS) to avoid unplanned interruption and to reduce the maintenance cost. However, the conditional data generated from WTGS operating in a tough environment is always dynamical and high-dimensional. To address these challenges, we propose a new fault diagnosis scheme which is composed of multiple extreme learning machines (ELM) in a hierarchical structure, where a forwarding list of ELM layers is concatenated and each of them is processed independently for its corresponding role. The framework enables both representational feature learning and fault classification. The multi-layered ELM based representational learning covers functions including data preprocessing, feature extraction and dimension reduction. An ELM based autoencoder is trained to generate a hidden layer output weight matrix, which is then used to transform the input dataset into a new feature representation. Compared with the t... [more]
Online Diagnosis for the Capacity Fade Fault of a Parallel-Connected Lithium Ion Battery Group
Hua Zhang, Lei Pei, Jinlei Sun, Kai Song, Rengui Lu, Yongping Zhao, Chunbo Zhu, Tiansi Wang
November 27, 2018 (v1)
Keywords: capacity fade, fault simulation, online fault diagnosis, parallel-connected battery group, recursive least squares algorithm with restricted memory and constraint
In a parallel-connected battery group (PCBG), capacity degradation is usually caused by the inconsistency between a faulty cell and other normal cells, and the inconsistency occurs due to two potential causes: an aging inconsistency fault or a loose contacting fault. In this paper, a novel method is proposed to perform online and real-time capacity fault diagnosis for PCBGs. Firstly, based on the analysis of parameter variation characteristics of a PCBG with different fault causes, it is found that PCBG resistance can be taken as an indicator for both seeking the faulty PCBG and distinguishing the fault causes. On one hand, the faulty PCBG can be identified by comparing the PCBG resistance among PCBGs; on the other hand, two fault causes can be distinguished by comparing the variance of the PCBG resistances. Furthermore, for online applications, a novel recursive-least-squares algorithm with restricted memory and constraint (RLSRMC), in which the constraint is added to eliminate the “i... [more]
An Intelligent Sensor for the Ultra-High-Frequency Partial Discharge Online Monitoring of Power Transformers
Jian Li, Xudong Li, Lin Du, Min Cao, Guochao Qian
November 27, 2018 (v1)
Keywords: field programmable gate array (FPGA), high-speed voltage comparator, intelligent sensor, level scanning method, online monitoring, partial discharge (PD), ultra-high-frequency (UHF)
Ultra-high-frequency (UHF) partial discharge (PD) online monitoring is an effective way to inspect potential faults and insulation defects in power transformers. The construction of UHF PD online monitoring system is a challenge because of the high-frequency and wide-frequency band of the UHF PD signal. This paper presents a novel, intelligent sensor for UHF PD online monitoring based on a new method, namely a level scanning method. The intelligent sensor can directly acquire the statistical characteristic quantities and is characterized by low cost, few data to output and transmit, Ethernet functionality, and small size for easy installation. The prototype of an intelligent sensor was made. Actual UHF PD experiments with three typical artificial defect models of power transformers were carried out in a laboratory, and the waveform recording method and intelligent sensor proposed were simultaneously used for UHF PD measurement for comparison. The results show that the proposed intellig... [more]
Open Fault Detection and Tolerant Control for a Five Phase Inverter Driving System
Seung-Koo Baek, Hye-Ung Shin, Seong-Yun Kang, Choon-Soo Park, Kyo-Beum Lee
November 27, 2018 (v1)
Keywords: Fault Detection, fault-tolerant control, five-phase induction machine, five-phase induction motor (IM), five-phase inverter
This paper proposes a fault detection and the improved fault-tolerant control for an open fault in the five-phase inverter driving system. The five-phase induction machine has a merit of fault-tolerant control due to its increased number of phases. This paper analyzes an open fault pattern of one switch and proposes an effective fault detection method based upon this analysis. The proposed fault detection method using the analyzed patterns is applied in the power inverter. In addition, when the open fault occurs in the one switch of the induction machine driving system, the proposed fault-tolerant control method is used to operate the induction machine using the remaining healthy phases, after performing the fault detection method. Simulation and experiment results are provided to validate the proposed technique.
