Power Of Frequency Components Research Articles

ICEEMDAN-based Combined Wind Power Forecasting

Background:: With the depletion of fossil energy and the increasingly serious environmental pollution, the task of developing renewable energy is imminent. As a green and pollutionfree renewable energy, the penetration of wind energy in the power grid continues to rise. Objective:: In order to reduce the volatility and randomness of wind power series and increase the accuracy of wind power prediction, a wind power combination model based on the ICEEMDAN (improved adaptive noise full set empirical mode decomposition) method is proposed. objective: In order to reduce the volatility and randomness of wind power series and increase the accuracy of wind power prediction, a wind power combination model based on ICEEMDAN (improved adaptive noise full set empirical mode decomposition) method is proposed Methodology:: First, the complex original wind power data have been decomposed into several relatively simple subsequences using the ICEEMDAN method. Aiming at the different lengths of coarse grain time series and data loss in traditional multi-scale entropy, a fine composite multiscale dispersion entropy is proposed to calculate the entropy value of each decomposition component, and divide the high- and low-frequency modal components to predict the modal components of different frequencies; secondly, differential moving autoregressive model (ARIMA) and shortterm memory neural network (LSTM) are used to establish the prediction models of high- and low-frequency components, respectively. Results:: Finally, the prediction results of each component have been superimposed and reconstructed to obtain the final prediction results. The effectiveness of the combined model is verified by the actual operation data of a European wind farm. result: The effectiveness of the combined model is verified by the actual operation data of a European wind farm. The results show that compared with the other four single and combined forecasting models, the combined model in this paper has higher forecasting accuracy. Conclusion:: As the effectiveness of the combined model is verified by the actual operation data of a European wind farm, the results have shown that compared to the other four single and combined forecasting models, the combined model in this paper has higher forecasting accuracy. Therefore, the model proposed in this article can be used for predicting wind power with significant fluctuations, which will help to provide support for optimized scheduling and energy storage configuration of wind farms, thereby reducing costs and increasing income for the power grid and wind farms. conclusion: ICEEMDAN decomposition algorithm can effectively reduce the influence of white noise on mode decomposition, and the prediction accuracy of wind power can be better improved by putting different frequency power components into different prediction models

Noise Reduction Method for Fiber Optical Current Transformer Based on Mode Decomposition-Sample Entropy

When a fiber optic current transformer (FOCT) malfunctions, its output signal is usually accompanied by a large noise, which affects the subsequent fault diagnosis results of the transformer. In response to the above noise issues, this paper constructs a new noise reduction algorithm by combining Complete Ensemble Empirical Mode Decomposition Adaptive Noise (CEEMDAN) and Sample Entropy (SE). Above all, the output signal of FOCT is decomposed into multiple fault components using the CEEMDAN algorithm. Then, by comprehensively considering the frequency domain characteristics and sample entropy calculation value of each component, the characteristics of each component are determined, so the power frequency and low-frequency components are selected as the feature vectors representing the fault mode. Finally, the noise components with high sample entropy are eliminated, and the power frequency current components with medium sample entropy and the low-frequency fault feature components with low sample entropy are recombined and superposed to build a fault signal dataset after noise reduction.

Faulty Feeder Detection Based on Grey Correlation Degree of Adaptive Frequency Band in Resonant Grounding Distribution System

Due to the particularity of their process, petrochemical enterprises have high requirements for the reliability of power supply. If a large-scale blackout occurs due to a grounding fault, it will pose a huge threat to safe production. When the resonant grounding system of petrochemical enterprises faults, due to the complex fault process and weak fault signal, it is difficult to accurately detect the faulty feeder by traditional methods. This paper presents a new method of grey correlation degree based on adaptive frequency band. Firstly, the transient zero-sequence current of each feeder is decomposed by coif5 wavelet, and the low frequency band a5 (power frequency component) and high frequency band d1, d2 (noise signal) are removed. By stacking all of the remaining frequency band signals to construct the wavelet area matrix, the faulty feeder detection characteristic scale and the first faulty feeder detection result are obtained. Secondly, based on the faulty feeder detection characteristic scale, the second faulty feeder detection result is obtained by the average grey correlation degree matrix, which detects the faulty feeder according to the waveform correlation degree. Finally, the final faulty feeder detection result is obtained by equal weight voting. In MATLAB/Simulink, the 10 kV resonant grounding system of petrochemical enterprises is modeled. A large number of simulation results show that the faulty feeder detection method is not affected by the initial phase angle (0°, 45° and 90°), transition resistance (10 Ω, 100 Ω and 1000 Ω), fault distance (1 km, 8 km and 15 km) and overcompensation degree (5%, 8% and 10%), and has good sensitivity.

