Pub Date : 2022-12-02DOI: 10.1109/UPCON56432.2022.9986384
Kunal Thakur, Ramesh Kumar Bhukya
Today, numerous biometric systems have been suggested and created. Most used among them are face, fingerprint, and voice recognition. Each of them has their own advantages and disadvantages. Discussing about the automatic speaker verification (ASV), speech signal is a natural signal which one can easily obtain even from a telephone call. Research in this area is carried out from decades. This speaker verification technology has advanced in recent years and has become a genuine method for biometric systems. Using an adaptable Gaussian Mixture Model (GMM-UBM), a text-independent speaker verification (TISV) technique has been developed and compared with state-of-art I-vector based speaker recognition system in this research. Parameters for universal background model (UBM) are trained using the EM (Expectation maximization) and MAP adaptation method is used for training speaker models. Multiple false acceptance and false rejection rates are calculated by changing the threshold values for comparison. The results are shown in equal error rate (EER) for both the GMM-UBM, and I-vector based ASV systems, and the lowest EER is found to be 5.31% and 4.74%, respectively, after adjusting the threshold settings and number of Gaussian mixtures utilized.
{"title":"Speaker Authentication Using GMM-UBM","authors":"Kunal Thakur, Ramesh Kumar Bhukya","doi":"10.1109/UPCON56432.2022.9986384","DOIUrl":"https://doi.org/10.1109/UPCON56432.2022.9986384","url":null,"abstract":"Today, numerous biometric systems have been suggested and created. Most used among them are face, fingerprint, and voice recognition. Each of them has their own advantages and disadvantages. Discussing about the automatic speaker verification (ASV), speech signal is a natural signal which one can easily obtain even from a telephone call. Research in this area is carried out from decades. This speaker verification technology has advanced in recent years and has become a genuine method for biometric systems. Using an adaptable Gaussian Mixture Model (GMM-UBM), a text-independent speaker verification (TISV) technique has been developed and compared with state-of-art I-vector based speaker recognition system in this research. Parameters for universal background model (UBM) are trained using the EM (Expectation maximization) and MAP adaptation method is used for training speaker models. Multiple false acceptance and false rejection rates are calculated by changing the threshold values for comparison. The results are shown in equal error rate (EER) for both the GMM-UBM, and I-vector based ASV systems, and the lowest EER is found to be 5.31% and 4.74%, respectively, after adjusting the threshold settings and number of Gaussian mixtures utilized.","PeriodicalId":185782,"journal":{"name":"2022 IEEE 9th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133456521","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 : 2022-12-02DOI: 10.1109/UPCON56432.2022.9986369
Hemant Singh, Hemant Kumar Meena, D. Saxena
Integration of renewable energy sources (RES) and storage systems at a huge scale into our electrical power system can be seen nowadays to meet the power demand. But the high cost of storage and intermittent nature of renewables is a concern for the economical and reliable operation of the microgrid. A dual-layer energy management system (EMS) is presented in this research, along with the degradation cost of the hybrid energy storage system (HESS), which consists of a battery and supercapacitor. The first layer minimizes the total operational expenditure by providing optimal dispatch, the second layer, on the other hand, deals with the fluctuations caused by forecasting error. The proposed EMS is tested for a time-of-use (TOU) pricing scheme and compared with existing techniques. Later it's compared with a different pricing scheme, i.e. a real-time (RT) pricing scheme. From the results, it can be seen that the proposed strategy has better performance which verifies dual-layer EMS effectiveness.
