{"title":"D-STATCOM Control using SRFT Method for PQ Improvement in a PV System","authors":"Namratha Sampath, P. Parimala","doi":"10.35940/ijitee.h9261.0610821","DOIUrl":"https://doi.org/10.35940/ijitee.h9261.0610821","url":null,"abstract":"The set of restrictions defined for a system's electrical characteristics so that the entire electrical system can function in the intended manner and without losses is known as power quality. Power quality issues such as transients, harmonics, voltage swell, sag, flicker, fluctuations, and power factor difficulties are becoming more common as power electronic devices become more widely used. The usage of a Distribution Static Compensator (D-STATCOM) to mitigate power quality issues is discussed in this study. In this case, D-STATCOM functions as a shunt active power filter to reduce harmonics caused by non-linear loads. The simulation studies on a PV-based Cascaded-H-Bridge Multi-Level Inverter i.e Solar PV and Cascaded H Bridge MLI are integrated using Selective Harmonic Elimination method with D-STATCOM injected at the load side to improve power quality are presented in this project. The Solar PV system is mathematically modelled using Boost regulator and P&O MPPT technique and to the D-STATCOM the controller is designed utilizing Synchronous Reference Frame Theory (SRFT) out of many control strategies for reactive power compensation, harmonic mitigation, and power factor enhancement as it is more accurate. A 2nd order low pass filter is employed at the load side to reduce the harmonics to some extent, and both 5-level and 7-level models are evaluated. MATLAB/SIMULINK is used for simulation.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88657659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Implementation of Fuzzy Logic Controller for DC–DC step Down Converter","authors":"Shaik Gousia Begum, S. S. Nawaz, G. Anjaneyulu","doi":"10.35940/ijitee.h9251.0610821","DOIUrl":"https://doi.org/10.35940/ijitee.h9251.0610821","url":null,"abstract":"This paper presents the design of a Fuzzy logic controller for a DC-DC step-down converter. Buck converters are step-down regulated converters which convert the DC voltage into a lower level standardized DC voltage. The buck converters are used in solar chargers, battery chargers, quadcopters, industrial and traction motor controllers in automobile industries etc. The major drawback in buck converter is that when input voltage and load change, the output voltage also changes which reduces the overall efficiency of the Buck converter. So here we are using a fuzzy logic controller which responds quickly for perturbations, compared to a linear controllers like P, PI, PID controllers. The Fuzzy logic controllers have become popular in designing control application like washing machine, transmission control, because of their simplicity, low cost and adaptability to complex systems without mathematical modeling So we are implementing a fuzzy logic controller for buck converter which maintains fixed output voltage even when there are fluctuations in supply voltage and load. The fuzzy logic controller for the DC-DC Buck converter is simulated using MATLAB/SIMULINK. The proposed approach is implemented on DC-DC step down converter for an input of 230V and we get the desired output for variations in load or references. This proposed system increases the overall efficiency of the buck converter.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75606891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Snehal Patil, Yash Shah, Payal Narkhede, A. Thakare, Rahul Pitale
{"title":"Gesture Detection using Tensor flow lite Efficient Net Model for Communication and\u0000E-learning Module for Mute and Deaf","authors":"Snehal Patil, Yash Shah, Payal Narkhede, A. Thakare, Rahul Pitale","doi":"10.35940/ijitee.h9204.0610821","DOIUrl":"https://doi.org/10.35940/ijitee.h9204.0610821","url":null,"abstract":"Human communication plays a vital role; without communicating, day-to-day tasks seem difficult to complete. And the world has an almost 5% population that struggles with hearing or speaking disability, which contributes to 430 million people worldwide, and this will grow up to 900million just in the next 25 to 30 years. With the increasing noise pollution, hearing capacity degrades, leading to various hearing problems. The WHO statistics show that 32million kids are acoustically impaired. With disabilities, there are multiple issues these people face, such as lack of learning facilities, job opportunities, communication platforms, etc. These people need a cooperative environment to express, learn at their pace and level of understanding. This paper focuses on developing an application that bridges the gap between these acoustically disabled people and people unknown to their way of communication. The proposed research is an edge device application provides features like a gesture to text, speech to text, e-learning platform, and Alert mechanism. This paper majorly focuses on developing a friendly all in one platform for mute and deaf community for communication, learning and emergency alerts. The research was conducted with two approaches the traditional CNN and Tensorflow lite Efficient Net model to train the ASL (American Sign Language) dataset for the communication platform, where we obtained accuracy of 98.91% and 98.82% respectively. To overcome the computational barriers of traditional CNN approach, Tensorflow lite Efficient Net model was brought into the picture. The proposed methodology would help build a platform for the deaf and mute community to express themselves better and gain wider exposure to the world.","PeriodicalId":23601,"journal":{"name":"VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE","volume":"181 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89815317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}