Online Steady-State Security Awareness Using Cellular Computation Networks and Fuzzy Techniques

Lili Wu, Ganesh K. Venayagamoorthy and Jinfeng Gao
Additional contact information
Lili Wu: School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
Ganesh K. Venayagamoorthy: Real-Time Power and Intelligent Systems Laboratory, Holcombe Department of Electrical and Computer Engineering, Clemson University, Clemson, SC 29634, USA
Jinfeng Gao: School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China

Energies, 2020, vol. 14, issue 1, 1-17

Abstract: Power system steady-state security relates to its robustness under a normal state as well as to withstanding foreseeable contingencies without interruption to customer service. In this study, a novel cellular computation network (CCN) and hierarchical cellular rule-based fuzzy system (HCRFS) based online situation awareness method regarding steady-state security was proposed. A CCN-based two-layer mechanism was applied for voltage and active power flow prediction. HCRFS block was applied after the CCN prediction block to generate the security level of the power system. The security status of the power system was visualized online through a geographic two-dimensional visualization mechanism for voltage magnitude and load flow. In order to test the performance of the proposed method, three types of neural networks were embedded in CCN cells successively to analyze the characteristics of the proposed methodology under white noise simulated small disturbance and single contingency. Results show that the proposed CCN and HCRFS combined situation awareness method could predict the system security of the power system with high accuracy under both small disturbance and contingencies.

Keywords: steady-state security assessment; situation awareness; cellular computational networks; load flow prediction; contingency; fuzzy system (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: 2020
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/1/148/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/1/148/ (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:14:y:2020:i:1:p:148-:d:470313

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 ().