CN113839398A - Variable droop coefficient control method for double-fed fan participating in primary frequency modulation of power grid - Google Patents

Variable droop coefficient control method for double-fed fan participating in primary frequency modulation of power grid Download PDF

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CN113839398A
CN113839398A CN202111013634.7A CN202111013634A CN113839398A CN 113839398 A CN113839398 A CN 113839398A CN 202111013634 A CN202111013634 A CN 202111013634A CN 113839398 A CN113839398 A CN 113839398A
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formula
coefficient
wind
droop
frequency
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CN113839398B (en
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王洋
吴倩
王琳媛
宋杉
缪舒馨
魏书荣
任子旭
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State Grid Jiangsu Electric Power Design Consultation Co ltd
Shanghai University of Electric Power
Economic and Technological Research Institute of State Grid Jiangsu Electric Power Co Ltd
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State Grid Jiangsu Electric Power Design Consultation Co ltd
Shanghai University of Electric Power
Economic and Technological Research Institute of State Grid Jiangsu Electric Power Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
    • H02J3/241—The oscillation concerning frequency
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/48—Controlling the sharing of the in-phase component
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P9/00—Arrangements for controlling electric generators for the purpose of obtaining a desired output
    • H02P9/007—Control circuits for doubly fed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P9/00—Arrangements for controlling electric generators for the purpose of obtaining a desired output
    • H02P9/10—Control effected upon generator excitation circuit to reduce harmful effects of overloads or transients, e.g. sudden application of load, sudden removal of load, sudden change of load
    • H02P9/105—Control effected upon generator excitation circuit to reduce harmful effects of overloads or transients, e.g. sudden application of load, sudden removal of load, sudden change of load for increasing the stability
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/76—Power conversion electric or electronic aspects

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Abstract

The invention relates to a variable droop coefficient control method for a double-fed fan participating in primary frequency modulation of a power grid, which comprises the following steps: step 1) acquiring real-time wind speed, and monitoring a power grid frequency deviation signal in real time; step 2) adding a self-defined droop characteristic unit into a traditional rotor active controller, and setting droop control difference adjustment coefficients of the double-fed fan participating in primary frequency modulation of the power grid at different wind speeds; step 3) optimizing a difference adjustment coefficient of droop control based on a gray wolf optimization algorithm; and 4) obtaining an additional active power increment according to the power grid frequency deviation signal and the droop control difference adjusting coefficient after setting optimization, and participating in frequency modulation according to the active power increment. The beneficial effects are that: the secondary frequency drop caused by excessive response of the wind turbine generator due to the over-small setting of the difference adjustment coefficient is avoided; the control precision is improved, the self-adaptive capacity is better, the available capacity of the real-time unit can be fully utilized, and the frequency response capacity of the unit is improved.

Description

Variable droop coefficient control method for double-fed fan participating in primary frequency modulation of power grid
Technical Field
The invention belongs to the technical field of wind power generation, and particularly relates to a variable droop coefficient control method for a double-fed fan to participate in primary frequency modulation of a power grid.
Background
The wind power generation technology is mature, the construction period is short, and the cost is low, so that the wind power generation technology becomes one of new energy sources which are vigorously developed in various countries in the world. The wind power plant is used as a renewable energy source, and has certain value in the aspects of energy conservation, emission reduction and power supply structure optimization, but wind in the nature has instability, and the wind speed is large or small, so that the randomness and the uncontrollable property are high. Therefore, large-scale wind power grid connection inevitably has great influence on the frequency stability of the system.
The double-fed wind driven generator is a mainstream model of wind power generation. Because the rotor of the doubly-fed wind generator is connected with the power grid through the converter, the rotor speed of the fan is completely decoupled from the system frequency, and the change of the system frequency cannot be responded. Therefore, after the large-scale wind power is merged into the power grid, the frequency modulation capability of the system is weakened, and the stability of the system is influenced. In addition, the frequency modulation capability of the wind turbine generator is closely related to the current wind speed, the load shedding standby of the wind turbine generator is less in a low wind speed section, the frequency modulation capability is limited, and if the load shedding standby energy and the rotor kinetic energy of the wind turbine generator are excessively utilized, the fan is easy to stall and exit the operation; under the condition of high wind speed, the load reduction standby of the wind turbine generator is sufficient, the available frequency modulation power is large, and the frequency modulation capability is strong.