{"title":"A Dual-Layer Energy Management System Consisting Degradation Cost of Hybrid Energy Storage System","authors":"Hemant Singh, Hemant Kumar Meena, D. Saxena","doi":"10.1109/UPCON56432.2022.9986369","DOIUrl":"https://doi.org/10.1109/UPCON56432.2022.9986369","url":null,"abstract":"Integration of renewable energy sources (RES) and storage systems at a huge scale into our electrical power system can be seen nowadays to meet the power demand. But the high cost of storage and intermittent nature of renewables is a concern for the economical and reliable operation of the microgrid. A dual-layer energy management system (EMS) is presented in this research, along with the degradation cost of the hybrid energy storage system (HESS), which consists of a battery and supercapacitor. The first layer minimizes the total operational expenditure by providing optimal dispatch, the second layer, on the other hand, deals with the fluctuations caused by forecasting error. The proposed EMS is tested for a time-of-use (TOU) pricing scheme and compared with existing techniques. Later it's compared with a different pricing scheme, i.e. a real-time (RT) pricing scheme. From the results, it can be seen that the proposed strategy has better performance which verifies dual-layer EMS effectiveness.","PeriodicalId":185782,"journal":{"name":"2022 IEEE 9th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133161296","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}
Recently, big data computing paradigm has been gaining proliferation due to wide applications for processing enormous volumes of data to produce meaningful information. The big data computing frameworks perform data processing in cloud computing or physical on-premises. Cloud service providers provide flexible, affordable, and reliable resources that are easier to manage than on-premise physical data centers. So many organization are now moving their big data computing framework over to the cloud computing environment. However, due to several limitations, including the need to reduce costs for using virtual machines, optimize system performance by lowering the Average job completion time, and adhere to service level agreements for the jobs, scheduling Spark jobs efficiently in a cloud environment is a challenging problem. Numerous heuristic-based solutions are available in the literature; however, they do not work well in heterogeneous cloud environments where many constraints are present while scheduling the jobs. So, in this paper, we have optimized the use of computing resources in a cloud environment by analyzing spark job scheduling based on reinforcement learning algorithms. The case study's proposed analysis demonstrates how a reinforcement learning algorithm enables an agent to learn the inherent properties of the computing environment for job scheduling.
{"title":"Reinforcement Learning based Scheduling for Spark Jobs in Cloud Environment","authors":"Vishnu Prasad Verma, Nenavath Srinivas Naik, Santosh Kumar","doi":"10.1109/UPCON56432.2022.9986440","DOIUrl":"https://doi.org/10.1109/UPCON56432.2022.9986440","url":null,"abstract":"Recently, big data computing paradigm has been gaining proliferation due to wide applications for processing enormous volumes of data to produce meaningful information. The big data computing frameworks perform data processing in cloud computing or physical on-premises. Cloud service providers provide flexible, affordable, and reliable resources that are easier to manage than on-premise physical data centers. So many organization are now moving their big data computing framework over to the cloud computing environment. However, due to several limitations, including the need to reduce costs for using virtual machines, optimize system performance by lowering the Average job completion time, and adhere to service level agreements for the jobs, scheduling Spark jobs efficiently in a cloud environment is a challenging problem. Numerous heuristic-based solutions are available in the literature; however, they do not work well in heterogeneous cloud environments where many constraints are present while scheduling the jobs. So, in this paper, we have optimized the use of computing resources in a cloud environment by analyzing spark job scheduling based on reinforcement learning algorithms. The case study's proposed analysis demonstrates how a reinforcement learning algorithm enables an agent to learn the inherent properties of the computing environment for job scheduling.","PeriodicalId":185782,"journal":{"name":"2022 IEEE 9th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115588384","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 : 2022-12-02DOI: 10.1109/UPCON56432.2022.9986473
I. Pandey, Jai Deo Tiwari
In the current era of autonomous mobility, designing safe energy storage system is one of the challenging tasks. The internal reactions such as electrolyte leakage and electrolysis are one of the major issues of Li-ion batteries failure. An advance nano-sensors can be one of the feasible solutions which can detect gas vapors (methane, carbon dioxide, oxygen, carbonates) at ppb levels. In the present work, advance sensing mechanism that is selective memory-based sensing film made up of the polymeric-Triethyl 1,3,5-triazine-2,4,6-tricarboxylate doped with copper grown on graphdiyne coated carbon nanofibers. The developed nanocomposite has high efficiency to sense gases and volatile organic compounds with no cross-selectivity. This miniaturized sensor has unique property of detection of carbonates as well as hydro fluorides, which can be the indicator of electrolysis in the batteries. Novel fabricated sensor has capability to sense vapors of carbonates, methane, and hydro fluorides at 10−2 ppb level with good resolution in signals. Real-time detection leakage gives very early signature of health of battery and gives opportunity to manufacturers to develop high performance Lithium-ion batteries. The developed sensor also provides insights on the chemical sensing capability of modified graphdiyne coated carbon nanofibers and capabilities to withstand in hazardous internal battery environment.
