Pub Date : 2024-12-19DOI: 10.1109/TLA.2025.10810396
Eder Peralta-Escobar;Sergio-Ricardo Galván-González;Gildardo Solorio-Díaz;Nicólas-David Herrera-Sandoval;Daniel Cahue-Díaz
Small-scale hydropower is considered one of the most economical, predictable, and environmentally friendly technologies. However, it is still under development, which has led to its limited application, especially to hydraulic resources with low head and fluid velocity like the irrigation canal of the "Centenario de la Revolucion Francisco J. Mugica" dam, located in a ruralzone of the state of Michoacan, Mexico. To estimate the actual energy that this hydraulic resource can give, we proposed an energy conversion methodology that consists of three main steps: the evaluation of the hydraulic energy using the annual Flow Duration Curve of the canal, the numerical design of the ducted hydrokinetic turbine using experimental measurements and the selection of a low-velocity electrical generator. The designed hydrokinetic turbine was able to convert 78.53% of the hydraulic energy available into useful energy, which agriculture could use directly in rural areas.
小型水力发电被认为是最经济、最可预测和最环保的技术之一。然而，该技术仍处于开发阶段，导致其应用范围有限，尤其是在水头和流速较低的水力资源方面，如位于墨西哥米却肯州农村地区的 "Centenario de la Revolucion Francisco J. Mugica "大坝灌溉渠。为了估算这一水力资源所能提供的实际能量，我们提出了一种能量转换方法，该方法包括三个主要步骤：利用水渠的年流量持续时间曲线评估水力能量；利用实验测量结果对管道式水力涡轮机进行数值设计；以及选择低速发电机。所设计的水动力涡轮机能够将 78.53% 的可用水能转化为有用能源，农村地区的农业可以直接使用这些能源。
{"title":"Estimation of the electrical energy provided by an irrigation canal with the design of a hydrokinetic turbine","authors":"Eder Peralta-Escobar;Sergio-Ricardo Galván-González;Gildardo Solorio-Díaz;Nicólas-David Herrera-Sandoval;Daniel Cahue-Díaz","doi":"10.1109/TLA.2025.10810396","DOIUrl":"https://doi.org/10.1109/TLA.2025.10810396","url":null,"abstract":"Small-scale hydropower is considered one of the most economical, predictable, and environmentally friendly technologies. However, it is still under development, which has led to its limited application, especially to hydraulic resources with low head and fluid velocity like the irrigation canal of the \"Centenario de la Revolucion Francisco J. Mugica\" dam, located in a ruralzone of the state of Michoacan, Mexico. To estimate the actual energy that this hydraulic resource can give, we proposed an energy conversion methodology that consists of three main steps: the evaluation of the hydraulic energy using the annual Flow Duration Curve of the canal, the numerical design of the ducted hydrokinetic turbine using experimental measurements and the selection of a low-velocity electrical generator. The designed hydrokinetic turbine was able to convert 78.53% of the hydraulic energy available into useful energy, which agriculture could use directly in rural areas.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"23 1","pages":"58-67"},"PeriodicalIF":1.3,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10810396","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142859233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-11DOI: 10.1109/TLA.2024.10789633
Xiaoxiao Sheng;Zhiqiang Shen;Gang Xiao
Action recognition on unmanned aerial vehicles (UAVs) must cope with complex backgrounds and focus on small targets. Existing methods usually use additional detectors to extract objects in each frame, and use the object sequence within boxes as the network input. However, for training, they rely on additional detection annotations, and for inference, the multi-stage paradigm increases the burden of deployment on UAV terminals. Therefore, we propose a saliency-aware spatio-temporal network (SaStNet) for UAV-based action recognition in an end-to-end manner. Specifically, the short-term and long-term motion information are captured progressively. For short-term modeling, a saliency-guided enhancement module is designed to learn attention scores for weighting the original features aggregated within neighboring frames. For long-term modeling, informative regions are first adaptively concentrated using a saliency-guided aggregation module. Then, a spatio-temporal decoupling attention mechanism is designed to focus on spatially salient regions and capture temporal relationships within all frames. Integrating these modules into classical backbones encourages the network to focus on moving targets, reducing interference from background noises. Extensive experiments and ablation studies are conducted on UAV-Human, Drone action, and something-something datasets. Compared to state-of-the-art methods, SaStNet achieves a 5.7% accuracy improvement on the UAV-Human dataset using 8-frame inputs.
