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Abstract--This paper proposes an optimized dispatch strategy
for active power cutback control in a wind farm. The strategy is considered as the supplement of the control strategy of the active
power control system for wind farm clusters. Based on the
priority list method, the control strategy is designed to realize the
dynamic control sequence of wind turbines considering
regulation capacity, regulation speed and response time. In this control approach, wind farm is supposed to respond to dispatch
command from centre control station in an optimal and
economical way. The strategy achieves the control target of wind
farm output constraint by pitch angle control and rotor speed
control instead of cutting off turbines. At last, the feasibility and validity of the presented strategy are tested on a wind power
system.
Index Terms--acti ve power control, priority list method, wind
farm
I. INTRODUCTION
Wind power generation has been significantly developed
during the last decades. Due to the intermittency and volatility
of wind power, it brings great challenge to the safe and stable
operation of power system. According to the “Technical
Requirements for Wind Farms Connected to the Grid” issued
by the State Grid, “Wind farm should be qualified with active
power adjustment ability and its active power output can be
controlled according to the dispatch command.” Hence, how
to control the active power output of wind farm actively is
concerned by the grid and the wind farm operators [1].
Recently, several research groups explored dispatch
problems of power system connected with wind farms[2][3].
On the other hand, active power dispatch problem in a wind
farm is also being studied by experts and scholars at home and
abroad[4]. The power control systems in wind farm have been
proposed in [ 5] and [ 6]. Among the studies at wind far m
control level, the power dispatch problem in a wind farm is
received great attentions. Reference [ 7 ] presents a new
integrated control system for a wind farm and its active power
controller is designed to share power reference from the grid
operator to each available machine equally. Automatic
generation control strategy in [8] is designed to dispatch the
control target to selected wind turbines according to utilizat ion
rates of their inverters.
This work is sponsored by Major Program of the National Natural Science
Foundation of China (51190103) and National High Technology Research and Development Program of China (863 Program)(2011AA05A104).
Li Lin, Yongjun Xie are with State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power
University, Beijing,102206, China (email: [email protected]; ) Ningbo Wang is with Gansu Electric Power Company, Lanzhou, 730050,
China (email: [email protected]).
Recently, reference [ 9 ] introduces a new approach that
applied the traditional unit commitment and dispatch method
to the active power control of wind farms . Reference [ 10]
proposes a classical mathematical model by designing an
objective function for min imizing wind power deviat ions
regarding the dispatch request.
This paper simply describes the active power control system
for wind farm clusters in Jiuquan wind power base and
designs the fundamental framework of monitor & control
system at wind farm level. And then considering real-t ime
operational information of wind turbines, this paper studies an
optimizing control strategy which is suitable for active power
dispatch of wind farm. Based on priority list method, three
parameters, regulation capacity, regulation speed and response
time, are comprehensively considered in the strategy. The
strategy is supposed to avoid cutting off wind turbines blindly
and improve the control ability of wind farm. This paper
focuses on the situation when wind farm output needs to be
constrained.
II. MONITOR &CONTROL SYSTEM FOR WIND FARM
A. The Active Power Control System for Wind Farm Clusters
At present, an active power control system for wind farm
clusters is constructed in Jiuquan wind power base[1]. The
control system framework has four layers, as shown in Fig.1.
