The document analyzes voltage deviation at the Condon wind farm connected to the Bonneville Power Administration network, highlighting persistent deviations of over 9%. It proposes the installation of a static synchronous compensator (STATCOM) as a remedy, validated through high-fidelity modeling and simulation. Various operational characteristics of wind turbines and their impact on voltage management are also discussed, along with recommendations for effective capacitor switching to maintain system stability.

1. © S. Suryanarayanan, 2014
Instructor: Dr. Sid Suryanarayanan
Associate Professor, ECE
sid@colostate.edu
Week 8 (part A)
Grid Integration of Wind Energy
Conversion Systems
ECE 566

2. © S. Suryanarayanan, 2014
Voltage Deviation Analysis of
a 50 MW Wind Farm
Practical case study

3. © S. Suryanarayanan, 2014
Outline of presentation
• BPA’s Condon wind farm scenario
• The proposed remedy
• Modeling and simulation based analysis
• Identification of the real cause
• Conclusions

4. © S. Suryanarayanan, 2014
Types of wind power installations
• Fixed speed induction generators (FSIG)
– Squirrel cage induction machines
– Robust and inexpensive
– Directly coupled to grid and draws reactive power
– Fluctuations in wind cause mechanical and
electrical fluctuations (V deviation)
– Not suitable for weak electric grids
• Variable speed induction generators (VSIG)
– Wound rotor induction machines
– Use power electronics
– More expensive and less robust

5. © S. Suryanarayanan, 2014
BPA network
• Bonneville Power Administration - federally
owned utility with regions of operation in WA, OR,
ID, and parts of MT
• ~15000 miles of lines and ~300 substations
• Connects to Canada in the North and Los
Angeles in the South thru 500 kV AC lines
• Pacific DC intertie between BPA (Celilo) and LA
(Sylmar)
• In 2011, BPA network had approximately 30% of
wind power on its system (one of the highest
concentrations in the US)

6. © S. Suryanarayanan, 2014
Condon Wind Farm on BPA
network
• 50 MW wind farm on 69 kV
network of BPA in central
Oregon
• 83 FSIG wind turbines of 600
kW capacity each
• Owned and operated by
private utility (SeaWest) on
federal electric network
• Reactive support included
• Power factor correction capacitors (10 MVAr) at wind farm
and at nearby substation (5.5 MVAr)
• Cable shunt capacitance (2 MVAr)
• Individual turbine caps (90/180 kVAr)

7. © S. Suryanarayanan, 2014
Voltage deviation on PCC at Condon
• Persistent voltage deviation of >9% seen regularly
• Note: x-axis is time (1 year period)
01/01/04 03/01/04 04/30/04 06/29/04 08/28/04 10/27/04 12/26/04
90
95
100
105
110
5 min Condon Wind SCADA Data for 365 days starting 01-Jan-2004
Voltage at Wind Farm [%]
Date [MM/DD/YY]
BPA’s nominal operating
voltage level
BPA’s nominal operating
voltage range
• Yet, voltage deviation on PCC was observed periodically

8. © S. Suryanarayanan, 2014
-10 0 10 20 30 40 50
0.95
0.96
0.97
0.98
0.99
1
1.01
1.02
1.03
1.04
1.05
1.06
1.07
1.08
Real power delivered by wind farm [MW]
Voltage at the
wind farm [pu]
2s SCADA 03/05/2006
5min SCADA 08/22/2004 - 08/24/2004
Δv = 9%
caused
only in
some
cases
Site established as candidate for testing and installing new
technology for mitigating V deviation
Voltage deviation on PCC at Condon

9. © S. Suryanarayanan, 2014
Remedy for voltage deviation on Condon
wind farm
• Flexible AC Transmission System (FACTS) technology
proposed
• Static synchronous compensator (STATCOM)
– Shunt device
– Fast acting, reactive power compensator
– Dynamic voltage control
• New technology in power electronics (ETO) based
STATCOM at 10 MVA power rating to be installed at
Condon
– developed by NCSU
• FSU-CAPS in collaboration with EPRI, BPA, NCSU to test
and characterize novel controller for ETO based STATCOM
– High-fidelity modeling, simulation and hardware-in-the-loop studies
– Also to identify actual source of V deviation

10. © S. Suryanarayanan, 2014
Hardware-in-the-loop
Real Time Digital Simulator
Universal
controller
D/A
A/D Protection relay
M
AC/AC power converter
(Motor Drive)
External Hardware
System Data in Simulation
Hardware response
M
G
G
G
Controller
Relay
DC Load
• Requirements
– Detailed models
– Real-time capability
– D/A & A/D conv. w/
amplification

11. © S. Suryanarayanan, 2014
Steps in modeling effort
• BPA system modeling and validation
• Individual wind turbine system modeling
and control
• Wind farm modeling and control
• Validation against SCADA data
• Isolate cause of V deviation in wind farm
using high-fidelity models