Identification Method for Pulse Wave Resulted From Fault Transient of Overhead Transmission Line

This paper presents a simple and effective method to extract the identification quantity of transient pulse waveform produced by the overhead transmission line short-circuit fault. This method employs the second-order time harmonic equation of the power frequency component to convert the fault full-wave data. After the conversion, only the identification quantity remains. This method can amplify high-frequency spectral content by the times of the square of the angular frequency, and hence improve the sensitivity of identifying fault transient. Using the identification quantity, one can clearly observe the arrival time and relative intensity of fault transient. A three-phase half wavelength transmission line of 50Hz/3000km is simulated with PSCAD to illuminate the effectiveness of this method. The effects of fault type, soil resistivity, fault resistance, power frequency fluctuation, sampling rate, transposition length,fault inception angle and white noise are analyzed. Calculated results show that this method can distinguish different fault type and can work effectively at low sampling rate down to 10kHz. This method is helpful for improving the performance of the traveling-wave based fault location method.

Fault Line Selection with Correlation Analysis of Zero Sequence Current and Voltage under High-Low Frequency

When a single-phase ground fault occurs near the zero or maximum point, the fault line selection of resonance grounding system is not sensitive enough. After analyzing the transient current and line impedance characteristics of zero sequence network, and making full use of the decaying DC component, power frequency component and high frequency component of the transient zero sequence current of the feeder, a fault line selection method based on correlation analysis of zero sequence current and bus zero sequence voltage derivative in high and low frequency band is proposed. The effectiveness of the method is verified by the examples from the aspects of fault closing angle, transition resistance.

Over current protection of distribution system with impact of solar and wind generation using DIgSIlent power factory

The utilization of renewable resources has been growing very fast worldwide recently to manage the increasing energy gap, but it also raises some challenges like protection issues, transient stability issues and security issues in the power system operation. Mainly, wind and solar photovoltaic renewable power generation sources are account for bulky renewable energy share. The transients in power systems including renewables are reduced and have recently attracted wide attention. The impact of renewables generation on power system transients should be effectively analyzed and evaluated to improve power system reliability, stability, operation and security. DIgSILENT Power Factory software is more powerful and useful for providing phasor of fundamental power frequency components better than other existing software’s; therefore, DIgSILENT Power Factory is proposed for modeling and analysis of the system.

Baseline for Split DC Link Design in Three-Phase Three-Level Converters Operating with Unity Power Factor Based on Low-Frequency Partial Voltage Oscillations

The study sets a baseline for split DC link capacitance values and voltage set points in three-phase three-level AC/DC (or DC/AC) converters operating with unity power factor. In order to equalize the average values of partial DC link voltages, the controller generates a zero-sequence containing DC components only while employing neither dedicated DC link capacitance balancing hardware nor high-order zero-sequence component injection. Such a baseline is required in order to evaluate the effectiveness of different DC link capacitance reduction methods proposed in the literature. Unlike most previous works, utilizing neutral point current based on cumbersome analytical expressions to determine neutral point potential oscillations, the instantaneous power balance-based approach is employed in this paper, resulting in greatly simplified and more intuitive expressions. It is demonstrated that while the total DC link voltage is low-frequency ripple-free under unity power factor balanced AC-side operation, split DC link capacitors absorb triple-fundamental frequency power components with one-sixth load power magnitude. This yields significant opposite phase partial voltage ripples. In such a case, selection of DC link capacitances and voltage set points must take into account the expected values of AC-side phase voltage magnitude and split DC link capacitor voltage and current ratings. Simulation and experimental results validate the proposed methodology by application to a 10 kVA T-type converter prototype.