Jayu Pass Center
Control Station
Yumen Master
Control Station
(Main or standby)
330kV
Yumen
Slave
Control
Station
Tianyun
Liuyuan
Wind
Farm
Terminal
Control
Station
Supevisory
Terminal
Unit for
Operator in
Wind Farm
Gansu Province
Dispatch Center
Guazhou Master
Control Station
(Main or standby)
330kV
Jiayu Pass
Slave
Control
Station
330kV
Shandan
Slave
Control
Station
330kV
Guazhou
Slave
Control
Station
330kV
Liangzhou
Slave
Control
Station
Jieyuan
Wind
Farm
Terminal
Control
Station
Shisanli-
jingzi
Wind
Farm
Terminal
Control
Station
Changma
Wind
Farm
Terminal
Control
Station
Yumen
Wind
Farm
Terminal
Control
Station
Beida-
qiaodong
Wind
Farm
Terminal
Control
Station
ZhongDian
Juquan
Wind Farm
Terminal
Control
Station
Zhangye
Thermal
Plant
Terminal
Control
Station
Supevisory
Terminal
Unit for
Operator in
Wind Farm
Supevisory
Terminal
Unit for
Operator in
Wind Farm
Supevisory
Terminal
Unit for
Operator in
Wind Farm
Supevisory
Terminal
Unit for
Operator in
Wind Farm
Supevisory
Terminal
Unit for
Operator in
Wind Farm
Supevisory
Terminal
Unit for
Operator in
Wind Farm
Supevisory
Terminal
Unit for
Operator in
Thermal
Plant
Fig. 1 Framework of Active Power Control System for Wind Farm Clusters
1): Center Control Station
The station is designed to realize the real-t ime monitor and
control of the whole wind power base. Its main functions
Priority List Method for Active Power Cutback
Control in a Wind Farm
Li LIN, Member,IEEE, Yongjun XIE and Ningbo WANG
IEEE PES ISGT ASIA 2012 1569528117
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include coordinating control, real-time calcu lating and
distributing planned values, automatic rep lying request of
output change of wind farm, switching operation and control
mode and so on.
2): Master Control Station
The station is designed to collect and exchange informat ion
among wind farm, slave control station and center control
station.
3): Slave Control Station
The function of this station is to monitor each interface flow
at 330kV level and upload operating conditions, fault
conditions and overload conditions to the center and master
control station.
4): Terminal Control Station
The station is designed to monitor active power output of
wind farm and dispatches wind farm output plan according to
the selected operating mode of the system automat ically.
The system has been successfully implemented in the wind
power base and the controllability and effectiv ity have been
demonstrated. However, optimal control strategy in wind farm
level has not been studied deeply.
B. Monitor &Control System for Wind Farm
Fig.2 The framework of monitor &control system for wind farm
The function of monitor &control system for wind farm is
supposed to realize the optimized power control of wind farm
response to the dispatch command. The framework is designed
as shown in Fig. 2.
The main functions of power control system shown in Fig. 2
are to receive power prediction signals and operation
informat ion of wind turbines dynamically, controlling the
wind turb ines and compensation device optimally, and
sending feedback signals to superior control station. To realize
those functions, the active power control strategy of the
decentralized controller is one of the important parts.
III. THE ACTIVE POWER CONTROL STRATEGY FOR WIND FARM
A. Passive control mode of wind farm
In the ordinary situation, each wind turbine in wind farm
operates over the maximum power point tracing curve, while
does not response to the active power variation of the grid.
B. Active control mode of wind farm
As the wind power penetration is increasing greatly, wind
farms with the ability of power control would be more suitable
for the requirement of safe and stable operation of power
system. It is infeasible to increase the power output of wind
farm temporarily because of the special characteristics of wind
energy. So this paper focuses on the power dispatch problem
when output power of wind farm needs to be constrained.
Methods for controlling power output of wind farm include
cutting off a row of wind turbines, cutting off the whole wind
farm and regulat ing active output of wind turbine by pitch
angle control and rotor speed control. Regulating act ive power
output of wind turbines is more economical than cutting off
turbines or wind farm directly, which would ensure more
turbines online. So this control method is used in this paper for
output power constraint of wind turbine. The active control
strategy of wind farm is shown as follows.
After receiv ing dispatch command for output constraint
from dispatch centre, the system at wind farm control level
analyzes and calculates the actual constrained value dP with
wind power prediction considered. Besides, the signals which
request for connecting to the grid or increasing output should
be postponed.
