Pub Date : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836588
Tafsir Ahmed Khan, Syed Abdullah-Al-Nahid, Md. Abu Taseen, S. Tasnim, T. Aziz
Generation Expansion Planning (GEP) is determining the type, location and number of new generating stations (GSs). In this paper, a GEP problem is formed by considering three types of GSs and then their possible combinations are sorted. Infeasible combinations are screened out based on the capacity limit and maximum allowable budget. The best solution with minimum cost is recognized by optimizing the feasible combinations using Genetic Algorithm (GA). Share of fuel mix (gas and oil) for winter and other seasons are considered as the constraints. In simulation, 14 out of 75 combinations came out feasible. GA was used to find the best combination which had an optimized amount of gas and oil usage. The results display the superiority of proposed methodology in contrast with other studies in finding the best solution of the GEP problem with minimum iteration.
{"title":"Generation Expansion Planning Optimized by Genetic Algorithm Considering Seasonal Impact and Fuel Price","authors":"Tafsir Ahmed Khan, Syed Abdullah-Al-Nahid, Md. Abu Taseen, S. Tasnim, T. Aziz","doi":"10.1109/icaeee54957.2022.9836588","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836588","url":null,"abstract":"Generation Expansion Planning (GEP) is determining the type, location and number of new generating stations (GSs). In this paper, a GEP problem is formed by considering three types of GSs and then their possible combinations are sorted. Infeasible combinations are screened out based on the capacity limit and maximum allowable budget. The best solution with minimum cost is recognized by optimizing the feasible combinations using Genetic Algorithm (GA). Share of fuel mix (gas and oil) for winter and other seasons are considered as the constraints. In simulation, 14 out of 75 combinations came out feasible. GA was used to find the best combination which had an optimized amount of gas and oil usage. The results display the superiority of proposed methodology in contrast with other studies in finding the best solution of the GEP problem with minimum iteration.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133676779","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836383
Md. Sohel Rana, Mamun Bepari, K. Ghosh, M. Abedin
Nowadays power inverters are widely used in various applications which range from domestic to industrial facilities. The Pulse Width Modulation (PWM) techniques are extensively used for the controlling of inverter circuit in which dead time, duty cycle, and frequency are important performance parameters. In the case of controlling multiple inverters with a single controller, control signals with embedded dead-time for all the inverters may lead to poor performance for some inverters due to shoot through and controlling of multiple inverters with common duty cycle and frequency cannot fulfill the requirement. Moreover, the use of an individual controller for each inverter is not cost-effective. In this work, the PWM switching strategies are designed with Verilog Hardware Description Language (HDL) and implemented using Xilinx Spartan-6 Nexys3 FPGA with precise control of dead time, duty cycle and frequency. This FPGA based controller enables us to control any inverter designed for a specific purpose and the same inverter for different applications by configuring its frequency and duty cycle. For the present work, we have generated six PWM signals with three different dead times and duty cycles which can control three single-phase PWM inverters with specified dead time and found that FPGA implementation provide desired output with negligible distortion avoiding shoot through.
{"title":"FPGA Implementation of Multiple Single Phase PWM Inverters with Configurable Duty Cycle and Dead Time","authors":"Md. Sohel Rana, Mamun Bepari, K. Ghosh, M. Abedin","doi":"10.1109/icaeee54957.2022.9836383","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836383","url":null,"abstract":"Nowadays power inverters are widely used in various applications which range from domestic to industrial facilities. The Pulse Width Modulation (PWM) techniques are extensively used for the controlling of inverter circuit in which dead time, duty cycle, and frequency are important performance parameters. In the case of controlling multiple inverters with a single controller, control signals with embedded dead-time for all the inverters may lead to poor performance for some inverters due to shoot through and controlling of multiple inverters with common duty cycle and frequency cannot fulfill the requirement. Moreover, the use of an individual controller for each inverter is not cost-effective. In this work, the PWM switching strategies are designed with Verilog Hardware Description Language (HDL) and implemented using Xilinx Spartan-6 Nexys3 FPGA with precise control of dead time, duty cycle and frequency. This FPGA based controller enables us to control any inverter designed for a specific purpose and the same inverter for different applications by configuring its frequency and duty cycle. For the present work, we have generated six PWM signals with three different dead times and duty cycles which can control three single-phase PWM inverters with specified dead time and found that FPGA implementation provide desired output with negligible distortion avoiding shoot through.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"2001 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131799015","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836428
Mohammad Hanif, Md. Saiful Islam
Due to the low power storing capability, extending the life span of microsensors in wireless sensor networks (WSN) is a difficult task. To maximize the lifespan of microsensors by reducing the dissipation of energy, Low Energy Adaptive Clustering Hierarchy (LEACH) protocol is utilized. In this study, the LEACH protocol's threshold selection is modified in order to identify the best cluster head to extend the lifetime of WSN. The authors looked at two modified LEACH protocols (mLEACH1 and mLEACH2) to minimize energy consumption, as well as to improve the sensor nodes' lifespan. Furthermore, the performance of these two modified LEACH protocols is evaluated by comparing them to the conventional LEACH protocol with respect to number of dead nodes and amount of energy left in the network. According to the analysis of FND (first node dead) and HNA (half node alive) performances, the mLEACH1 can improve the sensor network's lifetime by 4.24% to 8.67% compared to traditional LEACH. Moreover, by lowering sensor nodes' death rate and maintaining the WSN's energy dissipation rate lower for a longer period of time, mLEACH2 can extend the network's lifespan by 253.73% and 331.5% for FND and HNA, respectively, when compared to standard LEACH.
