IEEE Power & Energy Magazine - July/August 2019 - 28

RTU
(154-kV Substation)

RTUs

Third-Party
Application
I/F

Operator Console

RTUs

Automatic Substation Restoration System
(Server)

SCADA

AP/FEP/
DB Server

DNP on
TCP/IP

Real-Time Data Storage Memory Sector
Server Internal
Process

AI/Expert
System
Dynamic
Model

Main
Engine

AI Search

Intelligence
Process

SCADA
DB

Failure
Facility
Judgment

*SCADA: Supervisory Control and Data Acquisition
*RTU: Remote Terminal Unit
*DNP: Distributed Network Protocol
*AP Server: Application Server
*FEP: Front-End Processor
*DB: Database

TCP/IP
* Operator HMI
* Relay, CB
* Fault Location
* Load Outage
* Fault Record
* Control Record
* Topology and so on
* Fault Restoration

Sending Data
* Monitoring
* Control
* Measuring

Automatic Substation
Restoration System (Client)

Control
Strategy

Substation
DB

Decision
Record

Intelligence
DB

* AI Engine
* DB Engineering
* Restoration
Procedure Engineering
* System Engineering

figure 2. The proposed architecture of the automatic substation restoration system.

IEC 61850 expects interoperability of various devices in a
substation, but it has been observed that complete interoperability cannot be guaranteed when devices from various
vendors are installed. To solve this, the development of the
second version of a client conformance testing system based
on IEC 61850 was started during the innovation stage, as seen
in Table 2. Procedures and systems for the test and verification
of the digital substation's high-level system are expected to be
developed. This will support installation by verifying the interoperability of IEDs in digital substations, which are being
installed more often in the future Korean power grid.

Development of an Automatic Substation
Restoration System
When a substation is tripped due to a fault, it needs to be
restored as soon as possible. Fault isolation and substation
restoration improve the reliability of a power system. As the
complexity of the modern grid increases, a new machinelearning-based automatic substation restoration strategy will
replace the existing expert system-based algorithms and
reinforce system restoration. Once a fault occurs, the faulty
zone will be instantly identified, and a smart strategy for
restoring the system will be executed, which will complete
restoration in 1 min. By comparison, the average recovery
time, over the past 10 years, of the existing fault recovery
system has been 4.8 min. The automatic restoration system
should help avoid potential failures due to human errors
in the existing system. Figure 2 shows the architecture of
the automatic substation restoration system using artificial
28

ieee power & energy magazine

intelligence (AI). This project will be completed in 2019,
and an automatic substation restoration system demonstration project in substations will be implemented from 2019
to 2020. Depending on the results of the project, the automatic substation restoration system may be expanded to
other substations.

Advanced Metering Infrastructures
KEPCO has expanded metering infrastructure in substations
to provide situational awareness of the grid state and
measurements of data. These details inform power system
operations and enable the accurate analysis of the system
impacts due to the expanded adoption of DERs. Currently,
KEPCO uses PMUs in several HV substations (e.g., 765 and
345 kV) to monitor system status. In substations (e.g., 345
and 154 kV) without PMUs, a power quality meter is used for
system monitoring as well as data measurements. In 22.9-kV
substations, a power quality management system (PQMS)
monitors the state of the system as well as power quality.
The data from these advanced metering infrastructures
(AMIs), analytical models of generators, transmission lines,
and loads have been developed that improve the accuracy of
power system analysis.

Online Load Modeling
Because power system data from substations can validate
dynamic load models for power system stability analysis, a
load-modeling automation system (LMAS) was developed.
Figure 3 illustrates the overall data and information flow
july/august 2019

IEEE Power & Energy Magazine - July/August 2019

Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - July/August 2019