Diagnostic Measurements for Power Transformers
Stefan Tenbohlen, Sebastian Coenen, Mohammad Djamali, Andreas Müller, Mohammad Hamed Samimi, Martin Siegel
November 27, 2018 (v1)
Keywords: condition assessment, dielectric response measurement, dissolved gas analysis (DGA), dynamic thermal modeling, failure statistic, frequency response analysis (FRA), moisture in oil, partial discharge measurement, power transformer, reliability
With the increasing age of the primary equipment of the electrical grids there exists also an increasing need to know its internal condition. For this purpose, off- and online diagnostic methods and systems for power transformers have been developed in recent years. Online monitoring is used continuously during operation and offers possibilities to record the relevant stresses which can affect the lifetime. The evaluation of these data offers the possibility of detecting oncoming faults early. In comparison to this, offline methods require disconnecting the transformer from the electrical grid and are used during planned inspections or when the transformer is already failure suspicious. This contribution presents the status and current trends of different diagnostic techniques of power transformers. It provides significant tutorial elements, backed up by case studies, results and some analysis. The broadness and improvements of the presented diagnostic techniques show that the power tr... [more]
Distributed Measuring System for Predictive Diagnosis of Uninterruptible Power Supplies in Safety-Critical Applications
Sergio Saponara
November 27, 2018 (v1)
Keywords: battery monitoring, measurements on power transformers, power electronics and components, predictive maintenance, uninterruptible power supply (UPS)
This work proposes a scalable architecture of an Uninterruptible Power Supply (UPS) system, with predictive diagnosis capabilities, for safety critical applications. A Failure Mode and Effect Analysis (FMEA) has identified the faults occurring in the energy storage unit, based on Valve Regulated Lead-Acid batteries, and in the 3-phase high power transformers, used in switching converters and for power isolation, as the main bottlenecks for power system reliability. To address these issues, a distributed network of measuring nodes is proposed, where vibration-based mechanical stress diagnosis is implemented together with electrical (voltage, current, impedance) and thermal degradation analysis. Power system degradation is tracked through multi-channel measuring nodes with integrated digital signal processing in the transformed frequency domain, from 0.1 Hz to 1 kHz. Experimental measurements on real power systems for safety-critical applications validate the diagnostic unit.
Extracting Steady State Components from Synchrophasor Data Using Kalman Filters
Farhan Mahmood, Hossein Hooshyar, Luigi Vanfretti
November 27, 2018 (v1)
Keywords: data processing, kalman filters, phasor measurement units, real-time simulation
Data from phasor measurement units (PMUs) may be exploited to provide steady state information to the applications which require it. As PMU measurements may contain errors and missing data, the paper presents the application of a Kalman Filter technique for real-time data processing. PMU data captures the power system’s response at different time-scales, which are generated by different types of power system events; the presented Kalman Filter methods have been applied to extract the steady state components of PMU measurements that can be fed to steady state applications. Two KF-based methods have been proposed, i.e., a windowing-based KF method and “the modified KF”. Both methods are capable of reducing noise, compensating for missing data and filtering outliers from input PMU signals. A comparison of proposed methods has been carried out using the PMU data generated from a hardware-in-the-loop (HIL) experimental setup. In addition, a performance analysis of the proposed methods is pe... [more]
Comparison of Dissolved Gases in Mineral and Vegetable Insulating Oils under Typical Electrical and Thermal Faults
Chenmeng Xiang, Quan Zhou, Jian Li, Qingdan Huang, Haoyong Song, Zhaotao Zhang
November 27, 2018 (v1)
Keywords: dissolved gas analysis (DGA), electrical fault, fault diagnosis, gas formation mechanism, thermal fault, vegetable insulating oil