{"title":"Saliency-aware Spatio-temporal Modeling for Action Recognition on Unmanned Aerial Vehicles","authors":"Xiaoxiao Sheng;Zhiqiang Shen;Gang Xiao","doi":"10.1109/TLA.2024.10789633","DOIUrl":"https://doi.org/10.1109/TLA.2024.10789633","url":null,"abstract":"Action recognition on unmanned aerial vehicles (UAVs) must cope with complex backgrounds and focus on small targets. Existing methods usually use additional detectors to extract objects in each frame, and use the object sequence within boxes as the network input. However, for training, they rely on additional detection annotations, and for inference, the multi-stage paradigm increases the burden of deployment on UAV terminals. Therefore, we propose a saliency-aware spatio-temporal network (SaStNet) for UAV-based action recognition in an end-to-end manner. Specifically, the short-term and long-term motion information are captured progressively. For short-term modeling, a saliency-guided enhancement module is designed to learn attention scores for weighting the original features aggregated within neighboring frames. For long-term modeling, informative regions are first adaptively concentrated using a saliency-guided aggregation module. Then, a spatio-temporal decoupling attention mechanism is designed to focus on spatially salient regions and capture temporal relationships within all frames. Integrating these modules into classical backbones encourages the network to focus on moving targets, reducing interference from background noises. Extensive experiments and ablation studies are conducted on UAV-Human, Drone action, and something-something datasets. Compared to state-of-the-art methods, SaStNet achieves a 5.7% accuracy improvement on the UAV-Human dataset using 8-frame inputs.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 12","pages":"1026-1033"},"PeriodicalIF":1.3,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10789633","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-11DOI: 10.1109/TLA.2024.10790546
Luiz Carlos Pinheiro Junior;Everton Gomede;Leonardo de Souza Mendes
The Gale-Shapley algorithm solves the problem of stable pair formation across various fields including economics, labor markets, biology, computer science, and physics. This study modifies the algorithm to use a single list of participants and calculates compatibility scores using Jaccard similarity coefficients from students' proficiency tests and academic performance. We compared the effectiveness of this modified algorithm by evaluating two groups of students engaged in digital educational games: an experimental group matched by the modified algorithm and a randomly matched control group. The results show that the modified algorithm forms pairs with superior compatibility, consistent performance, and balanced competition. These findings suggest integrating the Gale-Shapley algorithm into educational technologies can enhance learning environments. The results significantly impact educational practices indicating that systematic peer training can improve collaboration, competition, and student engagement.
