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Many citizens of European countries may soon experience a long and extensive blackout. The lack of predictability in the output of renewable energy sources, aggravating the problem of consistently matching supply with demand on electric grids, along with cyber-attacks or even worse unpredictable incidents in the electric grid are some factors that may mean a blackout is much more likely than in previous years. This paper covers the possibility of an extensive blackout in a country of the interconnected European electricity transmission system or, even worse, a blackout in a wide area of the European continent. The topic of this paper becomes even more important and timely given the energy crisis due to the war in Ukraine, which has made the possibility of a blackout in the winter of 2022–2023 high. First, the major European blackouts that occurred in the past 20 years are presented, examining their causes. On 8 January 2021, the European electricity grid was divided into two separate sections, with different frequencies; some additional scenarios are considered which, if they had happened, could have led to blackouts in some European countries or, even worse, a wide area of Europe. This work also examines how to avoid such an eventuality, as well as how European TSOs should react in case a blackout occurs. Focused on the fast and reliable supply of consumers after a blackout, a novel restoration strategy based on the A* Algorithm is presented. Its efficiency is validated in the IEEE-39 and IEEE-68 bus systems.

New methods for state estimation are required due to the complexity of the topology of transmission and distribution systems, and the predictability in the management of prosumer dispatch. This paper describes a pilot project in Greece that, in accordance with OneNet’s architecture, addresses the challenges of congestion and balancing management that system operators face due to the high penetration of renewable energy sources. The respective data requirements and the IT/OT environment are described, as well as the interconnections among the various modules and functionalities. Available resources of the grid’s flexibility are identified, and the implementation of an integrated monitoring system based on efficient forecasting of volatile generation and demand is addressed. Congestion management and frequency and voltage control are in the center of interest of the demonstrator where, in close collaboration with system operators, respective network models are being developed.

With the increase in the complexity of the topology of transmission and distribution systems, associated with the predictability in the management of the dispatch of prosumers, new techniques for state estimation, and application of metaheuristics are necessary. In the current work a pilot project in Greece that addresses the difficulties of congestion and balancing management that system operators face in the renewable energy sources era, in accordance with the OneNet’s architecture is described. Available resources of grid’s flexibility are identified, and the implementation of an integrated monitoring system based on weather conditions with an energy control and dispatch system in the Greek electricity grid is addressed. The document suggests that flexibility resources will derive through predictions that have been improved and efficient forecasts from increased spatial resolution Numerical Weather Predictions and integration of Artificial Intelligence preventing the power system of entering dangerous topological or operational states.

In the study of cosmic rays, the measurement of the energy spectrum of the primaries is one of the main issues and provides fundamental information on the most energetic phenomena in the Universe. At ultrahigh energies, beyond 10 18 eV, the cosmic rays are studied by the two largest observatories built so far, the Pierre Auger Observatory and the Telescope Array. Both observatories are based on a hybrid design and reported a measurement of the energy spectrum using the high duty cycle of the surface detector and the calorimetric estimation of the energy scale provided by the fluorescence detector. The differences among the reported spectra are scrutinized by a working group made by members of the Pierre Auger and Telescope Array Collaborations. The two measurements have been found well in agreement below 10 19 eV while, at higher energies, they show an energy-dependent difference that is beyond the systematic uncertainties associated to the energy scale. In this contribution we review the status and perspectives of the working group activities including new studies aiming at addressing the impact on the flux measurement at the highest energies of potential biases in the estimation of the shower size.

This work focused on prescribing, designing, implementing, and evaluating a pilot project conducted in the Greek power system that addressed balancing and congestion management issues that system operators (SOs) face within the clean energy era. The considered pilot project fully focused on the development of the F-channel platform, including the idea behind this application, the steps that were taken in the process, and the outcomes of the performed activities fitting into the overall picture of the OneNet project. The specified F-channel platform is a web-based, client-server application that uses artificial intelligence (AI) techniques and cloud computation engines to improve the management of the active power for the TSO-DSO coordination. The flexibility of the grid’s resources was identified, and an integrated monitoring system based on the precise forecasting of variable generation and demand was implemented. The focus areas were congestion management, frequency control, and voltage control services, for which corresponding network models were created in close cooperation with system operators. The obtained results are essential for the remaining demonstration results because they offer an incredibly accurate basis for further research into their use in congestion management and other weather-related enhanced transmission and distribution system planning and operation practices.

The European Union’s 2030 target of decreasing net greenhouse gas emissions by at least 55% has resulted in a significant uptake of renewable energy sources (RESs) in the European power system, primarily wind and solar power, as well as the closure of conventional power plants that mostly used fossil fuels. The European Union’s members have accelerated the process of energy transition driven by climate change, and public authorities’ involvement in this process is impressive. The goal of this study is to present a broad overview of the existing challenges for the energy transition in Europe and how they can affect the reliability and stability of the interconnected power system in Europe and future investments, focusing especially on Greece. Unfortunately, this environmentally friendly transition is taking place without the required amount of investment in electrical energy storage technology, which raises the risk of a blackout due to the high predicted variability of RES. The gradual abandonment of conventional energy production units such as natural gas in the coming decades will intensify the problem of frequency regulation, which will become even more acute due to the particularly increased installed capacity in RESs across Europe and Greece. The European Power System, being partially unprepared for the energy transition, frequently faces a paradox: it rejects green power originating from high-RES production because of low demand, a lack of transmission line interconnections, or extremely low energy storage capacity. This paper examines all the prerequisites, including how the European electrical transmission system will be developed in the future and how new energy storage technologies will be used. Lastly, Greece’s energy future and potential risks associated with realizing the environmental goals of the European Green Deal is studied using a PESTEL analysis.