Dissolved gas analysis (DGA) is attracting greater and greater interest from researchers as a fault diagnostic tool for power transformers filled with vegetable insulating oils. This paper presents experimental results of dissolved gases in insulating oils under typical electrical and thermal faults in transformers. The tests covered three types of insulating oils, including two types of vegetable oil, which are camellia insulating oil, Envirotemp FR3, and a type of mineral insulating oil, to simulate thermal faults in oils from 90 °C to 800 °C and electrical faults including breakdown and partial discharges in oils. The experimental results reveal that the content and proportion of dissolved gases in different types of insulating oils under the same fault condition are different, especially under thermal faults due to the obvious differences of their chemical compositions. Four different classic diagnosis methods were applied: ratio method, graphic method, and Duval’s triangle and Duv... [more]
Indices to Study the Electrical Power Signals in Active and Passive Distribution Lines: A Combined Analysis with Empirical Mode Decomposition
Silvano Vergura, Roberto Zivieri, Mario Carpentieri
November 27, 2018 (v1)
Keywords: coherence degree, Empirical Mode Decomposition, Hilbert-Huang Transform, periodicity degree, Smart Grids, Wavelet Transform
The broad diffusion of renewable energy-based technologies has introduced several open issues in the design and operation of smart grids (SGs) when distributed generators (DGs) inject a large amount of power into the grid. In this paper, a theoretical investigation on active and reactive power data is performed for one active line characterized by several photovoltaic (PV) plants with a great amount of injectable power and two passive lines, one of them having a small peak power PV plant and the other one having no PV power. The frequencies calculated via the empirical mode decomposition (EMD) method based on the Hilbert-Huang transform (HHT) are compared to the ones obtained via the fast Fourier transform (FFT) and the wavelet transform (WT), showing a wider spectrum of significant modes mainly due to the non-periodical behavior of the power signals. The results obtained according to the HHT-EMD analysis are corroborated by the calculation of three new indices that are computed starti... [more]
Asymmetrical Fault Correction for the Sensitive Loads Using a Current Regulated Voltage Source Inverter
Syed Sabir Hussain Bukhari, Shahid Atiq, Thomas A. Lipo, Byung-il Kwon
November 27, 2018 (v1)
Keywords: asymmetrical faults, current regulated inverter, current regulation, fault correction
Numerous industrial applications involve loads that are very sensitive to electrical supply instabilities. These instances involve various types of voltage imbalances as well as more serious disturbances such as symmetrical and asymmetrical faults. This paper proposes a cost-effective voltage imbalance and asymmetrical fault correction solution for the three phase sensitive loads utilizing an industry-standard current regulated voltage source inverter by connecting it in parallel to the grid mains powering to the sensitive load. The inverter regulates the current for the load and never permits it to go beyond a prescribed value under any type of asymmetrical fault condition, which ensures high power regulating and conditioning capacities. Experimental results are obtained from a small laboratory size prototype to validate the operation of the proposed technique.
A Time-Frequency Analysis Method for Low Frequency Oscillation Signals Using Resonance-Based Sparse Signal Decomposition and a Frequency Slice Wavelet Transform
Yan Zhao, Zhimin Li, Yonghui Nie
November 27, 2018 (v1)
Keywords: frequency slice wavelet transform, Hilbert transform, low-frequency oscillation, resonance-based sparse signal decomposition, time-frequency analysis
To more completely extract useful features from low frequency oscillation (LFO) signals, a time-frequency analysis method using resonance-based sparse signal decomposition (RSSD) and a frequency slice wavelet transform (FSWT) is proposed. FSWT can cut time-frequency areas freely, so that any band component feature can be extracted. It can analyze multiple aspects of the LFO signal, including determination of dominant mode, mode seperation and extraction, and 3D map expression. Combined with the Hilbert transform,the parameters of the LFO mode components can be identified. Furthermore, the noise in the LFO signal could reduce the frequency resolution of FSWT analysis, which may impact the accuracy of oscillation mode identification. Complex signals can be separated by predictable Q-factors using RSSD. The RSSD method can do well in LFO signal denoising. Firstly, the LFO signal is decomposed into a high-resonance component, a low-resonance component and a residual by RSSD. The LFO signal... [more]
Efficient Photovoltaic System Maximum Power Point Tracking Using a New Technique
Mehdi Seyedmahmoudian, Ben Horan, Rasoul Rahmani, Aman Maung Than Oo, Alex Stojcevski
