Pub Date : 2020-11-27DOI: 10.1109/UPCON50219.2020.9376578
Shahrukh Khan, Mohammad Zaid, Arshad Mahmood, Javed Ahmad, A. Alam
A non-isolated quadratic boost high gain dc to dc converter is proposed in this paper. The converter has a wide gain ratio than conventional high gain boost converters. Along with the high voltage gain the proposed topology has a single switch and reduced voltage stress across switch and diodes. Moreover, the converter draws continuous input current which makes the proposed converter an attractive choice for renewable energy applications. Simulation is carried out in PLECS software. The software is specially designed to determine the efficiency of the converter by considering switching and conduction losses. A 50W laboratory prototype of the proposed converter is developed. The theoretical, simulated and experimental results closely agree with each other.
{"title":"A Single Switch High Gain DC-DC converter with Reduced Voltage Stress","authors":"Shahrukh Khan, Mohammad Zaid, Arshad Mahmood, Javed Ahmad, A. Alam","doi":"10.1109/UPCON50219.2020.9376578","DOIUrl":"https://doi.org/10.1109/UPCON50219.2020.9376578","url":null,"abstract":"A non-isolated quadratic boost high gain dc to dc converter is proposed in this paper. The converter has a wide gain ratio than conventional high gain boost converters. Along with the high voltage gain the proposed topology has a single switch and reduced voltage stress across switch and diodes. Moreover, the converter draws continuous input current which makes the proposed converter an attractive choice for renewable energy applications. Simulation is carried out in PLECS software. The software is specially designed to determine the efficiency of the converter by considering switching and conduction losses. A 50W laboratory prototype of the proposed converter is developed. The theoretical, simulated and experimental results closely agree with each other.","PeriodicalId":192190,"journal":{"name":"2020 IEEE 7th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130092973","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}
Pub Date : 2020-11-27DOI: 10.1109/UPCON50219.2020.9376507
A. Saxena, S. Pandey, L. Srivastava
As the cost of the entire embedded system is large in the competitive power market, forecasting future load growth and consequently increasing cost has become extremely important. For this, the calculation of incremental cost is the necessary subject for the future of any well operated system. In addition, the premature detection of horizon to reinforcement due to uncertain load variations also proves beneficial for the system. Keeping the above context, in this paper, an attempt has been made to find the incremental cost and also the time of reinforcement of the system with additional and without additional power. In order to apply all the above mentioned problems correctly and authentically, an attempt has been discussed in this paper to display the results with few lines of Garver 6 bus system and IEEE-30 bus system.
{"title":"Assessment of Incremental Cost and Reinforcement Timing for Uncertain Future Generation and Demand in Competitive Power Market","authors":"A. Saxena, S. Pandey, L. Srivastava","doi":"10.1109/UPCON50219.2020.9376507","DOIUrl":"https://doi.org/10.1109/UPCON50219.2020.9376507","url":null,"abstract":"As the cost of the entire embedded system is large in the competitive power market, forecasting future load growth and consequently increasing cost has become extremely important. For this, the calculation of incremental cost is the necessary subject for the future of any well operated system. In addition, the premature detection of horizon to reinforcement due to uncertain load variations also proves beneficial for the system. Keeping the above context, in this paper, an attempt has been made to find the incremental cost and also the time of reinforcement of the system with additional and without additional power. In order to apply all the above mentioned problems correctly and authentically, an attempt has been discussed in this paper to display the results with few lines of Garver 6 bus system and IEEE-30 bus system.","PeriodicalId":192190,"journal":{"name":"2020 IEEE 7th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129358655","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}
Pub Date : 2020-11-27DOI: 10.1109/upcon50219.2020.9376452
Biswarup Ganguly, A. Chatterjee
This paper presents an extensive control and monitoring of DC motor-based drive for electrical vehicular (EV) application based on Message Queuing Telemetry Transport (MQTT) protocol of internet of things (IoT). MQTT based control is flexible and opens avenue for applications in different domains. The DC motor speed from below rated to twice rated is controlled by an ESP8266 Wi-Fi controller which has full MQTT support. The experimental prototype is capable for better control with Wi-Fi support and has lower power requirement than conventional closed loop control. The proposed control also achieves better accuracy. Suitable simulations and experimental results prove the viability and suitability of the proposed control technique.