Impact of Gonadectomy on Sex‐Selective Dysregulation of Cardiovascular Function Resulting From In UteroExposure to Dexamethasone

Prenatal insults leading to increased fetal glucocorticoid exposure can sex‐selectively impact cardiovascular function in adulthood. In support of this, we have shown that when pregnant rat dams are treated with the glucocorticoid, dexamethasone (DEX), for the last 4 days of gestation, female‐specific changes resulting in enhanced pressor and heart rate (HR) responses to stress occur in adult offspring. Moreover, we demonstrated that females exposed to DEX in uteroshow altered autonomic function compared to vehicle‐exposed females. This is characterized by a reduced high frequency (HF) power component of heart rate variability (HRV) in DEX‐exposed rats, suggesting a lower reliance on parasympathetic drive. The present study evaluated the degree to which the sex‐specific changes in autonomically‐driven cardiovascular responses are due to activational effects of gonadal steroid hormones. Pregnant dams were administered DEX (0.4mg/kg per day, s.c.) or vehicle on gestation days 18‐21. This resulted in a significant reduction in birthweight in DEX‐exposed males and females. At 8 weeks, rats underwent a gonadectomy (GDX) or sham surgery, or remained intact, and at 10 weeks rats were instrumented with radiotelemetric transmitters for direct recording of arterial pressure, HR, and HRV in conscious, freely moving male and female rats. At 11‐12 weeks rats were placed in a restraint tube for 20 minutes, followed by a 3‐hour recovery period, to assess whether GDX alters the sex‐specific stress responses in DEX‐exposed offspring. Restraint‐stress testing was performed on diestrus in intact and sham females, and absence of cycling in GDX females was confirmed via cytological analysis. We demonstrate that intact females, but not males, that were exposed to DEX in utero exhibit an exaggerated pressor response to restraint, as compared to vehicle‐exposed females. We found that GDX did not alter stress‐responsive MAP in males regardless of prenatal treatment, suggesting testosterone does not play a role in acute cardiovascular stress responses in adult rats. In vehicle‐exposed females, when compared to intact, both sham and GDX surgery resulted in an exaggerated pressor response to restraint. However, in females that were prenatally exposed to DEX, there was no difference in the pressor response to restraint between intact, sham, and GDX rats. This suggests that the exaggerated pressor response observed in DEX females compared to males is not due to activational effects of estradiol. GDX was shown to have opposing effects on HRV in males and females, with no influence of prior DEX. In females, GDX resulted in a tendency toward reduced HF (p=0.065) and low frequency (LF, p=0.074) power component of HRV, whereas males showed a significant increase in HF (p=0.044) and a tendency toward increased LF (0.051). Taken together, activational effects of gonadal steroids appear to impact HRV, but not acute cardiovascular responses to stress. It may be that gonadal steroids act at an organizational level to mediate the sex difference observed in rats exposed to DEX in utero. Future studies to identify the mechanisms by which prenatal dexamethasone produce long‐term changes in cardiovascular function will be important for better understanding the sex‐specific consequences of prenatal programming over the lifespan.

Transformerless Grid Connected Control of Wind Turbine Based on H-MMC

A high-power wind turbine has low rotational speed and a relatively low terminal voltage level. Thus, the wind energy conversion system (WECS) is commonly connected to the grid by an isolated boost transformer, which increases costs and room greatly. In this article, the hexagonal modular multilevel converter (H-MMC) is applied so that the high-power wind turbine can be directly connected to the medium-voltage ac grid. It has the advantages of transformerless grid connection and low ripples of capacitor voltages. As the bridge arm voltage of H-MMC contains both the low-frequency component induced by a wind turbine and the power frequency component induced by the grid, the voltage ripples of submodules (SMs) are reduced. Due to the large differences in the voltage level between the wind turbine and the grid, the low-amplitude-modulation voltage of the wind turbine side is easily obliterated by the high-amplitude-modulation voltage of the grid side, which will cause distortion of the bridge arm current. Therefore, auxiliary SMs with variable reference voltage are adopted to improve the tracking accuracy. The MATLAB/Simulink simulation and the RT-LAB hardware-in-the-loop experimental results verify the feasibility of the proposed topology and the effectiveness of the control strategy.