{"title":"Implementation of Stable Pairing Algorithms for Optimizing Educational Games: A Computational and Pedagogical Perspective","authors":"Luiz Carlos Pinheiro Junior;Everton Gomede;Leonardo de Souza Mendes","doi":"10.1109/TLA.2024.10790546","DOIUrl":"https://doi.org/10.1109/TLA.2024.10790546","url":null,"abstract":"The Gale-Shapley algorithm solves the problem of stable pair formation across various fields including economics, labor markets, biology, computer science, and physics. This study modifies the algorithm to use a single list of participants and calculates compatibility scores using Jaccard similarity coefficients from students' proficiency tests and academic performance. We compared the effectiveness of this modified algorithm by evaluating two groups of students engaged in digital educational games: an experimental group matched by the modified algorithm and a randomly matched control group. The results show that the modified algorithm forms pairs with superior compatibility, consistent performance, and balanced competition. These findings suggest integrating the Gale-Shapley algorithm into educational technologies can enhance learning environments. The results significantly impact educational practices indicating that systematic peer training can improve collaboration, competition, and student engagement.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 12","pages":"991-999"},"PeriodicalIF":1.3,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10790546","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-11DOI: 10.1109/TLA.2024.10790547
Hélcio Ferreira Sarabando;Eurípedes Guilherme de Oliveira Nóbrega
Recently, several machine learning approaches have been proposed to provide predictions of the remaining useful life of rotating machine. This study presents a strong framework that employs machine learning algorithms to predict the useful life of rotating machine bearings by evaluating their vibration signals. In this approach, the raw vibration signal undergoes feature extraction through auxiliary methods, trend analysis through statistical methods, and time-dependent feature extraction through a specialized hybrid neural network algorithm. The architecture is composed of three distinct phases: Feature analysis, where the raw vibration data are processed to extract important characteristics for the definition of the signal trend creating a time series and Modeling, where the training data is processed in a hybrid convolutional neural network, which returns a degradation model aiming at estimating the instant of total failure. The neural network is also utilized to analyze test data and identify the moment just prior to the occurrence of failure; and finally the Prediction, phase where the future failure trend of the test data is identified, using the failure threshold extracted from the training data. We used the architecture to predict the remaining useful life of rotating machines in various cases, and the results error ranged between 3 and 4%, which is considered a good result.
{"title":"Convolutional and long short-time memory network configuration to predict the remaining useful life of rotating machinery","authors":"Hélcio Ferreira Sarabando;Eurípedes Guilherme de Oliveira Nóbrega","doi":"10.1109/TLA.2024.10790547","DOIUrl":"https://doi.org/10.1109/TLA.2024.10790547","url":null,"abstract":"Recently, several machine learning approaches have been proposed to provide predictions of the remaining useful life of rotating machine. This study presents a strong framework that employs machine learning algorithms to predict the useful life of rotating machine bearings by evaluating their vibration signals. In this approach, the raw vibration signal undergoes feature extraction through auxiliary methods, trend analysis through statistical methods, and time-dependent feature extraction through a specialized hybrid neural network algorithm. The architecture is composed of three distinct phases: Feature analysis, where the raw vibration data are processed to extract important characteristics for the definition of the signal trend creating a time series and Modeling, where the training data is processed in a hybrid convolutional neural network, which returns a degradation model aiming at estimating the instant of total failure. The neural network is also utilized to analyze test data and identify the moment just prior to the occurrence of failure; and finally the Prediction, phase where the future failure trend of the test data is identified, using the failure threshold extracted from the training data. We used the architecture to predict the remaining useful life of rotating machines in various cases, and the results error ranged between 3 and 4%, which is considered a good result.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 12","pages":"1034-1041"},"PeriodicalIF":1.3,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10790547","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-11DOI: 10.1109/TLA.2024.10789629
{"title":"Table of Contents December 2024","authors":"","doi":"10.1109/TLA.2024.10789629","DOIUrl":"https://doi.org/10.1109/TLA.2024.10789629","url":null,"abstract":"","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 12","pages":"990-990"},"PeriodicalIF":1.3,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10789629","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-11DOI: 10.1109/TLA.2024.10789632
Daniel Ramos-Rivera;Arnoldo Díaz-Ramírez;Leonardo Trujillo;Juan Pablo García-Vázquez;Pedro Mejía-Álvarez
Dementia has emerged as a significant health concern due to global aging trends. A degenerative brain disorder, dementia leads to cognitive decline, memory loss, impaired communication skills, reduced abilities, and shifts in personality and mood. Dementia lacks a definitive cure, but accurate diagnosis and treatment can improve the quality of life for those affected. Wandering behavior is common in patients, and a link between wandering patterns and the severity of the disease has been established. This work addresses the challenge of detecting dementia-related wandering behaviors. The proposed strategy utilizes data imputation methods and feature extraction with the Discrete Wavelet Transformation applied to a recently developed and comprehensive dataset. Machine learning algorithms are used to perform the final detection, and hyperparameter optimization is also evaluated.Experiments show that performance achieves an accuracy of approximately 98% using the Random Forest classifier. Results are competitive with the state-of-the-art in time series classification, with improved efficiency. The proposed methodology can be used for the development of applications for dementia related research and care.
