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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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Performance Analysis of Routable GOOSE Security Algorithm for Substation Communication through Public Internet

Soohyun Shin¹, Hyosik Yang¹

¹Department of Computer Science and Engineering, Sejong University, 209, Neungdong-ro, Gwangjin-gu, Seoul 05006, Republic of Korea.

Sensors (Basel, Switzerland)

|July 8, 2023

Summary

Next-generation substations need external data for accurate system monitoring. This study proposes a secure method using R-GOOSE over public networks to acquire this crucial data, enhancing power grid efficiency.

Keywords:

IEC 61850 routable GOOSE protocol data aggregator micro-grid public internet network security

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Area of Science:

Electrical Engineering
Power Systems
Cybersecurity

Background:

Traditional power grids are evolving towards increased efficiency, necessitating advanced data acquisition methods.
Current substation protection relays are limited by relying solely on internal data, hindering accurate system change detection.
Acquiring data from external substations, including microgrids, is essential for next-generation power systems.

Purpose of the Study:

To propose a secure method for acquiring data from external substations for enhanced power system monitoring.
To address the challenges of cost and security in inter-substation data acquisition.
To develop a data aggregator utilizing a novel communication protocol.

Main Methods:

Applying security enhancements to the R-GOOSE protocol, as defined in the IEC 61850 standard.
Utilizing a public internet network for data transmission between substations.
Developing a data aggregator specifically designed for R-GOOSE communication.

Main Results:

Demonstrated the feasibility of acquiring data from external substations using the proposed secure R-GOOSE method.
Successfully developed and tested a data aggregator capable of collecting data via R-GOOSE.
Showcased the potential for improved system monitoring and efficiency in next-generation substations.

Conclusions:

The proposed secure R-GOOSE approach enables cost-effective and secure data acquisition from external substations.
This method overcomes previous limitations of relying solely on internal substation data.
The developed data aggregator facilitates enhanced real-time monitoring and control of distributed power systems.