Extended CIM Model to WAMS - Epcc-workshop.net

Extended CIM Model to WAMS
Wenbin Qi
qiwenbin@sf-auto.com
Beijing Sifang Automation Co., Ltd.,CHINA

Introduction
�In china , WAMS were established in the
Regional \ Provincial control centers.
� More than 700 substations or power plants have
been equipped with PMU, that includes:
– Nearly all 750kV, 500kV, 330kV substations in state grid and
regional grids
– Key 220kV and 110kV substations in provincial grids
– All generators with capacity of 600MW or above

�Sifang Automation Co., Ltd . has over 50% of
the WAMS and PMU market share in China.
Until May 13, 19,982 measuring points of
PMU have been installed at 103 substations
and power plants in North China grid.
�Experience of using WAMS has been
accumulated ,but the usage of its information
is still a challenge.

The Architecture of Master station of
firewall
switch
comunication
server
WEB
Server
PMU
Application
Server
Magnetic
disk panel
Communicatio
server
Data Server
EMS
SAN
exchanger
WAMS
Workstation of dispatching
modes and maintenance
I/O Node Ser ver
Administrative
ser ver
Parallel
Computer

Network model and
parameters check
Synchronous machine
parameters check
Load model identification
data integration and
state estimation
PMU SCADA
System Function
Low-frequency oscillations
in real-time alarm
Voltage stability in real-time alarm
power angle stability Real-time
Alarm
Frequency stability Real-time Alarm
Heat stability Real-time Alarm
Auxiliary services Assessment
Disturbance identification
Transient stability assessment
Voltage stability assessment
transmission power limit Calculation
Dynamic Stability Assessment
Static stability assessment
Dispatch Decision
Supporting
Security Stability
Control

The Main Functions Achieved
� Application
– Disturbance identification
– An FM Unit features assessment
– Small disturbance oscillation
statistics
– Low-frequency oscillations
detection
– The relative phase angle Monitor
– The characteristics of Wind
monitoring and analysis
– Model parameters analysis
– State Estimation
� Dispatching monitor and control
– Power flow distribution diagram
– Power angle distribution diagram
– Frequency / voltage monitor
– Wind power output monitor plan
– Generator run status monitor
– Plant Main wiring diagram
– Master / sub-station operating
conditions

Coherent bus grouping for low
� Besides mode frequency,
amplitude and damping
coefficient.
� Provide coherent bus
grouping function.
� Identify the oscillation
interface or oscillation
center.
� Calculate oscillation power
contribution of each nodes.
frequency oscillation
Nearly in the same phase
Nearly in opposite phase

Coherent bus grouping and oscillation
power contribution in contour map

The mode frequency distribution of oscillations
satisfying statistic conditions in a Shandong power grid
(1) Online scan all the active power PMU measurement and make fast
frequency spectrum analysis
(2) If an oscillation power has amplitude greater than 10MW and lasts at
least for 5 periods, then one oscillation with such mode frequency is
recorded
(3) The above figure is a oscillation statistics for one month
(4) For the found dangerous mode, an oscillation instance can be selected
to make further analysis(e.g. to get coherent bus groups and oscillation
center)

Unit Frequency Characteristics
Assessment

The Assessment of Unit FM
Characteristics
� Studies have shown that a unit
characteristic frequency shows a great
dynamic characteristics ,steady-state
results have a larger deviation, therefore,
only once time unit of data can’t reflect
the capacity of a frequency modulation ,
it must be accumulated with the longterm
real-time data which reflect an FM
unit functional contribution to the
system, also as a basis for assessment.
� using high-precision and synchronization
measurement of unit frequency and
power of WAMS, the energy
contribution of unit FM can be
calculated, if it is positive, shown unit
contribution to the grid frequency
modulation.
� Day \ Month\ Quarter power of unit
output.
t1+ δ+
Tmax
i = ∑
sgn( ) × (
t= t + δ
t−
0)
Δ
H x P P T
0

Evaluation of An FM Unit

Parameter Identification and
Verification
Figure
5 .3 the typical model and the parameters of the
simulation curve and the measured curves
� WAMS parameter
identification and
verification, tell us:
� Model parameters
accurate or not.
� How much error ?
– Active error is not
Serious
– Reactive error is
Serious
� Model accurate?
– no!
no

Real-time Stability Monitor

The Critical Phase Angle and Transmission
Power Monitor

System Layout

CIM Model in Database
�Tables and it’s corresponding column
(Attributes ) follow CIM standard.
�Terminal attributes are introduced

HostControlArea
SubControlArea
Substation
VoltageLevel
Basic Table
Bay
PowerTransformer
BusbarSection
Breaker
Disconnector
SynchronousMachine
EnergyConsumer
Compensator
TransformerWinding
GroundDisconnector
TapChanger

PowerSystem Resource
(from C o re)
Equipm ent
(from C o re)
ConductingEquipm ent
(from C o re)
Switch
Jum per
EquivalentSource
Ground
RegulatingCondEq
Fuse
Equipm entContainer
( from C o re)
P ow e rTra ns form e r
ProtectionEquipm ent
(from Protection)
Transform erWinding
Breaker
VoltageControlZone
LoadArea
(from LoadM odel)
H eatExchanger
GeneratingUnit
(from Production)
Connector
Conductor
EnergyC onsumer
RectifierInverter
StaticVarCom pensator
TapChanger
Line
Com positeSwitch
Bay
(fro m C o re )
Disconnector LoadBreakSwitch
S u b s ta tio n
(fro m C o re )
VoltageLevel
(fro m C o re )
DCLineSegm ent
ACLineSegm ent
CustomerMeter
(from Load Mode l)
StationSupply
(from LoadM odel)
EquivalentLoad
(from LoadM odel)
InductionMotorLoad
(from LoadM odel)
BusbarSection
Junction
SynchronousMachine
Compensator
GroundDisconnector