Brain-Heart Link in Schizophrenia: Cognitive Inhibitory Control Deficit in Patients Is Specifically Related to Parasympathetic Dysregulation.

BackgroundThis study examined the connection between two prominent deficits in schizophrenia: the deficit in parasympathetic regulation and the deficit in cognitive inhibitory control, within the framework of the Neurovisceral Integration Model (NIM).Study DesignThirty healthy controls and 30 patients with schizophrenia performed the internationally standardized antisaccade protocol while their electrocardiographic data were recorded. The interaction between the group, the cognitive inhibitory control as measured with error rate (ER) in the antisaccade task and parasympathetic activity as measured with the High Frequency power component of Heart Rate Variability (HF-HRV) was tested.Study ResultsFindings confirmed that decreased HF-HRV was specifically related to increased ER in patients with schizophrenia. In contrast, patient deficits in other oculomotor function measures such as reaction time and reaction time variability related to volitional movement control and cognitive stability respectively were not linked to the deficit in parasympathetic regulation.ConclusionsOur study validates the theory behind NIM proposing that cognitive inhibition has common physiological substrate with parasympathetic regulation. Future research could test this brain-heart link in other mental disorders especially those with a prominent deficit in inhibitory cognitive function.

Experimental study on short-circuit current characteristics of a photovoltaic system with low voltage ride through capability under a symmetrical fault

Large number of photovoltaic (PV) power plants connected to a power grid can bring significant impacts to fault currents and the operation of protection systems. In this paper, short-circuit current characteristics of a PV system with low voltage ride through (LVRT) capability under a symmetrical fault is studied. PV system short-circuit experiments with different voltage dips at high and low output power levels are designed and conducted. The experiment results provide useful and valuable references for researches of PV system short-circuit current characteristics, modeling and PV system short-circuit current contribution to a power grid. Then, based on the experiment results, steady-state values, peak values and steady state short-circuit currents harmonic characteristics at different conditions are obtained and analyzed. It is found that, the DC component amplitude of a PV system short-circuit current is almost negligible compared with that of the power frequency component, which is different from conventional synchronous generator short-circuit current. Meanwhile, based on the LVRT control strategy and experimental results, the expression of steady-state short-circuit current RMS value is derived and verified, which provides an important basis for short-circuit current calculation of power system with large scale of PV plants.

Model parameter identification for scaled-down analogous HVDC transmission lines using broad spectral response analysis

Traditional analogous π-shape transmission line models are mainly designed based on the amplitude and phase response characteristics of the distributed-parameter transmission lines at the power frequency. It cannot be directly used to build analogous high-voltage direct current (HVDC) transmission line models because the signals in a wide frequency band from 0 Hz to 10 kHz are used to protect HVDC transmission lines instead of power frequency components. In this paper, a novel model parameter identification method for scaled-down analogous HVDC transmission lines is proposed based on broad spectral response analysis. The broad spectral responses of distributed parameter-based and π-shape lumped parameter-based models are analyzed and compared with each other first. And then frequency-dependent per-unit parameters of HVDC transmission lines are obtained and used to form a modified π-shape HVDC transmission line model with the same zero- and positive-sequence​ impedance as those of distributed parameter lines. The element parameters of the π-shape circuit model are identified optimally based on the weighted sum of the results at selected several frequencies in the broadband from 0 hertz to thousands of hertz. The simulation results show that the amplitude and polarity of the dc voltage and current in our scaled-down analogous lines are close to distributed parameter-based HVDC transmission lines once a fault occurred on the lines.