{"title":"Advance Sensor for Monitoring Electrolyte Leakage in Lithium-ion Batteries for Electric Vehicles","authors":"I. Pandey, Jai Deo Tiwari","doi":"10.1109/UPCON56432.2022.9986473","DOIUrl":"https://doi.org/10.1109/UPCON56432.2022.9986473","url":null,"abstract":"In the current era of autonomous mobility, designing safe energy storage system is one of the challenging tasks. The internal reactions such as electrolyte leakage and electrolysis are one of the major issues of Li-ion batteries failure. An advance nano-sensors can be one of the feasible solutions which can detect gas vapors (methane, carbon dioxide, oxygen, carbonates) at ppb levels. In the present work, advance sensing mechanism that is selective memory-based sensing film made up of the polymeric-Triethyl 1,3,5-triazine-2,4,6-tricarboxylate doped with copper grown on graphdiyne coated carbon nanofibers. The developed nanocomposite has high efficiency to sense gases and volatile organic compounds with no cross-selectivity. This miniaturized sensor has unique property of detection of carbonates as well as hydro fluorides, which can be the indicator of electrolysis in the batteries. Novel fabricated sensor has capability to sense vapors of carbonates, methane, and hydro fluorides at 10−2 ppb level with good resolution in signals. Real-time detection leakage gives very early signature of health of battery and gives opportunity to manufacturers to develop high performance Lithium-ion batteries. The developed sensor also provides insights on the chemical sensing capability of modified graphdiyne coated carbon nanofibers and capabilities to withstand in hazardous internal battery environment.","PeriodicalId":185782,"journal":{"name":"2022 IEEE 9th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114551867","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 : 2022-12-02DOI: 10.1109/UPCON56432.2022.9986365
A. Srivastava, A. K. Barnwal, M. K. Verma
Power systems are desired to operate within defined limits of voltages and line power flow. But many times, they get severely constrained and breach these limits and therefore the security of power system gets compromised. Such challenging situations generally occur in case of occurrence of some form of contingency in the system. Contingency can be a simple one such as a line outage or a complex one like cascade line outages leading to blackout etc. To suggest some ways to save the system from disastrous consequences of these contingencies is the motivation of the present work. This work is synthesized basically in two parts. First part deals with the study of contingency in detail, such as, in what form it occurs, where in a power system it could be most severe etc. For this part some power flow indices have been calculated via simulations and then these indices are used to determine severity in each case. The second part makes an attempt to propose a way out to mitigate the negative impacts of these contingencies which usually are driving the system beyond its operational limits in terms of bus voltages, line power flows etc. The technique proposed in this part is the use of Distributed Generations optimally in the power system to increase its reliability. All simulations in this paper are carried out in MATLAB environment and test system deployed for this work is IEEE 6 bus system.
