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Adaptive Fault Detection Based on Neural Networks and Multiple Sampling Points for Distribution Networks and Microgrids
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作者 J.Marín-Quintero C.Orozco-Henao +4 位作者 A.S.Bretas J.C.Velez A.Herrada A.Barranco-Carlos W.S.Percybrooks 《Journal of Modern Power Systems and Clean Energy》 SCIE EI CSCD 2022年第6期1648-1657,共10页
Smart networks such as active distribution network(ADN)and microgrid(MG)play an important role in power system operation.The design and implementation of appropriate protection systems for MG and ADN must be addressed... Smart networks such as active distribution network(ADN)and microgrid(MG)play an important role in power system operation.The design and implementation of appropriate protection systems for MG and ADN must be addressed,which imposes new technical challenges.This paper presents the implementation and validation aspects of an adaptive fault detection strategy based on neural networks(NNs)and multiple sampling points for ADN and MG.The solution is implemented on an edge device.NNs are used to derive a data-driven model that uses only local measurements to detect fault states of the network without the need for communication infrastructure.Multiple sampling points are used to derive a data-driven model,which allows the generalization considering the implementation in physical systems.The adaptive fault detector model is implemented on a Jetson Nano system,which is a single-board computer(SBC)with a small graphic processing unit(GPU)intended to run machine learning loads at the edge.The proposed method is tested in a physical,real-life,low-voltage network located at Universidad del Norte,Colombia.This testing network is based on the IEEE 13-node test feeder scaled down to 220 V.The validation in a simulation environment shows the accuracy and dependability above 99.6%,while the real-time tests show the accuracy and dependability of 95.5%and 100%,respectively.Without hard-to-derive parameters,the easy-to-implement embedded model highlights the potential for real-life applications. 展开更多
关键词 Distribution network MICROGRID adaptive protection intelligent electronic device machine learning
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Operational Control of Low-voltage MTDC Systems in a Cyber-physical Environment
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作者 Wei Deng Wei Pei +3 位作者 Ningning Li Xue Zhang Yin Yi Li Kong 《CSEE Journal of Power and Energy Systems》 SCIE EI CSCD 2022年第6期1569-1582,共14页
Based on the standardized cyber-physical modeling and communication system-IEC 61850,this paper establishes the operational control architecture of a low-voltage multi-terminal DC(LV-MTDC)system.The coordinated operat... Based on the standardized cyber-physical modeling and communication system-IEC 61850,this paper establishes the operational control architecture of a low-voltage multi-terminal DC(LV-MTDC)system.The coordinated operational control strategies,including power electronic transformer(PET),and voltage source converter(VSC),are proposed.Then a cyberphysical model of the system based on IEC 61850 is built,according to the application requirements of operational control in the LV-MTDC system.On this basis,the implementation method of system operational control based on IEC 61850 is proposed,including the software/hardware design of the intelligent electronic device(IED),dispatching operations and uninterrupted power supply.The simulation environment is further built to verify the system operational control technology,and the test platform is used to carry out the actual tests.The research results show that the operational control technology for the LV-MTDC system proposed in this paper is feasible,which can guarantee the rapid and accurate information exchange of control commands and settings,and thus effectively realize the operational control of the LV-MTDC system under complex conditions. 展开更多
关键词 Cyber-physical system distributed energy resources IEC 61850 intelligent electronic device low-voltage multi-terminal DC system
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