Design and Analysis of Second Order Passive Filters for Grid Connected Inverter with Series and Parallel Damping Resistors

Background/Objectives: Grid connected inverters are widely used to integrate renewable sources into the grid. The suitable power quality is required which can be either achieved using active or passive filters. This paper focuses on second order passive filters such as inductor capacitor (LC) and LC inductor (LCL) which can be used to attenuate harmonics for grid connect inverters. Methods/Statistical Analysis: To overcome the resonance of LCL filters passive damping6–8 or active damping can be used. Active power filters are more expensive because of sensors and control systems additional cost. Passive damping strategies due to simple circuit and low cost are more favored. A LCL filter equipped with series or parallel resistor with a capacitor forms a LCL filter with damped resistor Addition of resistor to filter circuit will cause an increase in power losses. The peak resonance of LCL filter depends upon the value of resistor so select a value of resistor which decline peak resonance of filter. Findings: At resonance frequency they have some issues related to stability. LCL filter can be equipped with damping resistor but there are some power loss and introduction of voltage, current harmonic. Mathematical characteristics of passive filters such as LC, LCL, LCL with series resistor and LCL with parallel resistors are discussed in terms of effectiveness and stability in this paper. Application/Improvements: It is very useful for industrial application and power electronic converter

Design and analysis of second order passive filters for grid connected inverter with series and parallel damping resistors

Background/Objectives: Grid connected inverters are widely used to integrate renewable sources into the grid. The suitable power quality is required which can be either achieved using active or passive filters. This paper focuses on second order passive filters such as inductor capacitor (LC) and LC inductor (LCL) which can be used to attenuate harmonics for grid connect inverters. Methods/Statistical Analysis: To overcome the resonance of LCL filters passive damping6–8 or active damping can be used. Active power filters are more expensive because of sensors and control systems additional cost. Passive damping strategies due to simple circuit and low cost are more favored. A LCL filter equipped with series or parallel resistor with a capacitor forms a LCL filter with damped resistor Addition of resistor to filter circuit will cause an increase in power losses. The peak resonance of LCL filter depends upon the value of resistor so select a value of resistor which decline peak resonance of filter. Findings: At resonance frequency they have some issues related to stability. LCL filter can be equipped with damping resistor but there are some power loss and introduction of voltage, current harmonic. Mathematical characteristics of passive filters such as LC, LCL, LCL with series resistor and LCL with parallel resistors are discussed in terms of effectiveness and stability in this paper. Application/Improvements: It is very useful for industrial application and power electronic converter

Investigating machine learning methods for tuberculosis risk factors prediction:a comparative analysis and evaluation

Abstract Tuberculosis (TB) is a killer disease, and its root can be traced to Mycobacterium tuberculosis. As the world population increases, the burden of tuberculosis is growing along. Low-and-middle-income nations are not exempted from the tuberculosis crisis. Due to a shortage of medical supplies, tuberculosis bacteria have become a huge public health concern. This study reviewed recent literature from 2015 to 2020 to critically examine what earlier researchers have done about TB burden and treatment. The data used were based on the hospital’s medical department’s record and used a machine-learning algorithm to predict and determine the risk factors associated with the disease. Furthermore, it developed five predictive models to offer the medical managers a valid alternative to the manual estimation of TB patients’ status as cured or not cured. The overall classification showed that all the classification methods performed well for classifying the TB treatment outcome (ranging between 67.5% and 73.4%). Our findings showed that MLP (testing) is the best model to predict TB patients’ treatment outcomes. Age and length of stay were identified as significant risk factors for TB patients in this study. This study explains the study’s limitation, contributions, managerial implications, and suggest future work