{"title":"Classification of wandering patterns in the elderly using machine learning and time series analysis","authors":"Daniel Ramos-Rivera;Arnoldo Díaz-Ramírez;Leonardo Trujillo;Juan Pablo García-Vázquez;Pedro Mejía-Álvarez","doi":"10.1109/TLA.2024.10789632","DOIUrl":"https://doi.org/10.1109/TLA.2024.10789632","url":null,"abstract":"Dementia has emerged as a significant health concern due to global aging trends. A degenerative brain disorder, dementia leads to cognitive decline, memory loss, impaired communication skills, reduced abilities, and shifts in personality and mood. Dementia lacks a definitive cure, but accurate diagnosis and treatment can improve the quality of life for those affected. Wandering behavior is common in patients, and a link between wandering patterns and the severity of the disease has been established. This work addresses the challenge of detecting dementia-related wandering behaviors. The proposed strategy utilizes data imputation methods and feature extraction with the Discrete Wavelet Transformation applied to a recently developed and comprehensive dataset. Machine learning algorithms are used to perform the final detection, and hyperparameter optimization is also evaluated.Experiments show that performance achieves an accuracy of approximately 98% using the Random Forest classifier. Results are competitive with the state-of-the-art in time series classification, with improved efficiency. The proposed methodology can be used for the development of applications for dementia related research and care.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 12","pages":"1009-1018"},"PeriodicalIF":1.3,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10789632","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-11DOI: 10.1109/TLA.2024.10789635
Luis Eduardo Ordoñez Palacios;Víctor Andrés Bucheli Guerrero;Eduardo Francisco Caicedo Bravo
Despite global efforts to adopt renewable energy, many remote regions still lack reliable electrical services. Addressing this requires a thorough analysis of solar resource data to identify viable solutions for these underserved areas. We evaluate the error in solar radiation data from a satellite image-based Random Forest (satellite RF) model by using data from IDEAM meteorological stations and NASA sources. By rigorously comparing these datasets, we aim to assess the reliability of predictive sources of solar radiation in the Amazon region. The results help establish confidence in various data sources, essential for utilizing estimated solar energy data in renewable energy research. We compared the data using the Relative Root Mean Squared Error (Relative RMSE). On the one hand, the relative RMSE between NASA and IDEAM ranges from 6.86% to 20.93%. On the other hand, the error between satellite RF model and IDEAM fluctuates between 6.56% and 12.33%. Similarly, the error between satellite RF model and NASA ranges from 4.80% to 15.27%. The findings indicate that the error in NASA data is higher compared to the error in satellite RF model data when benchmarked against IDEAM. Despite the limited number of meteorological stations and a maximum error of 20.93% between the two predictive data sources compared to ground-based observed data, we consider it reliable to use estimated solar radiation data for developing effective renewable energy solutions in remote locations.