{"title":"Life Time Enhancement of Wireless Sensor Network by Modified Threshold of LEACH Protocol","authors":"Mohammad Hanif, Md. Saiful Islam","doi":"10.1109/icaeee54957.2022.9836428","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836428","url":null,"abstract":"Due to the low power storing capability, extending the life span of microsensors in wireless sensor networks (WSN) is a difficult task. To maximize the lifespan of microsensors by reducing the dissipation of energy, Low Energy Adaptive Clustering Hierarchy (LEACH) protocol is utilized. In this study, the LEACH protocol's threshold selection is modified in order to identify the best cluster head to extend the lifetime of WSN. The authors looked at two modified LEACH protocols (mLEACH1 and mLEACH2) to minimize energy consumption, as well as to improve the sensor nodes' lifespan. Furthermore, the performance of these two modified LEACH protocols is evaluated by comparing them to the conventional LEACH protocol with respect to number of dead nodes and amount of energy left in the network. According to the analysis of FND (first node dead) and HNA (half node alive) performances, the mLEACH1 can improve the sensor network's lifetime by 4.24% to 8.67% compared to traditional LEACH. Moreover, by lowering sensor nodes' death rate and maintaining the WSN's energy dissipation rate lower for a longer period of time, mLEACH2 can extend the network's lifespan by 253.73% and 331.5% for FND and HNA, respectively, when compared to standard LEACH.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"17 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131550782","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836477
M. Alam, Moin Uddin Siddique, H. Sakib, Imtiaz Hossain, Iftekher Alam Rahat
A hybrid energy system combines two or more renewable energy sources to improve system efficiency and supply balance. Vehicles will be a huge source of power. Among all renewable energy sources, solar and wind are the most efficient to attach to a car. The Hybrid Renewable Energy Vehicle System (HREVS) proposes charging the vehicle's battery with hybrid renewable energy sources. This work's major goals are to minimize vehicle dependence on fossil fuels, increase reliance on renewable energy sources, and lower fuel costs. Development of a full battery charging system each photovoltaic and wind model is designed separately, then combined with a charge controller and a battery. A maximum power point tracking system and code have been developed for solar tracking using the Perturb and Observe (P & O) method. State of Charge (SOC) controls the battery's charging and draining. We tried to address the issues raised above. A desired output result from a hybrid energy configuration has also been explored. All simulation and setup are done in MATLAB-SIMULINK. Blender creates a 3D model of a hybrid car. A minor expansion created and controlled using Arduino-UNO is also included. The results of the experiments and simulations suggest that the proposed system can generate power and reduce fuel usage.