{"title":"PSO based Optimal Placement of Distributed Generation for Loss Minimization and Voltage Profile Improvement under Contingencies","authors":"A. Srivastava, A. K. Barnwal, M. K. Verma","doi":"10.1109/UPCON56432.2022.9986365","DOIUrl":"https://doi.org/10.1109/UPCON56432.2022.9986365","url":null,"abstract":"Power systems are desired to operate within defined limits of voltages and line power flow. But many times, they get severely constrained and breach these limits and therefore the security of power system gets compromised. Such challenging situations generally occur in case of occurrence of some form of contingency in the system. Contingency can be a simple one such as a line outage or a complex one like cascade line outages leading to blackout etc. To suggest some ways to save the system from disastrous consequences of these contingencies is the motivation of the present work. This work is synthesized basically in two parts. First part deals with the study of contingency in detail, such as, in what form it occurs, where in a power system it could be most severe etc. For this part some power flow indices have been calculated via simulations and then these indices are used to determine severity in each case. The second part makes an attempt to propose a way out to mitigate the negative impacts of these contingencies which usually are driving the system beyond its operational limits in terms of bus voltages, line power flows etc. The technique proposed in this part is the use of Distributed Generations optimally in the power system to increase its reliability. All simulations in this paper are carried out in MATLAB environment and test system deployed for this work is IEEE 6 bus system.","PeriodicalId":185782,"journal":{"name":"2022 IEEE 9th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114661126","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 : 2022-12-02DOI: 10.1109/UPCON56432.2022.9986429
Neha Garg, Yogesh Pratap, S. Kabra
This research work presents, the dynamic behavior of CMOS inverter designed using n-MOS and p-MOS double-gate junctionless transistors (DG-JLT). Rise time, fall time, propagation delay, and dynamic power dissipation are used to assess the CMOS inverter's performance using ATLAS-3D device simulator. Three-stage ring oscillator is implemented using DG-JLT and its frequency is utilized for propagation delay and dynamic power consumption calculation. Various performance metrics are calculated considering three values of load capacitance (21aF, 31.5aF, and 42aF) to take into account parasitic capacitance and it is observed that with the increase in value of load capacitance from 21aF to 42aF the rise time, fall time, delay and dynamic power consumption increases by 26%,18.18%,16.06%, and 71.70% respectively. In addition, the change in the various parameters of the CMOS inverter because of the presence of two different interface trap charge density profiles is also analyzed. It has been observed that existence of positive charges reduces the load capacitance.
{"title":"Impact of Load Capacitance and Interface Trap Charges On Dynamic Behaviour of Double-Gate Junctionless Transistor Based CMOS Inverter","authors":"Neha Garg, Yogesh Pratap, S. Kabra","doi":"10.1109/UPCON56432.2022.9986429","DOIUrl":"https://doi.org/10.1109/UPCON56432.2022.9986429","url":null,"abstract":"This research work presents, the dynamic behavior of CMOS inverter designed using n-MOS and p-MOS double-gate junctionless transistors (DG-JLT). Rise time, fall time, propagation delay, and dynamic power dissipation are used to assess the CMOS inverter's performance using ATLAS-3D device simulator. Three-stage ring oscillator is implemented using DG-JLT and its frequency is utilized for propagation delay and dynamic power consumption calculation. Various performance metrics are calculated considering three values of load capacitance (21aF, 31.5aF, and 42aF) to take into account parasitic capacitance and it is observed that with the increase in value of load capacitance from 21aF to 42aF the rise time, fall time, delay and dynamic power consumption increases by 26%,18.18%,16.06%, and 71.70% respectively. In addition, the change in the various parameters of the CMOS inverter because of the presence of two different interface trap charge density profiles is also analyzed. It has been observed that existence of positive charges reduces the load capacitance.","PeriodicalId":185782,"journal":{"name":"2022 IEEE 9th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116998149","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 : 2022-12-02DOI: 10.1109/UPCON56432.2022.9986396
Shreyash Mishra, R. Sanodiya
The field of Domain Adaptation(DA) involves the usage of data from a source to train a model, and then predict the class of data samples of a different distribution. Domain Adaptation (DA) aims to leverage the available training and testing data to model a target domain classifier. Domain invariant features are extracted, and are used to minimize the distribution divergence between the source and target domains. The existing works do not consider reducing the discrepancy between the source and target covariance matrices, an important information source. No previous work has incorporated all objectives like manifold feature learning, scatter matrix normalization, discriminative information preservation, variance maximization, divergence minimization and geometric similarity preservation into a single objective function. In this work, we propose a novel domain adaptation framework for image classification that utilizes the covariance matrices of the source and target domains along with other important objectives like discrimination information preservation, divergence minimization, among others. A robust objective function that comprises of all these objectives is designed for optimal performance of the algorithm. The significance and impact of different types of normalization on the overall performance of the algorithm is also described. Experiments on benchmark domain adaptation datasets like PIE and Office-Home signify improvements over existing state of the art algorithms.
