CN107979112B - Fan control method, system, terminal and readable storage medium - Google Patents
Fan control method, system, terminal and readable storage medium Download PDFInfo
- Publication number
- CN107979112B CN107979112B CN201711235449.6A CN201711235449A CN107979112B CN 107979112 B CN107979112 B CN 107979112B CN 201711235449 A CN201711235449 A CN 201711235449A CN 107979112 B CN107979112 B CN 107979112B
- Authority
- CN
- China
- Prior art keywords
- fan
- power
- output value
- moment
- current
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 58
- 238000003860 storage Methods 0.000 title claims abstract description 14
- 238000012545 processing Methods 0.000 claims description 37
- 230000015654 memory Effects 0.000 claims description 29
- 230000006870 function Effects 0.000 claims description 21
- 230000001052 transient effect Effects 0.000 claims description 20
- 238000004422 calculation algorithm Methods 0.000 claims description 11
- 230000008859 change Effects 0.000 claims description 9
- 238000013461 design Methods 0.000 claims description 6
- 238000010586 diagram Methods 0.000 description 15
- 238000004891 communication Methods 0.000 description 8
- 238000004590 computer program Methods 0.000 description 7
- 238000005457 optimization Methods 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 238000004088 simulation Methods 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 230000006399 behavior Effects 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 238000004146 energy storage Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000013178 mathematical model Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 240000006829 Ficus sundaica Species 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000002068 genetic effect Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
Images
Classifications
-
- H02J3/386—
-
- 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]
-
- 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
Landscapes
- Wind Motors (AREA)
Abstract
The invention provides a fan control method, a fan control system, a terminal and a readable storage medium, wherein the method comprises the following steps: collecting system parameters of the whole wind power plant transmitted to a power grid at the current moment, working state information of each fan at the current moment and rated frequency of the system; outputting the fan output value of each fan at the next moment according to the system parameters at the current moment, the working state information at the current moment and the rated frequency of the system; outputting the power output value of each fan at the next moment according to the fan output value; and controlling the working state of each fan at the next moment according to the power output value. According to the control method, when the system frequency changes, the optimal output value and the optimal power output of each fan are determined according to the working state information of each fan, so that each fan can participate in the adjustment of the system, the primary frequency modulation of the system is met, the stability of the whole system is ensured, and the control accuracy of the fans is improved.
Description
Technical Field
The invention relates to the technical field of flexible direct current power transmission, in particular to a fan control method, a fan control system, a fan control terminal and a readable storage medium.
Background
In the initial development stage of wind power, due to small scale, research on the wind power is mainly focused on modeling of a single wind turbine and reducing the order of a single model. With the increase of types of wind generation sets and the continuous expansion of the scale of wind power plants, people pay attention to modeling of the whole wind power plant. The modeling ideas of the large wind power plant are divided into two types, one type adopts a detailed model, and the other type adopts an equivalent model. The detailed model is a high-order mathematical model, which is added to a power system by regarding a wind power plant as a plurality of small-capacity generators, step-up transformers and a large number of connecting lines, not only increases the order of the power system, but also increases the time of load flow calculation, especially the time required by time domain simulation, and simultaneously causes a plurality of serious problems, such as the validity of the model, the correction of data and the like. Based on the above, an equivalent model is proposed to describe various dynamic behaviors of a large wind farm, and the model is researched by considering the wind farm as a whole from the influence of the whole wind farm on a power grid.
The existing wind power plant model is divided into a wind speed-wind power relation modeling, a steady-state load flow calculation model, a dynamic model, a transient model and the like according to application scenes and functions on the basis of fan modeling. When a large amount of wind power is connected to the system, the control of the power system becomes more and more important. The large-scale wind power plant dynamic model is mainly used for researching the dynamic behavior of the wind power plant under the condition of wind speed fluctuation or power grid fault, and can also be used for researching the influence of the wind power plant on the dynamic steady state of the power grid. The wind power plant dynamic model mainly adopts a simplified equivalent model and is divided into a single-machine equivalent method and a multi-machine equivalent method.
