Coordinated Control for Optimal Wind Farm Operation
Coordinated WF Operation, WILL4WIND, July 2013
Mato Baotić
Vedrana Spudić, Mate Jelavić, Nedjeljko Perić
AeolusDistributed Control of Large-Scale Offshore Wind Farms
ACROSSCentre of Research Excellence for Advanced Cooperative Systems
Offshore wind farm in operation
Coordinated WF Operation, WILL4WIND, July 2013
Thanet offshore wind farm
Vestas V90 3MW turbines100 turbines, in 7 rows (12, 14, 15, 17, 17, 14, 11)
Coordinated WF Operation, WILL4WIND, July 2013
Control problem
Coordinated WF Operation, WILL4WIND, July 2013
Centralized controller
Control system requirements:– track wind farm power reference– reduce fatigue loads of wind turbines – tower and shaft loads considered– obtain scalability of control algorithm to different wind farm sizes
Control problem features:– optimal control approach required– variable constraints – nonlinear system– the system model size and complexity increases drastically with wind farm size
Conventional optimal control approaches not suitable for the problem!
Coordinated WF Operation, WILL4WIND, July 2013
Wind farm control – simplistic approach
Coordinated WF Operation, WILL4WIND, July 2013
Wind farm coupling - static optimization
Coordinated WF Operation, WILL4WIND, July 2013
Wind farm coupling – dynamic optimization (AEOLUS)
Coordinated WF Operation, WILL4WIND, July 2013
Wind farm optimization (AEOLUS)
Coordinated WF Operation, WILL4WIND, July 2013
Hierarchical centralized wind farm controller
Coordinated WF Operation, WILL4WIND, July 2013
Reconfigurable controller overview
Coordinated WF Operation, WILL4WIND, July 2013
Reconfigurable controller factsheet
Objectives:
Track wind farm power reference
Minimize fatigue loads on tower and shaft
Respect optimal operating point distribution from the supervisory controller
Requirements:
Control sampling time 1sRelevant for wind turbine mechanical systemFeasible for wind farm control systemRequires dedicated optimal control approach
Respects system constraints
Can be applied in the entire operation region
Provides fast response to:Wind gusts and turbulenceChanges in system constraintsChanges in wind turbine availabilityChanges in wind farm power reference
Coordinated WF Operation, WILL4WIND, July 2013
Reconfigurable controller factsheet
Interface:
Approach:Assumption:
no coupling between wind turbines at fast time scalesModeling:
wind farm is a cooperative control systemconsists of dynamically independant subsystems – wind turbineseach subsystem has an independant control objective – minimize fatigue loads, stay close to optimal operating pointssubsystems cooperate to achieve a common objective – deliver required wind farm power
Control design based on precomputation of control laws via parametric programming
Coordinated WF Operation, WILL4WIND, July 2013
Local optimal control problem
Coordinated WF Operation, WILL4WIND, July 2013
Local control objective: Minimize fatigue loads on tower and shaftStay close to optimal operating points – loads and powers
Solution: Introduce optimal load and power tracking into the controller cost functionLoad tracking can reduce fatigue load
Local control objective
Time [s]
Sha
ft to
rque
[Nm
]
0 5 10 15 20 25 303.1
3.15
3.2
3.25
3.3
3.35
3.4
3.45
3.5
3.55
3.6x 10
6
Coordinated WF Operation, WILL4WIND, July 2013
Local control objectiveLocal control objective:
Minimize fatigue loads on tower and shaftStay close to optimal operating points – loads and powers
Solution: Introduce optimal load and power tracking into the controller cost functionLoad tracking can reduce fatigue load
0 5 10 15 20 25 303.1
3.15
3.2
3.25
3.3
3.35
3.4
3.45
3.5
3.55
3.6x 10
6
1
2 3
4
56
7
8
9
10
11
12
13
14
1516
17 1819 20
21
22
2324
2526
2728 29
3031
32
33
3435
36
37
38
39
404142
43
44 4546
474849
5051
52
53
54
55
56
57
58 5960
6162
63
64
65
66 67
68
69
70
71
72
73
Rainflow cycles extracted from signal
Time [s]
Sha
ft to
rque
[Nm
]
Coordinated WF Operation, WILL4WIND, July 2013
Local control objectiveLocal control objective:
Minimize fatigue loads on tower and shaftStay close to optimal operating points – loads and powers
Solution: Introduce optimal load and power tracking into the controller cost functionLoad tracking can reduce fatigue load
0 5 10 15 20 25 303.1
3.15
3.2
3.25
3.3
3.35
3.4
3.45
3.5
3.55
3.6x 10
6
1
2 3
4
56
7
8
9
10
11
12
13
14
1516
17 1819 20
21
22
2324
2526
2728 29
3031
32
33
3435
36
37
38
39
404142
43
44 4546
474849
5051
52
53
54
55
56
57
58 5960
6162
63
64
65
66 67
68
69
70
71
72
73
Rainflow cycles extracted from signal
Time [s]
Sha
ft to
rque
[Nm
]
Coordinated WF Operation, WILL4WIND, July 2013
Local optimal control problem
Wind model – persistance assumptionPrediction horizon N=4References assumed constant in prediction
horizon
Track power and loads
WT model
Available power constraint
Other constraints
Coordinated WF Operation, WILL4WIND, July 2013
Cooperation of turbines
Coordinated WF Operation, WILL4WIND, July 2013
Cooperation of turbines
A new variable for cooperation of wind turbines introduced in the local control problem
Proposed wind farm controller
Coordinated WF Operation, WILL4WIND, July 2013
Results
Coordinated WF Operation, WILL4WIND, July 2013
Results – Scalability
20 40 60 800
1
2
3
4
5
6
7
8
Number of wind turbines
Mean t
ime r
equired f
or
one c
ontr
ol co
mputa
tion [
s]
Classical approach
Reconfigurable controller
Coordinated WF Operation, WILL4WIND, July 2013
Results – Hierarchical controller
Supervisory and reconfigurable controller merged into hierarchical controllerNo stability issuesThe supervisory control actions practicaly the same after adding the reconfigurable controller
Coordinated WF Operation, WILL4WIND, July 2013
Results – Hierarchical controller
Wind farm layout:
The hierarchical controller was extensively tested
Test results can be found in deliverable 3.3a and deliverable 5.6
Here we present the basic tests from D5.6 – tracking of the constant power reference for high and low wind speed
Measures for comparison:Wind farm power tracking standard deviation Damage equivalent load on shaftDamage equivalent load on tower
Coordinated WF Operation, WILL4WIND, July 2013
Results – Performance evaluation
Wind farm power reference (36 MW)Mean wind speed 15 m/s
Coordinated WF Operation, WILL4WIND, July 2013
Results – Performance evaluation
400 420 440 460 480 500 520 540 560 580
3.58
3.585
3.59
3.595
3.6
3.605
x 107
Win
d f
arm
pow
er
[W]
Time[s]
SUPSUP+REC
300 320 340 360 380
-8
-6
-4
-2
0
x 107 WT1
Tow
er
bendin
g m
pm
ent
[Nm
]
Time[s]
120 140 160 180 200
3.5
3.6
3.7
3.8
3.9
4
4.1x 10
6 WT1
Shaft
tors
ional m
om
ent
[Nm
]
Time[s]
Coordinated WF Operation, WILL4WIND, July 2013