{"title":"Assessment of Solar Irradiation Data Sources and Prediction Models for Rural Villages in the Colombian Amazon Region","authors":"Luis Eduardo Ordoñez Palacios;Víctor Andrés Bucheli Guerrero;Eduardo Francisco Caicedo Bravo","doi":"10.1109/TLA.2024.10789635","DOIUrl":"https://doi.org/10.1109/TLA.2024.10789635","url":null,"abstract":"Despite global efforts to adopt renewable energy, many remote regions still lack reliable electrical services. Addressing this requires a thorough analysis of solar resource data to identify viable solutions for these underserved areas. We evaluate the error in solar radiation data from a satellite image-based Random Forest (satellite RF) model by using data from IDEAM meteorological stations and NASA sources. By rigorously comparing these datasets, we aim to assess the reliability of predictive sources of solar radiation in the Amazon region. The results help establish confidence in various data sources, essential for utilizing estimated solar energy data in renewable energy research. We compared the data using the Relative Root Mean Squared Error (Relative RMSE). On the one hand, the relative RMSE between NASA and IDEAM ranges from 6.86% to 20.93%. On the other hand, the error between satellite RF model and IDEAM fluctuates between 6.56% and 12.33%. Similarly, the error between satellite RF model and NASA ranges from 4.80% to 15.27%. The findings indicate that the error in NASA data is higher compared to the error in satellite RF model data when benchmarked against IDEAM. Despite the limited number of meteorological stations and a maximum error of 20.93% between the two predictive data sources compared to ground-based observed data, we consider it reliable to use estimated solar radiation data for developing effective renewable energy solutions in remote locations.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 12","pages":"1019-1025"},"PeriodicalIF":1.3,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10789635","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article presents a progressive compensation strategy for gait recovery in patients with different degrees of limited knee mobility, based on angular analysis and muscle electrical activity, and artificial intelligence. Ten subjects were tested during gait on a flat surface simulating 4 conditions of limited knee mobility with an active knee brace. Data on the amplitude of the electrical signal from 3 leg muscles were analyzed: rectus femoris, tibialis anterior, and gastrocnemius. In addition to the electromyography sensors, an angular position sensor was placed on the knee joint. An artificial neural network was trained to identify the type of limitation of each patient in their muscle activity. A knee orthosis with a linear actuator was designed to compensate for the loss of force during knee flexion-extension movement, according with limiting condition. The actuator trajectory is controlled through a model reference adaptive controller with a fuzzy logic-based adaptation mechanism. The simulation demonstrates the efficiency of this strategy, despite the high-amplitude disturbances in the system.
{"title":"Mobility Deficit Identification and Compensation through an Artificial Neural Network and Adaptive Controller Design during Gait","authors":"Silvia Liliana Chaparro Cárdenas;Eduardo Castillo-Castañeda;Alejandro Alfredo Lozano-Guzmán","doi":"10.1109/TLA.2024.10789627","DOIUrl":"https://doi.org/10.1109/TLA.2024.10789627","url":null,"abstract":"This article presents a progressive compensation strategy for gait recovery in patients with different degrees of limited knee mobility, based on angular analysis and muscle electrical activity, and artificial intelligence. Ten subjects were tested during gait on a flat surface simulating 4 conditions of limited knee mobility with an active knee brace. Data on the amplitude of the electrical signal from 3 leg muscles were analyzed: rectus femoris, tibialis anterior, and gastrocnemius. In addition to the electromyography sensors, an angular position sensor was placed on the knee joint. An artificial neural network was trained to identify the type of limitation of each patient in their muscle activity. A knee orthosis with a linear actuator was designed to compensate for the loss of force during knee flexion-extension movement, according with limiting condition. The actuator trajectory is controlled through a model reference adaptive controller with a fuzzy logic-based adaptation mechanism. The simulation demonstrates the efficiency of this strategy, despite the high-amplitude disturbances in the system.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 12","pages":"1063-1072"},"PeriodicalIF":1.3,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10789627","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-11DOI: 10.1109/TLA.2024.10789634
Andres Navarro;Leonardo Vargas;Nicolas Salazar;Alfredo Serna-Sabater;José Maria Molina
The deployment of 5G services varies across the globe, in Europe, Asia, and North America have seen the most significant deployment, while some Latin American countries are still in the process. This review examines the regulations related to radio frequency bands and analyzes ways to optimize radio space in the 2300-2400 MHz band in Colombia. The findings and recommendations serve as a reference for similar countries in Latin America. Based on the results, it is recommended to maintain a minimum distance of 100 meters between IMT base stations and Bluetooth and ZigBee systems. For WiFi, it is advisable to use channels higher than 5 or ensure a separation of at least 1 kilometer. Indoors, no special attention is required due to wall attenuation. A separation of around 5 MHz is necessary between the two bands in laboratory tests. This ensures that the interference effects of IMT towards WiFi or vice versa stay within the acceptable limits of PER. The guard band should be established with respect to the LTE signal, which is the most restrictive case, and serves as the reference signal. In connection with band 40 of LTE, the guard band will be 0.6 MHz and 0.8 MHz with respect to the WLAN signal.