The most common method in the single-machine equivalent method is to equate all generators in the wind power plant into one, take the sum of the mechanical power of a single unit as the mechanical power input of the equivalent generator, focus on the research of parameter optimization, and determine the parameters or control parameters of the equivalent wind turbine by applying optimization algorithms such as a least square method, a genetic algorithm, a simplex method and the like so as to accurately simulate the whole dynamic process of the wind power plant. The multimachine equivalence method mainly performs clustering division on wind turbine groups in a wind power plant, and the idea of the multimachine equivalence method is derived from a homodyne equivalence method in dynamic equivalence of a power system. In the homodyne equivalence method, the cluster is divided according to the difference of the power angles of the generators in the dynamic process. The wind turbine generator set does not have a so-called power angle, so that the research mainly defines the clustering index of the wind turbine generator set, and clusters and partitions the wind turbine generator set according to the difference of index values, so that each wind turbine generator set can be equivalent to one wind turbine.
The most common method in multi-machine equivalence is to classify and aggregate the fans according to indexes such as wind speed, arrangement position, wake effect or characteristic root of a mechanical transient mathematical model equation set. The physical concepts of the methods are clear, but the methods have self limitations, for example, when modeling is carried out according to the arrangement positions of the fans, the same exhaust fan is often equivalent to one wind turbine, and in an actual wind power plant, even the same exhaust fan can have larger wind speed difference; the characteristic root is taken as a clustering basis, and the equivalent model is usually only suitable for small interference analysis; these all result in a low accuracy of the fan control.
Disclosure of Invention
Therefore, the technical problem to be solved by the invention is to overcome the defect that the control of the fan in the prior art is not accurate enough.
Therefore, the invention provides the following technical scheme:
in a first aspect of the present invention, a method for controlling a fan is provided, which includes the following steps: collecting system parameters of the whole wind power plant transmitted to a power grid at the current moment, working state information of each fan in the wind power plant at the current moment and rated frequency of the system; outputting the fan output value of each fan at the next moment according to the current moment system parameters, the current moment working state information and the system rated frequency; outputting the power output value of each fan at the next moment according to the fan output value of each fan at the next moment; and controlling the working state of each fan at the next moment according to the power output value of each fan at the next moment.
Optionally, the system parameter comprises a system power output value and a system frequency output value.
Optionally, the operating state information includes a wind turbine rotor angular speed, a wind turbine final angular speed, a pitch angle speed, a linear speed of a wind speed, and a tip speed ratio.
Optionally, the working state of each fan at the next moment is controlled according to the maximum power tracking algorithm, and the working state at the next moment is the optimal output power state of the fan under the maximum power tracking algorithm.
Optionally, the step of outputting the fan output value of each fan at the next moment according to the current moment system parameter, the current moment operating state information, and the system rated frequency includes: establishing a wind power plant model of the whole wind power plant; and inputting the current-time system parameters, the current-time working state information and the system rated frequency into the wind power plant model for processing to obtain the fan output value of each fan at the next time.
Optionally, obtaining the fan output value at the next moment by making an objective function to obtain an optimal value, and then determining the fan optimal power output,
ui(k+1)＝f[gmin|yi(k+1)-y*|，ui(k)]
wherein u isi(k +1) is a fan output value at the next moment of the ith fan; u. ofi(k) The current fan output value of the ith fan at the current moment is obtained; y isi(k +1) is the system frequency of the ith fan at the next moment; y is*The system nominal frequency.
Optionally, the step of outputting the power output value of each fan at the next moment according to the fan output value of each fan at the next moment includes: establishing a transient model of each fan; and inputting the fan output value of the next moment into the transient model for processing to obtain the power output value of each fan at the next moment.
Alternatively, the transient model is obtained by the following formula,
wherein i is the ith fan; j. the design is a squarerIs the rotational inertia of the fan motor; j. the design is a squaregIs the rotational inertia of the fan impeller; pa，iThe power of the fan of the ith fan at the current moment; omegar，iThe speed of a fan rotor of the ith fan at the current moment; omegag，iThe final fan angular speed of the ith fan at the current moment;
the fan rotor speed of the ith fan at the next moment;
the final fan angular speed of the ith fan at the next moment; mu is an integral coefficient of a fan model PI controller; k is a proportional coefficient of the fan model PI controller; thetad，iThe pitch angle speed of the ith fan at the current moment;
the pitch angle speed of the ith fan at the next moment; ρ is the air density; r is the fan blade radius; v. ofiThe linear velocity is the linear velocity of the wind speed of the ith fan at the current moment;
the wind energy utilization rate of the ith fan at the current moment is a function of the blade tip speed ratio and the pitch angle.
