CN114726005A - Wind power plant double-layer frequency control method considering fan power optimal distribution - Google Patents

Wind power plant double-layer frequency control method considering fan power optimal distribution Download PDF

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CN114726005A
CN114726005A CN202111674279.8A CN202111674279A CN114726005A CN 114726005 A CN114726005 A CN 114726005A CN 202111674279 A CN202111674279 A CN 202111674279A CN 114726005 A CN114726005 A CN 114726005A
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fan
power
wind
time point
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CN114726005B (en
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桂前进
钟成元
江千军
王京景
李智
罗利荣
郭力
王中冠
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State Grid Anhui Electric Power Co Ltd Anqing Power Supply Co
Tianjin University
State Grid Corp of China SGCC
State Grid Anhui Electric Power Co Ltd
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State Grid Anhui Electric Power Co Ltd Anqing Power Supply Co
Tianjin University
State Grid Corp of China SGCC
State Grid Anhui 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
    • H02J3/38—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
    • 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
    • H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
    • 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
    • H02J3/381—Dispersed generators
    • 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 discloses a wind power plant double-layer frequency control method considering fan power optimization distribution, which comprises the steps of utilizing a wind power plant centralized controller to execute centralized prediction control according to a fixed period, predicting the frequency of a power system and the future state of each fan, generating a wind power plant of each power set point and an active power reference value of each fan according to the frequency, and issuing the reference values to each fan controller; and each fan controller executes real-time correction control at fixed intervals, and the correction of the active power instruction of the fan is realized through distributed iteration, so that the wind power plant and the fan power are close to a set value issued by the wind power plant centralized controller, and the rotating speed of each fan is ensured to be within a safety range. The method can meet the requirement of the wind power plant on rapid frequency control, and can also meet the target of reasonable power distribution between the overall characteristics of the wind power plant and the fans.

Description

Wind power plant double-layer frequency control method considering fan power optimal distribution
Technical Field
The invention relates to the technical field of operation and control of power systems, in particular to a double-layer frequency control method for a wind power plant.
Background
Under the double pressure of energy shortage and environmental pollution, renewable energy power generation is increasingly becoming the choice of clean energy replacement. Among them, wind power generation has been rapidly developed in recent years, and the structure and operation of a conventional power system have been greatly changed. The uncertainty of the wind resource itself may cause adverse effect on the frequency stability of the power system, because most wind power plants operate in a maximum output power tracking mode to obtain the maximum power generation benefit, and the fluctuation of the wind power causes the obvious change of the power generation power of the power system. Meanwhile, most of novel fans are connected with a power grid through a power electronic converter, the rotating speed of a fan rotor is decoupled with the system frequency, along with the improvement of the wind power ratio, the inertia of a power system is relatively reduced, and the problem of frequency fluctuation under power fluctuation is increasingly highlighted.
In fact, as a rotating device, the kinetic energy stored in the wind turbine blades and the flexibility of control of the power electronic converter provide the possibility for wind power to participate in frequency regulation. Through adjusting the power electronic converter of fan rotor side, can its active output of quick adjustment, utilize the kinetic energy that fan self stored to provide quick frequency control service for electric power system. However, currently, most wind turbines are involved in power system frequency control using a "distributed approach," i.e., individual wind turbines independently provide simulated inertial and droop characteristics based on their measured frequency. However, in operation in the power system, the wind power plant should simulate the frequency modulation characteristics of the traditional thermal power generating unit as a whole to achieve the frequency control target of the power system. However, if the wind farm as a whole responds to the frequency change of the power system, how to reasonably distribute power among all the fans in the wind farm becomes a main problem for restricting frequency control. For this problem, in the prior art, a centralized optimization control method is generally adopted, a centralized optimization model is established and solved according to the frequency change of the power system and the operation state of each fan of the wind farm, and then an adjustment instruction of the active power of each fan is issued. However, due to the fact that the number of fans in a large-scale wind power plant is large, geographical distribution is far, communication time and calculation time required by centralized control are long, large delay exists, the method greatly depends on the parameter precision of a fan model and the prediction precision of wind speed, if the model parameter or wind speed error is large, power distribution among the fans is unreasonable, and fan off-line can be caused in serious situations. Since centralized model maintenance and optimization calculations will take a lot of time, this type of method is not suitable for frequency control with high response speed requirements.
