2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)最新文献_第8页

Statistical Time Features-based Methodology for Fatigue Cracks Detection in a Four-Story Building 基于统计时间特征的四层建筑疲劳裂纹检测方法

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258724

Jesus J. Yanez-Borjas, D. Camarena-Martinez, M. Valtierra-Rodríguez, J. Amezquita-Sanchez

引用次数: 0

Increase of solar harvest time with a double static concentration refractive-reflective system 双静态浓缩折射反射系统增加太阳收获时间

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258725

Guillermo Luque-Zuñiga, R. Vázquez-Medina, G. Ramos-López, H. Yee-Madeira, D. Pérez-Márquez

{"title":"Increase of solar harvest time with a double static concentration refractive-reflective system","authors":"Guillermo Luque-Zuñiga, R. Vázquez-Medina, G. Ramos-López, H. Yee-Madeira, D. Pérez-Márquez","doi":"10.1109/ROPEC50909.2020.9258725","DOIUrl":"https://doi.org/10.1109/ROPEC50909.2020.9258725","url":null,"abstract":"In static solar devices, the acceptance angle is limited by the entry angle and the sun movement. Hence, the solar harvesting time in them is short. To increase the collection time it is usually necessary to sacrifice the concentration factor. Several investigations have been made to increase the solar harvest time. Some of them using a primary and secondary optical system with different degrees of complexity in the optical devices. In this work, a new design, a double static concentrating system to increase the solar harvesting time is presented, Its performance is analyzed using CAD simulation. The device is based on a funnel type reflective concentration system as a secondary optical element with an on-top prism as primary optics. The device shows an acceptance angle of 60° with an effective maximum concentration factor of 3.3X. The mean optical efficiency is of 66%, having its best performance for incidence angles between $pm 41.25^{circ}$, allowing 5.5 hours of use. Furthermore, the design has the additional benefit of its ease to build.","PeriodicalId":177447,"journal":{"name":"2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121247906","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

Economic dispatch in DC Microgrids considering different battery technologies: A Benchmark Study 考虑不同电池技术的直流微电网经济调度:一个基准研究

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258675

J. Dominguez-Jimenez, O. Montoya, J. Campillo, W. Gil-González

引用次数: 1

Brain Tumor Segmentation using an Encoder-Decoder Network with a Multiscale Feature Module 基于多尺度特征模块的编码器-解码器网络的脑肿瘤分割

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258718

Olanda Prieto-Ordaz, Graciela Ramírez-Alonso, L. González, Roberto López-Santillán, M. Montes-y-Gómez

{"title":"Brain Tumor Segmentation using an Encoder-Decoder Network with a Multiscale Feature Module","authors":"Olanda Prieto-Ordaz, Graciela Ramírez-Alonso, L. González, Roberto López-Santillán, M. Montes-y-Gómez","doi":"10.1109/ROPEC50909.2020.9258718","DOIUrl":"https://doi.org/10.1109/ROPEC50909.2020.9258718","url":null,"abstract":"The correct identification of brain tumors in multisequence images is a very challenging task and of high relevance in the correct treatment of patients affected by this illness. In this paper, we present a segmentation neural network approach named FPM-BrainSeg. FPM-BrainSeg incorporates important features on its architecture such as residual connections, anisotropic convolutions, instance normalization, and a Feature Pooling Module (FPM) that increases the field of view of the extracted features. We compare the performance of FPM-BrainSeg with three state-of-the-art segmentation networks trained over a common Graphic Processing Unit (GPU) of the GTX family, by using the BraTS 2018 dataset. The performance obtained with FPM-BrainSeg surpassed the other neural models. The features extracted by the FPM increase the ability of the network to segment the different tumor regions as demonstrated in the visualization of the activation layers. Furthermore, a second comparison of our approach with state-of-the-art models (as presented in their original papers), demonstrate that our architecture attained competitive performance.","PeriodicalId":177447,"journal":{"name":"2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125765549","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: 2

Vulnerability and Resilience Assessment of Power Systems: From Deterioration to Recovery via a Topological Model based on Graph Theory 电力系统脆弱性与恢复力评估:基于图论的拓扑模型