{"title":"MQTT Protocol based Extensive Smart Motor Control for Electric Vehicular Application","authors":"Biswarup Ganguly, A. Chatterjee","doi":"10.1109/upcon50219.2020.9376452","DOIUrl":"https://doi.org/10.1109/upcon50219.2020.9376452","url":null,"abstract":"This paper presents an extensive control and monitoring of DC motor-based drive for electrical vehicular (EV) application based on Message Queuing Telemetry Transport (MQTT) protocol of internet of things (IoT). MQTT based control is flexible and opens avenue for applications in different domains. The DC motor speed from below rated to twice rated is controlled by an ESP8266 Wi-Fi controller which has full MQTT support. The experimental prototype is capable for better control with Wi-Fi support and has lower power requirement than conventional closed loop control. The proposed control also achieves better accuracy. Suitable simulations and experimental results prove the viability and suitability of the proposed control technique.","PeriodicalId":192190,"journal":{"name":"2020 IEEE 7th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130101332","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}
Pub Date : 2020-11-27DOI: 10.1109/UPCON50219.2020.9376409
J. Gupta, Bhim Singh
A single stage, bridgeless, and improved efficiency along with revamped supply side performances-based charger, is investigated in this work for the electric vehicles (EVs) charging. A conventional buck-boost DC-DC converter is considered for the implementation of the charging process and a major drawback of an orthodox converter is alleviated by getting positive voltage polarity at the output. Moreover, the essential feature of isolation is inserted along with involving discontinuous inductor current conduction mode (DICCM) of the transformer magnetizing inductance, for enhancing safety feature in the charger. The DICCM ensures safe operation of the transformer and makes control implementation easier and cost effective. Moreover, the zero current switching of devices allows higher switching frequency operation, which further reduces the volume of the transformer and enhances power density without increasing switching losses. Additionally, the front end bridge rectifier and corresponding conduction losses are removed by utilizing bridgeless configuration. The overall performance of the charger is simulated by using Simscape toolbox of MATLAB environment while operating under different modes of a charging process. Furthermore, the operation of the charger is validated against the wide fluctuations in supply voltages. Finally, simulated performance is analyzed and obtained results are provided for authentication of the design and operation of the charger.
{"title":"A Single Phase Pre-Regulated High Power-Factor Bridgeless Isolated AC-DC Converter for EV Charging Application","authors":"J. Gupta, Bhim Singh","doi":"10.1109/UPCON50219.2020.9376409","DOIUrl":"https://doi.org/10.1109/UPCON50219.2020.9376409","url":null,"abstract":"A single stage, bridgeless, and improved efficiency along with revamped supply side performances-based charger, is investigated in this work for the electric vehicles (EVs) charging. A conventional buck-boost DC-DC converter is considered for the implementation of the charging process and a major drawback of an orthodox converter is alleviated by getting positive voltage polarity at the output. Moreover, the essential feature of isolation is inserted along with involving discontinuous inductor current conduction mode (DICCM) of the transformer magnetizing inductance, for enhancing safety feature in the charger. The DICCM ensures safe operation of the transformer and makes control implementation easier and cost effective. Moreover, the zero current switching of devices allows higher switching frequency operation, which further reduces the volume of the transformer and enhances power density without increasing switching losses. Additionally, the front end bridge rectifier and corresponding conduction losses are removed by utilizing bridgeless configuration. The overall performance of the charger is simulated by using Simscape toolbox of MATLAB environment while operating under different modes of a charging process. Furthermore, the operation of the charger is validated against the wide fluctuations in supply voltages. Finally, simulated performance is analyzed and obtained results are provided for authentication of the design and operation of the charger.","PeriodicalId":192190,"journal":{"name":"2020 IEEE 7th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126436571","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}
This paper explores the conversion of Devanagari Hindi Braille, first to text, and subsequently to speech. The first part of the implementation is the conversion of Hindi Braille to text, in which two approaches are used for Braille character recognition: a conventional sequence-mapping approach and a deep learning-based method. The second part of the paper deals with the conversion of Hindi text to speech, in which text is converted to speech by concatenating speech samples corresponding to Hindi vowels and consonants. Successful conversion of Hindi Braille to text and, consequently, speech, yielded two forms of output. Generated samples of Hindi Braille letters, as well as extracts from a Hindi Braille textbook, were used to create an image dataset. A Hindi speech corpus was created using speech coefficients extracted from a recorded audio sample. The authors achieved an accuracy of 100 percent using the conventional method of Hindi Braille to text conversion and an accuracy of 96 percent using the deep learning approach. Experts also validated the quality of Hindi speech generated from the text-to-speech model, based on factors such as clarity of speech, pronunciation, sound quality, and speed of speech.
