UKF based estimation approach for DVR control to compensate voltage swell in distribution systems

AbstractThe Dynamic Voltage Restorer (DVR) is identified as the best solution for mitigation of voltage sag and swell related problems in the much taped distribution system. The compensation performance of the DVR very much depends on its control algorithm. In the paper, an estimation method based on Unscented Kalman Filter (UKF) is proposed for mitigating the voltage swell concern. The proposed UKF based estimation technique is used to assist the control algorithm for generating reference signals of Voltage Source Converter (VSC) of DVR. DVR presents the compensation voltage as output which is included in the connected line. With this estimation method, voltage swell issues are discovered with accuracy and faster performance to retract out the swell problem in sensitivity load linked distribution systems. In MATLAB/Simulink platform the suggested method is executed and its performance is assessed and contrasted with the Linear Kalman Filter (LKF) and Extended Kalman Filter (EKF)

Recommended reporting items for epidemic forecasting and prediction research : the EPIFORGE 2020 guidelines

Funding: MIDAS Coordination Center and the National Institutes of General Medical Sciences (NIGMS 1U24GM132013) for supporting travel to the face-to-face consensus meeting by members of the Working Group. NGR was supported by the National Institutes of General Medical Sciences (R35GM119582). Travel for SV was supported by the National Institutes of General Medical Sciences (1U24GM132013-01). BMA was supported by Bill & Melinda Gates through the Global Good Fund. RL was funded by a Royal Society Dorothy Hodgkin Fellowship.Background  The importance of infectious disease epidemic forecasting and prediction research is underscored by decades of communicable disease outbreaks, including COVID-19. Unlike other fields of medical research, such as clinical trials and systematic reviews, no reporting guidelines exist for reporting epidemic forecasting and prediction research despite their utility. We therefore developed the EPIFORGE checklist, a guideline for standardized reporting of epidemic forecasting research. Methods and findings  We developed this checklist using a best-practice process for development of reporting guidelines, involving a Delphi process and broad consultation with an international panel of infectious disease modelers and model end users. The objectives of these guidelines are to improve the consistency, reproducibility, comparability, and quality of epidemic forecasting reporting. The guidelines are not designed to advise scientists on how to perform epidemic forecasting and prediction research, but rather to serve as a standard for reporting critical methodological details of such studies. Conclusions  These guidelines have been submitted to the EQUATOR network, in addition to hosting by other dedicated webpages to facilitate feedback and journal endorsement.Publisher PDFNon peer reviewe

UKF based estimation approach for DVR control to compensate voltage swell in distribution systems

The Dynamic Voltage Restorer (DVR) is identified as the best solution for mitigation of voltage sag and swell related problems in the much taped distribution system. The compensation performance of the DVR very much depends on its control algorithm. In the paper, an estimation method based on Unscented Kalman Filter (UKF) is proposed for mitigating the voltage swell concern. The proposed UKF based estimation technique is used to assist the control algorithm for generating reference signals of Voltage Source Converter (VSC) of DVR. DVR presents the compensation voltage as output which is included in the connected line. With this estimation method, voltage swell issues are discovered with accuracy and faster performance to retract out the swell problem in sensitivity load linked distribution systems. In MATLAB/Simulink platform the suggested method is executed and its performance is assessed and contrasted with the Linear Kalman Filter (LKF) and Extended Kalman Filter (EKF). Keywords: Unscented Kalman Filter, Extended Kalman Filter, Dynamic Voltage Restorer, Voltage swell and distribution syste

Dynamic analysis of a guillotine shearing machine

The major components of guillotine shears, both over-crank and under-crank, including the side-stands, the bottom connecting plate, the hold-down, the top connecting plate and the blade carrier, are examined critically for rigidity and strength, vibration characteristics, dynamic stresses and factor of safety whilst the shear is in operation. The vibration and strength characteristics of the machines and the blade carrier, when the thickness of the plates are changed, are also examined

Porcine pancreatic α-amylase inhibitors from Euonymus laxiflorus Champ

[[abstract]]Twenty-six samples of indigenous medicinal plants were collected in Dak Lak Province of Vietnam and evaluated for α-amylase inhibitory activity. Of these samples, trunk bark extract from Euonymus laxiflorus Champ. (ELC extract) showed the greatest α-amylase inhibitory activity with the smallest 50 % inhibitory concentration (IC50) of 6.6 ± 0.6 µg/mL against porcine pancreatic α-amylase. This extract possessed strong inhibitory activity against human saliva α-amylase and slightly lower activity against Bacillus subtilis α-amylase, with IC50 values of 4.2 ± 0.2 and 27.8 ± 1.8 µg/mL, respectively. ELC extract was found to be strongly thermostable, retaining 72–100 % relative activity even after heating at 100 °C for 5 min to 2 h. This extract was also stable at various pH values. These results suggest that ELC extract may be a good candidate for treatment of non-insulin-dependent diabetes mellitus (NIDDM) and obesity.[[notice]]補正完

Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines.

BackgroundThe importance of infectious disease epidemic forecasting and prediction research is underscored by decades of communicable disease outbreaks, including COVID-19. Unlike other fields of medical research, such as clinical trials and systematic reviews, no reporting guidelines exist for reporting epidemic forecasting and prediction research despite their utility. We therefore developed the EPIFORGE checklist, a guideline for standardized reporting of epidemic forecasting research.Methods and findingsWe developed this checklist using a best-practice process for development of reporting guidelines, involving a Delphi process and broad consultation with an international panel of infectious disease modelers and model end users. The objectives of these guidelines are to improve the consistency, reproducibility, comparability, and quality of epidemic forecasting reporting. The guidelines are not designed to advise scientists on how to perform epidemic forecasting and prediction research, but rather to serve as a standard for reporting critical methodological details of such studies.ConclusionsThese guidelines have been submitted to the EQUATOR network, in addition to hosting by other dedicated webpages to facilitate feedback and journal endorsement