Stochastic modelling of the correlation between transformer loading and distributed energy resources in LV distribution networks

The rapid growth of distributed energy resources (DERs) poses operational challenges for the low-voltage (LV) distribution networks, such as overloading of the transformer and/or voltage violation. Many smart strategies based on flexibility and coordinated control of DER have been developed to address these issues. To facilitate this implementation, this study presents a stochastic modelling technique, based on the Monte Carlo approach, to analyse the correlation between transformer loading and voltage magnitudes measured at the point of connection (POC) of DER in the network. A case study has been performed using IEEE European LV test feeder and smart meter measurement from the Netherlands to reflect the realistic aspects of operational conditions. Advanced statistical modelling techniques are applied to generate a set of scenarios, consisting of solar irradiation, and electric vehicle charging and load consumption profiles. Simulation results reveal a strong linear relationship between transformer loading and voltage magnitudes at the POC of DERs. Thus, these findings can aid in implementing flexibility and coordinated control DERs for congestion management in the LV distribution network.</p

Stochastic modelling of the correlation between transformer loading and distributed energy resources in LV distribution networks

The rapid growth of distributed energy resources (DERs) poses operational challenges for the low-voltage (LV) distribution networks, such as overloading of the transformer and/or voltage violation. Many smart strategies based on flexibility and coordinated control of DER have been developed to address these issues. To facilitate this implementation, this study presents a stochastic modelling technique, based on the Monte Carlo approach, to analyse the correlation between transformer loading and voltage magnitudes measured at the point of connection (POC) of DER in the network. A case study has been performed using IEEE European LV test feeder and smart meter measurement from the Netherlands to reflect the realistic aspects of operational conditions. Advanced statistical modelling techniques are applied to generate a set of scenarios, consisting of solar irradiation, and electric vehicle charging and load consumption profiles. Simulation results reveal a strong linear relationship between transformer loading and voltage magnitudes at the POC of DERs. Thus, these findings can aid in implementing flexibility and coordinated control DERs for congestion management in the LV distribution network.</p

Self-adaptive Controllers for Renewable Energy Communities Based on Transformer Loading Estimation

In this paper, self-adaptive controllers for renewable energy communities based on data-driven approach are proposed to mitigate the voltage rise and transformer congestion at the community level. In the proposed approach, the transformer loading percentage is estimated by the trained data-driven model, which uses the extreme gradient boosting regression algorithm based on a measurement set acquired from critical coupling points of the communities. To avoid voltage rise issues, the droop control parameters (i.e., voltage threshold for P - V, Q - V curves) are adaptively tuned based on the solar irradiance availability and estimated transformer loading. The proposed approach has been tested in the IEEE European LV distribution network. Results showed that the control approach could effectively reduce 22.2 % of the total overloaded instances, while still keeping voltage magnitude in the operation range. This method can help DSOs manage voltage violation and congestion without further communication

An overview of grid-edge control with the digital transformation

Distribution networks are evolving to become more responsive with increasing integration of distributed energy resources (DERs) and digital transformation at the grid edges. This evolution imposes many challenges to the operation of the network, which then calls for new control and operation paradigms. Among others, a so-called grid-edge control is emerging to harmonise the coexistence of the grid control system and DER’s autonomous control. This paper provides a comprehensive overview of the grid-edge control with various control architectures, layers, and strategies. The challenges and opportunities for such an approach at the grid edge with the integration of DERs and digital transformation are summarised. The potential solutions to support the network operation by using the inherent controllability of DER and the availability of the digital transformation at the grid edges are discussed

Appropriate Antibiotic Use and Associated Factors in Vietnamese Outpatients

Background: Inappropriate antibiotic use among outpatients is recognized as the primary driver of antibiotic resistance. A proper understanding of appropriate antibiotic usage and associated factors helps to determine and limit inappropriateness. We aimed to identify the rate of appropriate use of antibiotics and identify factors associated with the inappropriate prescriptions. Methods: We conducted a cross-sectional descriptive study in outpatient antibiotic use at a hospital in Can Tho City, Vietnam, from August 1, 2019, to January 31, 2020. Data were extracted from all outpatient prescriptions at the Medical Examination Department and analyzed by SPSS 18 and Chi-squared tests, with 95% confidence intervals. The rationale for antibiotic use was evaluated through antibiotic selection, dose, dosing frequency, dosing time, interactions between antibiotics and other drugs, and general appropriate usage. Results: A total of 420 prescriptions were 51.7% for females, 61.7% with health insurance, and 44.0% for patients with one comorbid condition. The general appropriate antibiotic usage rate was 86.7%. Prescriptions showed that 11.0% and 9.5% had a higher dosing frequency and dose than recommended, respectively; 10.2% had an inappropriate dosing time; 3.1% had drug interactions; and only 1.7% had been prescribed inappropriate antibiotics. The risk of inappropriate antibiotic use increased in patients with comorbidities and antibiotic treatment lasting >7 days (p < 0.05). Conclusions: The study indicated a need for more consideration when prescribing antibiotics to patients with comorbidities or using more than 7 days of treatment