{"title":"Reducing Fuel Dependency of Electric Vehicles using Hybrid Renewable Energy System","authors":"M. Alam, Moin Uddin Siddique, H. Sakib, Imtiaz Hossain, Iftekher Alam Rahat","doi":"10.1109/icaeee54957.2022.9836477","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836477","url":null,"abstract":"A hybrid energy system combines two or more renewable energy sources to improve system efficiency and supply balance. Vehicles will be a huge source of power. Among all renewable energy sources, solar and wind are the most efficient to attach to a car. The Hybrid Renewable Energy Vehicle System (HREVS) proposes charging the vehicle's battery with hybrid renewable energy sources. This work's major goals are to minimize vehicle dependence on fossil fuels, increase reliance on renewable energy sources, and lower fuel costs. Development of a full battery charging system each photovoltaic and wind model is designed separately, then combined with a charge controller and a battery. A maximum power point tracking system and code have been developed for solar tracking using the Perturb and Observe (P & O) method. State of Charge (SOC) controls the battery's charging and draining. We tried to address the issues raised above. A desired output result from a hybrid energy configuration has also been explored. All simulation and setup are done in MATLAB-SIMULINK. Blender creates a 3D model of a hybrid car. A minor expansion created and controlled using Arduino-UNO is also included. The results of the experiments and simulations suggest that the proposed system can generate power and reduce fuel usage.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124320375","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836541
Tasmima Noushiba Mahbub, M. Yousuf, M.N. Uddin
Every year a significant number of women dies because of suffering from breast cancer all over the world. The rate of mortality due to breast cancer can be decreased if the cancer and the stage is early detected. Early Diagnosis is not possible in every corner of all countries over the world because of the lack of experienced consultant or doctor. A novel approach is presented in this study based on convolutional neural network and fuzzy analytical hierarchy process for diagnosis of breast cancer along with stage identification. The proposed model detects breast cancer from mammographic images using modified convolutional neural network. Then identifies the stage using fuzzy analytical hierarchy process model which is comprised of 3 layers (goal, criteria and alternative). Proposed modified convolutional neural network model achieves 98.75% validation accuracy on detecting breast cancer from mammograms as well as the fuzzy AHP model efficiently identifies the stage of the cancer.
{"title":"A Modified CNN And Fuzzy AHP Based Breast Cancer Stage Detection System","authors":"Tasmima Noushiba Mahbub, M. Yousuf, M.N. Uddin","doi":"10.1109/icaeee54957.2022.9836541","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836541","url":null,"abstract":"Every year a significant number of women dies because of suffering from breast cancer all over the world. The rate of mortality due to breast cancer can be decreased if the cancer and the stage is early detected. Early Diagnosis is not possible in every corner of all countries over the world because of the lack of experienced consultant or doctor. A novel approach is presented in this study based on convolutional neural network and fuzzy analytical hierarchy process for diagnosis of breast cancer along with stage identification. The proposed model detects breast cancer from mammographic images using modified convolutional neural network. Then identifies the stage using fuzzy analytical hierarchy process model which is comprised of 3 layers (goal, criteria and alternative). Proposed modified convolutional neural network model achieves 98.75% validation accuracy on detecting breast cancer from mammograms as well as the fuzzy AHP model efficiently identifies the stage of the cancer.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125316958","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836390
Foez Ahmed, Arif Ahammad
With the advancement of modern lifestyle, Smart Switchboards are becoming a new trend. They not only provide remote switching, but also allow us to set schedules for automatically switching the appliances. However, most Smart Switchboards do not come with the facility of monitoring the electrical power consumption or detecting faults in the electrical equipment. Therefore, the aim of this research is to design a compact and effective system that can monitor the behavior of the electrical appliances and detect faults, and also detect presence of any person in the designated area and notify the authorized person in case of any hazards. Moreover, the data stored by the system is utilized to calculate the total power consumption. By implementing this system, electrical power is utilized more effectively. With further research and cost minimization through industrialized processing, this type of Smart Switchboards will become the norm.