Therefore, on the basis of the advantages of the power optimal allocation of the distributed control and the centralized control, a frequency control method which can give consideration to the wind farm frequency control rapid response, the wind farm overall frequency control characteristic and the power optimal allocation among the fans needs to be provided urgently, the limitations of the wind farm actual communication and hardware conditions on the control time interval and the calculation speed are considered, and the dependence of the traditional frequency control mode on model parameters and wind speed prediction is avoided.
Disclosure of Invention
Based on the technical problems in the prior art, the invention provides a wind power plant double-layer frequency control method considering fan power optimal allocation, which realizes distributed communication and real-time correction control of fan controllers of all nodes among fans by using a double-layer control architecture, enables the wind power plant and each fan to track an active power reference value, and ensures the operation safety of each fan.
The invention is realized by the following technical scheme:
a wind power plant double-layer frequency control method considering fan power optimal distribution specifically comprises the following steps:
step 1, calculating to obtain a centralized prediction control period T by utilizing a wind power plant centralized controller according to the running state of a power system and the wind speed of a wind power plantWFSetting the active power reference value of the wind power plant and the active power reference value of each fan at a time point of each power, and issuing the active power reference values to each fan controller, wherein the specific execution flow is as follows:
step 1-1, in the centralized predictive control period TWFIn the method, a prediction model of each power setting time point frequency of the power system is defined as follows:
Figure BDA0003450986070000031
wherein t represents the serial number of the power setting time point, zero clearing is carried out at the beginning of each centralized prediction control period, f (t) represents the prediction frequency of the t-th power setting time point, f (t +1) represents the prediction frequency of the t + 1-th power setting time point, and KfAnd KinDroop coefficient and inertia coefficient respectively representing wind power plant participating in frequency modulation, f*Representing the rated frequency of the power system, and H represents the equivalent inertia of the power system;
step 1-2, calculating an active power reference value of the wind power plant at each power setting time point, wherein the formula is as follows:
Figure BDA0003450986070000032
wherein, Pref(t) represents an active power reference value at the tth power setting time point of the wind farm,
Figure BDA0003450986070000033
representing the active power when the wind power plant does not participate in frequency modulation;
1-3, alternately calculating a fan rotating speed predicted value and a fan active power reference value of each power setting time point according to the following steps:
step 1-3-1, calculating a predicted value of the rotating speed of the fan at the tth power setting time point, wherein a formula is as follows:
Figure BDA0003450986070000034
wherein, ω isi,ref(t) the predicted value of the rotation speed of the ith fan at the t-th power setting time point, JiRepresenting the moment of inertia, P, of the ith fani,ref(t-1) the ith active power reference value, P, of the ith fan at the t-1 th power setting time pointi,m,ref(t-1) the predicted value of the input wind power of the ith fan at the t-1 th power setting time point is represented by the following calculation formula:
Figure BDA0003450986070000035
wherein ρ represents air density, R represents fan blade radius, and v representswRepresenting wind speed of the wind farm, Ci,ref(t-1) the predicted value of the wind energy capturing coefficient of the ith fan at the t-1 th power setting time point is represented by the following formula:
Figure BDA0003450986070000041
wherein, ω isi,ref(t-1) representing the predicted value of the rotating speed of the ith fan at the t-1 th power setting time point, and beta representing the pitch angle of the fan;
step 1-3-2, calculating the predicted value of the energy state of each fan at the tth power setting time point, wherein the formula is as follows:
Figure BDA0003450986070000042
wherein, SOEi,ref(t) the ith predicted value of the energy state of the wind turbine, ω, at the tth power setting time pointmaxAnd ωminRespectively representing the upper limit value and the lower limit value of the rotating speed of the fan;
1-3-3, calculating the active power reference value of each fan at the tth power setting time point, wherein the formula is as follows:
Figure BDA0003450986070000043
step 1-3-4, returning to step 1-3-1 until the centralized prediction control period TWFThe predicted value of the rotating speed of each fan and the reference value of the active power of the fan at the time point of setting all internal power are calculated;