{"title":"Conversion of Hindi Braille to Speech using Image and Speech Processing","authors":"Parmesh Kaur, Sahana Ramu, Sheetal Panchakshari, Niranjana Krupa","doi":"10.1109/UPCON50219.2020.9376566","DOIUrl":"https://doi.org/10.1109/UPCON50219.2020.9376566","url":null,"abstract":"This paper explores the conversion of Devanagari Hindi Braille, first to text, and subsequently to speech. The first part of the implementation is the conversion of Hindi Braille to text, in which two approaches are used for Braille character recognition: a conventional sequence-mapping approach and a deep learning-based method. The second part of the paper deals with the conversion of Hindi text to speech, in which text is converted to speech by concatenating speech samples corresponding to Hindi vowels and consonants. Successful conversion of Hindi Braille to text and, consequently, speech, yielded two forms of output. Generated samples of Hindi Braille letters, as well as extracts from a Hindi Braille textbook, were used to create an image dataset. A Hindi speech corpus was created using speech coefficients extracted from a recorded audio sample. The authors achieved an accuracy of 100 percent using the conventional method of Hindi Braille to text conversion and an accuracy of 96 percent using the deep learning approach. Experts also validated the quality of Hindi speech generated from the text-to-speech model, based on factors such as clarity of speech, pronunciation, sound quality, and speed of speech.","PeriodicalId":192190,"journal":{"name":"2020 IEEE 7th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121618410","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}
Pub Date : 2020-11-27DOI: 10.1109/upcon50219.2020.9376431
D. Singh, A. Singh
Purpose: Breast thermography is an emerging adjunct screening tool to mammography in early breast cancer detection due to its non-invasiveness and safety. In this paper, the finite element method (FEM) based steady-state and transient thermal analysis of gravity shaped realistic breast model, is presented. The main objective of this study is to analyze the effectiveness of numerical simulation in measuring the thermal profile of small-sized and deep tumors in the breast model. Methods: COMSOL Multiphysics software is used to simulate bioheat transfer in this study. Thickness/ Dimensions in six tissue layers: epidermis, reticular dermis, papillary dermis, fat, gland, muscle, and axisymmetric tumor in both the mentioned models, are inversely calculated for four density compositions, extremely dense (ED), heterogeneously dense (HD), scattered fibro glandular (SF) and predominantly fatty (PF). Different steady-state and transient studies are performed on 2D multi-layered breast models by varying tumor depth and radius of tumor from 20 mm to 60 mm and 2.5mm to 7.5 mm respectively. Results: Steady state contrast and transient contrast for SF and PF compositions are high which enable tumor depth detection up to 0.03m for small sized tumors. Conclusion: By proper calibration of thermal model with clinical data, it is possible to quantify thermal parameters which will improve monitoring of tumor response to cancer treatment.
{"title":"Tumor parameter estimation of realistic breast model having different densities by steady state and transient thermal analysis","authors":"D. Singh, A. Singh","doi":"10.1109/upcon50219.2020.9376431","DOIUrl":"https://doi.org/10.1109/upcon50219.2020.9376431","url":null,"abstract":"Purpose: Breast thermography is an emerging adjunct screening tool to mammography in early breast cancer detection due to its non-invasiveness and safety. In this paper, the finite element method (FEM) based steady-state and transient thermal analysis of gravity shaped realistic breast model, is presented. The main objective of this study is to analyze the effectiveness of numerical simulation in measuring the thermal profile of small-sized and deep tumors in the breast model. Methods: COMSOL Multiphysics software is used to simulate bioheat transfer in this study. Thickness/ Dimensions in six tissue layers: epidermis, reticular dermis, papillary dermis, fat, gland, muscle, and axisymmetric tumor in both the mentioned models, are inversely calculated for four density compositions, extremely dense (ED), heterogeneously dense (HD), scattered fibro glandular (SF) and predominantly fatty (PF). Different steady-state and transient studies are performed on 2D multi-layered breast models by varying tumor depth and radius of tumor from 20 mm to 60 mm and 2.5mm to 7.5 mm respectively. Results: Steady state contrast and transient contrast for SF and PF compositions are high which enable tumor depth detection up to 0.03m for small sized tumors. Conclusion: By proper calibration of thermal model with clinical data, it is possible to quantify thermal parameters which will improve monitoring of tumor response to cancer treatment.","PeriodicalId":192190,"journal":{"name":"2020 IEEE 7th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126822206","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}
Pub Date : 2020-11-27DOI: 10.1109/UPCON50219.2020.9376450
H. Rai, K. Chatterjee, Chandra Mukherjee
Automatic and accurate prognosis of cardiac arrhythmias from ECG big data is a very challenging task for the diagnosis and treatment of heart diseases. Hence, we have proposed a hybrid CNN-LSTM deep learning model for accurate and automatic prediction of cardiac arrhythmias using the ECG big dataset. The total 123,998 ECG beats from combined benchmark datasets “MIT-BIH arrhythmias database” and “PTB diagnostic database” are employed for validation of the model performance. The ECG beat time interval and its gradient value is directly considered as the feature and given as the input to the proposed model. The Model performance was verified using six types of evaluation metrics and compared the result with the state-of-art method. The overall and average accuracy percentage obtained using the proposed model is 99% and 99.7%.