Struc BREAKER
{
int m_ID;
char m_name[32];
char m_description[64];
char m_phases[4];
int m_terminal0_id;
int m_terminal1_id;
SF_Byte m_normalOpen;
SDateTime m_switchOnDate;
int m_basevoltage_id;
int m_equipmentcontainer_id;
……
};
Table Example 1

Table Example 2
struct BUSBARSECTION
{
int m_ID;
char m_name[32];
char m_description[64];
char m_phases[4];
int m_terminal0_id;
int m_basevoltage_id;
int m_equipmentcontainer_id;
……
};

Naming
(f rom C ore)
Measurement Model
+ValueAliasSet
ValueAliasSet 1
+Values
1..n
ValueToAlias
va lu e : N u m e ric
+ValueAliasSet
0..1
0..1
+ValueAliasSet
0..n
Measurem ent
0 ..n
+Measurem ents
+Controls
Control
value : Num eric
positiveFlowIn : Boolean
tim e S ta m p : Ab s o lu te D a te Tim e
+MeasuredBy_Measurem ent
m axValue : Num eric
0..1
operationInProgress : Boolean
m inValue : Num eric
dataType : Num ericType
m axValue : Num eric
0..1
+ControlledBy_ControlminValue
: Num eric
normalValue : Num eric
dataType : Num ericType
+Measurem ents
normalValue : Num eric
1
0..n
0..n +Meas urem ents 0..n
+Controls 0..n
+Controls
+Measurements +Mem berOf_Measurem ent
1 1+Measurem
entType
0..n
1 +ControlType
ControlType
MeasurementValue
+Measurem entValue
value : Num eric
+Measurem entValueQuality
tim e S ta m p : Ab s o lu te D a te T im e
sensorAccuracy : PerCent 1
1
0..n
+Measurem entValues
1
+Measurem entValueSource
0 ..n
+L im itSe ts
Lim itSet
isPercentageLim its : Boolean
1..n
+Contain_Measurem entValues
Measurem entType
Measurem entValueSource
+Lim itSet
1
+Unit
1
+Unit
+Limits
Unit
(f rom C ore)
0..n
1
Limit
val ue : N u m e ric
Measurem entValueQuality

Extended Model for PMU Data
Table Object
{
ID;
NAME;//
DESCRIPTION;//
TERMINAL0_ID;// ID
TERMINAL1_ID;// ID
EQUIPMENTCONTAINER_ID;// ID
EQUIPMENTCONTAINER_TABLEID;// ID
measId;
measIdx;
}
TABLE MEASUREMENT
{
ID;// ID
TERMINAL_ID; //
MEASUREMENTTYPE_ID; //
POWERSYSTEMRESOURCE_ID; // ID
POWERSYSTEMRESOURCE_TABLEID; // ID
POINTID0; //
POINTTABLEID0; //
POINTID1; //Pmu_DataCfg ID
POINTTABLEID1; //Pmu_DataCfg_ID 1006
POINTID2; //
POINTTABLEID2; //
ObjLinkNext
}

PMU data model
� Continuous uploading PMU data, Its own time scale, interval
20ms.
� Changing in SCADA(RTU) data transmission, No time scale,
interval 1s.
� Using fast Database design :
– the entire Seconds data of SCADA and PMU cache in Database , to meet
the data requirements of second-class update of Man-machine interface.
– PMU data cache in the fast database with time scales to meet the
dynamic curves of MS-level display and advanced applications.
� Human-machine interface through CIM model , achieve the
multi-source data access of SCADA and PMU.

RTDB mixed PMU data and
PMU Real-time DataBase
time
time0
time1
time2
point0
Point1:SCADA data
SCADA Data
point1 point2 point3
mixed Data
from SCADA or PMU
data from PMU at
1ms period
Quick Data service
Point1:PMU data point2:SCADA data Point 2:PMU data
Slow data service
In second
WAMS APP
Dynamic Curve in ms

PMU/SCADA relation table
Real-time DataBase
SCADA
PMU

Analog Table

Time stamp of PMU data
PMU Table

Multi-source Data Display

SVG Data

CIM DATA

Relation to CIM and SVG files

Five Steps for WAMS Implementation
� Import CIM data from EMS
� Import the SVG graphics of EMS
� Upload the PMU configuration files from PMU substation
� Automatically map the Measurement record to PMU point.
� draw some display pictures for WAMS
WAMS
IEC 61970 CIM file
SVG Vector graphic
file
SCADA Telemetry、Remote (104)
EMS

Online Lossless Compression
� Online Lossless
Compression;
� high-density non-
destructive
preservation, the
compression ratio of
30%;
� Quick search;
of WAMS Data
1000G

The History of Data Storage of
WAMS Master Station

Summary
� Using the CIM model and SVG from EMS, the
WAMS modeling becomes a much easier task.

Thank you!