ForskEL-6316 project
Operation and Control of Modern
Distribution Systems
Institute of Energy Technology, Aalborg University (AAU)
Himmerlands Elforsyning (HEF)
SEAS-NVE Energy Group
Dansk Energi Forskning og Udvikling (DEFU)
March 2007-May 2010
Part A: PhD started in March 2007
Part B: PhD started in June 2007
Subprograms of the project
Part A: Normal Operation Optimization
Part B: Control Strategies in Abnormal Operation
Situations
The Contents of Subprogram A
1. Developing models of linking real time electricity pricing
and the load controlled by a management system,
2. Establishing models of linking real time electricity
pricing and renewable energy based generation units,
3. Power system operation
electricity pricing system,
constraints’
effects
on
4. Development of operation and control strategies to
minimize the overall system cost.
Work reported in February 2008 (part A)
•
•
•
•
•
Data collection
Load response model at kWh level
Model to identify the patterns of response price
Market exchange and pricing model at MWh level
The interaction between load and price
New development since February 2008 (Part A)
Stochastic Model of Wind Power Production
Stochastic Simulation of Real-time Balancing
Market and Price
Relationship between wind power and
electricity price
Stochastic Model of Wind Power Production
Capacity coefficient & Samples preparation
MW
Installed wind power capacity from 2000 to 2007
3500
3000
2500
2000
1500
1000
500
0
DK-East
DK-West
Total
2000
2001
2002
2003
2004
2005
2006
2007
Capacity coefficient=hourly value of wind
power production/installed wind power
capacity of the corresponding year
Year
C ap acity co efficien t
Monthly trend of wind power production (2000-2007)
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
DK-East
DK-West
Jan Feb Mar Apr May Jun
Jul
Month
Aug Sep Oct
Nov Dec
Stochastic Model of Wind Power Production
S a m p le v a lu e s o f
e a c h c a p a c ity c o e ffic ie n t g ro u p
D is trib u tio n fittin g
P ro b a b ility d is trib u tio n
d e s c rib e d b y P D F
S to c h a tic v a lu e g e n e ra tio n
S im u la te d v a lu e s
Stochastic simulation framework
Stochastic Model of Wind Power Production
After the raw vector formed by stochastic value generation, the correlation treatment
should be performed based on the filter of moving average concept.
Stochastic Model of Wind Power Production
Stochastic Simulation of Real-time Balancing Market and Price
• The stochastic models of wind power production, primary production, local production, consumption,
• The system unbalance can be synthesized with these stochastic simulations,
• A model of the regulation bids in real-time market,
• With system unbalance and regulation bids, the prices of real-time balancing market can be simulated.
Stochastic Simulation of Real-time Balancing Market and Price
Sim ulation res ults of prices in balancing m arket
350
300
DKK/MWh
250
200
s pot price
up-regulation price
down-regulation price
150
100
50
0
1
51
101
hour
151
Relationship between wind power and electricity price
Relationship between wind power and electricity price
Electricity price
(DKK/MWh)
y
y
Lognormal distribution
x
a
The largest
and smallest
prices in this
year within
concentrated
area (abcd)
e
b
g
f
h
c
d
x
0
Simulation
width of
wind power
A model consideration
The largest
wind power in
this year within
concentrated
area (abcd)
Wind power
(MWh/h)
Conclusion (Part A)
Development of Stochastic Model of Wind
Power Production
Work on Stochastic Simulation of Real-time
Balancing Market and Price
Consideration of the relationship between wind
power and electricity price
The Contents of Subprogram B
1. Effective detection method of operation states .
2. Power system protection system and power electronic
converters in island operation conditions.
3. Control strategies for stable transition between
different operation states.
4. Coordination control of the stand alone system to
minimize the damage and inconvenience to
consumers .
