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Data driven analysis of Southern Regional Grid of india
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Data Driven Analysis of Southern Regional Grid of India
by
Sarasij Das
.
Based on Thesis “Power System Data Compression For Archiving”
http://etd.ncsi.iisc.ernet.in/handle/2005/572
Aim
Understanding the parameter interrelations of
Southern Regional Grid of India (using SCADA
data)
Highlight the challenges of data driven analysis of
a power grid
Introduction
• Power system instrumentation - transforming from analog to digital• Huge data being generated• Data : an asset • SCADA not designed to handle/analyze huge system data• Data analysis: new tool to understand power system better
• Indian power system going through major changes
• SRLDC - apex body responsible for integrated operation of power system in Southern Regional Grid of India
• 320 RTUs involved in system monitoring across Southern region.
• Huge system information generated
• Presently most of the recorded data remains un-used
• Recorded system data can be analyzed for better system understanding, decision making and optimizing system performance.
Context and Scope
Collected Data Description
• In SRLDC, data stored in compact discs Excel files• Collected data duration year 2005-06• Data logging interval 1 minute – steady state data• Data of four system parameters are used for study
1. Voltage - 26 buses of 400 KV – 1 KV precision
2. MW generation – 60 units – 1 MW precision
3. MVAr generation - 88 units – 1 MVAr precision
4. Frequency - 0.01216 Hz precision
Studies Performed
• System frequency Vs. average system voltage• System frequency Vs. total system demand• Total system demand Vs. average system voltage• Total system demand Vs. Total MVAr generation• Total MVAr vs. average system voltage• MVAr injection averaged at generation bus voltage• System demand averaged at frequency
Average system voltage
Sys
tem
fr
eque
ncy
On 06/06/2006
System frequency
Tot
al S
yste
m D
eman
d On 16/04/2006
Average system voltage
Tot
al S
yste
m D
eman
d On 19/01/2006
Total MVAr generation
Tot
al S
yste
m D
eman
d On 19/01/2006
Average system voltage (kV)
Tot
al M
VA
r ge
nera
tion
On 19/01/2006
Bus voltage (kV)
MV
Ar
gen
erat
ion
On 06/06/2006 - Scatter plot
Bus voltage (kV)
MV
Ar
gen
erat
ion
aver
aged
at e
ach
volt
age
On 06/06/2006
Bus voltage (kV)
MV
Ar
gen
erat
ion
aver
aged
at e
ach
volt
age
On 13/03/2006
Bus voltage (kV)
MV
Ar
gen
erat
ion
aver
aged
at e
ach
volt
age
March 2006
Sys
tem
Dem
and
aver
aged
ov
er e
ach
freq
uenc
y
System frequency
Month - December 2005
Sys
tem
Dem
and
aver
aged
ov
er e
ach
freq
uenc
y
System frequency
Month - April 2006
Change in frequency
Cha
nge
in T
otal
Sys
tem
Dem
and
in c
onse
cut i
ve in
stan
tMonth - December 2005
Change in frequency
Cha
nge
in T
otal
Sys
tem
Dem
and
in c
onse
cut i
ve in
stan
tMonth - March 2006
Challenges
• Presence of outliers
• Incomplete data• Inaccurate time stamping of data
RCHR bus voltage on 02/01/2006 for the period 12:59 to 13:29
Conclusion Data analysis can reveal interesting system characteristics
Outliers, incomplete data pose challenges towards successful mining
Utility data archiving system should be designed keeping data analysis requirement as a criteria
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