At present, some experts and scholars at home and abroad research a control method for participating in primary frequency modulation of a power grid based on a variable droop control coefficient double-fed wind turbine generator. However, in some existing researches, the pulsatility and uncertainty of natural wind are ignored, and simulation checking calculation is only carried out under a fixed wind speed. In some methods, the control rule of the double-fed wind turbine generator is not considered, and only a fixed droop coefficient is simply adopted. If the droop coefficient is set to be smaller, the wind turbine generator is caused to respond excessively, and the system frequency falls for the second time; if the droop coefficient is set to be larger, the frequency response capability of the wind turbine generator cannot be fully exerted. Some wind speed points are selected to obtain the value of the corresponding wind speed droop control coefficient, and the obtained data are fit into a droop control curve, so that the control accuracy is insufficient, and a large improvement space is still provided.
Disclosure of Invention
Aiming at the defects of the prior art, the method solves the problems that the droop control curve is synthesized by a small amount of data in a fitting mode, the control precision is insufficient, the frequency secondary drop is caused by the excessive response of the wind turbine generator due to the undersized setting of the difference adjustment coefficient, and the frequency response capability of the wind turbine generator cannot be fully exerted due to the overlarge setting of the difference adjustment coefficient, and the invention provides a droop coefficient control method for a double-fed fan to participate in the primary frequency modulation of a power grid, which is implemented by the following scheme:
the variable droop coefficient control method for the double-fed fan to participate in the primary frequency modulation of the power grid comprises the following steps:
step 1) acquiring real-time wind speed, and simultaneously monitoring a power grid frequency deviation signal delta f in real time;
step 2) adding a self-defined variable droop characteristic unit into a traditional rotor active controller, and setting droop control difference adjusting coefficients of the double-fed fan participating in primary frequency modulation of the power grid at different wind speeds through the self-defined variable droop characteristic unit;
step 3) optimizing the difference adjustment coefficient of droop control based on a gray wolf optimization algorithm, so that the double-fed fan can automatically select the optimal droop control difference adjustment coefficient according to the current wind speed;
and 4) obtaining an additional active power increment according to the power grid frequency deviation signal delta f and the droop control difference adjusting coefficient after setting optimization, and participating in frequency modulation according to the active power increment.
The variable droop coefficient control method for the double-fed fan to participate in the primary frequency modulation of the power grid is further designed in that the self-defined variable droop characteristic unit in the step 2) completes the setting of the droop control difference coefficient of the double-fed fan to participate in the primary frequency modulation of the power grid according to the formula (1),
Figure BDA0003239121730000021
in the formula (1), Δ f0Is set to 0.2Hz, f for allowable frequency deviationNRated for the grid at 50Hz, Pdel' Total reserve power for load shedding of n doubly-fed wind turbines in wind farm, PWNRated active power of the wind power plant; calculating the total reserve power P of n doubly-fed wind turbines in the wind power plant for load shedding according to the formula (2)del’：
Figure BDA0003239121730000022
in the formula ,PdelThe reserve power for load shedding of a single doubly-fed wind generator is represented by rho air density, d load shedding coefficient and Cp，maxThe maximum wind energy capture coefficient is the maximum wind power tracking, and v is the wind speed.