Then, considering regulation capacity S , regulation speed
V and response time T of turbines, the control center
dispatches control signals to selected wind turbines following
priority list which is detailed studied below. At last, the
selected wind turbines would operate with the power control
method mentioned above. The proposed control strategy aims
to obtain a minimum deviat ion between the total active power
output of the wind farm and the dispatch command, while
another control objective is to realize the optimal act ive power
dispatch in a wind farm. Considering dispatch accuracy, this
paper takes 15 minutes as one control period. The process of
the calculations of priority list and wind turbine output power
references is studied as follows and turbine i is chosen as a
representative.
1): Calculation of Relevant Parameters of turbines
a. Regulation Capacity Si
The regulation capacity is the adjustable capacity of a wind
turbine with controlling pitch angle actively. Considering
wind velocity variation, turbine i needs to reserve a certain
amount of control margin of p itch angle to prevent wind
turbines online abnormally disconnected from power grid.
Suppose maximum pitch angle of turbine i max max
i i , where max
i is the actual maximum p itch
angle, and is reserve marg in of pitch angle . max
i is
determined by the possible increasing value of active power
output of wind turbine during a control period:
*)(2
1
*)(2
1
1
max
max
3
1
2
max
max
3
2
optiP
optiP
CS
CSP
,
,
(1)
where 1v and
2v are wind velocit ies at the first and last
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moment of a control period. v is the approximate value of
wind fluctuation during the adjacent control period and
2 1v v v . The wind power coefficient
0.255( ) 0.5( 0.022 2)
RC f
f
p
RCC e
(2)
where fC is the blade design constant,
opt is the tip speed
ratio and is wind power generator efficiency.
Assuming that wind velocity 1v is constant during the
control period, regulat ion capacity of turbine i is
3 max
1
1[ ( ) ( )]*
2i w p i p iS S v C C . (3)
And then max
i can be calculated based on (4)
max( )i i i iP P S P (4)
where
max 3 max
1
1( ) ( )*
2i i w p iP S v C (5)
and iP is the active power output of turbine i corresponding to
wind velocity 1v .Through the formulas above, regulation
capacity iS can be calculated at last.
Because of the difficu lties to determine regulation capacity
of wind turbines operating over the maximum power point
tracking curve, this paper focuses on wind turbines operating
in constant rotor speed region.
b. Regulation Speed iV
The regulation speed is defined as the maximum rate of
change of the pitch angle when the wind turbine operates at its
rated power. Regulation speed can be determined by
/i iV P t (6)
where P is a certain power variation and it is the time cost
by pitch angle variation. The parameter can be obtained in the
manual book or in the test.
c. Response Time iT
Response time iT is the t ime ranging from the moment
turbine i receiving control signal to pitch angle control startup,
which can be obtained in the manual book or in the test.
2): Calculation of Regulation Performance Index
The regulation performance index iK is relevant to the
three parameters above, which can determine the priority
levels of wind turbines. The index iK can be calcu lated by (7)
as follows:
i i ii S V TK aK bK cK (7)
whereiSK ,
iVK and iTK are the indexes representing
regulation capacity, regulation speed and response time of
turbine i. a , b and c are the weighting coefficients and
1a b c . This paper takes regulation capacity as prior
factor and sets 0.8 0.1 0.1i i ii S V TK K K K .
As there is no normative standard for optimal control of
wind farm at present, this paper references the requirements of
AGC for the calculat ion of iSK ,
iVK and iTK [ 11 ]. The
assessment process of the indexes is shown as follows.
a. Index of Regulation Capacity
Set regulation capacity index iSK as 1.0 when regulation
capacity takes 10% of the rated capacity of wind turbine. And
when regulation capacity rises or drops 1% of the rated
capacity, iSK increases or decreases 0.015:
1.0 ( / 0.1)*1.5iS i NiK S S (8)
where NiS is the rated capacity of turbine i.
b. Index of Regulation Speed
Suppose that the required regulation capacity per minute
must be more than 10% of the rated capacity. Set 1.0iVK
when regulation capacity per minute miniVS equals to 10% of
the rated capacity. And increase iVK by 0.01 while regulat ion
capacity per minute rises 1% of the rated capacity.
min1.0 ( / 0.1)*1.0i iV V NiK S S (9)
c. Index of Response Time
If the system requests response time must be less than 30s,
set 1.0iTK when 30iT s . 0.5 is used to balance orders of
magnitude of three indexes.
