Donald M. Hepburn

A Methodology for Optimization of Power Systems Demand Due to Electric Vehicle Charging Load

This paper presents a methodology of optimizing power systems demand due to electric vehicle (EV) charging load. Following a brief introduction to the charging characteristics of EV batteries, a statistical model is presented for predicting the EV charging load. The optimization problem is then described, and the solution is provided based on the model. An example study is carried out with error and sensitivity analysis to validate the proposed method. Four scenarios of various combinations of EV penetration levels and charging modes are considered in the study. A series of numerical solutions to the optimization problem in these scenarios are obtained by serial quadratic programming. The results show that EV charging load has significant potential to improve the daily load profile of power systems if the charging loads are optimally distributed. It is demonstrated that flattened load profiles may be achieved at all EV penetration levels if the EVs are charged through a fast charging mode. In addition, the implementation of the proposed optimization is discussed with analyses on the impact of travel pattern and the willingness of customers.

Second generation wavelet transform for data denoising in PD measurement

Detection and diagnosis of partial discharge (PD) activity has been widely adopted in electrical plant condition monitoring. Analysis and detection of PD in practical applications is often hampered by noise in the signal. Recent research has shown that the discrete wavelet transform (DWT) is effective in extracting PD pulses from severe noise. One disadvantage, however, is that DWT does not reproduce accurate PD pulse magnitude and pulse shape after thresholding in the presence of strong noise. This paper presents the application of the second generation wavelet transform (SGWT), as an improved algorithm, to extraction of PD pulse from electrical noise. The paper begins with the description of the fundamental theory and structure of SGWT analysis and comparisons with DWT. The method is then applied to both simulated and real world PD data. Results prove that SGWT can significantly improve the effectiveness of PD denoising.

Application of K-Means method to pattern recognition in on-line cable partial discharge monitoring

On-line Partial Discharge (PD) monitoring is being increasingly adopted in an effort to improve asset management of the vast network of MV and HV power cables. This paper presents a novel method for autonomous recognition of PD patterns recorded under conditions in which a phase-reference voltage waveform from the HV conductors is not available, as is often the case in on-line PD based insulation condition monitoring. The paper begins with an analysis of two significant challenges for automatic PD pattern recognition. A methodology is then proposed for applying the K-Means method to the task of recognizing PD patterns without phase reference information. Results are presented to show that the proposed methodology is capable of recognising patterns of PD activity in on-line monitoring applications for both single-phase and three-phase cables and is also effective technique for rejecting interference signals.

Fault location and diagnosis in a medium voltage EPR power cable

This paper presents a case study on fault location, characterization and diagnosis in a length of shielded 11 kV medium voltage ethylene-propylene rubber (EPR) power cable. The defect was identified on-site as a low resistance fault occurring between the sheath and the core. A 43 m section was removed for further analysis. The fault resistance was characterized and the location of the defect pinpointed to within a few cm using a combination of time-difference-of-arrival location and infra-red imaging. A combination of X-ray computed tomography, scanning electron microscopy and energy dispersive X-ray spectroscopy were then applied to characterize any abnormalities in the dielectric surrounding the breakdown region. A significant number of high density contaminants were found to be embedded in the dielectric layer, having an average diameter of the order of 100 μm, a maximum diameter of 310 μm and an average density of 1 particle per 2.28 mm3. Scanning electron microscopy and energy-dispersive X-ray spectroscopy were used to determine the geometry and elemental composition of some initial contaminant samples. It was concluded that contamination of the EPR layer, combined with an observed eccentricity of the cable¿s core and sheath resulting in a reduced insulation gap, may have led to an electric field concentration in the region of the defect sufficient to initiate breakdown. Preventative strategies are discussed for similar families of cables, including more stringent dielectric testing requirements at the manufacturing stage and PD monitoring to detect incipient failure.

Identification of Multiple Defects in Solid Insulation Using Combined RF and IEC60270 Measurement

Using an integrated measurement system, partial discharge activity has been recorded simultaneously on a pulse-by-pulse basis in terms of radiated radio-frequency (RF) pulse energy and the apparent charge measured according to IEC60270. Plotting the energy of the RF pulses against the corresponding apparent charge produces a correlation that will be sensitive to the shape of the underlying current pulse, which would be expected to vary depending on the type and severity of the defect. This paper presents combined measurements for several resin insulation samples containing a number of voids of known dimensions. Results indicate that using a combined measurement strategy, it may be possible to discriminate between discharge activity occurring in each void based on the correlation between apparent charge and RF energy.