A novel MMC bridge arm protection based on sum current of upper and lower bridge arms

In flexible direct current transmission system, due to the nonlinear operation of the converter, the bridge arm current contains other components besides the power frequency component when a fault occurs at the outlet of DC line, which may lead to the calculated power frequency current amplitude greater than the setting value, and the existing bridge arm overcurrent protection will misoperate. In order to solve the problem, a novel converter bridge arm protection based on the sum current of upper and lower bridge arms is proposed. Firstly, the equivalent circuit of high voltage direct current system based on modular multilevel converter (MMC-HVDC) before blocking the insulated gate bipolar transistors (IGBTs) is established in the case of a bipolar short-circuit occurs at the outlet of DC line, the bridge arm current is deduced, and the influence factors and variation characteristics of each component in bridge arm current are studied. Secondly, the misoperation reasons of the existing overcurrent protection of converter bridge arms are analyzed. Finally, a novel MMC bridge arm protection based on the sum current of upper and lower bridge arms is proposed, and its action characteristics of the internal and external faults of the bridge arm are analyzed. To overcome the problem that the proposed protection cannot reflect the upper and lower bridge arms short-circuit, a supplementary criterion is proposed to identify this fault by measuring whether the upper bridge arm current and the lower bridge arm current are mainly power frequency components. The sum current protection and the supplementary criterion can reflect various faults in bridge arms, including the short-circuit between two bridge arms which can not be reflected by the existing bridge arm overcurrent protection, and they will not misoperate in the case of a fault occurs in DC line. The simulation results verifies the effectiveness of the proposed protection principle.

Effects of Alzheimer's disease of varying severity on cardiac and autonomic function.

Alzheimer’s disease (AD) is one of the most common neurodegenerative diseases in the elderly. The aim of this study was to explore the effects of AD on cardiac function and autonomic nervous function, and the feasibility of electrocardiogram (ECG) in monitoring the development of AD. APP/PS1 double transgenic mice were used in the Morris water maze (MWM) experiment to evaluate the changes of cognitive ability of AD mice, then the non-invasive ECG acquisition system was used and the changes of ECG intervals and heart rate variability (HRV) were analyzed. AD mice already had cognitive dysfunction at the age of 5 months, reaching the level of mild dementia, and the degree of dementia increased with the course of disease. There were no significant changes in ECG intervals in the AD group at each month. The mean square of successive RR interval differences, percentage of intervals >6 ms different from preceding interval, and normalized high frequency power component in the AD group were decreased and low-to-high frequency power ratio and normalized low frequency power component were increased. Combined with the results of the MWM, it was shown that the regulation mechanism of sympathetic and parasympathetic nerves in mice was already imbalanced in early stage AD, which was manifested as the increase of excessive activity of sympathetic nerves and the inhibition of parasympathetic activities. Therefore, ECG-based analysis of HRV may become a means of daily monitoring of AD and provide an auxiliary basis for clinical diagnosis.

Sugar‐Sweetened Soft Drink Consumption Acutely Modifies Cardiovascular Control in Healthy Adults