1.0 (1.0 / 30)*0.5iT iK T (10)
3): The Determination of Priority List
According to the regulation performance index of each
turbine, the priority list can be determined finally. Using the
priority list obtained, the units are committed based on their
priority with the highest priority being on first to control
followed by other units in the list accordingly. As shown in
section Ⅳ , the studied wind farm includes three turbines. The
indexes and the priority level of turb ines can be shown in
Table I as fo llows. TABLE I
REGULATION PERFORMANCE INDEX AND REGULATION
PRIORITY OF TURBINES
Unit Serial Num. iK Regulation priority
1 1.23 2
2 1.31 1
3 1.15 3
4): The Calculation of the Output Power References
The decentralized controller determines the wind turbines
participating in output constraint and dispatches the control
targets to selected wind turbines according to the priority list.
Suppose the number of turbines participating in output
constraint is j considering the total adjustable capacity equal to
the dispatch command valuedP approximately. We can get
1
1
j
d i j
i
P S P
(11)
where jP is regulation capacity of the selected turbine which
is in the lowest priority level, namely j jP P where P is
the decreased power value required. Other selected turbines
should take regulation capacity as the adjustable capacity
value, namely i iP S .
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The adjustable capacity P will be sent to each selected
turbine when dispatch command is received. Then ref iP P
will be taken as new output reference as refP is the output
reference when wind generator operates in ordinary control
mode. The control target for output constraint can be achieved
by rotor speed control and pitch angle control.
C. Flow Diagram of the Control Strategy
Flow diagram of the strategy is shown as follows.
The Operation Information
of Wind Turbines
Si Vi Ti
Priority List
Dispatch
Command
Confirm the dispatch command
value and postpone the
connecting signal of wind
turbines
Operate over the
Maximum Power
Point Tracing Curve
JUDGE
According to the priority list,
the adjustable wind turbines can
be selected and ordered
Send the control signals
containing power references to
the selected wind turbines
limit output based on rotor
speed control and pitch
angle control
iSKiVK
iTK
No Demand
iK
When the strategy cannot satisfy the dispatch demand of
output constraint in a certain period, wind turbines should be
cut off following a principle then.
IV. SIMULATION RESULTS
A test system is presented to test the proposed methodology,
using a small wind farm with three equivalent turbines
(6*1.5MW nominal capacity for each). In the test system each
wind generator would be connected to its own transformer
without the need of any internal wind park grid
reconfiguration. Line capacity restrictions are also not
considered. The wind farm is connected to an infinite bus bar
which represents the grid, as shown in Fig.3.
Fig.3 The test system
The system simulated and analyzed based on Matlab/
Simulink tool.
Wind speed and the priority level of each turbine are shown
in Table Ⅱ. The controller receives dispatch command at 10s
and 7.36MW need be reduced for safe and stable operation of
the power system in this simulat ion. The result would be
compared with conventional control strategy which constrains
wind farm output by cutting off turbines. TABLE Ⅱ
WIND SPEED AND REGULATION PRIORITY OF TURBINES
Unit Serial Num. Wind Speed(m/s) Regulation priority
1 24.5 2
2 16 1
3 12 3
TABLE Ⅲ UNIT COMMITMENT WITH TWO STRATEGIES
Unit Serial Num. Proposed Strategy Conventional Strategy
1 1 1
2 1 1
3 1 0
(a) Output performance with priority list strategy
(b) Output performance with cutting turbine strategy
Fig.4The variation of total output of wind farm with active control (MW)
Table Ⅲ shows unit commitment of wind turbines with the
two control strategies alternatively applied(1 represents
online). And Fig.4 presents the simulation results of the two
strategies respectively. It is obvious that the proposed method
in this paper is more effect ive as the performance in Fig.4 (a)
is much more accurate than in Fig.4 (b) and the number of
turbines which needs to be cut off is reduced.
