Review of approaches for using synchrophasor data for real-time wide-area control

Due to the changing nature of power systems—with reduced electrical inertia and the prevalence of smaller controllable power resources rather than large generators—new control approaches are required to mitigate disturbances. Ubiquitous measurements and communications networks can beleveraged to accelerate and provide a targeted, real-time response in such future systems. However, autonomous control of power systems requires dependable measurements. This paper provides a review of state of the art approaches to real-time power system control using synchrophasor measurements. In particular, examples are given involving recent developments in frequency regulation. Through a case study, it is shown how laboratories can be linked using Software-Defined Networking technologies to conveniently share resources in order to realistically and comprehensively validate synchrophasor-based control systems

Relating Corrosion of Mechanically Stabilized Earth Reinforcements with Fluid Conductivity of Backfill Soils

The service life of mechanically stabilized earth (MSE) walls depends on the rate of corrosion of the metallic reinforcements used in their construction. A methodology was designed to monitor and estimate the corrosion rate of galvanized steel in MSE walls with a conductivity sensor coupled with laboratory electrochemical techniques. The fluid conductivity of six coarse-grained backfill soils undergoing either wet-dry cycles or under submerged conditions were measured regularly for up to 120 weeks. The corrosion rates of the galvanized steel were determined indirectly by measuring the conductivities of the leachates from the six backfills. The conductivity of the leach-liquor appears promising to monitor the corrosion rate even though the predicted corroded thickness was less than the actual corroded thickness measured with a scanning electron microscope

Assessing Suitable Areas of Common Grapevine (Vitis vinifera L.) for Current and Future Climate Situations: The CDS Toolbox SDM

Climate Data Science (CDS) Toolbox Species Distribution Model (SDM) aims identifying the suitable areas for species, community of species and landscape units. This model is based on the use of 23 variables available over the Internet, for which any assumptions are formulated about their relationships with the spatial distribution of species. The application of CDS Toolbox SDM on the assessment of the potential impact of two scenarios of climate change (Representative Concentration Pathways RCP4.5 and RCP6.0) on the suitability of grapevine crops in France shows a general decrease of the most suitable areas for grapevine crops between 41% and 83% towards 2070 according to the current location of the vineyard parcels. The results underline a potential shift of the suitable areas in northern part of the French territory. They also show a potential shift of the most suitable areas in altitude (60 m in average) for RCP6.0 scenario. Finally, the model shows that RCP4.5 scenario should be more drastic than RCP6.0 scenario by 2050 and 2070. In effect, the model underlines a significant potential decrease of cultivated crops in the areas of high probably of suitable areas, according to the baseline scenario. This decrease would be of 630,000 ha for 2070 RCP4.5 scenario and 330,000 ha for 2070 RCP6.0 scenario

Tomographic assessment of pulmonary abnormalities of Long COVID: a cohort study

Introduction: SARS-CoV-2 infection primarily affects the lungs leading to a range of tomographic findings, from ground-glass opacity to emphysema. However, studies on the long-term effects of the infection, known as Long COVID, are still limited. Therefore, this cohort aimed to identify pulmonary abnormalities in adult patients with Long COVID, assessed by chest computed tomography (CT) 6 to 30 months after the initial infection. Material and Methods: A cohort of patients from northern Mexico, diagnosed with COVID-19 in 2020-2021 using RT-PCR and undergoing a simple chest CT examination, was followed up for 6 to 30 months. Logistic regression was used to determine predictors of Long COVID. Results: A total of 67 patients were included. Pulmonary tomographic abnormalities at 6 to 30 months were interstitial thickening (n = 41, 61.2%), subpleural bands (n = 41, 61.2%), ground-glass opacity (n = 30, 44.8%), pleural thickening (n = 18, 26.9%), bronchiectasis (n = 13, 19.4%), lymphadenomegaly (n = 11, 16.4%), emphysema (n = 6, 9.0%), and consolidation (n = 2, 3.0%). Ground-glass opacity and fibrotic abnormalities decreased with increasing follow-up time: e.g., interstitial thickening from 6 to 11 months (84.6%), 12 to 18 (65.0%), and 19 to 30 months (50.0%). Hypertension was the most significant predictor of Long COVID. Conclusion: Our study showed a high prevalence of persistent pulmonary abnormal tomographic findings in patients with Long COVID, probably due to the high prevalence of hypertension and diabetes. Ground-glass opacity and fibrotic abnormalities were the most commonly observed findings, which showed a decreasing trend over time