step 1-4, the control period T is predicted in a centralized mannerWFWind power plant active power reference value P of each power setting time pointref(t) and active power reference value P of each fani,ref(t) sending the data to the fan controllers of the nodes;
step 1-5, reaching the centralized prediction control period TWFReturning to the step 1-1, and restarting timing;
step 2, the fan controllers of all nodes receive the wind power plant active power reference value P issued by the wind power plant centralized controllerref(t) and active power reference value P of each fani,ref(T) setting time intervals T at corresponding powerrefAt a time interval TWTAnd (3) performing real-time correction control, wherein the specific execution flow is as follows:
step 2-1, calculating an energy state distribution index x of the ith fan in the kth real-time correction control according to the active power output and the actual rotating speed of the corresponding fan in the kth real-time correction controli(k) The calculation formula is as follows:
Figure BDA0003450986070000051
wherein, Pi(k) Representing the kth step to correct and control the active power output, omega, of the ith fan in real timei(k) Representing the k step to correct and control the actual rotating speed, P, of the ith fan in real timei,m(k) Representing the input wind power of the ith fan controlled by the real-time correction of the kth step, the calculation formula is as follows:
Figure BDA0003450986070000052
wherein, Ci(k) Representing the wind energy capture coefficient of the ith fan for the k-th real-time correction control, the calculation formula is as follows:
Figure BDA0003450986070000053
step 2-2, electrically connecting any two adjacent fans in the wind power plant, and exchanging energy state distribution indexes x by corresponding fan controllersi(k)；
Step 2-3, calculating the second-order gradient H of the kth real-time correction control of the ith fani(k) The calculation formula is as follows:
Figure BDA0003450986070000054
wherein, K1、K2And K3Respectively representing punishment coefficients corresponding to wind field active power deviation, fan active power deviation and inter-fan power distribution deviation, wherein N (i) represents a fan set adjacent to the ith fan in electrical connection;
step 2-4, calculating a first-order Jacobian gradient g of the kth real-time correction control of the ith fani(k) The calculation formula is as follows:
Figure BDA0003450986070000061
step 2-5, calculating the iteration direction d of the k-th real-time correction control of the ith fani(k) The calculation formula is as follows:
di(k)＝-Hi(k)-1·gi(k) (13)
step 2-6, calculating the energy state distribution index x of the ith fan in the (k +1) th real-time correction controli(k +1), the calculation formula is as follows:
xi(k+1)＝xi(k)+ε·di(k) (14)
wherein epsilon is an iteration step length;
step 2-7, calculating the active power set value P of the fan in the ith fan, which is subjected to the k +1 step of real-time correction controli(k +1), the calculation formula is as follows:
Figure BDA0003450986070000062
step 2-8, according to the active power set value Pi(k +1) controlling the active power output of the fan;
step 2-9, achieving real-time correction control interval TWTAnd returning to the step 2-1 and restarting timing.
Compared with the prior art, the invention can achieve the following beneficial technical effects:
1) the energy stored in the fan blades and the active power adjusting capacity of the fan can be fully utilized, so that the wind power plant integrally participates in the frequency adjustment of the power system and presents stable droop and inertia characteristics on the premise of ensuring the safe operation of the fan, and the frequency stability of the power system is facilitated;
2) the time required by actual communication of the wind power plant is fully considered, the target of the overall frequency modulation characteristic of the wind power plant and the power optimal distribution among the fans is met through the centralized predictive control of the wind power plant centralized controller, so that the kinetic energy stored by the fans tends to be uniform, and the requirement of the overall frequency modulation rapid control of the wind power plant is met through the real-time correction control of the fan controller; the requirement of the wind power plant on rapid frequency control can be met, and the target of reasonable power distribution between the overall characteristics of the wind power plant and fans can also be met;
3) the adopted time correction control method realizes the quick correction of the active power of the fan through distributed communication and iteration, and does not depend on the accurate model parameters of each fan, so that the good frequency control effect can still be ensured under the scene of inaccurate model parameters.
Drawings
FIG. 1 is an overall flow chart of a wind farm double-layer frequency control method considering optimal allocation of fan power according to the present invention.
Detailed Description
The technical scheme of the invention is explained in detail by combining the drawings and the specific embodiment.
