2022 IEEE International Power and Renewable Energy Conference (IPRECON)最新文献_第6页

Estimation of Remaining Travel Range of Electric Boat using Extended Kalman Filter 基于扩展卡尔曼滤波的电船剩余行程估计

2022 IEEE International Power and Renewable Energy Conference (IPRECON) Pub Date : 2022-12-16 DOI: 10.1109/IPRECON55716.2022.10059494

Adrian Martin Z. De Vera, F. Cruz

{"title":"Estimation of Remaining Travel Range of Electric Boat using Extended Kalman Filter","authors":"Adrian Martin Z. De Vera, F. Cruz","doi":"10.1109/IPRECON55716.2022.10059494","DOIUrl":"https://doi.org/10.1109/IPRECON55716.2022.10059494","url":null,"abstract":"With the increasing demand for electric mobility, marine transportation modes are beginning to implement electric propulsion. Range anxiety is one of the more common consumer concerns regarding the adoption of electric propulsion in transportation. Remaining range estimation capabilities can reduce range anxiety and provide vehicle passengers with insights into their vehicles. Given the nature of water-based transportation being different from that of land transportation, being stranded at sea poses different challenges than being stranded on land. As electrically propelled boats grow in popularity, systems that monitor the remaining energy capacity of the batteries used in such boats and the remaining capable travel range of the said vessels become increasingly important. This study utilizes an extended Kalman filter (EKF) to monitor the battery state of charge (SOC) while incorporating travel distance-based models to estimate the remaining range at given values of state of charge. The results from the study show that the EKF is capable of accurately determining SOC during operation. The range estimation model is also shown to predict the travel distance, with the error value from the total actual distance traveled being 3.29%.","PeriodicalId":407222,"journal":{"name":"2022 IEEE International Power and Renewable Energy Conference (IPRECON)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115780258","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}

引用次数: 0

Prediction of FBC Boiler Efficiency using Machine Learning Algorithm 基于机器学习算法的FBC锅炉效率预测

2022 IEEE International Power and Renewable Energy Conference (IPRECON) Pub Date : 2022-12-16 DOI: 10.1109/IPRECON55716.2022.10059501

Raunak Pawar, M. A. Khandekar, S. Agashe, Pratap Makwana

引用次数: 0

Root Cause Analysis in Power Transformer Failure with Improved Intelligent Methods 基于改进智能方法的电力变压器故障根本原因分析

2022 IEEE International Power and Renewable Energy Conference (IPRECON) Pub Date : 2022-12-16 DOI: 10.1109/IPRECON55716.2022.10059538

Sreelakshmi S Baiju, A. S.

引用次数: 0

Design, modeling and analysis of transverse flux active mover switched reluctance actuator 横向磁通有源电机开关磁阻执行器的设计、建模与分析

2022 IEEE International Power and Renewable Energy Conference (IPRECON) Pub Date : 2022-12-16 DOI: 10.1109/IPRECON55716.2022.10059513

Juan Chowdhury, G. Kumar, K. Kalita, Plabon Kakoty

引用次数: 0

Exploring fusion model for the detection and localization of colorectal polyps 探讨融合模型在结肠直肠息肉检测与定位中的应用

2022 IEEE International Power and Renewable Energy Conference (IPRECON) Pub Date : 2022-12-16 DOI: 10.1109/IPRECON55716.2022.10059512

S. Geetha, C. Gopakumar

{"title":"Exploring fusion model for the detection and localization of colorectal polyps","authors":"S. Geetha, C. Gopakumar","doi":"10.1109/IPRECON55716.2022.10059512","DOIUrl":"https://doi.org/10.1109/IPRECON55716.2022.10059512","url":null,"abstract":"Computer Vision (CV) and Artificial Intelligence (AI) have reported unprecedented growth in recent years and demonstrated potential in almost all domains. In the medical realm machine learning and deep learning techniques are widely used for detection as well as classification o fa nomalies and segmentation of anomaly regions. Salient feature extraction is a challenging task in traditional machine learning techniques but deep learning models successfully extract better features with convolutional neural networks (CNN) and report better performance when the training dataset is tremendous. In the medical domain, the main challenge is the limited availability of annotated data to perform training. Colorectal polyp detection and localization is an arduous task due to the close resemblance of polyps with the surrounding colon regions and the irregular shapes of the polyps. But detection, localization, and segmentation of colon polyps are of great importance in the screening and removal of polyp regions for the prevention of colorectal cancer. Currently used U-Net and Mask-RCNN-based architectures for polyp segmentation are computationally expensive. In this paper, we explore a fusion model to overcome the downsides of both machine learning and deep learning techniques. The fusion model serves the similar purpose of segmentation with less computational overhead and can be used to assist clinicians in screening tests. In the proposed work, pre-trained deep CNNs are explored to extract salient features from image patches followed by ensemble machine learning techniques for the detection of colon polyps. A localization algorithm is applied on the detected image patches for localizing the position of the colon polyps.","PeriodicalId":407222,"journal":{"name":"2022 IEEE International Power and Renewable Energy Conference (IPRECON)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122774777","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}