{"title":"Design and Development of an IoT based Power Monitoring and Management System","authors":"Foez Ahmed, Arif Ahammad","doi":"10.1109/icaeee54957.2022.9836390","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836390","url":null,"abstract":"With the advancement of modern lifestyle, Smart Switchboards are becoming a new trend. They not only provide remote switching, but also allow us to set schedules for automatically switching the appliances. However, most Smart Switchboards do not come with the facility of monitoring the electrical power consumption or detecting faults in the electrical equipment. Therefore, the aim of this research is to design a compact and effective system that can monitor the behavior of the electrical appliances and detect faults, and also detect presence of any person in the designated area and notify the authorized person in case of any hazards. Moreover, the data stored by the system is utilized to calculate the total power consumption. By implementing this system, electrical power is utilized more effectively. With further research and cost minimization through industrialized processing, this type of Smart Switchboards will become the norm.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125593057","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836426
M. Halim, Ruma
This paper aims to assess the impact of high voltage discharge on Chlamydomonas algae. Chlamydomonas has been chosen as a sample in this study due to its availability in Bangladesh. It grows on the surface of the water and causes various adverse effects on humans, environment, and other animal beings. There are various methods to inactivate the harmful effects of algae. The use of chemicals (like chlorine) produces harmful by-products and also affects human health. The application of high voltage discharge is an effective technique, which has a great impact on removing harmful algae. It has been found that discharge starts as a streamer with thin light intensity, then spreads in the form of branching on the surface of the water, and then converts to spark discharge with increasing input voltage. The application of discharge results in the complete deactivation of Chlamydomonas algae. The results and findings of this study will lead to developing more accurate knowledge about the real-life application of high voltage discharge.
{"title":"Analysis of the Impact of Various Properties of High Voltage Discharge for Deactivation of Water Algae","authors":"M. Halim, Ruma","doi":"10.1109/icaeee54957.2022.9836426","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836426","url":null,"abstract":"This paper aims to assess the impact of high voltage discharge on Chlamydomonas algae. Chlamydomonas has been chosen as a sample in this study due to its availability in Bangladesh. It grows on the surface of the water and causes various adverse effects on humans, environment, and other animal beings. There are various methods to inactivate the harmful effects of algae. The use of chemicals (like chlorine) produces harmful by-products and also affects human health. The application of high voltage discharge is an effective technique, which has a great impact on removing harmful algae. It has been found that discharge starts as a streamer with thin light intensity, then spreads in the form of branching on the surface of the water, and then converts to spark discharge with increasing input voltage. The application of discharge results in the complete deactivation of Chlamydomonas algae. The results and findings of this study will lead to developing more accurate knowledge about the real-life application of high voltage discharge.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116700516","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836377
Sadia Enam, M. Rana
This study evaluates the performance of a textile antenna close to a human body phantom developed for on-body wireless communication applications. A rectangular textile antenna (RTA) with fabric (wash cotton, polycot, and polyester) substrate has been designed in 2.45 GHz WLAN band. The antennas are also analyzed in close proximity (2 mm away) to a three-layered (skin, fat, and muscle) flat human body tissue model (HBTM). A frequency detuning and reduction in antenna performance are noticed after applying flat HBTM. The curtain cotton made RMPA shows better return loss (−54.5843 dB and −49.7967 dB), peak directivity (9.220 dBi and 9.106 dBi), gain (7.965 dBi and 7.732 dBi), and efficiency (76.12% and 74.25%) for both off body and on body by maintaining a bandwidth of 100.3 MHz and 99.8 MHz. The Specific Absorption Rate (SAR) recorded for RMPA (curtain cotton) is 0.0277 W/kg< 2 W/kg averaged over 10g tissue.
{"title":"Impact of Body Proximity on Body Worn Textile Antenna Performance","authors":"Sadia Enam, M. Rana","doi":"10.1109/icaeee54957.2022.9836377","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836377","url":null,"abstract":"This study evaluates the performance of a textile antenna close to a human body phantom developed for on-body wireless communication applications. A rectangular textile antenna (RTA) with fabric (wash cotton, polycot, and polyester) substrate has been designed in 2.45 GHz WLAN band. The antennas are also analyzed in close proximity (2 mm away) to a three-layered (skin, fat, and muscle) flat human body tissue model (HBTM). A frequency detuning and reduction in antenna performance are noticed after applying flat HBTM. The curtain cotton made RMPA shows better return loss (−54.5843 dB and −49.7967 dB), peak directivity (9.220 dBi and 9.106 dBi), gain (7.965 dBi and 7.732 dBi), and efficiency (76.12% and 74.25%) for both off body and on body by maintaining a bandwidth of 100.3 MHz and 99.8 MHz. The Specific Absorption Rate (SAR) recorded for RMPA (curtain cotton) is 0.0277 W/kg< 2 W/kg averaged over 10g tissue.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116077090","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836351
Sanjid-E-Elahi, M. Rahman, Md. Alamgir Hossain, M. Sikder
This paper presents several optimized control methods for voltage control of an islanded microgrid connected through an inverter system. The control methodology of the microgrid is based on converter control using the PWM. Optimal controllers such as Linear Quadratic Regulator (LQR), Linear Quadratic Integrator (LQI) and Linear Quadratic Gaussian (LQG) are developed to control the voltage of converters. A robust optimal controller provides fast dynamic response and is capable of resisting voltage fluctuations from instantaneous reference grid voltage; to control the inverter voltage that can be utilized in a microgrid (MG). The proposed control strategies basically allow the MG to be controlled with minimum control input while impeding voltage deviation from a reference voltage during disturbances in the power system, such as sudden load change. The performance of designed controllers has been compared against linear and non-linear loads with several conditions. The studied systems are modeled and simulated in the MATLAB/SIMULINK environment and the comparison results show that both LQI and LQG controllers provide good tracking and reasonable performance.