A Multinational Data Set of Game Players' Behaviors in a Virtual World and Environmental Perceptions

Video gaming has been rising rapidly to become one of the primary entertainment media, especially during the COVID-19 pandemic. Playing video games has been reported to associate with many psychological and behavioral traits. However, little is known about the connections between game players' behaviors in the virtual environment and environmental perceptions. Thus, the current data set offers valuable resources regarding environmental worldviews and behaviors in the virtual world of 640 Animal Crossing: New Horizons (ACNH) game players from 29 countries around the globe. The data set consists of six major categories: 1) socio-demographic profile, 2) COVID-19 concern, 3) environmental perception, 4) game-playing habit, 5) in-game behavior, and 6) game-playing feeling. By making this data set open, we aim to provide policymakers, game producers, and researchers with valuable resources for understanding the interactions between behaviors in the virtual world and environmental perceptions, which could help produce video games in compliance with the United Nations (UN) Sustainable Development Goals

Burden of respiratory syncytial virus infection in older and high-risk adults: a systematic review and meta-analysis of the evidence from developed countries

BACKGROUND: Respiratory syncytial virus (RSV) significantly impacts the health of older and high-risk adults (those with comorbidities). We aimed to synthesise the evidence on RSV disease burden and RSV-related healthcare utilisation in both populations. METHODS: We searched Embase and MEDLINE for papers published between 2000 and 2019 reporting the burden and clinical presentation of symptomatic RSV infection and the associated healthcare utilisation in developed countries in adults aged ≥60 years or at high risk. We calculated pooled estimates using random-effects inverse variance-weighted meta-analysis. RESULTS: 103 out of 3429 articles met the inclusion criteria. Among older adults, RSV caused 4.66% (95% CI 3.34–6.48%) of symptomatic respiratory infections in annual studies and 7.80% (95% CI 5.77–10.45%) in seasonal studies; RSV-related case fatality proportion (CFP) was 8.18% (95% CI 5.54–11.94%). Among high-risk adults, RSV caused 7.03% (95% CI 5.18–9.48%) of symptomatic respiratory infections in annual studies, and 7.69% (95% CI 6.23–9.46%) in seasonal studies; CFP was 9.88% (95% CI 6.66–14.43%). Data paucity impaired the calculation of estimates on population incidence, clinical presentation, severe outcomes and healthcare-related utilisation. CONCLUSIONS: Older and high-risk adults frequently experience symptomatic RSV infection, with appreciable mortality; however, detailed data are lacking. Increased surveillance and research are needed to quantify population-based disease burden and facilitate RSV treatments and vaccine development

Identifying hotspots for antibiotic resistance emergence and selection, and elucidating pathways to human exposure: Application of a systems-thinking approach to aquaculture systems

Aquaculture systems are highly complex, dynamic and interconnected systems influenced by environmental, biological, cultural, socio-economic and human behavioural factors. Intensification of aquaculture production is likely to drive indiscriminate use of antibiotics to treat or prevent disease and increase productivity, often to compensate for management and husbandry deficiencies. Surveillance or monitoring of antibiotic usage (ABU) and antibiotic resistance (ABR) is often lacking or absent. Consequently, there are knowledge gaps for the risk of ABR emergence and human exposure to ABR in these systems and the wider environment. The aim of this study was to use a systems-thinking approach to map two aquaculture systems in Vietnam – striped catfish and white-leg shrimp – to identify hotspots for emergence and selection of resistance, and human exposure to antibiotics and antibiotic-resistant bacteria. System mapping was conducted by stakeholders at an interdisciplinary workshop in Hanoi, Vietnam during January 2018, and the maps generated were refined until consensus. Thereafter, literature was reviewed to complement and cross-reference information and to validate the final maps. The maps and component interactions with the environment revealed the grow-out phase, where juveniles are cultured to harvest size, to be a key hotspot for emergence of ABR in both systems due to direct and indirect ABU, exposure to water contaminated with antibiotics and antibiotic-resistant bacteria, and duration of this stage. The pathways for human exposure to antibiotics and ABR were characterised as: occupational (on-farm and at different handling points along the value chain), through consumption (bacterial contamination and residues) and by environmental routes. By using systems thinking and mapping by stakeholders to identify hotspots we demonstrate the applicability of an integrated, interdisciplinary approach to characterising ABU in aquaculture. This work provides a foundation to quantify risks at different points, understand interactions between components, and identify stakeholders who can lead and implement change

Expanding HIV Testing Efforts in Concentrated Epidemic Settings: A Population-Based Survey from Rural Vietnam

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