As shown in fig. 1, an overall flowchart of a wind farm double-layer frequency control method considering optimal allocation of fan power according to the present invention specifically includes the following steps:
step 1, calculating to obtain a centralized prediction control period T by utilizing a wind power plant centralized controller according to the running state of a power system and the wind speed of a wind power plantWFInner (T)WFValue is selectable as 5 seconds), and sending the wind power field active power reference value and each fan active power reference value of each power setting time point to each fan controller, specifically, when each prediction control period begins, predicting the change of system frequency and fan rotating speed per second in the period, wherein each second is a power setting time point, and the interval between two adjacent power setting time points is TrefThe value can be selected to be 1 second, and the specific execution flow is as follows:
step 1-1, in the centralized predictive control period TWFIn the method, a prediction model of each power setting time point frequency of the power system is defined as follows:
Figure BDA0003450986070000071
wherein t represents the serial number of the power setting time point, zero clearing is carried out at the beginning of each centralized prediction control period, f (t) represents the prediction frequency of the t-th power setting time point, f (t +1) represents the prediction frequency of the t + 1-th power setting time point, and KfAnd KinDroop coefficients and inertia coefficients, respectively, representing the participation of the wind farm in frequency modulation, are usually specified by the power system, f*Representing the rated frequency of the power system, taking the value as 50Hz, and H representing the equivalent inertia of the power system, wherein the value is issued to the wind power plant integrated controller through a power system dispatching center;
step 1-2, calculating an active power reference value of the wind power plant at each power setting time point, wherein the formula is as follows:
Figure BDA0003450986070000081
wherein, Pref(t) represents an active power reference value at the tth power setting time point of the wind farm,
Figure BDA0003450986070000082
representing the active power when the wind power plant does not participate in frequency modulation;
1-3, alternately calculating a fan rotating speed predicted value and a fan active power reference value of each power setting time point according to the following steps:
step 1-3-1, calculating a predicted value of the rotating speed of the fan at the tth power setting time point, wherein a formula is as follows:
Figure BDA0003450986070000083
wherein, ω isi,ref(t) the predicted value of the rotation speed of the ith fan at the t-th power setting time point, JiRepresenting the moment of inertia of the ith fan, obtained from a fan design Manual, Pi,ref(t-1) the ith active power reference value, P, of the ith fan at the t-1 th power setting time pointi,m,ref(t-1) prediction of input wind power of ith fan representing t-1 power setting time pointThe value, the calculation formula is as follows:
Figure BDA0003450986070000084
wherein ρ represents air density, R represents fan blade radius, and v representswRepresentative of wind farm wind speed, Ci,ref(t-1) the predicted value of the wind energy capturing coefficient of the ith fan at the t-1 th power setting time point is represented by the following formula:
Figure BDA0003450986070000091
wherein, ω isi,refAnd (t-1) representing the predicted value of the rotation speed of the ith fan at the t-1 th power setting time point, and beta representing the pitch angle of the fan.
Step 1-3-2, calculating the predicted value of the energy state of each fan at the tth power setting time point, wherein the formula is as follows:
Figure BDA0003450986070000092
wherein, SOEi,ref(t) the ith predicted value of the energy state of the wind turbine, ω, at the tth power setting time pointmaxAnd omegaminRespectively representing the upper limit value and the lower limit value of the rotating speed of the fan;
1-3-3, calculating the active power reference value of each fan at the tth power setting time point, wherein the formula is as follows:
Figure BDA0003450986070000093
step 1-3-4, returning to step 1-3-1 until the centralized predictive control period TWFFinishing the calculation of the predicted values of the rotating speed of each fan and the reference values of the active power of the fans at the time points of setting all internal power;
step 1-4, the control period T is predicted in a centralized mannerWFWind power plant active power with internal power set time pointsPower reference value Pref(t) and active power reference value P of each fani,ref(t) sending the data to the fan controllers of all the nodes;
step 1-5, reaching the centralized prediction control period TWFReturning to the step 1-1 and restarting timing;
step 2, the fan controllers of all nodes receive the wind power plant active power reference value P issued by the wind power plant centralized controllerref(t) and active power reference value P of each fani,ref(T) setting time intervals T at corresponding powerrefAt a time interval TWTPerforming real-time correction control, TWTThe value can be selected to be 100 milliseconds, and the specific execution flow is as follows:
step 2-1, setting the starting step of real-time correction control as k equal to 0;
step 2-2, calculating an energy state distribution index x of the ith fan in the kth real-time correction control according to the active power output and the actual rotating speed of the corresponding fan in the kth real-time correction control stepi(k) The calculation formula is as follows:
Figure BDA0003450986070000101
wherein, Pi(k) Represents the active power output, omega, of the ith fan in the kth real-time correction control stepi(k) Representing the actual speed, P, of the ith fan of the kth real-time correction control stepi,m(k) Representing the input wind power of the ith fan in the kth real-time correction control step, and the calculation formula is as follows:
Figure BDA0003450986070000102
wherein, Ci(k) Representing the wind energy capture coefficient of the ith fan in the kth real-time correction control step, and the calculation formula is as follows:
Figure BDA0003450986070000103
step 2-3, electrically connecting any two adjacent fans in the wind power plant, and exchanging the energy state distribution index x by the corresponding fan controllersi(k)；
Step 2-4, calculating a second-order gradient H of the kth real-time correction control step of the ith fani(k) The calculation formula is as follows:
Figure BDA0003450986070000104
wherein, K1、K2And K3Penalty coefficients respectively representing the active power deviation of the corresponding wind field, the active power deviation of the fans and the power distribution deviation among the fans can be selected to be 1, N (i) represents a fan set adjacent to the ith fan in electrical connection;
step 2-5, calculating the first-order Jacobian gradient g of the kth real-time correction control step of the ith fani(k) The calculation formula is as follows:
Figure BDA0003450986070000111
step 2-6, calculating the iteration direction d of the kth real-time correction control step of the ith fani(k) The calculation formula is as follows:
di(k)＝-Hi(k)-1·gi(k) (13)
step 2-7, calculating an energy state distribution index x of the (k +1) th real-time correction control step of the ith fani(k +1), the calculation formula is as follows:
xi(k+1)＝xi(k)+ε·di(k) (14)
wherein epsilon is an iteration step length, and the value range can be set to be 0.01-0.1.