November 27, 2018 (v1)
Keywords: computational cost, Energy Efficiency, maximum power point tracking, partial shading conditions, photovoltaic systems, soft computing methods, stability
Partial shading is an unavoidable condition which significantly reduces the efficiency and stability of a photovoltaic (PV) system. When partial shading occurs the system has multiple-peak output power characteristics. In order to track the global maximum power point (GMPP) within an appropriate period a reliable technique is required. Conventional techniques such as hill climbing and perturbation and observation (P&O) are inadequate in tracking the GMPP subject to this condition resulting in a dramatic reduction in the efficiency of the PV system. Recent artificial intelligence methods have been proposed, however they have a higher computational cost, slower processing time and increased oscillations which results in further instability at the output of the PV system. This paper proposes a fast and efficient technique based on Radial Movement Optimization (RMO) for detecting the GMPP under partial shading conditions. The paper begins with a brief description of the behavior of PV... [more]
Monte Carlo Evaluation of the Impact of Subsequent Strokes on Backflashover Rate
Fabio Massimo Gatta, Alberto Geri, Stefano Lauria, Marco Maccioni
November 27, 2018 (v1)
Keywords: ATP-EMTP, backflashover rate, grounding system, HV overhead line, Monte Carlo, subsequent strokes
The paper deals with the impact of subsequent strokes on the backflashover rate (BFR) of HV overhead transmission lines (OHLs), assessed by means of an ATP-EMTP Monte Carlo procedure. The application to a typical 150 kV Italian OHL is discussed, simulating several tower grounding system arrangements. Subsequent strokes parameters are added to the statistical simulation variables: peak current, front time, time-to-half value, lightning polarity, line insulation withstand, lightning location and phase angle of the power frequency voltage. The input data are fed to an ATP-EMTP complete circuit model of the OHL, including line insulation, lightning representation and tower grounding system, the latter simulated by a pi-circuit model able to simulate the effects due to propagation and soil ionization, at modest computational costs. Numerical results evidence a non-negligible BFR increase (in relative terms) due to subsequent strokes: for spatially concentrated grounding systems the BFR incr... [more]
Joint Estimation of the Electric Vehicle Power Battery State of Charge Based on the Least Squares Method and the Kalman Filter Algorithm
Xiangwei Guo, Longyun Kang, Yuan Yao, Zhizhen Huang, Wenbiao Li
November 16, 2018 (v1)
Keywords: AUKF, joint estimation, least square method with a forgetting factor
An estimation of the power battery state of charge (SOC) is related to the energy management, the battery cycle life and the use cost of electric vehicles. When a lithium-ion power battery is used in an electric vehicle, the SOC displays a very strong time-dependent nonlinearity under the influence of random factors, such as the working conditions and the environment. Hence, research on estimating the SOC of a power battery for an electric vehicle is of great theoretical significance and application value. In this paper, according to the dynamic response of the power battery terminal voltage during a discharging process, the second-order RC circuit is first used as the equivalent model of the power battery. Subsequently, on the basis of this model, the least squares method (LS) with a forgetting factor and the adaptive unscented Kalman filter (AUKF) algorithm are used jointly in the estimation of the power battery SOC. Simulation experiments show that the joint estimation... [more]
Measurement of penetration and cycle time of jets from an industrial fluid coking spray nozzle
Francisco Sanchez Careaga, Cedric Briens, Franco Berruti
October 30, 2018 (v1)
Keywords: Fluidization, Liquid Injection in Fluidized Beds
Fluid CokingTM is a process to upgrade heavy oils through thermal cracking. Oil is injected in a downward-flowing bed of hot coke particles, where it heats up and cracks into smaller vapour molecules. The down-flowing coke particles are sent to a burner where they are reheated and send back to the reactor to provide heat for cracking reactions. Liquid sprayed with atomization gas into a fluidized bed forms a jet cavity that absorbs bubbles from the bubbling bed and periodically releases a large bubble from its tip. The jet penetration length, thus, cycles. With a faster jet cycle, the liquid is distributed more uniformly inside the bed, which is highly desirable. Poor liquid distribution increases the formation of wet agglomerates that slow down the coking reactions and lead to operating problems in commercial Fluid CokersTM. A novel method is proposed to measure the jet penetration and cycle time in large, room-temperature fluidized beds. It is applied to the study of jet cavities fro... [more]
