Pulong Geng

A novel dual closed-loop control scheme based on repetitive control for grid-connected inverters with an LCL filter

Grid-connected inverters with LCL filters need high steady-state control accuracy, fast dynamic response performance, and strong robustness to guarantee the power quality. However, there are many problems in traditional control strategies that restrict improvements to control system performance, such as poor dynamic performance of traditional single-repetitive control, large ripples, low steady-state accuracy of inverter current feedback based repetitive dual-loop control or grid-current feedback based single-loop proportional-integral control. In this paper, a novel dual closed-loop repetitive control strategy based on grid current feedback is proposed for single-phase grid-connected inverters with LCL filters. The proportional-integral inner loop is stabilized by using an inherent one-beat delay achieved by digital controller. Based on the inner loop system, a detailed design scheme of a repetitive controller is presented, through which direct control of the grid current is realized, the reference is tracked perfectly to a zero phase shift, and high-attenuation gain is achieved in the high frequency range. In particular, the gird-voltage feed forward control and current reference feedforward control are adopted to suppress grid-voltage disturbance and increase dynamic tracking performance. Finally, the simulation and experimental results show that the proposed method has the advantages of high steady-state accuracy, fast dynamic response, and anti-disturbance ability.

Influence of cavities on the dielectric properties of Ethylene Propylene Rubber insulation

Cavities are one of the typical defects leading to the degradation of Ethylene Propylene Rubber (EPR) insulation in extruded power cables. It had been observed by previous experiments that ageing phenomena on the surface of dielectric bounded cavities (DBC) and electrode bounded cavities embedded in EPR insulation was different. The surface of DBC is corroded by partial discharges (PD) which leads to the decrease of surface conductivity. To describe this phenomena, it is essential to analyse the dielectric properties of EPR insulation. So this paper is concerned on the investigation of EPR dielectric behavior which involves permittivity and dissipation factor in frequency domain (0.01 Hz ~ 1 MHz). It has been found by the experiments that the dielectric loss of pure samples are increased with the increase of temperature in low frequency region. The real permittivity of pure EPR have the temperature dependence only in lower frequency region. The real parts of complex permittivity of samples with DBC and EBC is larger than that of EPR without cavities. Moreover, the dielectric loss of samples with DBC is more sensitive to frequency in low frequency region. Thus, the study of dielectric properties is effective for assessment of EPR insulation caused by cavities. The corrosion can be observed on the surface of DBC aging under AC voltage.

Influence of thermal aging on AC leakage current in XLPE insulation

Cross-linked polyethylene (XLPE) has been widely used as cable insulation material because of its excellent dielectric properties, thermal stability and solvent resistance. To understand the influence of thermal aging on AC leakage current in XLPE insulation, all XLPE specimens were aged in oven in temperature range from 120 °C to 150 °C, and a series of tests were conducted on these XLPE specimens in different aging stages to measure the characteristic parameters, such as complex permittivity, leakage current and complex dielectric modulus. In the experiments, the effects of thermal aging, temperature and frequency on the AC leakage current in XLPE insulation were studied by analyzing complex dielectric constant and dielectric relaxation modulus spectrum, the change of relaxation peak and activation energy. It has been found that the active part of leakage current increases sharply with the increase of aging degree, and the test temperature and frequency have an influence on AC leakage current but the in...

Fault pattern recognition method for the high voltage circuit breaker based on the incremental learning algorithms for SVM

In order to recognize faults of the high voltage circuit breaker (HVCB) in the whole fault state space precisely and minimize the impact of the lack of fault data on the accuracy of fault recognition, a method of fault recognition was proposed based on the incremental learning algorithm for SVM. Firstly, the incremental learning algorithm for SVM was analyzed theoretically, and the state monitoring variables were determined by the current signal and voltage signal of control unit and the vibration signal of the switching for HVCB. Based on the fault mechanism, the feature extraction method for the monitoring variables was proposed. Secondly, four common faults, including the spring loosening, the core jamming, the coil aging and the abnormal electrical power supply, were simulated. Then the fault feature was extracted, and the fault data samples as well as the incremental learning data samples were established. After training the feature variables based on the incremental learning algorithms for SVM, the fault recognition model was acquired and its accuracy was validated through exerting the new fault features into the model. Finally, it is shown that the incremental learning algorithms for SVM can be used to recognize the faults of HVCB effectively, and its recognition accuracy can be improved by continuous learning of the new samples.