The variable droop coefficient control method for the double-fed fan to participate in the primary frequency modulation of the power grid is further designed in that the adjusting difference coefficient for optimizing droop control based on the gray wolf optimization algorithm in the step 3) specifically comprises the following steps:
step 3-1) randomly defining and generating a group of wolf clusters based on a difference adjustment coefficient formula according to different wind speeds, referring to formula (3), and using the most initial wolf optimization algorithm to search a local possible optimal solution range;
Figure BDA0003239121730000031
Figure BDA0003239121730000032
wherein ,
Figure BDA0003239121730000033
is the distance between the wolf individual and the prey, t is the number of iterations,
Figure BDA0003239121730000034
and
Figure BDA0003239121730000035
is a vector of coefficients that is a function of,
Figure BDA0003239121730000036
is the position of the prey over t iterations,
Figure BDA0003239121730000037
is the position of the gray wolf after t iterations;
step 3-2) controlling that the optimized objective function is minimum in the constraint condition to achieve the optimal power point tracking, and constructing the objective function according to the formula (4):
Figure BDA0003239121730000038
wherein f (x) is frequency overshoot, Δ fmaxThe maximum frequency deviation amount in the frequency response process;
the constraints for constructing the objective function according to equations (5) to (12) are:
vin＜v＜vout (5)
wherein v is wind speed, v isinFor cutting into the wind speed, voutCutting out the wind speed;
Δf0≤0.2Hz (6)
in the formula ,Δf0Is a frequency deviation allowable value;
ωmin≤ωref≤ωmax (7)
in the formula ,ωminIs the minimum value of the speed of rotation, ωrefAs reference value of the speed of rotation, ωmaxIs the maximum value of the rotation speed;
βmin≤βref≤βmax (8)
in the formula ,βminAt the minimum value of pitch angle, βrefAs pitch angle reference value, βmaxIs the maximum value of the pitch angle;
Figure BDA0003239121730000039
in the formula ,PmMechanical power for doubly-fed wind turbines, CpAs a factor of wind energy capture, Cp，maxFor maximum wind energy capture coefficient, v, at maximum wind power trackingnRated wind speed;
Figure BDA00032391217300000310
in the formula ,ωrIs the rotation speed;
Figure BDA0003239121730000041
in the formula ,PGIs the output power of the doubly-fed wind turbine, KCAs MPPT coefficient, ωr,nIs a rated rotating speed;
Figure BDA0003239121730000042
in the formula, f is frequency, t' is time, and the constraint condition ensures that the frequency response process does not have frequency secondary drop;
and (3) searching an optimal difference adjustment coefficient under the corresponding wind speed based on a wolf optimization algorithm according to a simultaneous equation of the formula (13), so that the frequency overshoot f (x) is minimum under the constraint of each constraint condition.
Figure BDA0003239121730000043
Step 3-3) constructing a generalized objective function according to the formula (14):
F(x)＝f(x)+δ(t)H(x) (14)
wherein, f (x) is an original objective function, δ (t) H (x) is a penalty term, δ (t) is a penalty degree, and H (x) is a penalty factor; step 3-4) calculating punishment factors of all constraint conditions of each wolf individual, calculating the fitness value of each wolf individual according to a formula (14), and recording the optimal fitness value and the corresponding position;
step 3-5) judging whether the penalty factor H (x) meets the precision requirement or the maximum iteration frequency, if so, finishing the algorithm and outputting an optimal solution; otherwise, executing step 3-6);
step 3-6) recording the individual positions of the wolfs with the three highest fitness values as the positions of the wolfs
Figure BDA0003239121730000044
As a decision layer, other individuals and
Figure BDA0003239121730000045
and updating the position of each individual wolf body according to the formulas (16) to (17), and returning to the step 3-4);
Figure BDA0003239121730000046
in the formula
Figure BDA0003239121730000051
Respectively represent the distances of alpha, beta and delta from other individuals in the wolf group;
Figure BDA0003239121730000052
current positions of α, β, and δ are represented, respectively;
Figure BDA0003239121730000053
is the coefficient vector and t is the number of iterations.
Figure BDA0003239121730000054
Figure BDA0003239121730000055
Equation (16) defines the direction and distance of the omega unit in the wolf cluster to advance towards alpha, beta and delta, respectively, and equation (17) represents the final position of the omega unit in the wolf cluster.