Statistical Quantification of Voltage Violations in Distribution Networks Penetrated by Small Wind Turbines and Battery Electric Vehicles

Voltage violation tends to be one of the dominant constraints or critical factors that limit the penetration of small wind turbines (SWTs) and battery electric vehicles (BEVs) in distribution networks. To quantify the voltage violation, a statistical time series based approach is developed in this paper. The daily time varying characteristics of electric loads, wind speeds and BEV charging loads have been taken into consideration in a statistical manner. The method has been compared with the conventional time series approach. It is proven that the proposed methodology, while providing a global picture on voltage violations, can potentially be used for fast evaluation of the probability of a voltage violation occurring in a network. The methodology has been applied to an example distribution network. Results show that the proposed methodology can reduce the computational requirement by over 98%, while the difference between the results obtained using the proposed method and applying the conventional time series approach is within 12.5%.

On-line PD detection and localization in cross-bonded HV cable systems

This paper addresses the detection and localization of partial discharge (PD) in crossbonded (CB) high voltage (HV) cables. A great deal has been published in recent years on PD based cable insulation condition monitoring, diagnostics and localization in medium voltage (MV) and high voltage (HV) cables. The topic of pulse propagation and PD source localization in CB HV cable systems has yet to be significantly investigated. The main challenge to PD monitoring of CB HV cables is as a result of the interconnectedness of the sheaths of the three single phase cables. The cross-bonding of the sheaths makes it difficult to localize which of the three phases a PD signal has emanated from. Co-axial cables are used to connect cable sheaths to cable link boxes, for ease of installation and protection against moisture. A second challenge is, therefore, the coupling effect when a PD pulse propagates in HV cable joints and the co-axial cables, making PD detection and localization more complex. The paper presents experimental investigations into PD pulse coupling between the cable center conductor and the sheath and the behavior of PD pulse propagation in CB HV cables. It proposes a model to describe PD pulse propagation in a CB HV cable system to allow monitoring and localization, and also presents the knowledge rules required for PD localization in CB HV cable systems.

An Algorithm for Indentifying the Arrival Time of PD Pulses for PD Source Location

In terms of locating the source of partial discharge, transient earth voltage (TEV) detection is well recognised to have advantages over electrical methods. A variety of sensors are suitable for on-line PD testing of outdoor equipment, including ultra-high frequency (UHF) and radio frequency (RF) antenna, transient earth voltage (TEV) sensors, acoustic emission (AE) sensors and high frequency current transformers (HFCT). Among these, UHF, TEV and AE are usually adopted to detect PD activity and to determine the partial discharge (PD) location. These three detection methods display similar response to PD activity. The main characteristic shown is multi-oscillation and gradual attenuation. To locate the source of a PD requires correlation of the PD pulse arrival times, accuracy of the location is determined by the ability to discriminate the difference in arrival time across the sensors. Unfortunately, since the UHF and TEV detection systems have higher sensitivity than others, the major problem faced in determining the arrival time of each pulse is the effect of interference and noise. The present paper proposes the use of discrete wavelet transform (DWT) to overcome the problems associated with noise in TEV measurement of PD in power plant. The method, which applies an effective denoising algorithm developed by the present authors to extract TEV signal from noise and identify the arrival time, is proved to be effective in on-site tests.

Partial discharge pulse propagation in power cable and partial discharge monitoring system

Partial discharge (PD) based condition monitoring has been widely applied to power cables. However, difficulties in interpretation of measurement results (location and criticality) remain to be tackled. This paper aims to develop further knowledge in PD signal propagation in power cables and attenuation by the PD monitoring system devices to address the localization and criticality issues. As on-line or in-service PD monitoring sensors commonly comprise of a high frequency current transformer (HFCT) and a high-pass filter, the characteristics of detected PD pulses depend on the attenuation of the cable, the HFCT used and the filter applied. Simulation of pulse propagation in a cable and PD monitoring system are performed, based on analyses in the frequency domain using the concept of transfer functions. Results have been verified by laboratory experiments and using on-site PD measurements. The knowledge gained from the research on the change in pulse characteristics propagating in a cable and through a PD detection system can be very useful to PD denoising and for development of a PD localization technique.

Comparison of PD characteristics and degradation in PET insulation with vented and unvented voids

Partial Discharge (PD) results from faults in power insulation systems and exacerbates failure. It is known that the presence of voids in solid and liquid insulation give rise to PD. Factors which control the PD activity include pressure and type of gas present. When PD occurs in insulation, pressure is created and gaseous products changed due to the energy input. A series of experiments is being carried out on artificial voids, created from layered sections of polymer. One set of samples has a void inside the polymer with no access to the outer atmosphere; a second set of samples is created with a vent connecting the void to the outer atmosphere. Both sample sets are stressed at the same electrical conditions for same period of time. Investigation of the physical and chemical differences and PD patterns recorded follows.