Analytical method for analyzing message transmission processes in FDDI networks for digital substations

Objectives. To develop analytical approaches for the evaluation of probability-time characteristics and fiber distributed data interface (FDDI) network performance with the marker access method, thus enabling communication processes for digital electrical substations to be automated.

Methods. The authors used theory reliability methods, random process theory, mass maintenance theory, the Laplace–Stieltjes transformation for inferring functional equations and the probability-time characteristics calculation for the information transfer processes with the occurring failures.

Results. We conducted a numerical study of packet transfer processes between central processing stations in the FDDI network. We considered the processes of discrete information exchange between electronic devices in the system of electrical digital substations. These included the main technological operations and electrical digital substations operator performed when preparing reports. We described the different modes of operation, both for the individual electrical digital substation and for the system. The authors calculated node loading dependencies, FDDI network performance and temporal characteristics of the packet transfer processes on the incoming message flow intensity and the transmission medium reliability. We conducted a functional analysis of the FDDI networks on two fiber-optic rings which form the main and redundant path of data transfer between the network nodes, significantly increasing network resiliency. The objective of the study was to analyze the information transfer processes in FDDI networks with an accent on ensuring the transmission medium reliability.

Conclusions. We were able to establish the existence of the critical operating network region, which leads to a sharp increase in node load and temporal characteristics, while performance reaches its maximum value and then sharply decreases. We propose the exchange of discrete messages to reflect the electronic devices state and information messages of operator between various remotely spaced electrical digital substation with the FDDI fiber-optic network.

1. Gromov I.V., Egorov E.P., Koshelkov I.A. Comparative analysis of the provisions of various editions of the IEK 61850 standard when using the GOOSE and SV protocols. Releinaya zashchita i avtomatizatsiya = Relay Protection and Automation. 2019;4(37):46–49 (in Russ.).

2. Sapna, Sharma M. Performance evaluation of a wired network with & without Load Balancer and Firewall. In: 2010 International Conference on Electronics and Information Engineering. Kyoto, Japan. 2010. P. V2-515–V2-519. https://doi.org/10.1109/ICEIE.2010.5559755

3. Bessoltsev V.S., Khorkov S.A. Digital substation: Structure, protocols, architecture. Collection of abstracts of the 12th International Scientific and Practical Conference. Izhevsk; 2022. P. 23–27 (in Russ.).

4. Zhmatov D.V. Technical Condition Monitoring of Electric Equipment in the Digital Substation. In: 2020 2nd International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA). 2020. P. 983–986. https://doi.org/10.1109/SUMMA50634.2020.9280800

5. Kharlamov V.A., Romanov S.E., Khasanov A.K. Ways to transmit GOOSE messages between substations for PAC systems. Releishchik. 2022(2):12–17 (in Russ.).

6. Bezdenezhnykh M.N., Egorov A.P., Koshelkov I.A., Doni N.A. GOOSE network load analysis software IEC 61850-8-1:2011. Avtomatizatsiya i IT v Energetike. 2019;8(121):22–25 (in Russ.). Available from URL: https://elibrary.ru/ojmxwt

7. Wei M., Chen Z. Study of LANs access technologies in wind power system. In: IEEE PES General Meeting. Minneapolis, MN, USA. 2010.

8. Zvonareva G.A., Buzunov D.S. Using Simulation Modeling to Estimate Time Characteristics of a Distributed Computing System. Otkrytoe obrazovanie = Open Education. 2022;26(5):32–39 (in Russ.). https://doi.org/10.21686/1818-4243-2022-5-32-39

9. Leontyev A.S. Multilevel Analytical and Analytical-Simulation Models for Evaluating the Probabilistic and Temporal Characteristics of Multimachine Computing Complexes with Regard to Reliability. Mezhdunarodnyi nauchno-issledovatel’skii zhurnal = International Research Journal. 2023;5(131) (in Russ.). https://doi.org/10.23670/IRJ.2023.131.8

10. Kul’ba V.V., Mamikonov A.G., Shelkov A.B. Redundancy of program modules and data arrays in a MIS. Avtomatika i telemekhanika = Automation and Remote Control. 1980;8:133–141 (in Russ.).

11. Talalaev A.A., Frolenko V.P. Fault-tolerant system for organizing high-performance computing for solving data stream processing problems. Programmnye sistemy: Teoriya i prilozheniya = Program Systems: Theory and Applications. 2018;9(1–36):85–108 (in Russ.). https://doi.org/10.25209/2079-3316-2018-9-1-85-108

12. Akimova G.P., Solovyev A.V., Tarkhanov I.A. Modeling the reliability of distributed information systems. Informatsionnye tekhnologii i vychislitel’nye sistemy = Journal of Information Technologies and Computing Systems. 2019;3:70–86 (in Russ.). https://doi.org/10.14357/20718632190307

13. Pavsky V.A., Pavsky K.V. Mathematical Model for Calculating Reliability Indicators of Scalable Computer Systems Considering Switching Time. Izvestiya YuFU. Tekhnicheskie nauki = Izvestiya SFedU. Engineering Sciences. 2020;2(212):134–145 (in Russ.). https://doi.org/10.18522/2311-3103-2020-2-134-145

14. Ahmed W., Wu Y.W. A survey on reliability in distributed systems. J. Comput. System Sci. 2013;79(8):1243–1255. https://doi.org/10.1016/j.jcss.2013.02.006

15. Leontyev A.S. Development of Analytical Methods, Models, and Techniques for Local Area Networks Analysis. In: Theoretical Issues of Software Engineering: Interuniversity Collection of Scientific Papers. Moscow: MIREA; 2001. Р. 70–94 (in Russ.).

16. Ivanichkina L.V., Neporada A.L. The Reliability model of a distributed data storage in case of explicit and latent disk faults. Trudy Instituta sistemnogo programmirovaniya RAN = Proceedings of the Institute for System Programming of the RAS. 2015;27(6):253–274 (in Russ.). https://doi.org/10.15514/ISPRAS-2015-27(6)-16