Long-term consumption of sugar-sweetened soft drinks is associated with an increased prevalence of cardiometabolic diseases. Previous reports demonstrate that consuming a bolus of fructose-sweetened water acutely increases blood pressure variability (BPV) and decreases spontaneous cardiovagal baroreflex sensitivity (cBRS) and heart rate variability (HRV). If caffeinated soft drinks containing high levels of fructose elicit similar responses is unknown. Objective Test the hypothesis that high-fructose corn syrup (HFCS) sweetened soft drink consumption increases BPV and decreases cBRS and HRV compared to water and artificially-sweetened (Diet) and sucrose-sweetened (Sucrose) soft drinks. Methods Twelve subjects (2 females; age 24 ± 4 y; body mass index: 24.1 ± 3.1 kg/m2) completed four randomized, double-blinded trials in which they drank 500 mL of water or commercially available soft drinks matched for taste and caffeine content (~77 mg). Subjects were not naïve to caffeine and consumed 346 ± 481 mL of soft drinks per week. We continuously measured beat-to-beat blood pressure (finger photoplethysmography) and R-R interval (ECG) before and 30 minutes after drink consumption during supine rest for 5 minutes during spontaneous and paced breathing (frequency of 15 breathes/minute). BPV was evaluated using standard deviation, average real variability, and successive variation methods for systolic and diastolic blood pressure. cBRS was assessed using the sequence method for up and down sequences. Overall cBRS was calculated as the average of up and down sequences. HRV was evaluated using the root mean square of successive differences in R-R interval (RMSSD) and the high frequency power component following power spectral density analysis (HF). Due to variation at baseline, data were analyzed as the magnitude of change (∆) from pre-drink consumption using a mixed-effects model with post hoc Sidak's test comparisons. Data are reported as mean ± SD. Results There were no differences between conditions for indices of BPV in standard deviation, average real variability, and successive variation during spontaneous and paced breathing (P≥0.07). Overall cBRS during spontaneous breathing was reduced in the HFCS (-3 ± 5 ms/mmHg) and Sucrose (-3 ± 5 ms/mmHg) trials compared to Water (+1 ± 5 ms/mmHg, P<0.03). Sucrose also elicited greater reductions in overall cBRS during spontaneous breathing compared to Diet (+1 ± 4 ms/mmHg, P=0.01) and HFCS was reduced during down sequences compared to Diet (-3 ± 5 vs. +2 ± 3 ms/mmHg, P=0.057). HFCS evoked greater reductions in RMSSD during paced breathing compared to Water (-26 ± 34 vs. +2 ± 26 ms, P<0.01), but not Diet (-11 ± 26 ms, P=0.43) nor Sucrose (-12 ± 11 ms, P=0.51). There were no differences in HF during paced breathing between HFCS and the other trials (Water: -408 ± 1178; Diet: -62 ± 1270; Sucrose: -871 ± 1549; HFCS: -155 ± 1505 ms2, P≥0.13). Conclusion These findings suggest that in healthy young adults, sugar-sweetened soft drink consumption acutely reduces cBRS and HRV but does not alter BPV.

Capacitors Voltage Ripple Complementary Control on Three-Level Boost Fed Single-Phase VSI With Enhanced Power Decoupling Capability

Power decoupling is always a strong desire for single-phase voltage source inverter (VSI) due to the inherent double-line (2ω) frequency ripple caused by the instantaneous power unbalance between dc- and ac-side. The existing solutions either apply a large capacitor or employ a small power converter to compensate it, which inevitably increases the system cost and control complexity. To overcome these drawbacks, this article performs the transient modeling analysis and it reveals that 2ω frequency power component in the converter achieves minimum value when the inductor current ripple is minimized. A novel capacitors' voltage ripple complementary control algorithm based on three-level boost fed single-phase VSI is proposed. By mitigating the 2ω power component from the inductor and redistributing the stored energy between two intermediate series-connected capacitors, the oscillating power is absorbed with notably eliminated input current ripple and significantly reduced dc-link voltage ripple. Thus, the good power quality of both dc- and ac-side is guaranteed. Furthermore, the total capacitance requirement is minimized under the given dc-link ripple tolerance without any more electric stress increment and lifetime reduction. Simulation and experiment results verify the theoretical analysis and proposed control method. It is promising in applications, where both input current ripple is strictly limited and ac output voltage quality is highly required with small dc-link capacitance.

Faulty Feeder Detection Method Based on VMD–FFT and Pearson Correlation Coefficient of Non-Power Frequency Component in Resonant Grounded Systems

Through analyzing the transient components and transient characteristics in transient zero-sequence current (TZSC), a novel fault feeder detection method based on the transient correlation of non-power frequency components (NPFCs) for the resonant grounded system is proposed. Firstly, using variational mode decomposition combined with fast Fourier transformation (VMD–FFT) to decompose the TZSC, by removing the power frequency components and noise signals, the transient NPFCs can be obtained. Secondly, to reflect the overall changing trend between faulty and healthy currents, the moving average filter is introduced to smooth the NPFCs; in this way, the fault transient features can be accurately revealed. Finally, the faulty feeder can be detected by comparing the threshold with the maximum difference value of comprehensive correlation coefficient of NPFCs. The detection results show that the proposed fault detection method can accurately select the faulty feeder; it is unaffected by fault resistances, fault phase angles, etc. Moreover, the detection method can resist noise interference.