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258709

J. Beyza, V. M. Bravo, Eduardo Garcia-Paricio, J. Yusta, J. S. Artal-Sevil

{"title":"Vulnerability and Resilience Assessment of Power Systems: From Deterioration to Recovery via a Topological Model based on Graph Theory","authors":"J. Beyza, V. M. Bravo, Eduardo Garcia-Paricio, J. Yusta, J. S. Artal-Sevil","doi":"10.1109/ROPEC50909.2020.9258709","DOIUrl":"https://doi.org/10.1109/ROPEC50909.2020.9258709","url":null,"abstract":"Traditionally, vulnerability is the level of degradation caused by failures or disturbances, and resilience is the ability to recover after a high-impact event. This paper presents a topological procedure based on graph theory to evaluate the vulnerability and resilience of power grids. A cascading failures model is developed by eliminating lines both deliberately and randomly, and four restoration strategies inspired by the network approach are proposed. In the two cases, the degradation and recovery of the electrical infrastructure are quantified through four centrality measures. Here, an index called flow-capacity is proposed to measure the level of network overload during the iterative processes. The developed sequential framework was tested on a graph of 600 nodes and 1196 edges built from the 400 kV high-voltage power system in Spain. The conclusions obtained show that the statistical graph indices measure different topological aspects of the network, so it is essential to combine the results to obtain a broader view of the structural behaviour of the infrastructure.","PeriodicalId":177447,"journal":{"name":"2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)","volume":"36 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130728827","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

Statistical Method for Single-Diode Model Parameters Extraction of a Photovoltaic Module 光伏组件单二极管模型参数提取的统计方法

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258754

Aldo J. Rivas-Vázquez, R. Loera-Palomo, C. Álvarez-Macías, Michel Rivero, F. Sellschopp-Sánchez

{"title":"Statistical Method for Single-Diode Model Parameters Extraction of a Photovoltaic Module","authors":"Aldo J. Rivas-Vázquez, R. Loera-Palomo, C. Álvarez-Macías, Michel Rivero, F. Sellschopp-Sánchez","doi":"10.1109/ROPEC50909.2020.9258754","DOIUrl":"https://doi.org/10.1109/ROPEC50909.2020.9258754","url":null,"abstract":"In this work a modeling method for photovoltaic (PV) modules based on statistical analysis is presented. In this sense, the work deals with the determination of the parameters of the non-linear I-V equation, represented by the single-diode model. The parameters estimation of the PV model starts with experimental tests on PV panels under different irradiance and temperature conditions. A database is built with the parameters extracted from the family of experimental curves, where mathematical expressions, through linear regression analysis, are obtained to determine electrical variables of interest, such as: $I_{sc}, V_{oc}, I_{m}, V_{m}$ and $P_{m}$ which are dependent of irradiance $text{and}/text{or}$ operating temperature. The parameters of the non-linear I-V equation given by the resistances $R_{sh}, R_{s}$ and the ideality factor $n$, the analysis demonstrate that average values are representative; while the light-generated and diode-saturation currents depend on the incident irradiance. The capacity of the models was validated through the analysis of different statistical criteria, such as: the root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and the coefficient of determination ($R^{2}$). The results were accepted for applications where a high precision is not necessary, or for modeling and/or forecasting purposes.","PeriodicalId":177447,"journal":{"name":"2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121228859","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: 2

Calculation of Optimal Switching Angles for a Multilevel Inverter through the Taguchi Design Approach 用田口设计方法计算多电平逆变器的最佳开关角

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258728

Adolfo R. López, J. M. Sosa, M. Juárez, Felipe-de-Jesús Torres, Carlos Correa-Betanzo

引用次数: 0

Remaining Useful Life of Lithium-ion Batteries as a Function of the Joule Effect 焦耳效应对锂离子电池剩余使用寿命的影响

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258726

M. Benavides, A. Arias, Juan Diego Cerdas, Aramis Pérez, M. Orchard

引用次数: 1

Optimal Switching Angles Calculation for a Multilevel Inverter through the SHE Method and the PSO Algorithm, a comparison 用SHE法和粒子群算法计算多电平逆变器的最优开关角，进行比较

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258680

Adolfo R. López, Christopher J. Cortés, C. A. Limones-Pozos, J. M. Sosa, J. Aguayo, Susana Estefany de León Aldaco

引用次数: 2

Mechatronic Design and Robust Control of an Artificial Ventilator in Response to the COVID-19 Pandemic 应对COVID-19大流行的人工呼吸机机电一体化设计与鲁棒控制

2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) Pub Date : 2020-11-04 DOI: 10.1109/ROPEC50909.2020.9258736

Serafin Ramos-Paz, Ruben Belmonte-Izquierdo, Luis Alfonso Inostroza-Moreno, Luisa Fernanda Velasco-Rivera, Ricardo Mendoza-Villa, Valeria Gaona-Flores

引用次数: 1