In a second aspect of the present invention, a fan control system is provided, including: the system comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for acquiring current-time system parameters transmitted to a power grid by a whole wind power plant, current-time working state information of each fan in the wind power plant and system rated frequency; the first processing module is used for outputting a fan output value of each fan at the next moment according to the current moment system parameter, the current moment working state information and the system rated frequency; the second processing module is used for outputting the power output value of each fan at the next moment according to the fan output value of each fan at the next moment; and the third processing module is used for controlling the working state of each fan at the next moment according to the power output value of each fan at the next moment.
Optionally, the first processing module includes: the first processing unit is used for establishing a wind power plant model of the whole wind power plant; and the second processing unit is used for inputting the current-time system parameters, the current-time working state information and the system rated frequency into the wind power plant model for processing to obtain the fan output value of each fan at the next time.
Optionally, the second processing module includes: the third processing unit is used for establishing a transient model of each fan; and the fourth processing unit is used for inputting the fan output value at the next moment into the transient model for processing to obtain the power output value of each fan at the next moment.
In a third aspect of the present invention, a terminal is provided, which includes: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method of any one of the first aspects of the invention.
In a fourth aspect of the invention, there is provided a computer readable storage medium having stored thereon computer instructions which, when executed by a processor, carry out the steps of the method according to any one of the first aspect of the invention.
The technical scheme of the invention has the following advantages:
the invention provides a fan control method, a fan control system, a terminal and a readable storage medium, wherein the method comprises the following steps: collecting system parameters of the whole wind power plant transmitted to a power grid at the current moment, working state information of each fan in the wind power plant at the current moment and rated frequency of the system; outputting the fan output value of each fan at the next moment according to the current moment system parameters, the current moment working state information and the system rated frequency; outputting the power output value of each fan at the next moment according to the fan output value of each fan at the next moment; and controlling the working state of each fan at the next moment according to the power output value of each fan at the next moment. According to the control method, when the system frequency changes, the optimal output value and the optimal power output of each fan are determined according to the working state information of each fan, so that each fan can participate in the adjustment of the system, the primary frequency modulation of the system is met, the stability of the whole system is ensured, and the control accuracy of the fans is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a specific example of a fan control method according to an embodiment of the present invention;
FIG. 2 is a flow chart of another specific example of a fan control method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a specific example of a transient model of wind farm wind turbines in an embodiment of the present invention;
FIG. 4 is a schematic diagram of a particular example of a wind turbine control model in an embodiment of the present invention;
FIG. 5 is a schematic diagram of the effect of a wind turbine generator on primary frequency modulation under overload conditions in an embodiment of the present invention;
FIG. 6 is a schematic illustration of the power transfer capacity of a wind turbine generator set during an overload condition in an embodiment of the present invention;
FIG. 7 is a block diagram of a particular example of a fan control system in an embodiment of the present disclosure;
fig. 8 is a schematic structural diagram of a terminal in an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," "third" and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; the two elements may be directly connected or indirectly connected through an intermediate medium, or may be communicated with each other inside the two elements, or may be wirelessly connected or wired connected. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The embodiment provides a fan control method, and a flow chart is shown in fig. 1. As a preferred embodiment, the flow chart is shown in fig. 2, and includes the following steps:
s1: and acquiring current-time system parameters transmitted to a power grid by the whole wind power plant, current-time working state information of each fan in the wind power plant and system rated frequency. In this embodiment, the current time system parameter includes a current time system power output value and a current time system frequency output value; of course, in other embodiments, the system parameters at the current moment may also include other parameters, such as voltage fluctuation, harmonic parameters, etc., and may be set reasonably as needed. In this embodiment, the current-time working state information includes a current-time fan rotor angular velocity, a current-time fan final angular velocity, a current-time pitch angle velocity, a current-time linear velocity of the wind speed, and a current-time tip speed ratio; of course, in other embodiments, the operating state information may also include other information, such as voltage, current, harmonic analysis, reactive compensation, etc., and may be set as appropriate as needed. In the embodiment, the rated frequency of the system is set as 50Hz of power frequency; of course, in other embodiments, the system rated frequency may be set to other values, such as 48Hz, 60Hz, etc., as appropriate.
