A Static State Estimation Approach Including Bad Data Detection and Identification in Power Systems

By Jeu-Min Lin, H. Pan. IEEE Power Engineering Society General Meeting, 2007

48 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Electrical and Electronic Engineering, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/5eea1b07331d5e717690bbe93c7c4a7775c211ad

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Michael K. Reiter
2. Peng Ning
3. Yao Liu

In Electrical and Electronic Engineering

1. Yao Liu
2. Michael K. Reiter
3. Peng Ning
4. Aleksandar D. Dimitrovski
5. Husheng Li
6. Henrik Sandberg
7. Karl Henrik Johansson
8. André M. H. Teixeira

In Statistical and Nonlinear Physics

1. Michael K. Reiter
2. Peng Ning
3. Yao Liu

Citations in the corpus

• Time Synchronization Attack in Smart Grid: Impact and Analysis (2013, background): “To launch FDIA successfully, malicious attackers need to have full knowledge of the power grid network such that a systematic false measurements can be generated to bypass the bad measurement detection [15].”
• False data injection attacks against state estimation in electric power grids (2011, background): “…is that all existing algorithms for bad measurement detection in DC power .ow models rely on the same assumption that when bad measurements take place, the squares of differences between the observed measurements and their corresponding estimates often become signi.cant [Lin and Pan 2007].”