Detection of arrhythmogenic substrate within QRS complex in patients with cardiac sarcoidosis using wavelet-transformed ECG.

Signal-averaged electrocardiography (SAECG) has been known to be useful for prediction of lethal ventricular arrhythmias (VA). However, this technique has limitations in patients with intraventricular conduction disturbance (IVCD), which is common in cardiac sarcoidosis (CS). Meanwhile, wavelet-transformed ECG (WTECG) has been reported to be useful for detecting arrhythmogenic substrate hidden within QRS complex. The objective of this study was to assess the utility of WTECG for detecting arrhythmogenic substrate in patients with CS. Forty-four CS patients including 18 patients with VA were retrospectively investigated. The parameters on the signal-averaged electrocardiography (SAECG) and the power of frequency components on WTECG were compared between VA group and non-VA group. Eighteen patients have VA (VT: n = 17, VF: n = 1). LP were detected in 17 in VA group and 24 in non-VA group. WTECG showed that high-frequency components (HFC; 80-150Hz) were developed in VA group. Peak power value at 150Hz (P150) was significantly higher in VA group than that in non-VA group (442.9 ± 160.2 vs 316.7 ± 100.8, p = 0.006). The receiver operating characteristic (ROC) curve analysis showed an optimal cutoff point of 336 of P150 for detecting patients with VA, with 82.4% sensitivity, 61.5% specificity, and area under the curve of 0.74 (95% confidence interval [CI] 0.59-0.89). WTECG may be useful for detecting CS patients who are prone to VA.

Using a Supercapacitor to Mitigate Battery Microcycles Due to Wind Shear and Tower Shadow Effects in Wind-Diesel Microgrids

Wind shear and tower shadow effects generate severe fluctuations on the generated power of wind turbines (WTs). Consequently, in WT-integrated microgrids (MGs) with battery energy storage, these power fluctuations can generate battery microcycles that can significantly reduce the battery’s lifetime. In this paper, the impact of battery microcycles on battery lifetime is investigated and a method that uses a hybrid supercapacitor-battery energy storage system to mitigate these microcycles in a wind-diesel microgrid is proposed. The design, power allocation strategy, and control of the power converters are discussed; the supercapacitor size is determined based on the decomposition of frequency components of the WT output power, using discrete Fourier transform to appropriately mitigate the battery microcycles. The components of the MG, wind shear, and tower shadow effects are modeled in detail using MATLAB/Simulink, TurbSim, AeroDyn, and FAST software tools. Finally, the performance of the proposed method is investigated and verified in simulation, considering two case studies where either battery-only or battery-supercapacitor are used. In addition, a cost-benefit analysis of the proposed system is given. The results show that the proposed method can appropriately mitigate the battery microcycles, which can result in increasing battery lifetime and reducing the total system costs.

An On-line Diagnosis Method of Broken Rotor Bars Fault in Motor of Aerospace Surveying Vessel via Salient Characteristic Residual Signal from Dynamic Model

Diagnosis of broken rotor bar fault in induction motors is a hot research focus in recent years. The most common method of diagnosis of this fault is to analyse the spectral characteristics of stator current. However the characteristic frequencies are too close to both sides of power frequency and usually covered by it in early failure. To overcome this limitation, this paper presents a method by introducing a dynamic model based on field-oriented control (FOC), which was widely applied in control. The FOC technique is modified to generate an estimated stator current signal in a little computation. The residual signal of stator current is produced by comparing the measured one and the estimated one as the motor running. The result of simulation shows that power frequency component is greatly reduced and the feature of fault is more significant than the measured current signal.