{"title":"Scatter Matrix Normalization for Unsupervised Domain Adaptation","authors":"Shreyash Mishra, R. Sanodiya","doi":"10.1109/UPCON56432.2022.9986396","DOIUrl":"https://doi.org/10.1109/UPCON56432.2022.9986396","url":null,"abstract":"The field of Domain Adaptation(DA) involves the usage of data from a source to train a model, and then predict the class of data samples of a different distribution. Domain Adaptation (DA) aims to leverage the available training and testing data to model a target domain classifier. Domain invariant features are extracted, and are used to minimize the distribution divergence between the source and target domains. The existing works do not consider reducing the discrepancy between the source and target covariance matrices, an important information source. No previous work has incorporated all objectives like manifold feature learning, scatter matrix normalization, discriminative information preservation, variance maximization, divergence minimization and geometric similarity preservation into a single objective function. In this work, we propose a novel domain adaptation framework for image classification that utilizes the covariance matrices of the source and target domains along with other important objectives like discrimination information preservation, divergence minimization, among others. A robust objective function that comprises of all these objectives is designed for optimal performance of the algorithm. The significance and impact of different types of normalization on the overall performance of the algorithm is also described. Experiments on benchmark domain adaptation datasets like PIE and Office-Home signify improvements over existing state of the art algorithms.","PeriodicalId":185782,"journal":{"name":"2022 IEEE 9th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122174907","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 : 2022-12-02DOI: 10.1109/UPCON56432.2022.9986478
P. Mishra, A. Yadav, Tilakdhari Singh, V. Tripathi
This paper presents a design of a dielectric resonator antenna (DRA) for millimeter-wave applications. An electromagnetic band gap (EBG) structure is used in the antenna design to enhance the antenna characteristics. The simulated with and without EBG results of the designed antenna is calculated to show the parameters such as impedance bandwidth, reflection coefficient, and gain. The parameters of the proposed antenna have improved after the periodic unit cell structure (EBG) introduction. The obtained reflection coefficients of the proposed antenna with and without EBG structure are −30.5 dB and −20.8 dB, respectively. In the presence of an EBG structure antenna shows a peak gain of 25 dBi, which is higher than the without EBG (8 dBi) structure. The designed antenna resonates at 33 GHz with an impedance bandwidth of 700 MHz. The Ansys HFSS software is used to design and simulate the proposed antenna.
{"title":"An Electromagnetic Band Gap Structure Based Dielectric Resonator Antenna for Millimeter-Wave Applications","authors":"P. Mishra, A. Yadav, Tilakdhari Singh, V. Tripathi","doi":"10.1109/UPCON56432.2022.9986478","DOIUrl":"https://doi.org/10.1109/UPCON56432.2022.9986478","url":null,"abstract":"This paper presents a design of a dielectric resonator antenna (DRA) for millimeter-wave applications. An electromagnetic band gap (EBG) structure is used in the antenna design to enhance the antenna characteristics. The simulated with and without EBG results of the designed antenna is calculated to show the parameters such as impedance bandwidth, reflection coefficient, and gain. The parameters of the proposed antenna have improved after the periodic unit cell structure (EBG) introduction. The obtained reflection coefficients of the proposed antenna with and without EBG structure are −30.5 dB and −20.8 dB, respectively. In the presence of an EBG structure antenna shows a peak gain of 25 dBi, which is higher than the without EBG (8 dBi) structure. The designed antenna resonates at 33 GHz with an impedance bandwidth of 700 MHz. The Ansys HFSS software is used to design and simulate the proposed antenna.","PeriodicalId":185782,"journal":{"name":"2022 IEEE 9th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125746007","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 : 2022-12-02DOI: 10.1109/UPCON56432.2022.9986474
Sourabh Ghosh, Soumyabrata Das, A. K. Singh, S. N. Singh
This paper presents optimal scheduling for electric vehicle (EV) charging in a community supported by solar photovoltaic (SPV) and battery energy storage system (BESS)-based parking lot. Each incoming EVs to the charging station gets connected to separate charge points and becomes eligible to participate in vehicle-to-vehicle (V2V) power transfer to decrease the charging cost and enhance the self-utilization of SPV. The problem is formulated as an offline mixed integer linear programming (MILP) model and solved by considering full availability of information of the EV demand, grid prices, and SPV generation. Later, three different cases, i.e., dumb charging, smart charging with V2V and BESS, and smart charging with V2V, BESS and SPV are considered for analysis of the proposed scheduling approach. When supported by V2V power transfer, demand profile flattens and total cost incurred by the parking lot operator is also reduced for a single day. The proposed model is validated on MATLAB® platform by performance evaluation of simulation results.