Hydrodynamics in Recirculating Fluidized Bed Mimicking the Stripper Section of the Fluid Coker
Francisco Sanchez Careaga
October 30, 2018 (v1)
Keywords: Agglomerates Drying Model, Baffles, Fluid Cokers, Fouling, Radioactive Particle Tracking, Recirculating Fluidized Beds, Sheds
The stripper section of a Fluid CokerTM consists of a system of baffles (sheds) that enhances the removal of interstitial and adsorbed hydrocarbon vapors from the fluidized coke-particles. Most of the hydrocarbon-vapors released below a stripper shed flow up to the stripper shed, where they may crack and form coke deposits that foul the shed. Extensive fouling changes the shapes of the sheds, makes them thicker and reduces the free-space between the adjacent sheds until downward solids flow is so impaired that the Coker has to be shut down. The Radioactive Particle Tracking (RPT) technique allows the determination of a radioactive tracer-particle location within a certain space inside a fluidized bed and has been the main tool used to study the motion of agglomerates and their interactions with internals. The research presents an innovative use of the RPT system, as a tool to measure the growth of internals fouling in time without the need of stopping the process. Moreover, the techniq... [more]
A New Fault Location Approach for Acoustic Emission Techniques in Wind Turbines
Carlos Quiterio Gómez Muñoz, Fausto Pedro García Márquez
October 23, 2018 (v1)
Keywords: acoustic emission, fault detection and diagnosis, macro-fiber composite, non-destructive testing, wind turbine
The renewable energy industry is undergoing continuous improvement and development worldwide, wind energy being one of the most relevant renewable energies. This industry requires high levels of reliability, availability, maintainability and safety (RAMS) for wind turbines. The blades are critical components in wind turbines. The objective of this research work is focused on the fault detection and diagnosis (FDD) of the wind turbine blades. The FDD approach is composed of a robust condition monitoring system (CMS) and a novel signal processing method. CMS collects and analyses the data from different non-destructive tests based on acoustic emission. The acoustic emission signals are collected applying macro-fiber composite (MFC) sensors to detect and locate cracks on the surface of the blades. Three MFC sensors are set in a section of a wind turbine blade. The acoustic emission signals are generated by breaking a pencil lead in the blade surface. This method is used to simulate the ac... [more]
Noise Emission of a 200 kW Vertical Axis Wind Turbine
Erik Möllerström, Fredric Ottermo, Jonny Hylander, Hans Bernhoff
October 23, 2018 (v1)
Keywords: H-rotor, noise, noise emission, sound power level, vertical axis wind turbine (VAWT)
The noise emission from a vertical axis wind turbine (VAWT) has been investigated. A noise measurement campaign on a 200 kW straight-bladed VAWT has been conducted, and the result has been compared to a semi-empirical model for turbulent-boundary-layer trailing edge (TBL-TE) noise. The noise emission from the wind turbine was measured, at wind speed 8 m/s, 10 m above ground, to 96.2 dBA. At this wind speed, the turbine was stalling as it was run at a tip speed lower than optimal due to constructional constraints. The noise emission at a wind speed of 6 m/s, 10 m above ground was measured while operating at optimum tip speed and was found to be 94.1 dBA. A comparison with similar size horizontal axis wind turbines (HAWTs) indicates a noise emission at the absolute bottom of the range. Furthermore, it is clear from the analysis that the turbulent-boundary-layer trailing-edge noise, as modeled here, is much lower than the measured levels, which suggests that other mechanisms are likely to... [more]
Wind Turbine Fault Detection through Principal Component Analysis and Statistical Hypothesis Testing
Francesc Pozo, Yolanda Vidal
October 22, 2018 (v1)
Keywords: FAST (Fatigue, Aerodynamics, Structures and Turbulence), Fault Detection, principal component analysis, statistical hypothesis testing, wind turbine