引用次数: 1

Combined Econo-Emission Dispatch Using Particle Swarm Optimisation 基于粒子群优化的联合经济排放调度

2022 IEEE International Power and Renewable Energy Conference (IPRECON) Pub Date : 2022-12-16 DOI: 10.1109/IPRECON55716.2022.10059607

E. Mithuna, C. Ismayil, D.K. Harisha

引用次数: 0

DC-DC converter with two energy storage devices for smart grid system: Experimental validation 智能电网系统中具有双储能装置的DC-DC变换器:实验验证

2022 IEEE International Power and Renewable Energy Conference (IPRECON) Pub Date : 2022-12-16 DOI: 10.1109/IPRECON55716.2022.10059543

Mohammad Afkar, Parham Karimi, R. Gavagsaz-Ghoachani, M. Phattanasak, S. Pierfederici

引用次数: 0

ETAP based Reliability Analysis of Power Converter System with Wind Energy Interfacing 基于ETAP的风电接口变换器系统可靠性分析

2022 IEEE International Power and Renewable Energy Conference (IPRECON) Pub Date : 2022-12-16 DOI: 10.1109/IPRECON55716.2022.10059504

Anupama V N, Naufal N, S. R

引用次数: 0

Secure and Light weight Data Sharing Scheme in Cyber Physical Cloud Environment 网络物理云环境下的安全轻量级数据共享方案

2022 IEEE International Power and Renewable Energy Conference (IPRECON) Pub Date : 2022-12-16 DOI: 10.1109/IPRECON55716.2022.10059571

Anagha V, K. Vijayanand

{"title":"Secure and Light weight Data Sharing Scheme in Cyber Physical Cloud Environment","authors":"Anagha V, K. Vijayanand","doi":"10.1109/IPRECON55716.2022.10059571","DOIUrl":"https://doi.org/10.1109/IPRECON55716.2022.10059571","url":null,"abstract":"It is still difficult to achieve secure and effective file storage and sharing via authenticated physical devices in a cyber-physical cloud environment because of the variety of devices used to access the services and data, as well as the geographical dispersion of these devices. In this circumstance, a wide variety of cryptographic alternatives are currently available. But the computational and communication overheads are slightly high, and we also need a safe, lightweight, and user-friendly technology. Thus employing a scrambling and unscrambling technique using Sudoku inspired Data Chunking and Scrambling (SiDCS) method. In this approach, the data is scrambled and then unscrambled using Sudoku puzzles. Before being stored in a public cloud, the original data is split up and scrambled. The data will be saved in the cloud independently and securely since each data chunk will only contain a minimal amount of information and because it is scrambled before being stored there. As a result, the cost of communication is reduced, computational overhead is reduced, and a simpler, lightweight model is developed without compromising the security.","PeriodicalId":407222,"journal":{"name":"2022 IEEE International Power and Renewable Energy Conference (IPRECON)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117225930","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}

引用次数: 0

Investigations on Coordinated Integration of Electric Vehicles with Renewables in the Distribution System 配电网中电动汽车与可再生能源协同集成研究

2022 IEEE International Power and Renewable Energy Conference (IPRECON) Pub Date : 2022-12-16 DOI: 10.1109/IPRECON55716.2022.10059482

Yashvi Mudgal, Rajive Tiwari

{"title":"Investigations on Coordinated Integration of Electric Vehicles with Renewables in the Distribution System","authors":"Yashvi Mudgal, Rajive Tiwari","doi":"10.1109/IPRECON55716.2022.10059482","DOIUrl":"https://doi.org/10.1109/IPRECON55716.2022.10059482","url":null,"abstract":"The presented work explores the incorporation of electric vehicles (EVs) and Renewable Energy Sources (RES) into the distribution system. Several benefits can be attained if renewables are adequately integrated into the distribution system, including improved voltage quality and reduced losses. The design of the home load takes into account the hourly charging needs. The Renewable Energy Feed-in Tariff (REFIT) database allows for the estimation of the residential load of about 200 households at the Residential Charging Parking Station (RCPS). The modeling of the arrival of EVs at the parking lot is done with a truncated Gaussian distribution. Incorporating Battery Charging Characteristics approximates the instantaneous charging time of each Electric Vehicle. In addition, the rising charging demand for electric vehicles (EVs) necessitates using renewable energy sources to reduce the negative impacts on the distribution system. The designed methodology is evaluated using 33 bus distribution systems as case studies. The simulation findings demonstrate the effectiveness of integrating renewable energy resources (RES) into the distribution network.","PeriodicalId":407222,"journal":{"name":"2022 IEEE International Power and Renewable Energy Conference (IPRECON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124364666","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}

引用次数: 0