Influence of temperature and frequency on leakage current of XLPE cable insulation

Crosslinked polyethylene (XLPE) with outstanding high temperature performance and electrical properties has been widely used as cable insulation. Leakage current of cable is the inevitable product in the process of electric energy transmission, and the gathering of leakage current is easy to cause gas combustion, explosion of the cap and other accidents. To understand the influence of temperature and frequency on the leakage current of cable, Novcontrol Broadband Dielectric Spectroscopy measurement system has been used to measure the dielectric spectroscope of XLPE samples in the temperature range from 20 °C to 200 °C and frequency range from 10−2 Hz to 105 Hz. In the experiments, the dependency of permittivity, conductivity and electric modulus on frequency and temperature has been conducted. By observing the dielectric spectrum, some variation rules of parameters could be found, for example, the real part of complex permittivity decrease repidly and dissipation factor decrease slowly with increasing frequency at higher temperature. The AC conductivity follows the Jonscher power law, which DC conductance region follows the Arrhenius rule. The dielectric dispersion phenomena can be also observed on the spectroscope of the electric modulus as well, the dielectric loss peak move to the higher frequency area with the increase of temperature. Finally, the mechanism and process of XLPE relaxation polarization were discussed, the contribution of relaxation polarization to leakage current and the generation of leakage current was explained. The results show that the leakage current of XLPE cable has a strong dependence on the temperature and frequency.

Analysis of partial discharge of spherical cavities in EPR at different frequency

Cavities are one of the typical defects resulting in partial discharges (PDs) in extruded power cables. This paper focuses on studying the PD characteristics of arbitrary dielectric bounded cavities and electrode bounded cavities embedded in EPR insulation, such as PD distribution, PD inception and extinction voltage, under different type of testing voltage. During the experiment, the applied voltage is sinusoidal waveform at frequencies of 20, 50 and 200 Hz and damped AC waveform at frequencies of 20, 50, 200 and 500 Hz. The amplitude of applied voltage, the peak value, is 1.25, 1.5 and 2 times of the amplitude of PD inception voltage (PDIV). The diameter of cavities is 1.2, 1.5 and 2.0 mm. A batch of five simples has been tested during PDIV test. Each sample has been tested five times so as to obtain accurate data. It has been found by the experiments that the PD inception voltage increases with increasing frequency of applied voltage. The symmetrical PDs distribution can be observed in the time lag. It seems that the PD distribution depends on the frequency. The maximum PD amplitude at higher frequency is slightly larger than at lower frequency. PD distribution spreads more widely at higher frequency. It is also found that the cavity diameter and the amplitude of applied voltage influence the frequency dependence of PD distribution. The speed of degradation of EPR insulation is related with the frequency of applied voltage. PDs can also corrode the surface of dielectric bounded cavities embedded in EPR insulation, whereas there is not obvious change on the surface of electrode bounded cavities.

A feature extraction and pattern recognition method of vibration signals of high voltage distribution equipment based on LabVIEW

Focusing on the non-stationary characteristics of mechanical vibration signals of high voltage distribution equipment, a novel feature extraction method of vibration signals was proposed based on a joint analysis of wavelet packet decomposition and reconstruction, Hilbert transform and normalized energy spectrum which all can be performed on the platform of LabVIEW. The signal was decomposed into finer bands by wavelet packet transform, then the signal envelope was extracted using Hilbert transform and the normalized energy spectrum can be got by calculating the energy of the envelope, the spectrum can be regarded as an eigen feature quantity of the distribution equipment diagnostic system. Simulation on the distribution equipment was conducted and vibration signals were collected in three different conditions of which are the normal condition, opening spring loose and friction in solenoid. The vibration signals were analyzed based on the characteristics of time-frequency and K-nearest neighbor algorithm for different conditions eigen quantity pattern recognition can be used to make a detailed analysis of the signals. Experiment results show that each element of the normalized energy spectrum vector of the normal signal is evenly distributed; while the elements of fault signal normalized energy spectrum vectors are remarkably varied. The 93.3% accuracy and fast recognition speed verify the feasibility of the mechanical fault diagnosis approach for high voltage distribution equipment.