EconPapers    
Economics at your fingertips  
 

A Comprehensive Risk Assessment Framework for Synchrophasor Communication Networks in a Smart Grid Cyber Physical System with a Case Study

Amitkumar V. Jha, Bhargav Appasani, Abu Nasar Ghazali and Nicu Bizon
Additional contact information
Amitkumar V. Jha: School of Electronics Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar 751024, India
Bhargav Appasani: School of Electronics Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar 751024, India
Abu Nasar Ghazali: School of Electronics Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar 751024, India
Nicu Bizon: Faculty of Electronics, Communication and Computers, University of Pitesti, 110040 Pitesti, Romania

Energies, 2021, vol. 14, issue 12, 1-20

Abstract: The smart grid (SG), which has revolutionized the power grid, is being further improved by using the burgeoning cyber physical system (CPS) technology. The conceptualization of SG using CPS, which is referred to as the smart grid cyber physical system (SGCPS), has gained a momentum with the synchrophasor measurements. The edifice of the synchrophasor system is its communication network referred to as a synchrophasor communication network (SCN), which is used to communicate the synchrophasor data from the sensors known as phasor measurement units (PMUs) to the control center known as the phasor data concentrator (PDC). However, the SCN is vulnerable to hardware and software failures that introduce risk. Thus, an appropriate risk assessment framework for the SCN is needed to alleviate the risk in the protection and control of the SGCPS. In this direction, a comprehensive risk assessment framework has been proposed in this article for three types of SCNs, namely: dedicated SCN, shared SCN and hybrid SCN in an SGCPS. The proposed framework uses hardware reliability as well as data reliability to evaluate the associated risk. A simplified hardware reliability model has been proposed for each of these networks, based on failure probability to assess risk associated with hardware failures. Furthermore, the packet delivery ratio (PDR) metric is considered for measuring risk associated with data reliability. To mimic practical shared and hybrid SCNs, the risk associated with data reliability is evaluated for different background traffics of 70%, 80% and 95% using 64 Kbps and 300 Kbps PMU data rates. The analytical results are meticulously validated by considering a case study of West Bengal’s (a state in India) power grid. With respect to the case study, different SCNs are designed and simulated using the QualNet network simulator. The simulations are performed for dedicated SCN, shared SCN and hybrid SCN with 64 Kbps and 300 Kbps PMU data rates. The simulation results are comprehensively analyzed for risk hedging of the proposed SCNs with data reliability and hardware reliability. To summarize, the mean risk with data reliability (RwDR) as compared to the mean risk with hardware reliability (RwHR) increases in shared SCN and hybrid SCN by a factor of 17.108 and 23.278, respectively. However, minimum RwDR increases in shared and hybrid SCN by a factor of 16.005 and 17.717, respectively, as compared to the corresponding minimum RwHR. The overall analysis reveals that the RwDR is minimum for dedicated SCN, moderate for shared SCN, and highest for hybrid SCN.

Keywords: smart grid; cyber physical system (CPS); smart grid cyber physical system (SGCPS); synchrophasor communication network; risk assessment; reliability; packet delivery ratio (PDR); QualNet (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: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/12/3428/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/12/3428/ (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:2021:i:12:p:3428-:d:572370

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 ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:14:y:2021:i:12:p:3428-:d:572370