4. The method for controlling the droop coefficient of the doubly-fed wind turbine participating in the primary frequency modulation of the power grid according to claim 1, wherein the coefficient in the step 3-1) is calculated according to a formula (18):
Figure BDA0003239121730000056
Figure BDA0003239121730000057
in the formula ,
Figure BDA0003239121730000058
linearly decreasing from 2 to 0 during the iteration,
Figure BDA0003239121730000059
and
Figure BDA00032391217300000510
are each [0,1]Random vector of (2).
The invention has the advantages of
According to the method, the difference adjustment coefficient of the droop control of the double-fed fan participating in the primary frequency modulation of the power grid is optimized based on the gray wolf optimization algorithm, the difference adjustment coefficient of the droop control can be adjusted according to different wind speeds, and the secondary frequency drop caused by excessive response of a wind turbine generator due to the over-small setting of the difference adjustment coefficient is avoided; the problem that the frequency response capability of the wind turbine generator cannot be fully exerted due to the fact that the adjustment difference coefficient is set to be too large is avoided. Meanwhile, the difference adjusting coefficient is optimized based on a wolf optimization algorithm, the control precision is improved, the self-adaptive capacity is better, the available capacity of the real-time unit can be fully utilized, the frequency response capacity of the unit is improved, and the problem that a droop control curve is fit by a small amount of data and the control precision is insufficient is solved.
Drawings
Fig. 1 is a control block diagram of variable droop coefficients of a doubly-fed wind turbine.
FIG. 2 is a graph of the relationship between the droop coefficient and the wind speed under the gray wolf optimization algorithm.
FIG. 3 is a diagram of a simulation model built in PSCAD.
Fig. 4 is a graph showing the simulation effect obtained by setting the droop control variation coefficients to 2%, 3.47%, and 5% in the PSCAD at a wind speed of 11 m/s.
FIG. 5 is a graph of simulation results obtained by setting droop control difference coefficients of 2%, 5% in PSCAD, respectively, and without adding a droop control link, when the wind speed is 13 m/s.
FIG. 6 is a pitch angle variation graph with droop control delta coefficients set to 2%, 5%, respectively, in PSCAD, and without the droop control link, when the wind speed is 13 m/s.
Detailed Description
The technical scheme of the invention is further explained by combining the attached drawings.
The invention discloses a variable droop coefficient control method for a double-fed fan to participate in primary frequency modulation of a power grid, which comprises the following steps:
step 1) acquiring real-time wind speed, and simultaneously monitoring a power grid frequency deviation signal delta f in real time.
And 2) adding a self-defined variable droop characteristic unit into the traditional rotor active controller, and setting a droop control difference adjusting coefficient of the double-fed fan participating in primary frequency modulation of the power grid at different wind speeds through the self-defined variable droop characteristic unit.
And 3) optimizing the droop control difference adjustment coefficient based on a gray wolf optimization algorithm, so that the double-fed fan can automatically select the optimal droop control difference adjustment coefficient according to the current wind speed.
And 4) obtaining an additional active power increment according to the power grid frequency deviation signal delta f and the droop control difference adjusting coefficient after setting optimization, and participating in frequency modulation according to the active power increment.
And 2) adding a self-defined droop characteristic unit on the basis of the traditional rotor active controller, and automatically setting a droop control coefficient according to the current wind speed. The control block diagram of the variable droop coefficient of the doubly-fed wind turbine generator is shown in fig. 1, and the control block diagram specifically comprises the following steps:
step 2-1) when the double-fed wind driven generator simulates the droop characteristic of the traditional synchronous generator, the value delta P is K delta f, and the traditional synchronous generator comprises the following components:
Figure BDA0003239121730000061
in the formula ,KGFor the conventional synchronous generator unit regulation of power, KG *Adjusting power per unit, P, for a conventional synchronous generatorGNRated active power, f, for a conventional synchronous generatorNAt a nominal frequency of 50Hz, deltaGFor the traditional synchronous generator difference adjustment coefficient, Δ f is the system frequency variation.
