Proactive Frequency Stability Scheme: A Distributed Framework Based on Particle Filters and Synchrophasors

Gian Paramo and Arturo Bretas ()
Additional contact information
Gian Paramo: Department of Electrical & Computer Engineering, University of Florida, Gainesville, FL 32608, USA
Arturo Bretas: Department of Electrical & Computer Engineering, University of Florida, Gainesville, FL 32608, USA

Energies, 2023, vol. 16, issue 11, 1-19

Abstract: The reactive nature of traditional under-frequency load shedding schemes can lead to delayed response and unnecessary loss of load. This work presents a proactive framework for power system frequency stability. Bayesian filters and synchrophasors are leveraged to produce predictions after disturbances are detected. By being able to estimate the future state of frequency corrective actions can be taken before the system reaches a critical condition. This proactive approach makes it possible to optimize the response to a disturbance, which results in a decrease in the amount of compensation utilized. The framework is tested via Matlab simulations based on Kundur’s Two-Area System, and the IEEE 14-Bus System. Performance metrics are provided and evaluated against other contemporary solutions found in literature. During testing this framework outperformed other solutions by drastically reducing the amount of load dropped during compensation.

Keywords: frequency stability; particle filter; phasor measurement units; 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: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/11/4530/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/11/4530/ (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:16:y:2023:i:11:p:4530-:d:1164368

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 ().