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PV hosting capacity quantification is currently of importance for distribution system operators to manage upcoming PV installation requests, especially within low-voltage grids. The violation-mitigation-based (VMB) method presented a novel downward approach to quantify the PV hosting capacity in low-voltage grids, having the advantage of also quantifying possible expansions in the hosting capacity. The VMB method, however, requires typically hundreds of power flow simulations to quantify the hosting capacity in a low-voltage grid. In this paper, we address this issue by introducing sensitivity matrices to optimize the downward process of quantification. Evaluated in 79 low-voltage feeders from Austria, the enhanced VMB method reduces the number of iterations required from a median of 1764 to 7 while obtaining the same or higher hosting capacity values. The reduced computational effort permits the application of the method proposed at a large-scale. The application of the method proposed on the standard CIGRE residential low-voltage grid is also presented for possible comparison with other methods. • A heuristic method to quantify the hosting capacity in low voltage grids. • The use of voltage and current sensitivities to reduce the computational effort. • Evaluation of the method proposed on real low voltage grids from Austria. [ABSTRACT FROM AUTHOR]

• Analyzed VFRS and LLS data set includes records of 519 negative Cloud-to-Ground (CG) flashes including 1683 negative CG strokes from the Austrian alpine region. • Results regarding strokes per flash, strokes per ground strike point (GSP) and distances between GSPs are given. • Results for the mean multiplicity of the analyzed ground truth data (3.3) revealed a lower value compared to multiplicities from other countries available in the literature. • Distances between the first ground strike point (GSP) of a flash to the other GSPs of the same flash showed a median of 1.4 km, an arithmetic mean of 1.6 km and a geometric mean of 1.2 km. • Maximum determined distance between the first stroke of a flash and a GSP in the same flash was 6.9 km. This paper presents an analysis of flashes and their Ground Strike Points (GSPs) by using Video and Field Recording System (VFRS) data and Lightning Location System (LLS) data from Austria. Analyses of the multiplicity of flashes and strokes per GSP have been performed. A comparison between strokes per flashes and strokes per GSPs has been conducted. By using the calculated strike point locations from the LLS, distances between different GSPs have been calculated. The used VFRS and LLS data set includes records from 2015, 2017, 2018 and 2021 recorded in the Austrian Alpine region. Atmospheric discharges have been recorded at 22 different measurement locations in Austria. For the present work a data set of 519 flashes including 1683 strokes were analyzed. Results for the mean multiplicity (3.3) revealed a lower value compared to multiplicities from other countries, but similar to the ones determined by former studies from Austria. Calculations of distances between the first GSP of a flash to the other GSPs of the same flash showed a median of 1.4 km, an arithmetic mean of 1.6 km and a geometric mean of 1.2 km. The maximum determined distance between two GSPs was 6.9 km for the analyzed data set. [ABSTRACT FROM AUTHOR]

This paper describes the first measurements of lightning currents from upward lightning events to a tall tower – the Sentech Tower – in Johannesburg, South Africa. The lightning activity in Johannesburg is described in context of other such sites around the world along with the high-speed camera setup and direct current measurement installation at the Sentech Tower, making up the project termed The Johannesburg Lightning Research Laboratory (JLRL). Measurements from the 2020–2021 lightning season are analysed in accordance with similar definitions used in other studies in Austria and Japan and the results are compared with the studies in these regions. A total of 42 lightning events to the tall tower are analysed. This resulted in 175 return strokes, 30 ICC fast pulses and 9 ICC Only events. The return stroke median current and median ICC fast pulse peak currents are comparable to the values seen in Austria and Japan at 7.51 kA and 3.75 kA, respectively. The median charge transfer is 41.36 C (35.51C for ICC Pulse events and 26.08C for ICC Only events) and is also similar to these studies. The return stroke multiplicity however, is higher for the Sentech Tower than elsewhere, with an average value of 6.41. Overall, the peak current distribution, charge transfer and inter-stroke time distribution showed agreement with the measurements made in Austria and Japan. However, the multiplicity of the events measured at the Sentech Tower appear to be twice as much as those seen in Austria and Japan. • The flash density is one of the highest of all locations where lightning studies have been conducted. • The first measurements of lightning currents in South Africa since Eriksson et al.'s work on the CSIR Tower. • The average peak current values of the subsequent return strokes and the average charge transfer appear to be similar to other upward lightning current measurements studies in Austria and Japan. • The multiplicity per event seems to be almost double that of Austria and Japan. [ABSTRACT FROM AUTHOR]

• Lightning ground truth data analyses in the Austrian Alps during 2015, 2017 and 2018. • Atmospheric discharges are recorded at different measurement locations in Austria. • 463 negative cloud-to-ground (CG) flashes and 1527 negative CG strokes analyzed. • LLS performance parameter, location accuracy and detection efficiency are determined. • Flash multiplicity and peak currents are analyzed too. This paper presents recent ground truth data analyses in the Austrian Alps run by Graz University of Technology in cooperation with Austrian Lightning Detection and Information System (ALDIS). Atmospheric discharges are observed at different measurement locations by using a Video and Field Recording System (VFRS). This system consists of a high speed video camera (2000 frames per second) and a flat plate antenna to measure the electric field. For the present analysis a data set of the measurement periods 2015, 2017 and 2018 was used for validation of the Lightning Location System (LLS) data of ALDIS. In total 463 negative cloud-to-ground (CG) flashes and 1527 negative CG strokes were recorded in Austria during 51 days. Values for LLS location accuracy are in the range of 90 m to 130 m. LLS flash detection efficiencies in the range from 96.08% to 98.62% and stroke detection efficiencies in the range from 76.36% to 85.60% have been determined. Mean multiplicity values determined with the VFRS data are comparable to the results of previous analyses in the Austrian Alps. [ABSTRACT FROM AUTHOR]

• A breakdown of the location accuracy of the SALDN and ALDIS per year, indicating that rare large location errors still occur even as performance improves. • A methodology to fit statistical models to geographical lightning data and evaluate the quality of the fit. • The methodology is applied to lightning location system data time-correlated with ground-truth lightning events - tall tower lightning in both South Africa and Austria. • It is shown that the bivariate Students' t-distribution is a better statistical model for lightning location system errors than the bivariate Gaussian distribution. Lightning location systems geolocate lightning strokes. Given assumptions made in the geolocation models, errors in the reported locations can occur. Modelling these errors as a bivariate Gaussian distribution of historic stroke detections has found success in the form of confidence ellipses. However, the presence of outliers - strokes with large location errors - indicate that there is a better model for these errors. The Students' t-distribution is a "heavier" tailed distribution. This paper investigates whether the bivariate Students' t-distribution is a better model for such errors. A methodology for modelling and evaluating the distribution of location errors using maximum likelihood estimation, expectation-maximization and a Mahalanobis distance quality-of-fit test is described. This method is applied to stroke reports from the South African Lightning Detection Network and the Austrian Lightning Detection and Information System time-correlated with photographed lightning events to the Brixton Tower, South Africa and current measurements to the Gaisberg Tower, Austria respectively. In both cases, we find outliers in the distribution of location errors - even as the performance of the networks increase. Using the Mahalanobis test, we find the bivariate Students' t-distribution to be a better statistical model for both the South African and the Austrian events. [ABSTRACT FROM AUTHOR]