Optimal Placement of Power Quality Monitors in Complex Distribution Network Based on Topological Degradation

Yu, Junwei; Sun, Yang; Lu, Jiangang; Qiwu, Zou; Xie, Xinlin; Fu, Bin; Liu, Wang; Ye, Liangpeng; Chen, Yiqin

doi:10.1109/iciea.2019.8834084

Cited by 3 publications

(1 citation statement)

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“…In Reference [128], the authors implemented the TLBO algorithm to optimally locate PQMs by considering degradation in large distribution networks. The objective of this approach was to minimize the number of PQMs in order to minimize the costs of assets in the monitoring system.…”

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confidence: 99%

Advanced Distribution Measurement Technologies and Data Applications for Smart Grids: A Review

et al. 2020

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The integration of advanced measuring technologies in distribution systems allows distribution system operators to have better observability of dynamic and transient events. In this work, the applications of distribution grid measurement technologies are explored in detail. The main contributions of this review are: (a) a comparison of eight advanced measurement devices for distribution networks, based on their technical characteristics, including reporting periods, measuring data, precision, and sample rate; (b) a review of the most recent applications of micro-Phasor Measurement Units, Smart Meters, and Power Quality Monitoring devices used in distribution systems, considering different novel methods applied for data analysis; and (c) an input-output table that relates measured quantities from micro-Phasor Measurement Units and Smart Meters needed for each specific application found in this extensive review. This paper aims to serve as an important guide for researches and engineers studying smart grids.

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Advanced Distribution Measurement Technologies and Data Applications for Smart Grids: A Review

et al. 2020

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A Power Quality Monitoring Method for Active Distribution Networks with Low Data Volume Dependence

Mao,

Wang,

Geng

et al. 2023

2023 IEEE 18th Conference on Industrial Electronics and Applications (ICIEA)

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Software Integration of Power System Measurement Devices with AI Capabilities

Arenas-Ramos,

Cuesta,

Pallares-Lopez

et al. 2024

Applied Sciences

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The latest changes on the distribution network due to the presence of distributed energy resources (DERs) and electric vehicles make it necessary to monitor the grid using a real-time high-precision system. The present work centers on the development of an open-source software platform that allows for the joint management of, at least, power quality monitors (PQMs), phasor measurement units (PMUs), and smart meters (SMs), which are three of the most widespread devices on distribution networks. This framework could work remotely while allowing access to the measurements in a comfortable way for grid analysis, prediction, or control tasks. The platform must meet the requirements of synchronism and scalability needed when working with electrical monitoring devices while considering the large volumes of data that these devices generate. The framework has been experimentally validated in laboratory and field tests in two photovoltaic plants. Moreover, real-time Artificial Intelligence capabilities have been validated by implementing three Machine Learning classifiers (Neural Network, Decision Tree, and Random Forest) to distinguish between three different loads in real time.

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Optimal Placement of Power Quality Monitors in Complex Distribution Network Based on Topological Degradation

Cited by 3 publications

References 0 publications

Advanced Distribution Measurement Technologies and Data Applications for Smart Grids: A Review

Advanced Distribution Measurement Technologies and Data Applications for Smart Grids: A Review

A Power Quality Monitoring Method for Active Distribution Networks with Low Data Volume Dependence

Software Integration of Power System Measurement Devices with AI Capabilities

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