Step 2-2), therefore, the expression of the conventional synchronous generator is simulated to obtain the following expression in the doubly-fed wind generator:
Figure BDA0003239121730000062
where K is the droop control coefficient, δwFor the difference adjustment coefficient, P, of the doubly-fed wind generatorWNThe rated active power of the doubly-fed wind generator is obtained.
Steps 2-3) thus have:
Figure BDA0003239121730000071
according to the formula, the droop control coefficient K and the difference adjustment coefficient delta of the doubly-fed wind generatorwIt is related.
Step 2-4) defining the difference adjustment coefficient of the variable droop control of the double-fed fan according to the definition formula of the difference adjustment coefficient of the traditional synchronous generator as follows:
Figure BDA0003239121730000072
in the formula ,Δf0Is set to 0.2Hz, f for allowable frequency deviationNFor a power grid rated frequency of 50Hz, consider the equivalence of a single machine, Pdel' Total reserve power for load shedding of n doubly-fed wind turbines in wind farm, PWNThe rated active power of the wind power plant.
Figure BDA0003239121730000073
in the formula ,PdelThe method is characterized in that the method is the reserve power for load shedding of a single doubly-fed wind generator, rho is air density, d is a load shedding coefficient, and the load shedding level is 20%. Cp，maxThe maximum wind energy capture coefficient is the maximum wind power tracking, and v is the wind speed.
The adjusting difference coefficient for optimizing droop control based on the gray wolf optimization algorithm in the step 3) specifically comprises the following steps:
step 3-1) randomly defining and generating a group of wolf clusters based on a difference adjustment coefficient formula according to different wind speeds, referring to formula (3), and using the most initial wolf optimization algorithm to search a local possible optimal solution range;
Figure BDA0003239121730000074
Figure BDA0003239121730000075
wherein ,
Figure BDA0003239121730000076
is the distance between the wolf individual and the prey, t is the number of iterations,
Figure BDA0003239121730000077
and
Figure BDA0003239121730000078
is a vector of coefficients that is a function of,
Figure BDA0003239121730000079
is the position of the prey over t iterations,
Figure BDA00032391217300000710
is the location of the gray wolf over t iterations.
Step 3-2) controlling that the optimized objective function is minimum in the constraint condition to achieve the optimal power point tracking, and constructing the objective function according to the formula (4):
Figure BDA0003239121730000081
wherein f (x) is frequency overshoot, Δ fmaxThe maximum frequency deviation amount in the frequency response process;
the constraints for constructing the objective function according to equations (5) to (12) are:
vin＜v＜vout (5)
wherein v is wind speed, v isinFor cutting into the wind speed, voutTo cut out wind speed；
Δf0≤0.2Hz (6)
in the formula ,Δf0Is a frequency deviation allowable value;
ωmin≤ωref≤ωmax (7)
in the formula ,ωminIs the minimum value of the speed of rotation, ωrefAs reference value of the speed of rotation, ωmaxIs the maximum value of the rotation speed;
βmin≤βref≤βmax (8)
in the formula ,βminAt the minimum value of pitch angle, βrefAs pitch angle reference value, βmaxIs the maximum value of the pitch angle;
Figure BDA0003239121730000082
in the formula ,PmMechanical power for doubly-fed wind turbines, CpAs a factor of wind energy capture, Cp，maxFor maximum wind energy capture coefficient, v, at maximum wind power trackingnRated wind speed;
Figure BDA0003239121730000083
in the formula ,ωrIs the rotation speed;
Figure BDA0003239121730000084
in the formula ,PGIs the output power of the doubly-fed wind turbine, KCAs MPPT coefficient, ωr,nIs a rated rotating speed;
Figure BDA0003239121730000085
where f is frequency and t' is time, the constraint condition ensures that no secondary frequency drop occurs in the frequency response process.
And (3) searching an optimal difference adjustment coefficient under the corresponding wind speed based on a wolf optimization algorithm according to a simultaneous equation of the formula (13), so that the frequency overshoot f (x) is minimum under the constraint of each constraint condition.