This paper addresses the problem of online fault detection of an advanced wind turbine benchmark under actuators (pitch and torque) and sensors (pitch angle measurement) faults of different type: fixed value, gain factor, offset and changed dynamics. The fault detection scheme starts by computing the baseline principal component analysis (PCA) model from the healthy or undamaged wind turbine. Subsequently, when the structure is inspected or supervised, new measurements are obtained are projected into the baseline PCA model. When both sets of data—the baseline and the data from the current wind turbine—are compared, a statistical hypothesis testing is used to make a decision on whether or not the wind turbine presents some damage, fault or misbehavior. The effectiveness of the proposed fault-detection scheme is illustrated by numerical simulations on a well-known large offshore wind turbine in the presence of wind turbulence and realistic fault scenarios. The obtained results demonstrat... [more]
Model-Based Fault Detection of Inverter-Based Microgrids and a Mathematical Framework to Analyze and Avoid Nuisance Tripping and Blinding Scenarios
Hashim A. Al Hassan, Andrew Reiman, Gregory F. Reed, Zhi-Hong Mao, Brandon M. Grainger
September 21, 2018 (v1)
Keywords: blinding, fault identification, inverters, microgrids, model-based, nuisance tripping
Traditional protection methods such as over-current or under-voltage methods are unreliable in inverter-based microgrid applications. This is primarily due to low fault current levels because of power electronic interfaces to the distributed energy resources (DER), and IEEE1547 low-voltage-ride-through (LVRT) requirements for renewables in microgrids. However, when faults occur in a microgrid feeder, system changes occur which manipulate the internal circuit structure altering the system dynamic relationships. This observation establishes the basis for a proposed, novel, model-based, communication-free fault detection technique for inverter-based microgrids. The method can detect faults regardless of the fault current level and the microgrid mode of operation. The approach utilizes fewer measurements to avoid the use of a communication system. Protecting the microgrid without communication channels could lead to blinding (circuit breakers not tripping for faults) or nuisance tripping (... [more]
A Data-Driven Approach for Condition Monitoring of Wind Turbine Pitch Systems
Cong Yang, Zheng Qian, Yan Pei, Lu Wei
September 21, 2018 (v1)
Keywords: condition monitoring, control chart, feature selection, pitch system, SVR
With the rapid development of wind energy, it is important to reduce operation and maintenance (O&M) costs of wind turbines (WTs), especially for a pitch system, which suffers the highest failure rate and downtime. This paper proposes a data-driven method for pitch- system condition monitoring (CM) by only using supervisory control and data acquisition (SCADA) data without any faults, which could be applied to reduce O&M costs of pitch system by providing fault alarms. The pitch-motor temperature is selected as the indicator, and three feature-selection algorithms are employed to select the most appropriate input parameters for modeling. Six data-driven algorithms are applied to model pitch-motor temperature and the support vector regression (SVR) model has the highest accuracy. The control-chart method based on the residual errors between model output and measured value is utilized to calculate the outliers, thus the abnormal condition could be clearly identified once the outl... [more]
Concurrent Real-Time Estimation of State of Health and Maximum Available Power in Lithium-Sulfur Batteries
Vaclav Knap, Daniel J. Auger, Karsten Propp, Abbas Fotouhi, Daniel-Ioan Stroe
September 21, 2018 (v1)
Keywords: extended Kalman filter, Lithium-Sulfur battery, maximum available power, state of charge, state of health
Lithium-sulfur (Li-S) batteries are an emerging energy storage technology with higher performance than lithium-ion batteries in terms of specific capacity and energy density. However, several scientific and technological gaps need to be filled before Li-S batteries will penetrate the market at a large scale. One such gap, which is tackled in this paper, is represented by the estimation of state-of-health (SOH). Li-S batteries exhibit a complex behaviour due to their inherent mechanisms, which requires a special tailoring of the already literature-available state-of-charge (SOC) and SOH estimation algorithms. In this work, a model of SOH based on capacity fade and power fade has been proposed and incorporated in a state estimator using dual extended Kalman filters has been used to simultaneously estimate Li-S SOC and SOH. The dual extended Kalman filter’s internal estimates of equivalent circuit network parameters have also been used to the estimate maximum available power of the batter... [more]
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