Exploration and mitigation of power quality problems in radial distribution system by placing distributed generation through voltage stability index

Introduction. Distributed generation has played an important role in many aspects of sustainability, such as improving voltage profiles and reducing power losses, in the distribution network. Problem. Frequent variation of loads causes many complications while placing and sizing of distributed generation in the radial distribution network, via quality of supply, and stability of the system. Goal of the paper is to investigate and mitigate the power quality issues towards stabilizing the system during distributed generations placed in the system under various loading conditions. Methodology. The line voltage stability index analyses and enhances the performance of the radial distribution network by effective sizing and location of distributed generation towards the objective function. Practical value. A standard test system IEEE-69 bus radial distribution network is used to understand through MATLAB environment.Вступ. Розподілена генерація відіграла важливу роль у багатьох аспектах стійкості, таких як покращення профілів напруги та зниження втрат електроенергії у розподільній мережі. Проблема. Часті коливання навантаження викликають безліч складнощів при розміщенні та визначенні розміру розподіленої генерації в радіальній розподільній мережі через якість постачання та стабільність системи. Мета статті полягає в тому, щоб дослідити та пом'якшити проблеми з якістю електроенергії для стабілізації системи під час розподіленої генерації, розміщеної у системі за різних умов навантаження. Методологія. Індекс стабільності лінійної напруги аналізує та підвищує продуктивність радіальної розподільної мережі за рахунок ефективного визначення розміру та розташування розподіленої генерації щодо цільової функції. Практична цінність. Для розуміння використовується стандартна тестова система радіальної розподільної мережі IEEE-69 за допомогою середовища MATLAB

Innovative framework for effective service parts management in the automotive industry

Effective service parts management and demand forecasting are crucial for optimizing operations in the automotive industry. However, existing literature lacks a comprehensive framework tailored to the specific context of the Thai automotive sector. This study addresses this gap by proposing a strategic approach to service parts management and demand forecasting in the Thai automotive industry. Drawing on a diverse set of methodologies, including classical time series models and advanced machine learning techniques, various forecasting models were assessed to identify the most effective approach for predicting service parts demand. Categorization of service parts based on demand criteria was conducted, and decision rules were developed to guide stocking strategies, balancing the need to minimize service disruptions with cost optimization. This analysis reveals substantial cost savings potential through strategic stocking guided by the developed decision rules. Furthermore, evaluation of the performance of different forecasting models recommends the adoption of Support Vector Regressor (SVR) as the most accurate model for forecasting service parts demand in this context. This research contributes to the automotive service industry by providing a nuanced framework for service parts management and demand forecasting, leading to cost-effective operations and enhanced service quality. The findings offer valuable insights for practitioners and policymakers seeking to improve efficiency and sustainability in the Thai automotive sector

Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic. Methods: The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic. Findings: Global DALYs increased from 2·63 billion (95% UI 2·44–2·85) in 2010 to 2·88 billion (2·64–3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7–17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8–6·3) in 2020 and 7·2% (4·7–10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0–234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7–198·3]), neonatal disorders (186·3 million [162·3–214·9]), and stroke (160·4 million [148·0–171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3–51·7) and for diarrhoeal diseases decreased by 47·0% (39·9–52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54–1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5–9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0–19·8]), depressive disorders (16·4% [11·9–21·3]), and diabetes (14·0% [10·0–17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7–27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6–63·6) in 2010 to 62·2 years (59·4–64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6–2·9) between 2019 and 2021. Interpretation: Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades. Funding: Bill & Melinda Gates Foundation

A two-stage methodology of optimal capacitor placement for the reconfigured network

105-112This paper describes a two-stage methodology of optimal capacitor placement for the reconfigured network. A two-stage methodology is used to reduce the losses and to improve the voltage profile of the balanced radial distribution networks. In the first stage, an improved fuzzy multi-objective algorithm is used for the network reconfiguration of the original network. In the second stage, capacitors are placed optimally for the reactive power compensation of the reconfigured network. Fuzzy approach is used to find the optimal capacitor locations and analytical method is used to find the sizes of the capacitors. The proposed method is tested on 11-bus, 33-bus and 69-bus test systems and the results indicate that considerable loss reduction is possible with substantial improvement in the voltage profile

OPTIMAL POWER FLOW USING PARTICLE SWARM OPTIMIZATION

The Optimal Power Flow (OPF) is an important criterion in today’s power system operation and control due to scarcity of energy resources, increasing power generation cost and ever growing demand for electric energy. As the size of the power system increases, load may be varying. The generators should share the total demand plus losses among themselves. The sharing should be based on the fuel cost of the total generation with respect to some security constraints. Conventional optimization methods that make use of derivatives and gradients are, in general, not able to locate or identify the global optimum. Heuristic algorithms such as genetic algorithms (GA) and evolutionary programming have been recently proposed for solving the OPF problem. Unfortunately, recent research has identified some deficiencies in GA performance. Recently, a new evolutionary computation technique, called Particle Swarm Optimization (PSO), has been proposed and introduced. This technique combines social psychology principles in socio-cognition human agents and evolutionary computations. In this paper, a novel PSO based approach is presented to solve Optimal Power Flow problem

Hybrid DC-DC Converter with Artificial Intelligence based MPPT Algorithm for FC-EV

539-535This manuscript covers the use of a Brushless DC Motor (BLDC) based on a fuel cell in an electric vehicle with a hybrid DC-DC converter with artificial intelligence-based Maximum Power Point (MPP) Tracking. The Boost converter and Cuk converter input stages are integrated in this study to produce a high step-up hybrid boost converter. Only one switch is required in the proposed topology, which decreases voltage stress across the diodes. The converter's overall efficiency increased because the voltage across the switch, diode, and capacitor voltage is less than the output voltage. A new Radial Basis Function Network (RBFN) based MPPT approach is developed for fuel cells based electric vehicles to extract maximum power at ambient temperatures. Computer software programme MATLAB/SIMULINK is used to evaluate the Fuel Cell (FC) fed electric vehicle system

Exploration and mitigation of power quality problems in radial distribution system by placing distributed generation through voltage stability index

Introduction. Distributed generation has played an important role in many aspects of sustainability, such as improving voltage profiles and reducing power losses, in the distribution network. Problem. Frequent variation of loads causes many complications while placing and sizing of distributed generation in the radial distribution network, via quality of supply, and stability of the system. Goal of the paper is to investigate and mitigate the power quality issues towards stabilizing the system during distributed generations placed in the system under various loading conditions. Methodology. The line voltage stability index analyses and enhances the performance of the radial distribution network by effective sizing and location of distributed generation towards the objective function. Practical value. A standard test system IEEE-69 bus radial distribution network is used to understand through MATLAB environment