{"title":"Hybrid CNN-LSTM model for automatic prediction of cardiac arrhythmias from ECG big data","authors":"H. Rai, K. Chatterjee, Chandra Mukherjee","doi":"10.1109/UPCON50219.2020.9376450","DOIUrl":"https://doi.org/10.1109/UPCON50219.2020.9376450","url":null,"abstract":"Automatic and accurate prognosis of cardiac arrhythmias from ECG big data is a very challenging task for the diagnosis and treatment of heart diseases. Hence, we have proposed a hybrid CNN-LSTM deep learning model for accurate and automatic prediction of cardiac arrhythmias using the ECG big dataset. The total 123,998 ECG beats from combined benchmark datasets “MIT-BIH arrhythmias database” and “PTB diagnostic database” are employed for validation of the model performance. The ECG beat time interval and its gradient value is directly considered as the feature and given as the input to the proposed model. The Model performance was verified using six types of evaluation metrics and compared the result with the state-of-art method. The overall and average accuracy percentage obtained using the proposed model is 99% and 99.7%.","PeriodicalId":192190,"journal":{"name":"2020 IEEE 7th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123049784","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}
Pub Date : 2020-11-27DOI: 10.1109/UPCON50219.2020.9376398
G. K. Taneja, Gaurav Modi, Bhim Singh, Ashu Verma
The diesel generator (DG) set is used to energize the load in remote areas. A battery energy storage (BES) integrated solar PV (Photovoltaic) system (SPVS) is presented in this work, to reduce the dependence on the DG set for power generation. The DG set operates only when the solar PV power and BES are not capable to supply power to loads. In a daytime, the power to loads is supplied by the solar PV array and BES. In the nighttime, the BES supplies power to loads until it discharges to its lower limit. The DG set is synchronized at the point of common coupling (PCC) only when both PV array and the BES cannot able to cope load demand and it always operates at its fuel economy zone (FCZ) to reduce the operational cost. An energy management strategy is developed to reduce the operating hours of the DG set and to reduce its unwanted switching. The SPVS also improves the power factor and power quality (as par IEEE std. 519) in a DG set. The seamless operation is incorporated in the control so that IEEE std. 1547 upholds when system changes its operating mode. Performance of this system is exhibited and validated through simulated results in a developed Simulink model.