Figure BDA0003239121730000091
Step 3-3) constructing a generalized objective function according to the formula (14):
F(x)＝f(x)+δ(t)H(x) (14)
wherein f (x) is the original objective function, δ (t) H (x) is the penalty term, δ (t) is the penalty degree, and H (x) is the penalty factor. And 3-4) respectively calculating the penalty factors of all the constraint conditions of each wolf individual, calculating the fitness value of each wolf individual according to the formula (14), and recording the optimal fitness value and the corresponding position.
Step 3-5) judging whether the penalty factor H (x) meets the precision requirement or the maximum iteration frequency, if so, finishing the algorithm and outputting an optimal solution; otherwise, step 3-6) is performed.
Step 3-6) recording the individual positions of the wolfs with the three highest fitness values as the positions of the wolfs
Figure BDA0003239121730000092
As a decision layer, other individuals and
Figure BDA0003239121730000093
and updating the position of each individual wolf body according to the formulas (16) to (17), and returning to the step 3-4).
Figure BDA0003239121730000094
in the formula
Figure BDA0003239121730000095
Respectively represent alpha, beta and delta and wolfDistance of other individuals in the population;
Figure BDA0003239121730000096
current positions of α, β, and δ are represented, respectively;
Figure BDA0003239121730000097
is the coefficient vector and t is the number of iterations.
Figure BDA0003239121730000098
Figure BDA0003239121730000099
Equation (16) defines the direction and distance of the omega unit in the wolf cluster to advance towards alpha, beta and delta, respectively, and equation (17) represents the final position of the omega unit in the wolf cluster.
The coefficient in step 3-1) is calculated as in equation (18):
Figure BDA0003239121730000101
Figure BDA0003239121730000102
in the formula ,
Figure BDA0003239121730000103
linearly decreasing from 2 to 0 during the iteration,
Figure BDA0003239121730000104
and
Figure BDA0003239121730000105
are each [0,1]Random vector of (2).
The relationship between the optimized difference adjustment coefficient and the wind speed is shown in fig. 2.
In order to verify the effectiveness of the frequency modulation strategy, a simulation model is built by adopting PSCAD software, and the model is shown in FIG. 3. In the model, a wind power plant consists of 10 fans with rated capacity of 2.5MW, 35/110kV is connected with a 110kV system through a 35kV collecting line in a boosting mode, and the rated wind speed is 11 m/s. The 110kV system simulates the P-f droop characteristic, 20MW load is initially connected, simulation is run to 6s, and 5MW load is connected. The input frequency of the analog load is reduced, and the fan participates in frequency modulation. And setting the load reduction of the doubly-fed wind generator to be 20%.
The invention also provides the following two specific examples, wherein 2 typical representative wind speeds are respectively 11m/s and 13 m/s. Since the frequency response timescale of the present invention is around 18s, it is assumed that the wind speed is constant during the frequency response.
Example 1:
when the wind speed is 11m/s, respectively taking delta to analyze the influence of the droop coefficient on the frequency response performance of the doubly-fed wind generating setw2%, 3.47%, 5%. Wherein 2% is a small setting value; 3.47% is the setting value obtained by the method of the invention; 5% is a larger setting value, and the obtained simulation is shown in FIG. 4.
From FIG. 4, it can be seen that when δwThe setting is smaller (2%), and the power grid frequency has secondary drop in the frequency modulation process. When deltawThe setting is larger (5%), the maximum deviation absolute value ratio delta of the dynamic frequency of the power grid is larger than the maximum deviation absolute value ratio delta of the dynamic frequency of the power grid although the power grid frequency does not drop secondarily in the frequency modulation processwWhen the absolute value of the maximum deviation of the dynamic frequency is set to be 3.47%, the dynamic response effect of the frequency is worse than that of the method. It is seen that when the variable droop control coefficient method disclosed by the invention is adopted to participate in frequency modulation, the maximum deviation absolute value of the dynamic frequency of the power grid can be reduced, the frequency fluctuation can be reduced more favorably, and the frequency stability of the power grid can be maintained.