{"title":"Coexistence Study for the 2300-2400MHz IMT band in Colombia","authors":"Andres Navarro;Leonardo Vargas;Nicolas Salazar;Alfredo Serna-Sabater;José Maria Molina","doi":"10.1109/TLA.2024.10789634","DOIUrl":"https://doi.org/10.1109/TLA.2024.10789634","url":null,"abstract":"The deployment of 5G services varies across the globe, in Europe, Asia, and North America have seen the most significant deployment, while some Latin American countries are still in the process. This review examines the regulations related to radio frequency bands and analyzes ways to optimize radio space in the 2300-2400 MHz band in Colombia. The findings and recommendations serve as a reference for similar countries in Latin America. Based on the results, it is recommended to maintain a minimum distance of 100 meters between IMT base stations and Bluetooth and ZigBee systems. For WiFi, it is advisable to use channels higher than 5 or ensure a separation of at least 1 kilometer. Indoors, no special attention is required due to wall attenuation. A separation of around 5 MHz is necessary between the two bands in laboratory tests. This ensures that the interference effects of IMT towards WiFi or vice versa stay within the acceptable limits of PER. The guard band should be established with respect to the LTE signal, which is the most restrictive case, and serves as the reference signal. In connection with band 40 of LTE, the guard band will be 0.6 MHz and 0.8 MHz with respect to the WLAN signal.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 12","pages":"1073-1083"},"PeriodicalIF":1.3,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10789634","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-11DOI: 10.1109/TLA.2024.10789630
Roberto Moreno;Nancy Visairo Cruz;Ciro Alberto A. Núñez Gutiérrez;Julio Hernández Ramirez;Juan Segundo Ramirez
This paper addresses the problem of subsynchronous oscillations (SSO) in a doubly fed induction generator (DFIG) wind farm originated by its interaction with a series-compensated transmission line. Given its relevance in the system, several solutions and analysis methods have been utilized to tackle this issue. This article proposes an innovative function for a battery energy storage system (BESS) in mitigating SSO without compromising its primary functions. To achieve this aim, the article explains the origin of SSO and outlines how incorporating a BESS can effectively ease it. To evaluate the feasibility of this proposal, we conduct extensive simulations on a power system integrating energy-distributed resources from DFIG-based wind farms, employing a BESS to compensate for SSO induced by a series-compensated transmission line. The results confirm that BESS is highly effective in reducing or even eliminating SSO.
{"title":"Supplementary Loop in BESS Control Scheme for SSO Mitigation in DFIG-Based Wind Farms","authors":"Roberto Moreno;Nancy Visairo Cruz;Ciro Alberto A. Núñez Gutiérrez;Julio Hernández Ramirez;Juan Segundo Ramirez","doi":"10.1109/TLA.2024.10789630","DOIUrl":"https://doi.org/10.1109/TLA.2024.10789630","url":null,"abstract":"This paper addresses the problem of subsynchronous oscillations (SSO) in a doubly fed induction generator (DFIG) wind farm originated by its interaction with a series-compensated transmission line. Given its relevance in the system, several solutions and analysis methods have been utilized to tackle this issue. This article proposes an innovative function for a battery energy storage system (BESS) in mitigating SSO without compromising its primary functions. To achieve this aim, the article explains the origin of SSO and outlines how incorporating a BESS can effectively ease it. To evaluate the feasibility of this proposal, we conduct extensive simulations on a power system integrating energy-distributed resources from DFIG-based wind farms, employing a BESS to compensate for SSO induced by a series-compensated transmission line. The results confirm that BESS is highly effective in reducing or even eliminating SSO.","PeriodicalId":55024,"journal":{"name":"IEEE Latin America Transactions","volume":"22 12","pages":"1054-1062"},"PeriodicalIF":1.3,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10789630","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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