{"title":"A Comparative Study of Robust Optimal Controllers for Grid Voltage Control in Islanded Microgrids","authors":"Sanjid-E-Elahi, M. Rahman, Md. Alamgir Hossain, M. Sikder","doi":"10.1109/icaeee54957.2022.9836351","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836351","url":null,"abstract":"This paper presents several optimized control methods for voltage control of an islanded microgrid connected through an inverter system. The control methodology of the microgrid is based on converter control using the PWM. Optimal controllers such as Linear Quadratic Regulator (LQR), Linear Quadratic Integrator (LQI) and Linear Quadratic Gaussian (LQG) are developed to control the voltage of converters. A robust optimal controller provides fast dynamic response and is capable of resisting voltage fluctuations from instantaneous reference grid voltage; to control the inverter voltage that can be utilized in a microgrid (MG). The proposed control strategies basically allow the MG to be controlled with minimum control input while impeding voltage deviation from a reference voltage during disturbances in the power system, such as sudden load change. The performance of designed controllers has been compared against linear and non-linear loads with several conditions. The studied systems are modeled and simulated in the MATLAB/SIMULINK environment and the comparison results show that both LQI and LQG controllers provide good tracking and reasonable performance.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116109572","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}
The high levels of blood sugar (or glucose) that occur in diabetes can damage organs such as the heart, blood vessels, eyes, kidneys, and nerves in time. Type 2 diabetes typically affects adults and is most prevalent in adults due to an insufficient supply of insulin. On the other hand, Diabetes type 1, also known as juvenile diabetes or insulin-dependent diabetes, is a chronic disease in which the body cannot produce insulin on its own. Diabetes prevalence has increased over the past three decades at every income level. Affordable treatment is vital for those with diabetes. Several cost-effective interventions can improve patient outcomes. However, a diagnosis of this disease can be costly and difficult. The aim of this research is, therefore, to demonstrate a comparative analysis and improved performance using deep learning to classify diabetic and non-diabetic patients that will provide a feasible way to diagnose this chronic disease. In this work, we used a neural network model with very low variance applying the synthetic minority oversampling technique to augment and improve the variety of data. By removing imbalances and classifying diabetes based on different features, our model achieved an accuracy of approximately 99 % for training and 98 % for validation.
{"title":"Diabetes Complication Prediction using Deep Learning-Based Analytics","authors":"Takrim Rahman Albi, Md Nakhla Rafi, Tasfia Anika Bushra, Dewan Ziaul Karim","doi":"10.1109/icaeee54957.2022.9836401","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836401","url":null,"abstract":"The high levels of blood sugar (or glucose) that occur in diabetes can damage organs such as the heart, blood vessels, eyes, kidneys, and nerves in time. Type 2 diabetes typically affects adults and is most prevalent in adults due to an insufficient supply of insulin. On the other hand, Diabetes type 1, also known as juvenile diabetes or insulin-dependent diabetes, is a chronic disease in which the body cannot produce insulin on its own. Diabetes prevalence has increased over the past three decades at every income level. Affordable treatment is vital for those with diabetes. Several cost-effective interventions can improve patient outcomes. However, a diagnosis of this disease can be costly and difficult. The aim of this research is, therefore, to demonstrate a comparative analysis and improved performance using deep learning to classify diabetic and non-diabetic patients that will provide a feasible way to diagnose this chronic disease. In this work, we used a neural network model with very low variance applying the synthetic minority oversampling technique to augment and improve the variety of data. By removing imbalances and classifying diabetes based on different features, our model achieved an accuracy of approximately 99 % for training and 98 % for validation.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"46 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129383404","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}
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