Step 2-8, calculating the active power set value P of the fan in the (k +1) th real-time correction control step of the ith fani(k +1), the calculation formula is as follows:
Figure BDA0003450986070000112
2-9, setting a value P according to the active poweri(k +1) controlling the active power output of the fan;
step 2-10, achieving real-time correction control interval TWTAnd (4) enabling the real-time correction control step k to be k +1, returning to the step 2-2, and restarting timing.
In conclusion, the invention fully utilizes the energy stored in the fan blades of the wind power plant and the fan adjusting capacity to control the active power output by the fan, so that the total active power of the wind power plant can be quickly adjusted, and the active power response is provided according to the frequency change of the power system, thereby ensuring the safe operation of the power system. The invention is characterized in that a double-layer control architecture is adopted, a wind power plant centralized controller utilizes centralized communication to collect the running state of each fan, predicts the frequency of a power system and the future state of each fan, adopts a poor centralized prediction control period, obtains the active power reference value of each wind power plant and each fan by rolling calculation, and sends the obtained result to each fan controller, each fan controller enables the wind power plant and each fan to track the active power reference value by distributed communication and real-time correction control according to the influence possibly caused by the inaccuracy of model parameters and the change of wind speed on the control effect of the centralized controller, and ensures the running safety of each fan.

Claims (1)

1. A wind power plant double-layer frequency control method considering fan power optimal distribution is characterized by comprising the following steps:
step 1, calculating by a wind power plant centralized controller to obtain a centralized prediction control period TWFSetting the active power reference value of the wind power plant and the active power reference value of each fan at a time point of each power, and issuing the active power reference values to each fan controller, wherein the specific execution flow is as follows:
step 1-1, in the centralized predictive control period TWFIn the method, a prediction model of each power setting time point frequency of the power system is defined as follows:
Figure FDA0003450986060000011
wherein t represents the serial number of the power setting time point, zero clearing is carried out at the beginning of each centralized prediction control period, f (t) represents the prediction frequency of the t-th power setting time point, f (t +1) represents the prediction frequency of the t + 1-th power setting time point, and KfAnd KinDroop coefficient and inertia coefficient respectively representing wind power plant participating in frequency modulation, f*Representing the rated frequency of the power system, and H represents the equivalent inertia of the power system;
step 1-2, calculating an active power reference value of the wind power plant at each power setting time point, wherein the formula is as follows:
Figure FDA0003450986060000012
wherein, Pref(t) represents an active power reference value at the tth power setting time point of the wind farm,
Figure FDA0003450986060000013
representing the active power when the wind power plant does not participate in frequency modulation;
1-3, alternately calculating a fan rotating speed predicted value and a fan active power reference value of each power setting time point according to the following steps:
step 1-3-1, calculating a predicted value of the rotating speed of the fan at the tth power setting time point, wherein a formula is as follows:
Figure FDA0003450986060000014
wherein, ω isi,ref(t) the predicted value of the rotation speed of the ith fan at the t-th power setting time point, JiRepresenting the moment of inertia, P, of the ith fani,ref(t-1) the active power parameter of the ith fan at the t-1 th power setting time point is representedExamination value, Pi,m,ref(t-1) represents the predicted value of the input wind power of the ith fan at the t-1 th power setting time point, and the calculation formula is as follows:
Figure FDA0003450986060000021
wherein ρ represents air density, R represents fan blade radius, and v representswRepresenting wind speed of the wind farm, Ci,ref(t-1) the predicted value of the wind energy capturing coefficient of the ith fan at the t-1 th power setting time point is represented by the following formula:
