Abstract
Security and consistency of smart grids is one of the main issues in the design and maintenance of highly controlled and monitored new power grids. Bad data injection attack could lead to disasters such as power system outage, or huge economical losses. In many attack scenarios, the attacker can come up with new attack strategies that couldn't be detected by the traditional bad data detection methods. Adaptive Partitioning State Estimation (APSE) method [3] has been proposed recently to combat such attacks. In this work, we evaluate and compare with a traditional method. The main idea of APSE is to increase the sensitivity of the chi-square test by partitioning the large grids into small ones and apply the test on each partition individually and repeat this procedure until the faulty node is located. Our simulation findings using MATPOWER program show that the method is not consistent where it is sensitive the systems size and the location of faulty nodes as well.
Original language | English |
---|---|
Title of host publication | 2019 International Conference on Computer and Information Sciences, ICCIS 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781538681251 |
DOIs | |
State | Published - 15 May 2019 |
Publication series
Name | 2019 International Conference on Computer and Information Sciences, ICCIS 2019 |
---|
Bibliographical note
Publisher Copyright:© 2019 IEEE.
Keywords
- APSE
- Bad data injection
- Partitioning of power systems
- Security
- Smart grid
- State estimation
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Information Systems and Management