Maximum Likelihood Ensemble Filter State Estimation for Power Systems-Reference-Cited by-同舟云学术

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Maximum Likelihood Ensemble Filter State Estimation for Power Systems

Published:2018-09 Issue:9 Volume:67 Page:2097-2106
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Uzunoglu Bahri^ORCID,Ulker Muhammed Akif

Funder

Computational Renewables LLC

European Union H2020 ERA-Net Smart-Grid Project Multi-Input Intelligent Distribution Automation System

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/8430491/08327845.pdf?arnumber=8327845

Cited by 16 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. GPU parallel processing to enable extensive criticality analysis in state estimation;Concurrency and Computation: Practice and Experience;2024-06-11

2. Supervised learning for more accurate state estimation fusion in IoT-based power systems;Information Fusion;2023-08

3. Robust Kalman Filter for Position Estimation of Automated Guided Vehicles Under Cyberattacks;IEEE Transactions on Instrumentation and Measurement;2023

4. Exact Modeling of Non-Gaussian Measurement Uncertainty in Distribution System State Estimation;IEEE Transactions on Instrumentation and Measurement;2023

5. Power Flow Parameter Estimation in Power System Using Machine Learning Techniques Under Varying Load Conditions;International Journal of Electrical and Electronics Research;2022-12-30

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