S2: and outputting the fan output value of each fan at the next moment according to the system parameters at the current moment, the working state information at the current moment and the rated frequency of the system.
In the present embodiment, as shown in fig. 2, the step S2 specifically includes steps S21-S22:
s21: and establishing a wind power plant model of the whole wind power plant. In this embodiment, the Model Predictive Control (MPC) is used to establish an MPC Model in the wind farm Model, specifically, a wind farm power allocation algorithm is used; certainly, in other embodiments, the MPC model may also be established by using other power distribution algorithms, such as a wind power prediction-based wind farm hybrid energy storage capacity multi-objective optimization configuration method, and the like, and may be reasonably set as needed; the wind power plant model can also be other models, such as a distributed new energy system model with energy storage, and the like, and can be reasonably set according to needs.
The MPC control is an output power tracking problem, and the control principle is as follows: the relationship between the state quantity, the input quantity and the output quantity of the discrete MPC controller can be expressed as:
x(i+1)＝Ax(i)+Bu(i)+Md(i)
y(i)＝Cx(i)+Du(i)
wherein x (i +1) is the system state quantity at the next moment; x (i) is the system state quantity at the current moment; y (i) is the system output quantity at the current moment; u (i) is the system input quantity at the current moment; d (i) is the system disturbance amount at the current moment; a is a system state variable coefficient in the MPC state equation; b is a system state input quantity coefficient in the MPC state equation; c is a correlation coefficient of the system output quantity and the system state quantity; d is a correlation coefficient of the system output quantity and the system input quantity; and M is the system disturbance quantity coefficient at the current moment. According to the formula, the system state quantity at the next moment can be obtained according to the system input variable at the current moment and the system state quantity at the current moment, then the output quantity at the next moment can be obtained according to the system state quantity at the next moment, and the system input variable has the function of enabling the output variable to track the reference value of the output variable.
S22: and inputting the current-time system parameters, the current-time working state information and the system rated frequency into the wind power plant model for processing to obtain the fan output value of each fan at the next time.
The relationship between the primary frequency, i.e. frequency f(s), and power p(s) of the power system can be expressed as:
wherein, Δ f is the frequency change of the power system; delta P is a power system power change value; tau is a system first order differential coefficient; k is a radical offIs the first-order integral coefficient of the system; omeganSynchronizing generator angular speed for the power system; δ is the power factor angle.
With the MPC model, the above formula can be written as a form of mathematical expression of the MPC model,
wherein Δ f is the system state output, here representing the power system frequency change; a is1Is a system state variable factor; x is the number offIs a system state variable; b1Is a power system power variation factor; delta P is a power system power change value; a is0Is a system state variable factor in an initial state; b0The power system power variation factor in the initial state.
The MPC control is applied to this embodiment, where u (i) is the system input quantity at the current time corresponding to the current-time output power of each fan, y (i +1) is the system output quantity at the next time corresponding to the system frequency at the next time, and x (i) is the system state quantity at the current time corresponding to the system power output value at the current time of the wind farm, that is, the total power of the wind farm.
In the embodiment, the fan output value at the next moment is obtained by making the following objective function obtain the optimal value, and then the optimal power output of the fan is determined,
ui(k+1)＝f[gmin|yi(k+1)-y*|，ui(k)]
wherein u isi(k +1) is a fan output value at the next moment of the ith fan; u. ofi(k) The current fan output value of the ith fan at the current moment is obtained; y isi(k +1) is the system frequency of the ith fan at the next moment; y is*The system nominal frequency. Of course, in other embodiments, the fan output value at the next moment can be obtained by other formulas, and the core is to select a suitable input quantity to make the output quantity y (k) and the reference value y0(k) Has the smallest deviation, i.e. the cost function is optimal, and the cost function is Δ y (k) ═ y (k) — y0(k) Wherein y (k) represents the system frequency, y0(k) And the rated frequency is represented and reasonably set according to needs.