V. CONLUSION
Considering the fundamental thought of active power
control system of wind power base and classical unit
commitment and dispatch strategies , a priority list method is
proposed for active power output constraint at wind farm
control level. The proposed strategy determines the dynamic
priority list of adjustable turbines considering regulation
capacity, regulation speed and response time. Through
sequential control of turbines, this strategy can realize fewer
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turbines disconnected from the grid and improve the ability of
optimal operation of wind farm. The simulation results show
the validity and feasibility of the method proposed.
VI. REFERENCES
[1] Li Xueming, Xing Zhou, Chen Zhenhuan, Chen Yonghua, Wang Fujun
and Luo Jianbo, “Design of Large Clusters of Wind Power Active
Intelligent Control System,”Automation of Electric Power Systems, vol. 34, pp. 59-63, Sep. 2010
[2] Liu Jun, Zhou Xichao, “Wind farm automatic generation control based on ultra-short-term wind-power forecasts,” Electric Power, vol. 44, pp. 74-77,
Feb. 2011 [3 ] Jung-Hyun Choi, Seon-Ju Ahn, Jin-Woo Park,Seung-Il Moon, “Active
power limitation of wind farm to reduce system operating cost ,” in Proc. 2009 Transmission & Distribution Conference & Exposition: Asia and
Pacific Conf., pp. 1-4 [4] Li Lin, Shiqian Wang, “Investigation of the strategy of wind farm power
regulation considering system frequency regulation demand,” in Proc.
2011 4th International Conference on DR PT, pp. 1138- 1143 [5] Hui Jing, Gu Xin, “Research on centralized power control strategies for
large wind farms,” East China Electric Power, vol. 36, pp. 57-61, Jun. 2008
[6 ] Mark Cardinal, “Monitoring, Control, and Automation of Large Wind Plants,” in Proc. 2008 IEEE/PES Transmission and Distribution Conference and Exposition, pp. 1-6
[7 ] Jose Luis Rodriguez-Amenedo, Santiago Arnalte, Juan Carlos Burgos,
“Automatic generation control of a wind farm with variable speed wind turbines,” IEEE Trans. On Energy Conversion, vol. 17, pp. 279-284, Feb. 2002
[ 8 ] Qiao Ying, Lu Zongxiang, “Wind Farms Active Power Control
Considering Constraints of Power Grids,” Automation of Electric Power Systems, vol. 33, pp. 88-93, Nov. 2009
[ 9 ] Moyano C.F., Lopes J.A. Pecas, “Unit Commitment and Dispatch
Strategies for a Wind Park ,” Power Engineering, Energy and Electrical Drives, 2007. 2007 , Page(s):12-17
[10] Liu Wei, “Study on Optimum Dispatching of Wind Farm Clusters,” M.D. dissertation ,Beijing Jiaotong University, 2011
[11] Lin Wanjing, Liu Rao and etc., “AGC Requirement Determination and Unit Selection in the Generation Market,” Automation of Electric Power Systems, vol.19, pp. 17-21, Oct. 2004
I. BIOGRAPHIES
Li Lin successively received her B.Sc. degree, M.Sc. degree and Ph.D.
degree in electrical engineering from North China Electric Power University, Beijing, China in 1991, 1997 and 2009. Now she is an associate professor in the School of Electrical and Electronic Engineering, North China Electric Power University. Her research mainly focuses on power system analysis,
operation and control. Yongjun Xie received a B.E. degree in electrical engineering from
Shandong University of Science and Technology, China, in 2010. He is
currently pursuing a M.Sc. degree at North China Electric Power University. His research interests are in power system analysis, operation and control and power system including wind power.
Ningbo Wang is a senior engineer in Gansu Electric Power Company. He
mainly focuses his research on wind power technology and power system planning.
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