In the new era of increasingly electric aircraft, the need for reliable and safe electrical systems is more important than ever. In addition, the wide-scale adoption of dc distribution is considered a key enabling technology for more efficient aircraft operation. In this context, arc fault detection devices (AFDDs) have become a topic of interest for the aviation industry with ongoing research to characterize the impact and adequately protect against severe dc series arc faults. Although dc arc faults have been widely investigated for utility applications (such as solar photovoltaic systems), direct adoption of current practices for validating arc detection devices is not straightforward due to the distinct aircraft operating environment. This article provides a first-of-its-kind landscaping exercise of published series arc fault testing based on factors associated with aircraft applications that have the potential to influence the arc characteristics. In addition, an appraisal and associated gap analysis of published arc test platforms is undertaken in order to assess their suitability to support in-depth testing of the impact and mitigation of series arcs within future aircraft dc electrical systems and identify future testing needs, in particular, to better facilitate a comprehensive performance validation of new AFDDs.

Electric arcing due to contact interruption between the pantograph and the overhead contact line in electrified railway networks is an important and unwanted phenomenon. Arcing events are short-term power quality disturbances that produce significant electromagnetic disturbances both conducted and radiated as well as increased degradation on contact wire and contact strip of the pantograph. Early-stage detection can prevent further deterioration of the current collection quality, reduce excessive wear in the pantograph-catenary system, and mitigate failure of the pantograph contact strip. This paper presents a novel arc detection method for DC railway networks. The method quantifies the rate-of-change of the instantaneous phase of the oscillating pantograph current signal during an arc occurrence through the Hilbert transform. Application of the method to practical pantograph current data measurements, demonstrates that phase derivative is a useful parameter for detecting and localizing significant power quality disturbances due to electric arcs during both coasting and regenerative braking phases of a running locomotive. The detected number of arcs may be used to calculate the distribution of the arcs per kilometre as an alternative estimation of the current collection quality index and consequently used to assess the pantograph-catenary system performance. The detected arc number may also contribute to lowering predictive maintenance costs of pantograph-catenary inspections works as these can be performed only at determined sections of the line extracted by using arcing time locations and speed profiles of the locomotive.

Railway electrical networks rated at 25 kV 50 Hz are characterised by significant levels of voltage and current harmonics. These frequency components are also time varying in nature due to the movement of trains and changing operational modes. Processing techniques used to evaluate harmonic results, although standardised, are not explicitly designed for railway applications, and the smoothing effect that the standard aggregation algorithms have on the measured results is significant. This paper analyses the application accuracy of standardised power quality (PQ) measurement algorithms, when used to measure and evaluate harmonics in railway electrical networks. A shorter aggregation time interval is proposed for railway power quality measurement instruments, which offers more accurate estimated results and improved tracking of time varying phenomena. Harmonic active power present in railway electrical networks is also evaluated in order to quantify the impact it has on the energy accumulated by electrical energy meters installed on-board trains. Analysis performed on 12 train journeys shows significant levels of non-fundamental active power developed for short periods of time. As an energy meter will inadvertently absorb the financial cost of non-fundamental energy produced by other trains or other external power flows, results are provided to support recommendations for future standards to measure only fundamental frequency energy within train energy measurement meters.

Pantograph arcing in electrified railway systems not only reduces the power collection quality of a locomotive but can also damage pantograph strips and overhead lines (OHLs). Most research detects pantograph-to-OHL arcs based on onboard voltage/current measurements, pantograph cameras, and so on. The use of onboard voltage/current data, though being cost-effective, rarely reflects arc locations along OHLs. This article develops an arc positioning method, which matches the position-dependent resonant frequency (RF) of an OHL with the RF extracted from voltage measurements in a pantograph arc event. A particular 20-km DC railway line supplied by two substations is first modelled in MATLAB/Simulink, with the model effectiveness being assessed based on voltage measurements in an arc event. Then, the OHL-related RFs estimated by the model are validated by the Tableau formula and discussed alongside impacts on RFs based on line models, locomotive locations, and line lengths. These evaluations permit the generation of an RF curve that links OHL-related RFs with arc locations. The arc positioning method is tested based on the pantograph arc events presumed at various positions along the 20-km line, showing errors within 0.2 km at certain locations. The ability to determine arc locations will permit periodic inspections to be performed on the determined line sections.

Power quality (PQ) phenomena characterizing the voltage and current signals of railway electricity networks differ from those present in transmission and distribution electricity grids. Presently, there are no standardized procedures focused on PQ measurement techniques explicitly for railway applications. This paper evaluates whether the standard power quality measurement algorithms used in monitoring 50 Hz electrical grids are sufficient for an accurate evaluation and classification of PQ parameters of voltage dips, swells and interruptions present in 25 kV AC railways. An algorithm is presented to better characterize different types of interruption, distinguishing between causes due to network configuration or by other factors. For voltage dips and swells it is also shown that a smaller window size (less than 1 cycle) produces a more accurate estimate of the disturbance magnitude and duration. The two methods are verified against recorded signals of pantograph voltage and current. Recommendations are therefore provided for PQ measurement algorithms for AC railways.

During the last few years, the accuracy of static electricity meters (SEM) has been questioned. Significant metering deviations with respect to a reference meter have been observed at customer premises, and laboratory experimental tests results support such findings. The root cause of such errors remains unknown, as there are multiple elements that could affect the accuracy of electricity meters. Furthermore, standard compliant meters exposed to distorted signals may produce negligible, positive or negative relative error depending on the instrument design. Distorted current signals with fast amplitude transitions have produced the highest error in SEMs reported in the literature. In this paper, the accuracy of an energy metering Integrated Circuit (IC) is evaluated beyond the limits of the standards requirements employing a selection of distorted signals from the standards, real-world captured signals and a set of waveforms designed to test the IC under fast changing currents conditions, which are representative of the waveforms resulting from power electronic devices. The experimental results reveal an accuracy boundary imposed by Gibb’s phenomenon for fast changing current signals and a strong relationship between the IC’s measurement error and two key parameters of the measured waveform: signal slope and phase angle. This paper therefore provides a methodology for the comprehensive analysis of SEMs in future power systems which are dominated with power electronic-controlled electrical demand and contributes to the search for the root cause of error in SEMs exposed to distorted waveforms.