Work reported in February 2008 (part B)
Start
PASSIVE
Measure voltage and
calculate dV/dt
No
Av5 =
dV/dt ≠0
Yes
A Hybrid Islanding
Detection Technique
No
1 5 ⎛ dVDG ⎞
∑
5 i =1 ⎜⎝ dt ⎟⎠(i )
⎛ dV ⎞
C = Av5 ⎜⎜ DG ⎟⎟ > V SMin
⎝ dt ⎠
Yes
Yes
C > VSMax
No
Initiate RPS
Measure voltage
and calculate dV/dt
⎛ dV ⎞
Av 25 ⎜⎜ DG ⎟⎟ > V SMax
⎝ dt ⎠
ACTIVE
Reset DG’s
real power
Av 25 =
No
Yes
System is islanded
End
Flowchart for islanding detection
1 25 ⎛ dVDG ⎞
∑⎜
⎟
25 i =1 ⎝ dt ⎠(i )
New development since February 2008 (Part B)
Under Frequency Load Shedding
(UFLS)
Controllers of Gas Turbines
Control of Gas Turbine for Islanding
and Grid Connection Operation
Under Frequency Load Shedding (UFLS)
•
When islanded - frequency will change - will go up with excess generation or
go down with excess load
•
If goes up, can be controlled by fast acting speed governors - If goes down, the
loads have to be shed when DG already operating at its rated capacity
•
Conventional UFLS use frequency ‘f’, df/dt, real time information to shed load
•
Real time system information may be hardly available and the implementation
is expensive for small distribution system
•
Small generators has small inertia and frequency tends to decay more rapidly
•
Load shedding may be not governed by technical reasons alone
•
With custom power, customers pay more for better power quality and reliability
Under Frequency Load Shedding
Start
Measure frequency every half cycle
Is RoCoF= df/dt <0
Yes
RoCoF <
RoCoFLLL ?
No
No
Case
Load
Rank
(NL)
Load
1
2
3
4
5
Load 09
Load 10
Load 11
Load 07
Load 08
NL
WTP
0.81
0.83
0.86
0.87
0.91
RoCoFLi
∑ RoCoFL
-8.17
-8.17
-8.17
-13.48
-17.72
-8.17
-16.34
-24.51
-37.99
-55.71
i
i =1
Yes
Calculate number of load to be
shed (N) from look up table by
ceiling the value
Is f<0.99
Yes
No
Look up table
Yes
Is NL≥N
No
Delay
No
Is df/dt ≤0 for 5 times
Yes
N=N+1
Shed the load Ranked NL
End
Flowchart
No
Is N=0
Yes
Test System
Test system
Simulation Results
• Peak demand of October used to create look up table
• Methodology tested during peak demand of November
• CHP produces 9 MW during both times
• WTGs are producing 84 kW each when islanding occurs
• WTGs operate at unity power factor
• IEEE Type ST1 excitation system and an IEEE Type 1 (gas
turbine) governor system are used in CHP plant
Simulation Results Cont…
• Worst Case Scenario (Case 1)
¾ Smaller loads are willing to pay less so shed first
• Random Case (Case 2)
¾ Load’s willingness to pay is random
• Best Case Scenario (Case 3)
¾ Load ranked 1 has a real power demand that almost matches the real power
deficiency in the system
¾ Load 2 and 3 there are the two smallest loads
Simulation Results Cont…
Load
Rank
(NL)
Case 1 (Worst Case)
Case 2 (Random Case)
NL
Load
WTP RoCoFLi
∑ RoCoFL
i
i =1
Case 3 (Best Case)
NL
Load
WTP RoCoFLi
∑ RoCoFL
i
i =1
NL
Load WTP RoCoFLi
∑ RoCoFL
i
i =1
1
Load 09 0.81
-8.17
-8.17
STSY
0.79
-34.16
-34.16
MAST
0.89
-47.03
-47.03
2
Load 10 0.83
-8.17
-16.34
Load 10 0.84
-8.17
-42.33
Load 09 0.9
-8.17
-55.2
3
Load 11 0.86
-8.17
-24.51
STNO
-39
-81.33
Load 10 0.91
-8.17
-63.37
4
Load 07 0.87
-13.48
-37.99
Load 09 0.86
-8.17
-89.5
STCE
0.92
-23.45
-86.82
5
JUEL
0.89
-17.58
-55.57
STCE
0.89
-23.45
-112.95
STNO
0.93
-39
-125.82
6
Load 08 0.91
-17.72
-73.29
Load 07 0.9
-13.48
-126.43
Load 11 0.94
-8.17
-133.99
7
STCE
0.92
-23.45
-96.74
Load 08 0.91
-17.72
-144.15
JUEL
0.95
-17.58
-151.57
8
FLØE
0.93
-32.34
-129.08
FLØE
0.95
-32.34
-176.49
FLØE
0.96
-32.34
-183.9
9
STSY
0.95
-34.16
-163.24
Load 11 0.98
-8.17
-184.66
Load 07 0.97
-13.48
-197.38
10
STNO
0.96
-39
-202.24
JUEL
0.99
-17.58
-202.24
Load 08 0.99
-17.72
-215.1
11
MAST
1
-47.03
-249.26
MAST
1
-47.03
-249.26
STSY
-34.16
-249.26
0.85
Look up table for three different cases
1
Simulation Results Cont…
1.02
Frequency (p.u.)
