Federico Carere

Deep subsurface defect detection (due to the so-called skin effect) and sensitivity in the detection of any orientation defects remain two of the main challenges in Eddy Current Testing (ECT). Although low-frequency excitation increases the penetration depth of the induced eddy currents, it also reduces the intensity of the generated magnetic field, significantly degrading the inspection capability. Rotating eddy current probes overcome the dependence on defect orientation, but their performance remains limited for deep subsurface defects. This paper proposes a ferrite-core four-quadrant probe that combines orientation-independent inspection with magnetic flux concentration provided by ferrite cores integrated inside the excitation coils. The proposed probe is first investigated through finite element analysis and then experimentally validated through a direct comparison with the corresponding air-core configuration. Both numerical and experimental results demonstrate that the ferrite-core configuration systematically enhances the inspection capability, with improvements ranging from approximately 22% for shallow defects to over 100% for the deepest investigated ones. Moreover, the proposed probe successfully detects defects buried up to 6 mm below the inspected surface, whereas the corresponding air-core configuration fails under the same operating conditions. These results demonstrate the potential of ferrite-core integration for extending the applicability of REC probes to deep subsurface inspections.

This study investigates the impact of monitoring infrastructure characteristics (specifically sensor penetration and measurement accuracy) on the effectiveness of voltage regulation and congestion management within distribution networks. As distribution system operators transition toward active management, the integration of Distributed renewable Generation (DG) and demand response introduces significant physical and cyber-physical uncertainties. To address these challenges, a smart grid service framework has been employed to optimize flexibility resources from aggregated users and DG inverters through a genetic algorithm. The framework was tested on the IEEE European Low Voltage Test Feeder across various scenarios defined by distributed monitoring systems’ penetration and their measurement accuracy. Results show that sensor penetration has a dominant impact: increasing monitoring coverage from 0% to 100% raises the percentage of cases with fewer than one residual congestion from 46.2% to 91.9% (sensors with an accuracy class of 2%), reaching 97.9% with an accuracy class of 0.5%, while voltage violations are eliminated under full monitoring. These findings suggest that widespread sensor deployment, with a suitable measurement accuracy, is a fundamental prerequisite for reliable and efficient smart grid operation.

The growing adoption of electric vehicles (EVs) is driving the demand for public charging infrastructure, including ultrafast charging stations (UFCS) with power ratings exceeding 100 kW. However, the rapid expansion of public charging infrastructure necessitates appropriate network reinforcements and strategic development plans from grid operators. In this context, this paper provides an analysis of the impact of UFCS on existing sub-transmission and distribution networks. The study employs a methodology to assess hosting capacity and grid reinforcements in relation to UFCS, validating the results against stochastic variations in UFCS power demand. The research evaluates the effects of widespread UFCS deployment on both an existing distribution network (DN) and a sub-transmission network (SN), examining three distinct electric mobility development scenarios. The findings reveal that public charging infrastructure could significantly increase the load on distribution networks, necessitating the identified grid reinforcements to ensure secure grid operation. In the case of the SN, the results indicate that the current hosting capacity is sufficient to accommodate the medium-term development of public charging infrastructure.

The article introduces a novel four-coil probe designed for eddy current (EC) nondestructive testing (NDT) on conductive materials. The key innovation lies in its capability to identify small surface and subsurface cracks regardless of their orientation. This is achieved through a suitable probe developed using two pairs of exciting coils that allow to generate two orthogonal magnetic fields. Using two excitation currents with an amplitude modulation approach, a rotation of the ECs induced in the conductive sample is obtained. This novel approach ensures the effective detection of deep and arbitrarily oriented cracks. Both numerical tests and experimental evaluations were employed to assess the performance of the proposed probe. The probe’s effectiveness was particularly observed in detecting a buried crack measuring 5 mm in length, 1 mm in height, and 0.1 mm in thickness at depths up to 3 mm in an aluminum plate. The results demonstrated the robustness of the probe’s detection capability, affirming its potential as a reliable tool for NDT in industrial applications.

The increasing penetration of distributed generation (DG) across power distribution networks (DNs) is forcing distribution system operators (DSOs) to improve the voltage regulation capabilities of the system. The increase in power flows due to the installation of renewable plants in unexpected zones of the distribution grid can affect the voltage profile, even causing interruptions at the secondary substations (SSs) with the voltage limit violation. At the same time, widespread cyberattacks across critical infrastructure raise new challenges in security and reliability for DSOs. This paper analyzes the impact of false data injection related to residential and non-residential customers on a centralized voltage regulation system, in which the DG is required to adapt the reactive power exchange with the grid according to the voltage profile. The centralized system estimates the distribution grid state according to the field data and provides the DG plants with a reactive power request to avoid voltage violations. A preliminary false data analysis in the context of the energy sector is carried out to build up a false data generator algorithm. Afterward, a configurable false data generator is developed and exploited. The false data injection is tested in the IEEE 118-bus system with an increasing DG penetration. The false data injection impact analysis highlights the need to increase the security framework of DSOs to avoid facing a relevant number of electricity interruptions.