{"title":"Islanded Solar PV-BES-DG Set for Remote Areas","authors":"G. K. Taneja, Gaurav Modi, Bhim Singh, Ashu Verma","doi":"10.1109/UPCON50219.2020.9376398","DOIUrl":"https://doi.org/10.1109/UPCON50219.2020.9376398","url":null,"abstract":"The diesel generator (DG) set is used to energize the load in remote areas. A battery energy storage (BES) integrated solar PV (Photovoltaic) system (SPVS) is presented in this work, to reduce the dependence on the DG set for power generation. The DG set operates only when the solar PV power and BES are not capable to supply power to loads. In a daytime, the power to loads is supplied by the solar PV array and BES. In the nighttime, the BES supplies power to loads until it discharges to its lower limit. The DG set is synchronized at the point of common coupling (PCC) only when both PV array and the BES cannot able to cope load demand and it always operates at its fuel economy zone (FCZ) to reduce the operational cost. An energy management strategy is developed to reduce the operating hours of the DG set and to reduce its unwanted switching. The SPVS also improves the power factor and power quality (as par IEEE std. 519) in a DG set. The seamless operation is incorporated in the control so that IEEE std. 1547 upholds when system changes its operating mode. Performance of this system is exhibited and validated through simulated results in a developed Simulink model.","PeriodicalId":192190,"journal":{"name":"2020 IEEE 7th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127707173","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}
Pub Date : 2020-11-27DOI: 10.1109/UPCON50219.2020.9376568
Mayank Sharma
In this paper, a data-driven comparison of the novel coronavirus strain (the SARS-CoV-2) with two bat-derived SARS-like coronaviruses, bat-SL-CoVZC45 and bat-SL-CoVZXC21 is presented. Biological research has shown that the SARS-CoV-2 shows sequence identity most similar to these two bat-derived viruses. Through comparison of guanine-cytosine content and oligonucleotide composition, variations in their genomes were observed. These genomes were then translated into proteins and their amino acid concentrations were compared. Finally, various properties of the 4 important structural proteins (envelope, membrane, spike and nucleocapsid proteins) such as aromaticity, isoelectric point, instability index and amino acid count were compared for the three coronaviruses. Not only does this paper present useful insights on the new virus strain, but also on the properties that distinguish it from other similar coronaviruses.
{"title":"The SARS-CoV-2 and its Similarity to Other Bat-Derived SARS-like Coronaviruses: A Data-Driven Study","authors":"Mayank Sharma","doi":"10.1109/UPCON50219.2020.9376568","DOIUrl":"https://doi.org/10.1109/UPCON50219.2020.9376568","url":null,"abstract":"In this paper, a data-driven comparison of the novel coronavirus strain (the SARS-CoV-2) with two bat-derived SARS-like coronaviruses, bat-SL-CoVZC45 and bat-SL-CoVZXC21 is presented. Biological research has shown that the SARS-CoV-2 shows sequence identity most similar to these two bat-derived viruses. Through comparison of guanine-cytosine content and oligonucleotide composition, variations in their genomes were observed. These genomes were then translated into proteins and their amino acid concentrations were compared. Finally, various properties of the 4 important structural proteins (envelope, membrane, spike and nucleocapsid proteins) such as aromaticity, isoelectric point, instability index and amino acid count were compared for the three coronaviruses. Not only does this paper present useful insights on the new virus strain, but also on the properties that distinguish it from other similar coronaviruses.","PeriodicalId":192190,"journal":{"name":"2020 IEEE 7th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134593952","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}
Pub Date : 2020-11-27DOI: 10.1109/UPCON50219.2020.9376463
Sukriti Tiwari, Ashwani Kumar
The emergence of renewable sources of energy in distribution networks has attracted attention to more powerful management methods from the distribution companies. Network reconfiguration that is still among emerging concepts, can carry the operation required to manage the varying output of renewable resources, owing to the smart grid concept. This paper proposes a hybrid methodology based on Taguchi Method (TM) and Particle Swarm Optimization (PSO), that is implemented in the presence of Distributed Generation (DG) to mitigate the active power losses and improve the voltage profile of radial distribution network. Considering the standard IEEE 33-nodes distribution network, various scenarios with DG integration and equivalent performance analysis are conducted and the corresponding findings are summarized and discussed.
{"title":"A Robust Taguchi Particle Swarm Optimization Approach for Network Reconfiguration with Distributed Generation","authors":"Sukriti Tiwari, Ashwani Kumar","doi":"10.1109/UPCON50219.2020.9376463","DOIUrl":"https://doi.org/10.1109/UPCON50219.2020.9376463","url":null,"abstract":"The emergence of renewable sources of energy in distribution networks has attracted attention to more powerful management methods from the distribution companies. Network reconfiguration that is still among emerging concepts, can carry the operation required to manage the varying output of renewable resources, owing to the smart grid concept. This paper proposes a hybrid methodology based on Taguchi Method (TM) and Particle Swarm Optimization (PSO), that is implemented in the presence of Distributed Generation (DG) to mitigate the active power losses and improve the voltage profile of radial distribution network. Considering the standard IEEE 33-nodes distribution network, various scenarios with DG integration and equivalent performance analysis are conducted and the corresponding findings are summarized and discussed.","PeriodicalId":192190,"journal":{"name":"2020 IEEE 7th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133443339","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：