1
0.98
0.96
Worst Case
Best Case
Random Case
0.94
0.0
0.3
0.6
0.9
1.2
1.5 1.8
Time (s)
2.1
2.4
2.7
System frequency during islanding and load shedding for all cases
Controllers of Gas Turbine
GAST Model with Speed Droop Controller
GAST Model with Isochronous Controller
GAST Model with Isochronous Controller and Feedback
1.01
4.5
1
3.5
GTG turbine power (MW)
Frequency (p.u.)
Simulation Result
0.99
0.98
1.5
Fixed droop
0.5
Fixed droop
0.97
2.5
Isochronous
Isochronous
Isochronous with feedback
Isochronous with feedback
-0.5
0.96
-1
0
1
2
3
4
5
6
7
8
9
Time (s)
Islanded Distribution System’s Frequency
10
-1
1
3
5
7
9
11
13
15
17
19
Time (s)
GTG Turbine Power for Grid Frequency
Increase by 0.1% at 0 seconds
Controllers of Gas Turbine
• Higher droop better when system is grid connected but
performs badly when the system is islanded
• Isochronous controller will try to keep frequency at a
specified level when the system is islanded but not good in
grid connection situation
• GTG can be operated in terminal voltage or VAr/power
factor control. If operated in terminal voltage control mode
¾ Either over or under excitation of the smaller generators
¾ Excessive reactive current may result in overload or loss of generator
synchronism
Control of Gas Turbine for Islanding and Grid
Connection Operation
Flow Chart for GTG Control
Block Diagram for GTG Control
Control of Gas Turbine for Islanding and Grid
Connection Operation
1
sTe
++
Ka
1+sTa
1
1+sT
⎛
1 ⎞
K i ⎜1 +
⎟
⎝ sTi ⎠
1
R
Kf
1+sT f 2
1+sT f 1
1+sT f 3
1
1+sT1
1
1+sT3
1
1+sT2
Modified IEEE Type AC5A Excitation System
K pf
Modified GAST Model
1+sTpf
Power Factor Controller
Results
1.035
1.025
1.1
Grid connection detected
GTG speed (p.u.)
1.07
-1
9
19
29
39
49
Time (s)
GTG Terminal Voltage
1.01
Grid
Distribution system
1.005
Speed
Active power
at t=15.72s
1.02
1.015
Frequency (p.u.)
3
2.8
1.04
2.6
1.01
2.4
0.98
2.2
0.95
2
-1
9
19
29
39
Time (s)
1
GTG Speed and Active Power
0.995
0.99
-1
9
19
29
Time (s)
System Frequencies
39
49
49
GTG active power (MW)
GTG terminal voltage (p.u.)
1.03
Conclusion (Part B)
• The GTG operates in power factor control and droop control mode
when the system is connected to the grid
• It operates in voltage control and isochronous mode when system is
islanded
• Shift from grid connected mode to island mode is achieved by
islanding detection
• Shift from island mode to grid connected mode is achieved by
detecting grid connection
• Simulation results show that system is able to operate satisfactorily
all the time
• It is able to maintain voltage and frequency when the system is
islanded and maintain power factor when it is connected to grid