A Multiobjective Intelligent Decision-Making Method for Multistage Placement of PMU in Power Grid Enterprises-Reference-Cited by-同舟云学术

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A Multiobjective Intelligent Decision-Making Method for Multistage Placement of PMU in Power Grid Enterprises

Published:2022 Issue: Volume: Page:1-9
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Cao Bin¹^ORCID,Yan Yanlong¹,Wang Yu¹,Liu Xin²^ORCID,Lin Jerry Chun-Wei³^ORCID,Sangaiah Arun Kumar⁴^ORCID,Lv Zhihan⁵^ORCID

Affiliation:

1. State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin, China

2. School of Economics and Management, Hebei University of Technology, Tianjin, China

3. Western Norway University of Applied Sciences, USA

4. Vellore Institute of Technology, India

5. Uppsala University, Sweden

Funder

National Natural Science Foundation of China

Natural Science Fund of Hebei Province for Distinguished Young Scholars

Fundamental Scientific Research Funds for Interdisciplinary Team of Hebei University of Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/9424/4389054/09925065.pdf?arnumber=9925065

Cited by 64 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep Reinforcement Learning-Based Optimal PMU Placement Considering the Degree of Power System Observability;IEEE Transactions on Industrial Informatics;2024-06

2. Optimal location of PMUs for full observability of power system using coronavirus herd immunity optimizer;Heliyon;2024-06

3. Utilizing sine trigonometric q-spherical fuzzy rough aggregation operators for group decision-making and their role in digital transformation;Heliyon;2024-05

4. Synchrophasor Technology Applications and Optimal Placement of Micro-Phasor Measurement Unit (μPMU): Part I;2024 28th International Electrical Power Distribution Conference (EPDC);2024-04-23

5. The residual life prediction of power grid transformers based on GA-ELM computational model and digital twin data;EAI Endorsed Transactions on Energy Web;2024-04-04

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