{"title":"Optimal Scheduling of Electric Vehicles in a Solar Rooftop Parking Lot with V2V Power Transfer","authors":"Sourabh Ghosh, Soumyabrata Das, A. K. Singh, S. N. Singh","doi":"10.1109/UPCON56432.2022.9986474","DOIUrl":"https://doi.org/10.1109/UPCON56432.2022.9986474","url":null,"abstract":"This paper presents optimal scheduling for electric vehicle (EV) charging in a community supported by solar photovoltaic (SPV) and battery energy storage system (BESS)-based parking lot. Each incoming EVs to the charging station gets connected to separate charge points and becomes eligible to participate in vehicle-to-vehicle (V2V) power transfer to decrease the charging cost and enhance the self-utilization of SPV. The problem is formulated as an offline mixed integer linear programming (MILP) model and solved by considering full availability of information of the EV demand, grid prices, and SPV generation. Later, three different cases, i.e., dumb charging, smart charging with V2V and BESS, and smart charging with V2V, BESS and SPV are considered for analysis of the proposed scheduling approach. When supported by V2V power transfer, demand profile flattens and total cost incurred by the parking lot operator is also reduced for a single day. The proposed model is validated on MATLAB® platform by performance evaluation of simulation results.","PeriodicalId":185782,"journal":{"name":"2022 IEEE 9th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129316044","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 : 2022-12-02DOI: 10.1109/UPCON56432.2022.9986370
B. Kumar, Rahul Sharma
The most well-known approach for parallel inverter operation is droop control, which is employed in the control of inverters of the power flow in the islanded microgrids or grid connected system according to the different load conditions without using any critical communication line and also useful in integrating several energy sources to meet the active and reactive power requirements of loads. In this paper, the droop control is implemented in the parallel operations of decentralized inverters, and analysis has been done with different types of feeder impedance and their X/R ratios and the parallel operation providing proportional and accurate sharing of active and reactive power. The proposed droop control is validated using Matlab/Simulink. The simulation results show that the suggested droop control approach can satisfactorily manage voltage, frequency, active and reactive power in an AC microgrid.
{"title":"Droop control in decentralized inverter-based AC microgrid and the analysis of the effect of different types of feeder impedances","authors":"B. Kumar, Rahul Sharma","doi":"10.1109/UPCON56432.2022.9986370","DOIUrl":"https://doi.org/10.1109/UPCON56432.2022.9986370","url":null,"abstract":"The most well-known approach for parallel inverter operation is droop control, which is employed in the control of inverters of the power flow in the islanded microgrids or grid connected system according to the different load conditions without using any critical communication line and also useful in integrating several energy sources to meet the active and reactive power requirements of loads. In this paper, the droop control is implemented in the parallel operations of decentralized inverters, and analysis has been done with different types of feeder impedance and their X/R ratios and the parallel operation providing proportional and accurate sharing of active and reactive power. The proposed droop control is validated using Matlab/Simulink. The simulation results show that the suggested droop control approach can satisfactorily manage voltage, frequency, active and reactive power in an AC microgrid.","PeriodicalId":185782,"journal":{"name":"2022 IEEE 9th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129668558","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：