Figure FDA0003450986060000022
wherein, ω isi,ref(t-1) representing the predicted value of the rotating speed of the ith fan at the t-1 th power setting time point, and beta representing the pitch angle of the fan;
step 1-3-2, calculating the predicted value of the energy state of each fan at the tth power setting time point, wherein the formula is as follows:
Figure FDA0003450986060000023
wherein, SOEi,ref(t) the ith predicted value of the energy state of the wind turbine, ω, at the tth power setting time pointmaxAnd ωminRespectively representing the upper limit value and the lower limit value of the rotating speed of the fan;
1-3-3, calculating the active power reference value of each fan at the tth power setting time point, wherein the formula is as follows:
Figure FDA0003450986060000024
step 1-3-4, returning to step 1-3-1 until the centralized predictive control period TWFAll fan rotating speed predicted values and fan active power of internal all-power set time pointsFinishing the calculation of the power reference value;
step 1-4, the control period T is predicted in a centralized mannerWFWind power plant active power reference value P of each power setting time pointref(t) and active power reference value P of each fani,ref(t) sending the data to the fan controllers of the nodes;
step 1-5, reaching the centralized prediction control period TWFReturning to the step 1-1 and restarting timing;
step 2, the fan controllers of all nodes receive the wind power plant active power reference value P issued by the wind power plant centralized controllerref(t) and active power reference value P of each fani,ref(T) setting time intervals T at corresponding powerrefAt a time interval TWTAnd performing real-time correction control, wherein the specific execution flow is as follows:
step 2-1, setting the starting step of real-time correction control as k equal to 0;
step 2-2, calculating an energy state distribution index x of the ith fan in the kth real-time correction control according to the active power output and the actual rotating speed of the corresponding fan in the kth real-time correction control stepi(k) The calculation formula is as follows:
Figure FDA0003450986060000031
wherein, Pi(k) Represents the active power output, omega, of the ith fan in the kth real-time correction control stepi(k) Representing the actual speed, P, of the ith fan of the kth real-time correction control stepi,m(k) Representing the input wind power of the ith fan in the kth real-time correction control step, and the calculation formula is as follows:
Figure FDA0003450986060000032
wherein, Ci(k) Representing the wind energy capture coefficient of the ith fan in the kth real-time correction control step, and the calculation formula is as follows:
Figure FDA0003450986060000033
step 2-3, any two adjacent fans are electrically connected in the wind power plant, and the corresponding fan controllers exchange energy state distribution indexes xi(k)；
Step 2-4, calculating a second-order gradient H of the kth real-time correction control step of the ith fani(k) The calculation formula is as follows:
Figure FDA0003450986060000041
wherein, K1、K2And K3Penalty coefficients respectively representing the active power deviation of the corresponding wind field, the active power deviation of the fans and the power distribution deviation among the fans can be selected to be 1, N (i) represents a fan set adjacent to the ith fan in electrical connection;
2-5, calculating the first-order Jacobian gradient g of the kth real-time correction control step of the ith fani(k) The calculation formula is as follows:
Figure FDA0003450986060000042
step 2-6, calculating the iteration direction d of the kth real-time correction control step of the ith fani(k) The calculation formula is as follows:
di(k)＝-Hi(k)-1·gi(k) (13)
step 2-7, calculating an energy state distribution index x of the (k +1) th real-time correction control step of the ith fani(k +1), the calculation formula is as follows:
xi(k+1)＝xi(k)+ε·di(k) (14)
wherein epsilon is an iteration step length, and the value range can be set to be 0.01-0.1.
Step 2-8, calculating the active power set value P of the fan in the (k +1) th real-time correction control step of the ith fani(k +1), the calculation formula is as follows:
Figure FDA0003450986060000043
2-9, according to the active power set value Pi(k +1) controlling the active power output of the fan;
step 2-10, achieving real-time correction control interval TWTAnd (4) enabling the real-time correction control step k to be k +1, returning to the step 2-2, and restarting timing.
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