A Comprehensive Review of Hybrid State Estimation in Power Systems: Challenges, Opportunities and Prospects

Leila Kamyabi, Tek Tjing Lie (), Samaneh Madanian and Sarah Marshall
Additional contact information
Leila Kamyabi: School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1120, New Zealand
Tek Tjing Lie: School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1120, New Zealand
Samaneh Madanian: School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1120, New Zealand
Sarah Marshall: Department of Information Systems and Operations Management, University of Aukland, Auckland 1120, New Zealand

Energies, 2024, vol. 17, issue 19, 1-20

Abstract: Due to the increasing demand for electricity, competitive electricity markets, and economic concerns, power systems are operating near their stability margins. As a result, power systems become more vulnerable following disturbances, particularly from a dynamic point of view. To maintain the stability of power systems, operators need to continuously monitor and analyze the grid’s state. Since modern power systems are large-scale, non-linear, complex, and interconnected, it is quite challenging and computationally demanding to monitor, control, and analyze them in real time. State Estimation (SE) is one of the most effective tools available to assist operators in monitoring power systems. To enhance measurement redundancy in power systems, employing multiple measurement sources is essential for optimal monitoring. In this regard, this paper, following a brief explanation of the SE concept and its different categories, highlights the significance of Hybrid State Estimation (HSE) techniques, which combine the most used data resources in power systems, traditional Supervisory Control and Data Acquisition (SCADA) system measurements and Phasor Measurement Units (PMUs) measurements. Additionally, recommendations for future research are provided.

Keywords: Static State Estimation; Dynamic State Estimation; Hybrid State Estimation; power systems (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/17/19/4806/pdf (application/pdf)
https://www.mdpi.com/1996-1073/17/19/4806/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:17:y:2024:i:19:p:4806-:d:1485805

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().