2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE)最新文献_第2页

A Novel Control Methodology for Stand-Alone Photovoltaic Systems Utilizing Maximum Power Point Tracking 一种利用最大功率点跟踪的独立光伏系统控制方法

2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE) Pub Date : 2019-05-05 DOI: 10.1109/CCECE.2019.8861548

Anshuman Sharma, Yahya Koraz, M. Youssef

{"title":"A Novel Control Methodology for Stand-Alone Photovoltaic Systems Utilizing Maximum Power Point Tracking","authors":"Anshuman Sharma, Yahya Koraz, M. Youssef","doi":"10.1109/CCECE.2019.8861548","DOIUrl":"https://doi.org/10.1109/CCECE.2019.8861548","url":null,"abstract":"This paper introduces an innovative Maximum Power Point Tracking (MPPT) technique to extract maximum available power from a Photovoltaic (PV) system irrespective of temperature, solar irradiation and load anomalies. A single-stage DC-DC buck converter that extracts maximum power from the connected PV module and controls the output battery state of charge (SoC) is a key component in achieving this target. The introduced circuit consists of three subsystems: a PV module, a Buck converter and an MPPT plus voltage regulation controller. MPPT is achieved via a novel methodology, not only applies to maximum energy extraction of the PV module but also combined with a feedback optimization of the battery charging and discharging modes. The developed system is geared towards Internet of Things (IoT) based wireless sensor nodes (WSN). In the proposed solution, power harvested from the PV module is combined with the battery power; to guarantee that the connected load receives a full supply of power. To maximize the energy conversion a converter controlled MPPT algorithm-Perturb and Observe (P& O) which considers the non-linear output of the PV is utilized with the aid of the buck converter. The validity of the introduced system is tested using the simulation model in PSIM and the results are presented and discussed.","PeriodicalId":352860,"journal":{"name":"2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128947753","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: 3

Linear Regression Models for Fat Free Mass Measurement Based on Bioelectrical Impedance Analysis 基于生物电阻抗分析的无脂质量测量线性回归模型

2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE) Pub Date : 2019-05-05 DOI: 10.1109/CCECE.2019.8861576

Tahasin Ahmed Fahim, M. Anower, Mst Farzana Khatun, S. T. Zuhori

{"title":"Linear Regression Models for Fat Free Mass Measurement Based on Bioelectrical Impedance Analysis","authors":"Tahasin Ahmed Fahim, M. Anower, Mst Farzana Khatun, S. T. Zuhori","doi":"10.1109/CCECE.2019.8861576","DOIUrl":"https://doi.org/10.1109/CCECE.2019.8861576","url":null,"abstract":"This work proposes new mathematical models for fat free mass (FFM) measurements for both male and female people based on bioelectrical impedance analysis. In this research total 2650 (1300 male and 1350 female) data have been used. Bioelectrical impedance at 50 kHz along with physical parameters like age, height, body mass index (BMI) have been used for the mathematical model development. The proposed models have been analyzed statistically by evaluating correlation (Pearson) coefficients, 95% limit of agreement (LOA), absolute errors, bias, root mean square error (RMSE) and compared with actual data. The results show that the correlation (Pearson) coefficients are $0.998 (mathrm{p}lt 0.001)$ for male and $0.997 (mathrm{p}lt 0.001)$ for female people which indicate very good matching with actual data. The intervals of LOA are only -1.93 kg to 1.80 kg and -1.48 kg to 1.38 kg for male and female data respectively and most of errors found by proposed models remain within the limit of agreement. The absolute errors (mean ± Standard Deviation) are $(0.81 pm 0.50)$ kg and $(0.62 pm 0.38)$ kg for male and female data respectively whereas the bias are -0.06 kg for male and -0.05 kg for female population only. The RMSE are also very low and which are 0.95 kg for male and 0.73 kg for female people. Comparing the results of this research with existing models it is seen that proposed mathematical models exhibit better results and hence the proposed models can be more suitable for FFM measurement.","PeriodicalId":352860,"journal":{"name":"2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE)","volume":"15 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132782512","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

An Efficient Automated Hybrid Algorithm to Predict Floods in Cloud Environment 云环境下洪水预测的一种高效自动混合算法

2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE) Pub Date : 2019-05-05 DOI: 10.1109/CCECE.2019.8861897

Gurleen Kaur, A. Bala

引用次数: 6

Parallelized QR decomposition using GPUs 使用gpu的并行QR分解

2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE) Pub Date : 2019-05-05 DOI: 10.1109/CCECE.2019.8861519

Ian Schofield, A. Alimohammad

引用次数: 1

Analysis on Nondispersive Infrared Device Characteristics Using Thermopile 热电堆非色散红外器件特性分析

2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE) Pub Date : 2019-05-05 DOI: 10.1109/CCECE.2019.8861852

Son Pham, A. Dinh

引用次数: 2

3D Models Recognition Using Overlap Histograms and Machine Learning 使用重叠直方图和机器学习的3D模型识别

2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE) Pub Date : 2019-05-05 DOI: 10.1109/CCECE.2019.8861595

Justin Salisi, Edmund Yao, Emilie Zhang, S. Raschke, Nigel Halsted, Thom Bellaire, Michal Aibin

引用次数: 2

Lumped Element RF Low Pass Filter with 20 dB Improved Suppression at the Center Frequency of an RF Injection Network for Conductive Emission Testing 用于导电发射测试的射频注入网络中心频率处具有20 dB改进抑制的集总元件射频低通滤波器

2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE) Pub Date : 2019-05-05 DOI: 10.1109/CCECE.2019.8861975

A. Attaran, W. Handler, B. Chronik

引用次数: 0

Control of a Mechanical Knee Based on Predictive Control Techniques 基于预测控制技术的机械膝关节控制

2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE) Pub Date : 2019-05-05 DOI: 10.1109/CCECE.2019.8861754

R. F. Campos, J. B. Machado, S. Givigi, L. H. C. Ferreira

引用次数: 2

Optimal Sizing of Power–to–Gas Units toward Elevated Renewable Power Penetration 面向提高可再生能源渗透率的电-气机组优化规模

2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE) Pub Date : 2019-05-05 DOI: 10.1109/CCECE.2019.8861741

Abdullah M. Sawas, H. Farag

引用次数: 7

Ground Segmentation From Outdoor Environments in Rural Areas 农村地区室外环境的地面分割

2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE) Pub Date : 2019-05-05 DOI: 10.1109/CCECE.2019.8861556

G. S. Vieira, Fabrízzio Soares, S. A. Santos, G. Laureano, J. C. Lima, R. M. Costa, J. P. Félix, T. H. Nascimento

引用次数: 0