Antenna deployment for the localization of partial discharges in open-air substations

Partial discharges are ionization processes inside or on the surface of dielectrics that can unveil insulation problems in electrical equipment. The charge accumulated is released under certain environmental and voltage conditions attacking the insulation both physically and chemically. The final consequence of a continuous occurrence of these events is the breakdown of the dielectric. The electron avalanche provokes a derivative of the electric field with respect to time, creating an electromagnetic impulse that can be detected with antennas. The localization of the source helps in the identification of the piece of equipment that has to be decommissioned. This can be done by deploying antennas and calculating the time difference of arrival (TDOA) of the electromagnetic pulses. However, small errors in this parameter can lead to great displacements of the calculated position of the source. Usually, four antennas are used to find the source but the array geometry has to be correctly deployed to have minimal errors in the localization. This paper demonstrates, by an analysis based on simulation and also experimentally, that the most common layouts are not always the best options and proposes a simple antenna layout to reduce the systematic error in the TDOA calculation due to the positions of the antennas in the array.Tests were done in the High-Voltage Research and Test Laboratory (LINEALT) at Universidad Carlos III de Madrid. This work has been partly funded by the Spanish Government through projects SI-DP (DPI2015-66478-C2-1), MIMOTEX (TEC2014-61776-EXP) and ELISA (TEC2014-59255-C3-3R)

Gated pipelined folding ADC based low power sensor for large-scale radiometric partial discharge monitoring

Partial discharge is a well-established metric for condition assessment of high-voltage plant equipment. Traditional techniques for partial discharge detection involve physical connection of sensors to the device under observation, limiting sensors to monitoring of individual apparatus, and therefore, limiting coverage. Wireless measurement provides an attractive low-cost alternative. The measurement of the radiometric signal propagated from a partial discharge source allows for multiple plant items to be observed by a single sensor, without any physical connection to the plant. Moreover, the implementation of a large-scale wireless sensor network for radiometric monitoring facilitates a simple approach to high voltage fault diagnostics. However, accurate measurement typically requires fast data conversion rates to ensure accurate measurement of faults. The use of high-speed conversion requires continuous high-power dissipation, degrading sensor efficiency and increasing cost and complexity. Thus, we propose a radiometric sensor which utilizes a gated, pipelined, sample-and-hold based folding analogue-todigital converter structure that only samples when a signal is received, reducing the power consumption and increasing the efficiency of the sensor. A proof of concept circuit has been developed using discrete components to evaluate the performance and power consumption of the system

Device-free Indoor WLAN Localization with Distributed Antenna Placement Optimization and Spatially Localized Regression

Wireless sensing is a promising technology for future wireless communication networks to realize various application services. Wireless local area network (WLAN)-based localization approaches using channel state information (CSI) have been investigated intensively. Further improvements in detection performance will depend on selecting appropriate feature information and determining the placements of distributed antenna elements. This paper presents a proposal of an enhanced device-free WLAN-based localization scheme with beam-tracing based antenna placement optimization and spatially localized regression, where beam-forming weights (BFWs) are used as feature information for training machine-learning (ML)-based models localized to partitioned areas. By this scheme, the antenna placement at the access point (AP) is determined by solving a combinational optimization problem with beam-tracing between AP and station (STA) without knowing the CSI. Additionally, we propose the use of localized regression to improve localization accuracy with low complexity, where classification and regression based ML models are used for coarse and precise estimations of the target position. We evaluate the proposed scheme effects on localization performance in an indoor environment. Experiment results demonstrate that the proposed antenna placement and localized regression scheme improve the localization accuracy while reducing the required complexity for both off-line training and on-line localization relative to other reference schemes.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Comparative study of AC and positive and negative DC visual corona for sphere-plane gaps in atmospheric air

Due to the expansion of high-voltage direct current (HVDC) power systems, manufacturers of high-voltage (HV) hardware for alternating current (ac) applications are focusing their efforts towards the HVDC market. Because of the historical preponderance of ac power systems, such manufacturers have a strong background in ac corona but they need to acquire more knowledge about direct current (dc) corona. Due to the complex nature of corona, experimental data is required to describe its behavior. This work performs an experimental comparative analysis between the inception of ac corona and positive and negative dc corona. First, the sphere-plane air gap is analyzed from experimental data, and the corona inception voltages for different geometries are measured in a high-voltage laboratory. Next, the surface electric field strength is determined from finite element method simulations, since it provides valuable information about corona inception conditions. The experimental data obtained are fitted to an equation based on Peek’slaw,whichallows determining the equivalence between the visual corona surface electric field strength for ac and dc supply. Finally, additional experimental results performed on substation connectors are presented to further validate the previous results by means of commercial high-voltage hardware. The results presented in this paper could be especially valuable for high-voltage hardware manufacturers, since they allow determining the dc voltage and electric field values at which their ac products can withstand free of corona when operating in dc grids.Peer ReviewedPostprint (published version