12. © S. Suryanarayanan, 2014
BPA system modeling
Condon wind
farm modeled
as P and Q
injections
(i.e. from
SCADA data)
• Dynamic PQ loads
• T-Lines
• Xfmrs (w/o tap
changers)
• C-bank at Fossil
• Breakers
• HV equivalents:
constant V-source
behind impedance
Klondike wind farm
modeled as
P and Q injections

13. © S. Suryanarayanan, 2014
BPA system model validation
• Comparative studies of fault analysis on system model
developed with data from BPA
Node 1 phase-ground fault 3 phase fault
Aspen
(Amps)
RTDS
(Amps)
% difference Aspen
(Amps)
RTDS
(Amps)
% difference
BIG1A 30099 29173 3.07 27308 26464 3.1
BIG2A 53205 52003 2.26 46672 45652 2.18
COW6A 1117 1115 0.18 2716 2671 1.65
DEM6A 1942 1961 0.97 2097 2134 1.76
FOS6A 905 898 0.77 1773 1767 0.33
MAU2A 4426 4343 1.87 7114 6996 1.65

14. © S. Suryanarayanan, 2014
BPA system model validation
• Condon wind farm as only P and Q injections
• Manual switching of capacitors for |V| ≤ 0.95 pu
0 10 20 30 40 50 60 70 80 90
0.95
1
1.05
Time (min)
Voltage
(pu)
Voltage at Condon Wind Farm Substation
SCADA Data
Simulated (with capacitors)
0 10 20 30 40 50 60 70 80 90
0
10
20
30
40
50
Time (min)
Power (MW)
Reactive Power (MVAR)
Voltage (pu)
0 10 20 30 40 50 60 70 80 90
0.95
1
1.05
Time (min)
Voltage
(pu)
Voltage at Condon Wind Farm Substation
SCADA Data
Simulated (with capacitors)
0 10 20 30 40 50 60 70 80 90
0
10
20
30
40
50
Time (min)
Power (MW)
Reactive Power (MVAR)
Voltage (pu)
0 10 20 30 40 50 60 70 80 90
0.95
1
1.05
Time (min)
Voltage
(pu)
Voltage at Condon Wind Farm Substation
SCADA Data
Simulated (with capacitors)
0 10 20 30 40 50 60 70 80 90
0
10
20
30
40
50
Time (min)
Power (MW)
Reactive Power (MVAR)
Voltage (pu)
0 10 20 30 40 50 60 70 80 90
0.95
1
1.05
Time (min)
Voltage
(pu)
Voltage at Condon Wind Farm Substation
SCADA Data
Simulated (with capacitors)
0 10 20 30 40 50 60 70 80 90
0
10
20
30
40
50
Time (min)
Power (MW)
Reactive Power (MVAR)
Voltage (pu)

15. © S. Suryanarayanan, 2014
Modeling characteristics of individual wind
turbine
• 600 kW fixed-speed wind turbine
• Modeled with available name plate details
• Induction machine mechanically coupled to a wind turbine
rotor model through a drive train model
• Controls include power electronic soft-starter, pitching, pole
switching, capacitor switching, and grid connection
PQ
Meter
Vabc
P
Q
Iabc
Capacitor Bank
ω
Induction
Machine
T β
ω
Wind
Turbine
Rotor
v
T
Pitch Control
P β
Wind
Profile
Soft Starter
Drive Train
Model

16. © S. Suryanarayanan, 2014
High-fidelity wind farm modeling
• Two modeling methods adopted
– Load flow tool based steady state analysis
– Hybrid model with individual strings of turbines for dynamic
analysis
• Developed load flow tool in MATLAB
– All 83 IG wind turbines (input is either torque or wind speed)
– Includes local transformers, cables, and PF correction capacitors
– Models BPA system as lumped impedance
• Studied voltage magnitude and angle deviations across
the wind farm (to help identifying V-control problem)
• Problems with convergence of the load flow brought to
light suspected voltage collapse problems at the Condon
Loop portion of the BPA system

17. © S. Suryanarayanan, 2014
Salient characteristics of wind farm
control
• Turbine goes online in 6 pole mode when wind speed > 3.5 m/s
• When induction m/c reaches 1100 rpm, soft starter engages
and connects m/c smoothly to grid
• At same time, one local cap bank (90 kVAr) is switched in
• If wind speed > 8m/s for at least 10 minutes, m/c switched to 4
pole operation
– Blades switch out (to remove torque)
– m/c disconnects from grid
– Turbine speeds up by pitching blades back in
– Re-energizing with the gird using soft starter
– 2 local cap banks (180 kVAr) switched in

18. © S. Suryanarayanan, 2014
Salient characteristics of wind farm
control
• Cap banks at substation switched in when |V|
< 1 pu
• Cap banks at substation disconnected when
|V| > 1.3 pu
• Caps at Fossil switch in when |VFS| < 0.96 pu
• Caps at Fossil disconnected when |VFS| >
1.04 pu