Example 2:
the pitch angle control is active to reserve spare capacity when the wind speed is 13 m/s. Respectively taking delta to analyze the influence of the droop coefficient on the frequency response performance of the doubly-fed wind generating setw2%, 5%, and no droop control. Wherein 2% is the setting value obtained by the invention; 5% is a large setting value, soThe simulation is shown in fig. 5.
As can be seen from fig. 5, after the variable droop coefficient setting method provided by the invention is adopted, the excessive response of the doubly-fed wind turbine generator can be avoided, and the dynamic response of the frequency can be effectively improved. Similar to 8m/s wind speed, when deltawThe setting is larger (5%), and the method provided by the invention has better frequency response capability.
As can be seen in connection with FIGS. 5 and 6, the pitch angle control takes part in the frequency modulation when the wind speed is 13 m/s. When the setting value obtained by the method is adopted, the pitch angle response is quicker, and the effect of improving the frequency response capability is more obvious.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can substitute or change the technical solution of the present invention and the inventive concept within the technical scope of the present invention.

Claims (4)

1. A variable droop coefficient control method for a doubly-fed wind turbine to participate in primary frequency modulation of a power grid is characterized by comprising the following steps:
step 1) acquiring real-time wind speed, and simultaneously monitoring a power grid frequency deviation signal delta f in real time;
step 2) adding a self-defined variable droop characteristic unit into a traditional rotor active controller, and setting droop control difference adjusting coefficients of the double-fed fan participating in primary frequency modulation of the power grid at different wind speeds through the self-defined variable droop characteristic unit;
step 3) optimizing the difference adjustment coefficient of droop control based on a gray wolf optimization algorithm, so that the double-fed fan can automatically select the optimal droop control difference adjustment coefficient according to the current wind speed;
and 4) obtaining an additional active power increment according to the power grid frequency deviation signal delta f and the droop control difference adjusting coefficient after setting optimization, and participating in frequency modulation according to the active power increment.
2. The method for controlling the droop coefficient of the doubly-fed wind turbine participating in the primary frequency modulation of the power grid according to claim 1, wherein the self-defined droop characteristic unit in the step 2) completes the setting of the droop control difference coefficient of the doubly-fed wind turbine participating in the primary frequency modulation of the power grid according to the formula (1),
Figure FDA0003239121720000011
in the formula (1), Δ f0Is set to 0.2Hz, f for allowable frequency deviationNRated for the grid at 50Hz, Pdel' Total reserve power for load shedding of n doubly-fed wind turbines in wind farm, PWNRated active power of the wind power plant;
calculating the total reserve power P of n doubly-fed wind turbines in the wind power plant for load shedding according to the formula (2)del′：
Figure FDA0003239121720000012
in the formula ,PdelThe reserve power for load shedding of a single doubly-fed wind generator is represented by rho air density, d load shedding coefficient and Cp，maxThe maximum wind energy capture coefficient is the maximum wind power tracking, and v is the wind speed.
