Yljon Seferi

The ambitious roadmap for a sustainable transport system adopted by the European Commission (EC) by 2050 includes the deployment of an extensive Electric Vehicle Charging Stations (EVCSs) infrastructure, which introduces significant challenges for distribution power grids. High power demand, particularly from fast-charging systems, may lead to network overloading and voltage unbalance. In addition, recent measurement campaigns highlight substantial changes in grid impedance and the emergence of resonance phenomena, together with the injection and propagation of high-frequency conducted disturbances. These effects extend over a wide frequency range, up to several hundreds of kHz, causing degradation, aging and malfunction of network assets, in particular Power Line Communications. This paper provides a comprehensive and updated review of the impact of EVCSs on electrical grids, covering power flow, power quality, stability, and impedance-related interactions. Particular attention is given to the role of power-electronic converters, high-frequency emissions, and the associated challenges in measurement and standardization. The analysis highlights that EVCS integration fundamentally alters the nature of electrical loads, requiring new approaches for grid planning, monitoring, and regulation. The study identifies key research gaps and outlines future directions to ensure the reliable and sustainable integration of electromobility into modern power systems.

The ambitious roadmap for a sustainable transport system adopted by the European Commission (EC) by 2050 includes the deployment of an extensive Electric Vehicle Charging Stations (EVCSs) infrastructure, which introduces significant challenges for distribution power grids. High power demand, particularly from fast-charging systems, may lead to network overloading and voltage unbalance. In addition, recent measurement campaigns highlight substantial changes in grid impedance and the emergence of resonance phenomena, together with the injection and propagation of high-frequency conducted disturbances. These effects extend over a wide frequency range, up to several hundreds of kHz, causing degradation, aging and malfunction of network assets, in particular Power Line Communications. This paper provides a comprehensive and updated review of the impact of EVCSs on electrical grids, covering power flow, power quality, stability, and impedance-related interactions. Particular attention is given to the role of power-electronic converters, high-frequency emissions, and the associated challenges in measurement and standardization. The analysis highlights that EVCS integration fundamentally alters the nature of electrical loads, requiring new approaches for grid planning, monitoring, and regulation. The study identifies key research gaps and outlines future directions to ensure the reliable and sustainable integration of electromobility into modern power systems.

In modern power systems, monitoring and control applications are subject to stringent requirements in terms of responsiveness and accuracy. The reference technology in this sense is represented by the Phasor Measurement Units (PMUs) which produce time-stamped measurements of synchrophasor, frequency, and rate-of-change-of-frequency. The delay introduced by different PMU acquisition and processing stages can be characterized in laboratory controlled conditions as per the relevant standards. This information, however, is hard to be integrated into online routines without prior knowledge of the system operating condition. To address this issue, this paper presents a PMU prototype which implements an online trust-worthiness metric, which can be used to preliminarily assess the measurement accuracy and track the settling time due to external disturbances. The results confirm the robustness of the proposed approach and its potential applicability to an emerging use case involving the online estimation of power system inertia level.

Decarbonizing rail transport in response to global warming is fundamental to achieving a net zero transportation system. Along with increased passenger mobility and network electrification initiatives, significant connectivity between the train and infrastructure is needed to underpin operational communications and safety, information exchange, and customer comfort. Track‐to‐train data connectivity solutions that are being proposed require a source of electrical power available at regular locations. This source of electricity is not always readily accessible along the railway track, even when the traction systems are powered by electricity. For low‐power and low‐voltage (LV) applications, deriving electric power from the overhead catenary system is costly, potentially bulky, complicated, or not even technically feasible with present conventional or innovative power derivation methods. This paper investigates the technical feasibility and applicability of the capacitive divider technology in electrified AC traction systems and proposes a power supply solution that could utilize the in situ 25 kV AC overhead line to supply low‐power LV applications. A prototype has been developed, and the principles of deriving active power up to 47 W at 108 V have been demonstrated through laboratory experiments and simulations. The prototype has a relatively low complexity, does not require any auxiliary power supply circuitry, has relatively a lower cost compared to other solutions, and can be constructed rapidly due to the availability of off‐the‐shelf components. The proposed power supply solution has the potential to support data connectivity applications thus becoming an enabler of the information exchanged between train and infrastructure.

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.

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.

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.

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.

This paper describes the measurement system used to monitor the energy dissipated in the braking rheostat resistors on board a locomotive operating in a DC rail system. The aim of the activity is the accurate estimation of the energy, nowadays wasted, that could be recovered thanks to the implementation of the smart grid paradigm in the DC railway system. To provide metrological reliability to the measured wasted energy, a preliminary identification and estimation of the uncertainty is provided. The target uncertainty of the measurements is 1 %.