19. © S. Suryanarayanan, 2014
V-fluctuations within the wind
farm
Near end of strings
No V-profile
problem within
wind farm
SS…Substation

20. © S. Suryanarayanan, 2014
Comparison between Load Flow Results and
SCADA Data
WF…Wind Farm (at Substation)
Leads into
V-Collapse
Strong
evidence that
malfunctioning
of Condon
Wind Farm
capacitor
switching
causes the
problem

21. © S. Suryanarayanan, 2014
40 turbines fully modeled,
scaled by 2.075 to account for
the 83 units actually in the field
40-turbine model of Condon wind farm and BPA
Fossil
DeMoss
Maupin
Condon
C
1
C
2
C
3
C
4
C
5
C
6
C
7
C
8
FSIG1
Turbine 1
Model
Wind
speed 1
C
aT1
C
bT1
34.5 kV
SS1
Turbine N
Model
Wind
speed N
C
aTN
C
bTN
SSn
N units
connected
through
underground
cabling
0.6 kV
TT1
TTN
ETO
STATCOM
TCW
WF
Turbine i
Model
Wind
speed i
C
aTi
C
bTi
SSi
TTi
FSIGi
FSIGN

22. © S. Suryanarayanan, 2014
0 5 10 15 20 25 30 35 40 45 50
0.88
0.9
0.92
0.94
0.96
0.98
1
1.02
1.04
1.06
Voltage
at
Condon
Wind
[pu]
Real Power Condon Wind [MW]
2 s SCADA Data
5 min SCADA Data for 3 days starting 22-Aug-2004
No Capacitors (RTDS)
Fossil Capacitors (RTDS)
CWF Capacitors (RTDS)
Power ramped by (slowly) increasing
wind speed uniformly
Validation of hybrid RTDS model
against SCADA Data
More evidence
that
malfunctioning
of Condon
Wind Farm
capacitor
switching
causes the
problem

23. © S. Suryanarayanan, 2014
BPA Recent Data
Proper cap bank switching
Condon Wind Farm Voltage
[kV]
time [s]
10 min
When cap switching control at Condon Wind works properly, the voltage stays within BPA
criteria as FSU studies predicted
- As confirmed by BPA via email on 11/22/2006

24. © S. Suryanarayanan, 2014
Contingency scenario in BPA system
Maupin line down
15 20 25 30 35 40 45 50
0.8
0.85
0.9
0.95
1
1.05
1.1
Power (MW)
Voltage
at
CW
Substation
(pu)
Wind Farm P-V Relationship With Maupin Connection Open (RTDS)
0 MVAR Caps
3 MVAR Caps
6 MVAR Caps
10 MVAR Caps
12.75 MVAR Caps
15.5 MVAR Caps
15 20 25 30 35 40 45 50
0.8
0.85
0.9
0.95
1
1.05
1.1
Power (MW)
Voltage
at
CW
Substation
(pu)
Wind Farm P-V Relationship With Maupin Connection Open (RTDS)
0 MVAR Caps
3 MVAR Caps
6 MVAR Caps
10 MVAR Caps
12.75 MVAR Caps
15.5 MVAR Caps
BPA C-banks

25. © S. Suryanarayanan, 2014
Contingency performance of a 5 MVA
STATCOM
15 20 25 30 35 40 45 50
0.8
0.85
0.9
0.95
1
1.05
1.1
Power (MW)
Voltage
at
CW
Substation
(pu)
Wind Farm P-V Relationship With Maupin Connection Open (RTDS)
0 MVAR Caps
3 MVAR Caps
6 MVAR Caps
10 MVAR Caps
12.75 MVAR Caps
15.5 MVAR Caps
Manually Switch Capacitors
Manually Switch Capacitors
With 5 MVAR STATCOM
15 20 25 30 35 40 45 50
0.8
0.85
0.9
0.95
1
1.05
1.1
Power (MW)
Voltage
at
CW
Substation
(pu)
Wind Farm P-V Relationship With Maupin Connection Open (RTDS)
0 MVAR Caps
3 MVAR Caps
6 MVAR Caps
10 MVAR Caps
12.75 MVAR Caps
15.5 MVAR Caps
Manually Switch Capacitors
Manually Switch Capacitors
With 5 MVAR STATCOM
…trying to maintain 1.05 pu
…trying to maintain 1.00 pu
…with 1.0 pu set point
Generic STATCOM
model
V-control loop not
optimized
Observed steady-state
performance only
Caps switched manually
to keep STATCOM VAr
supply close to zero

26. © S. Suryanarayanan, 2014
Conclusions
• High-fidelity modeling and simulation of utility
system (BPA’s), existing wind farm, and generic
STATCOM performed
• Actual source of voltage deviation in Condon wind
farm identified as controller of PFC
• Possible use of STATCOM during contingency
situations established
• Sizing of novel STATCOM aided by high-fidelity
modeling effort