3. The method for controlling the variable droop coefficient of the doubly-fed wind turbine participating in the primary frequency modulation of the power grid according to claim 1,
the optimization of the difference adjustment coefficient of the droop control based on the gray wolf optimization algorithm in the step 3) specifically comprises the following steps: step 3-1) randomly defining and generating a group of wolf clusters based on a difference adjustment coefficient formula according to different wind speeds, referring to formula (3), and using the most initial wolf optimization algorithm to search a local possible optimal solution range;
Figure FDA0003239121720000021
Figure FDA0003239121720000022
wherein ,
Figure FDA0003239121720000023
is the distance between the wolf individual and the prey, t is the number of iterations,
Figure FDA0003239121720000024
and
Figure FDA0003239121720000025
is a vector of coefficients that is a function of,
Figure FDA0003239121720000026
is the position of the prey over t iterations,
Figure FDA0003239121720000027
is the position of the gray wolf after t iterations;
step 3-2) controlling that the optimized objective function is minimum in the constraint condition to achieve the optimal power point tracking, and constructing the objective function according to the formula (4):
Figure FDA0003239121720000028
wherein f (x) is frequency overshoot, Δ fmaxThe maximum frequency deviation amount in the frequency response process;
the constraints for constructing the objective function according to equations (5) to (12) are:
vin＜v＜vout (5)
wherein v is wind speed, v isinFor cutting into the wind speed, voutCutting out the wind speed;
Δf0≤0.2Hz (6)
in the formula ,Δf0For allowing frequency deviationA value;
ωmin≤ωref≤ωmax (7)
in the formula ,ωminIs the minimum value of the speed of rotation, ωrefAs reference value of the speed of rotation, ωmaxIs the maximum value of the rotation speed;
βmin≤βref≤βmax (8)
in the formula ,βminAt the minimum value of pitch angle, βrefAs pitch angle reference value, βmaxIs the maximum value of the pitch angle;
Figure FDA0003239121720000029
in the formula ,PmMechanical power for doubly-fed wind turbines, CpAs a factor of wind energy capture, Cp，maxFor maximum wind energy capture coefficient, v, at maximum wind power trackingnRated wind speed;
Figure FDA00032391217200000210
in the formula ,ωrIs the rotation speed;
Figure FDA0003239121720000031
in the formula ,PGIs the output power of the doubly-fed wind turbine, KCAs MPPT coefficient, ωr,nIs a rated rotating speed;
Figure FDA0003239121720000032
in the formula, f is frequency, t' is time, and the constraint condition ensures that the frequency response process does not have frequency secondary drop;
according to a simultaneous equation of the formula (13), based on a wolf optimization algorithm, searching an optimal difference adjustment coefficient under the corresponding wind speed, so that the frequency overshoot f (x) is minimum under the constraint of each constraint condition;
Figure FDA0003239121720000033
step 3-3) constructing a generalized objective function F (x) according to the formula (14):
F(x)＝f(x)+δ(t)H(x) (14)
wherein, f (x) is an original objective function, δ (t) H (x) is a penalty term, δ (t) is a penalty degree, and H (x) is a penalty factor;
step 3-4) calculating punishment factors of all constraint conditions of each wolf individual, calculating the fitness value of each wolf individual according to a formula (14), and recording the optimal fitness value and the corresponding position;
step 3-5) judging whether the penalty factor H (x) meets the precision requirement or the maximum iteration frequency, if so, finishing the algorithm and outputting an optimal solution; otherwise, executing step 3-6);
step 3-6) recording the individual positions of the wolfs with the three highest fitness values as the positions of the wolfs
Figure FDA0003239121720000034
As a decision layer, other individuals and
Figure FDA0003239121720000035
and updating the position of each individual wolf body according to the formulas (16) to (17), and returning to the step 3-4);
Figure FDA0003239121720000041
in the formula
Figure FDA0003239121720000042
Respectively representing alpha, beta and delta and others in the wolf groupA distance;
Figure FDA0003239121720000043
current positions of α, β, and δ are represented, respectively;
Figure FDA0003239121720000044
is a coefficient vector, t is the number of iterations;
Figure FDA0003239121720000045
Figure FDA0003239121720000046
equation (16) defines the direction and distance of the omega unit in the wolf cluster to advance towards alpha, beta and delta, respectively, and equation (17) represents the final position of the omega unit in the wolf cluster.
4. The method for controlling the droop coefficient of the doubly-fed wind turbine participating in the primary frequency modulation of the power grid according to claim 1, wherein the coefficient in the step 3-1) is calculated according to a formula (18):
Figure FDA0003239121720000047
Figure FDA0003239121720000048
in the formula ,
Figure FDA0003239121720000049
linearly decreasing from 2 to 0 during the iteration,
Figure FDA00032391217200000410
and
Figure FDA00032391217200000411
are each [0,1]Random vector of (2).
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