Abstract
Ensuring accurate estimation of the system's states (voltage-magnitude and phase-angle) is a vital task for protection, monitoring, controlling and smooth running of modern power systems. Meters, located randomly in different parts of the system often provide the estimators with wrong measurement (single or multiple) which could cause deterioration in the estimation performance badly. Cosequently, dealing with such bad data is one of the major challenges in the field of power system State Estimation (SE). This paper presents a robust estimator, Least Measurement Rejected (LMR), that has the capability of dealing with different single and multiple bad data scenarios successfully. The proposed LMR estimator is formulated with appropriate selection of tolerances of the meter readings. The performance of the proposed estimator is compared with the Weighed Least Square (WLS) and Weighted Least Absolute Value (WLAV) estimators. IEEE 14-bus and 30- bus systems are used to prove the robustness of the proposed estimator.
| Original language | English |
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| Title of host publication | 2017 IEEE Innovative Smart Grid Technologies - Asia |
| Subtitle of host publication | Smart Grid for Smart Community, ISGT-Asia 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1-6 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781538649503 |
| DOIs | |
| State | Published - 8 Jun 2018 |
Publication series
| Name | 2017 IEEE Innovative Smart Grid Technologies - Asia: Smart Grid for Smart Community, ISGT-Asia 2017 |
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Bibliographical note
Publisher Copyright:© 2017 IEEE.
Keywords
- Bad-data
- Least Measurement Rejected
- State Estimation
- Weighted Least Absolute Value
- Weighted Least Square
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering
- Control and Optimization
- Safety, Risk, Reliability and Quality