It is challenging for the European power system to exactly predict RES output and match energy production with demand due to changes in wind and sun intensity and the unavoidable disruptions caused by severe weather conditions. Therefore, in order to address the so-called “flexibility challenge” and implement the variable RES production, the European Union needs flexible solutions. In order to accommodate quicker reactions, compared to those performed today, and the adaptive exploitation of flexibility, grid operators must adjust their operational business model, as the electrical grid transitions from a fully centralized to a largely decentralized system. OneNet aspires to complete this crucial step by setting up a new generation of grid services that can fully utilize distributed generation, storage, and demand responses while also guaranteeing fair, open, and transparent conditions for the consumer. Using AI methods and a cloud-computing approach, the current work anticipates that active management of the power system for TSO–DSO coordination will be improved by the web-based client-server application F-channel. In the current work, a user’s experience with the platform for a Business Use Case (BUC) under the scenario of severe weather conditions is presented. The current work aims to increase the reliability of outage and maintenance plans for the system operators (SOs) by granting them a more accurate insight into the conditions under which the system may be forced to operate in the upcoming period and the challenges that it might face based on those conditions. In this way, the methodology applied in this case could, via AI-driven data exchange and analyses, help SOs change the maintenance and outage plans so the potential grave consequences for the system can be avoided. The SOs will have accurate forecasts of the relevant weather parameters at their disposal that will be used in order to achieve the set targets. The main results of the presented work are that it has a major contribution to the optimal allocation of the available resources, ensures the voltage and frequency stability of the system, and provides an early warning for hazardous power system regimes.

The greater number of electrostatic discharges (ESDs) that occur in nature is by air rather than by contact. However, due to low reproducibility in the current of air discharges, the IEC 61000-4-2 defines that the current’s calibration of an ESD gun must be made only for contact discharges. In the work presented here, there is an attempt to improve the poor reproducibility of air discharges by a significant observation derived from ESD measurements and, more specifically, the relationship between the rise time and the peak current for every ESD gun. This fact validated in this paper from current measurements of two different ESD guns will help all who are involved in ESD measurements in EMC laboratories by reducing the existing uncertainty in measurements of air discharges.

Bubbles and super-bubbles are ubiquitous in the interstellar medium and influence their local magnetic field. Starting from the assumption that bubbles result from violent explosions that sweep matter away in a thick shell, we derive the analytical equations for the divergence-free, regular magnetic field in the shell. The explosion velocity field is assumed to be radial but not necessarily spherical, making it possible to model various-shaped bubbles. Assuming an explosion center, the magnetic field at the present time is fully determined by the initial uniform magnetic field, the present-time geometry of the bubble shell, and a radial vector field that encodes the explosion-induced displacement of matter, from its original location to its present-time location. We present the main characteristics of our magnetic-field model using a simple linear model for the radial displacements. Next, we use our analytical prescription, informed by a three-dimensional dust density map, to estimate the expected contribution of the shell of the Local Bubble, the super-bubbles in which the Sun resides, to the integrated Faraday rotation measures and synchrotron emission and compare these to full-sky observational data. We find that, while the contribution to the former is minimal, the contribution to the latter is very significant at Galactic latitudes \\(|b|>45^\\circ\\). Our results underline the need to take the Local Bubble into account in large-scale Galactic magnetic field studies.

There is an increase in the prevalence of diabetes mellitus (DM) globally. Individuals with diabetes mellitus are at higher risk of impairment of kidney function. This study evaluated the diagnostic performance of Cystatin C in the early detection of diabetic kidney disease (DKD). Across a sectional analytical study of 300 participants (200 study group and 100 control group). A relevant clinical history was obtained, and a physical examination was carried out. Venous blood was collected to assay for serum creatinine, serum albumin, serum cystatin C, serum urea, fasting blood glucose, and urine for the quantification of urine albumin excretion rate. The median age of the study group versus the control group was 62.50 for DM with proteinuria, 60.00 for DM without proteinuria, and 60.00 years for the control group (F = 3.524, p = 0.172). The laboratory parameters that were higher in the study group compared to the control group were FBG (141.0, 130, vs. 104 mg/dl, F = 68.456, p = <0.001), serum creatinine (109.0, 88.5, vs. 105.0 umol/l, F = 35.50, p = <0.001), serum cystatin C (1.24, 1.11, vs. 0.84 mg/L, F = 59.27, p = <0.001), and urine albumin excretion (230.0, 102.0, vs. 30.0 mg, F = 128.62, p = <0.001). The diagnostic performance of cystatin C using MDRD and cystatin C eGFR <60ml/min/1.73m2 was 13% and 23%, respectively, for the study group without proteinuria. Also, when the diagnostic efficiency of the variables was compared using ROC, the AUC of creatinine eGFR (MDRD) was less than that of cystatin C eGFR between the cut-off levels of 30 mg and 300 mg of urine albumin excretion. Cystatin C eGFR had a strong negative correlation with urine albumin excretion when compared to creatinine eGFR (MDRD). This study showed the diagnostic performance of serum cystatin C in the early detection of DKD and that cystatin C-derived eGFR is more sensitive than serum creatinine-derived eGFR in detecting DKD early in people with DM.