Analysis of Superconducting Fault Current Limiterin DC System with Renewable Energy Sources

Superconducting fault-current limiters (SFCLs) have been the subject of research and development for many years and offer an attractive solution to the problem of rising fault levels in electrical distribution systems. SFCLs can greatly reduce fault currents and the damage at the point of fault, and help improve the stability of a power system. Superconducting fault-current limiters (SFCL) provide a new efficient approach to the reliable handling of such faults.(SCFLs) can be used for various nominal voltages and currents, and can be adapted to particular limiting characteristics in case of short circuits. In this project, dc resistive type superconducting fault current limiter (SFCL) is presented. This SFCL is designed for the HVDC system. Uniform current and voltage sharing among the SFCL modules can be observed through contact resistance tests, dc flow-through tests, and ac flow-through tests. Results of tests show that each limiting module has good uniformity in higher current system. The proposed concept can be implemented using renewable energy sources.The results are presented by using Matlab/Simulink platform

Analysis of Superconducting Fault Current Limiterin DC System with Renewable Energy Sources

Superconducting fault-current limiters (SFCLs) have been the subject of research and development for many years and offer an attractive solution to the problem of rising fault levels in electrical distribution systems.  SFCLs can greatly reduce fault currents and the damage at the point of fault, and help improve the stability of a power system. Superconducting fault-current limiters (SFCL) provide a  new efficient approach to the reliable handling of such  faults.(SCFLs) can be used for various nominal voltages and currents, and can  be  adapted  to  particular  limiting  characteristics  in  case  of  short  circuits. In this project, dc resistive type superconducting fault current limiter (SFCL) is presented. This SFCL is designed for the HVDC system. Uniform current and voltage sharing among the SFCL modules can be observed through contact resistance tests, dc flow-through tests, and ac flow-through tests. Results of tests show that each limiting module has good uniformity in higher current system. The proposed concept can be implemented using renewable energy sources.The results are presented by using Matlab/Simulink platform

Load Flow Solution of Distribution Systems - A Bibliometric Survey

In this paper, Bibliometric Survey has been carried out on ‘Load Flow Solution of Distribution Systems’ from 2012 to 2021. Scopus database has been used for the analysis. There were total 1711 documents found on this topic. The statistical analysis is carried out source wise, year wise, area wise, Country wise, University wise, author wise, and based on funding agency. Network analysis is also carried out based on Co-authorship, Co-occurrence. Results are presented. During 2020 and 2018, there were 263 documents published which is the highest. ‘IEEE Transactions on Power Systems’ has published 90 documents during the period of study which is the highest in terms of articles under the category of sources. Highest citations were received by the article authored by Hung and Mithulanathan with 484 citations in the collected database with the chosen key words. VOSviewer 1.6.16 is the software that is used for the statistical analysis and network analysis on the database. It provides a very effective way to analyze the co-authorship, co-occurrences, citation and bibliometric analysis etc. The Source for all Tables and figures is www.scopus.com, The data is assessed on 6th July, 2021

IoT based solar panel fault and maintenance detection using decision tree with light gradient boosting

Solar PV (photovoltaic) technology has advanced greatly in recent years due to advantages such as renewability, environmental friendliness, simple maintenance, and dependability. Nevertheless, a number of PV faults may appear and result in degradation, a decrease in output power, or even a storm surge at different levels, depending on the outside working conditions and regular weather changes that might cause harm to the production, distribution, or setup, it is critical to monitor PVSs (PV systems) for their power generation efficiencies. IoT (Internet of Things) are evolving technologies that have been studied for enhanced fault detection and predictive analysis in the maintenance and environmental monitoring of solar power plants. This research work suggests a method based on MLTs (machine learning techniques) to analyze power data and predict faults for the maintenance of solar power plants. Input data from solar power plants consist of plant power generation and weather data which are first pre-processed and then trained using the suggested DT-LGB (Decision Trees with Light Gradient Boosting) algorithm to predict errors. The trained model was able to identify major/minor faults or anomalies present in input data. Conventionally these identifications require more effort in detection and maintenance. The results of this work showed that the suggested model obtained 8.74 MSEs ((Mean Square Errors), 2.96 RMSEs (Root Mean Square Errors), and R2 values of 0.9939 which is 12.8%, 6.8%, and 11.08% improved than the existing method respectively

Anti-Phospholipid Syndrome in SLE in Association with Autoimmune Hypothyroidism

Antiphospholipid antibodies may occur spontaneously or associated with other diseases, including rheumatic autoimmunediseases and autoimmune thyroid diseases. One-third of patients with Systemic Lupus Erythematosus (SLE) possess Anti-PL antibodies while their prevalence in other autoimmune connective tissue disorders ranges from 6% to 15%.AntiCardiolipin Antibody presence has been described in Graves’ disease and Hashimoto´s thyroiditis patients with or withoutclinical manifestations of the antiphospholipid syndrome. However, thyroid autoantibodies have seldom been described inantiphospholipid syndrome patients. Among lupus patients, there is increased mortality rate among patients havingsecondary APS compared with lupus patients who do not have APS. Thus every case of SLE with a history of spontaneousabortions needs to be evaluated for Anti phospholipid antibody syndrom

Are technologies assisted homes safer for the elderly?

The elderly population of the world is growing rapidly, creating the increasing need for elderly care. The aged people expect that this increased longevity will help them to enjoy living an independent and high quality life. Yet, at the same time they know there is a high risk of injury as many unforeseen accidents can take place. Surely, with the technology of today, there is a better way for these people in the society to resolve this problem. The chapter will present the development work and implementation details of a wireless sensors network based safe home monitoring system targeted for the elder people to provide a safe, sound and secured living environment in the society. The system is designed to support people who wish to live alone but, because of old age, ill health or disability, there is some risk in this, which worries their family or friends.18 page(s

Applying SARIMA time series to forecast sleeping activity for wellness model of elderly monitoring in smart home

In this paper, we have reported a mechanism to forecast the sensing durations of various object usages in a smart home environment. Prognosis will assist in determining the quantitative well-being of an elderly and notify the daily activity behavior as regular or irregular. Prediction process involved in wellness model is the seasonal auto regression integration moving average routines based on the recorded sensing active status of everyday objects used by an elderly living alone.6 page(s