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Comparative Analysis of Stability and Electromagnetic Transient Studies for HVDC Multi-infeed Systems

CSEE Journal of Power and Energy Systems 2017年第3期3卷 253-259页

作者： Marcio Szechtman Maria Jose Ximenes Arnoldo rodrigo saavedra Dual Consulting Rio de JaneiroBrazil ONS-National System Operator of Brazil Rio de JaneiroBrazil Electel Engineering Rio de JaneiroBrazil

In previous papers,the authors presented various electromagnetic transient(EMT)results for multi-infeed configurations focusing on possible effects from failures in one link being transferred to others in terms of induced commutation failures(CF),either during the fault events or after fault clearing in the recovery ***,the AC system networks in these cases were represented by simplified *** interesting conclusions arose from these publications without enabling a much-detailed analysis of overall system effects,which is only possible when the network is modeled in full *** paper aims at complementing and comparing simulation results on HVDC multi-infeed configurations using both dynamic stability and electromagnetic transient,while establishing some basic proposals for optimal use of both *** identifies the limitations from each type of study so that a comprehensive and useful analysis of HVDC multi-infeed systems can be obtained.

关键词： AC/DC interactions commutation failures HVDC multi-infeed configurations

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Precision silviculture:use of UAVs and comparison of deep learning models for the identification and segmentation of tree crowns in pine crops

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International Journal of Digital Earth 2022年第1期15卷 2223-2238页

作者： Manuel Ignacio Perez Bruno Karelovic Roberto Molina rodrigo saavedra Pierluigi Cerulo Guillermo Cabrera Department of Computer Sciences Universidad de Concepcion Biblioteca CentralConcepcionChile Celulosa Arauco y Constitucion SA I&DSantiagoChile

The monitoring of trees is crucial for the management of large areas of forest cultivations,but this process may be ***,remotely sensed data offers a solution to automate this *** this work,we used two neural network methods named You Only Look Once(YOLO)and Mask R-CNN to overcome the challenging tasks of counting,detecting,and segmenting high dimensional Red–Green–Blue(RGB)images taken from unmanned aerial vehicles(UAVs).We present a processing framework,which is suitable to generate accurate predictions for the aforementioned tasks using a reasonable amount of labeled *** compared our method using forest stands of different ages and *** counting,YOLO overestimates 8.5%of the detected trees on average,whereas Mask R-CNN overestimates a 4.7%of the *** the detection task,YOLO obtains a precision of 0.72 and a recall of 0.68 on average,while Mask R-CNN obtains a precision of 0.82 and a recall of *** segmentation,YOLO overestimates a 13.5%of the predicted area on average,whereas Mask R-CNN overestimates a 9.2%.The proposed methods present a cost-effective solution for forest monitoring using RGB images and have been successfully used to monitor∼146,500 acres of pine cultivations.

关键词： Artificial intelligence tree identification forestry remote sensing

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