S3: and outputting the power output value of each fan at the next moment according to the fan output value of each fan at the next moment.
In the present embodiment, as shown in fig. 2, the step S3 specifically includes steps S31-S32:
s31: and establishing a transient model of each fan. In this embodiment, the control method of the transient model of the wind turbine is Maximum Power Tracking (MPT) control; of course, in other embodiments, the transient model of the wind turbine may also be other model control methods, such as model algorithm control, dynamic matrix control, and the like, and may be set reasonably as needed. Transient models are shown in fig. 3, including synchronous generator, generator side converter, grid side converter, medium/low voltage transformer and medium voltage system, wind turbine model, aerodynamic model, power model, maximum power tracker, pitch angle control and converter control.
A wind power model: the simulation step length is 5s and real measurement data are adopted, the data are processed in a statistical mode and are transmitted to different fans after spline interpolation; an aerodynamic model: calculating mechanical torque considering factors such as wind speed, pitch angle and angular speed; a dynamic model: the model represents a generator rotor and is gambled in terms of both system complexity and compliance with the overall control system; a maximum power tracker: inputting active power to a power grid side converter, wherein the power is obtained from a lookup table drawn according to corresponding maximum power output of a generator at different speeds; pitch angle control: the angular speed of the rotor is limited, the output power is ensured to be within a normal range, and the effectiveness of the dynamic characteristics of the blades is improved; controlling a converter: the converter on the generator side controls the direct current side voltage and the generator bus side voltage, and the converter on the grid side controls the active power and the reactive power flowing to the grid. The determination of the active power in the normal operating state comes from the maximum power tracker (which also functions as frequency support). In this embodiment, the voltage support of the system by the wind turbine is not taken into account, and thus the reactive power input is also set to zero.
Considering a wind farm with N wind turbines, each comprising a turbine, a generator and a converter, the transient model is obtained by the following formula,
wherein i is the ith fan; j. the design is a squarerIs the rotational inertia of the fan motor; j. the design is a squaregIs the rotational inertia of the fan impeller; pa，iThe power of the fan of the ith fan at the current moment; omegar，iThe speed of a fan rotor of the ith fan at the current moment; omegag，iThe final fan angular speed of the ith fan at the current moment;
the fan rotor speed of the ith fan at the next moment;
the final fan angular speed of the ith fan at the next moment; mu is an integral coefficient of a fan model PI controller; k is a proportional coefficient of the fan model PI controller; thetad，iThe pitch angle speed of the ith fan at the current moment;
the pitch angle speed of the ith fan at the next moment.
The relationship between the power and the wind speed of each fan is obtained by the following formula,
wherein, Pa，iThe power of the fan of the ith fan at the current moment; ρ is the air density; r is the fan blade radius; v. ofiThe linear velocity is the linear velocity of the wind speed of the ith fan at the current moment; cp(βi，λi) The current time is the wind energy utilization rate of the ith fan, namelyTip speed ratio and pitch angle.
S32: and inputting the output value of the fan at the next moment into the transient model for processing to obtain the power output value of each fan at the next moment.
S4: and controlling the working state of each fan at the next moment according to the power output value of each fan at the next moment. In this embodiment, in order to optimize the total output power of the wind farm, the operating state of each wind turbine at the next moment is controlled under the maximum power tracking algorithm, and the operating state at the next moment is the optimal power output state of a single wind turbine, which can minimize the objective function.
Due to the linear relationship between the frequency variation and the power variation, the cost function can be set to optimize the frequency variation under the condition that the frequency variation is not more than the system limit, namely, the total output power of the wind power plant is optimized, namely
Wherein, Pg，iThe total output power of the wind power plant; omegag，iThe final fan angular velocity; u. ofiThe output power of a single fan in the MPC wind power plant model is used as an input system state variable;
and the total output power reference value of the wind power plant. When the frequency changes, the power of each local wind power plant can be controlled, the condition that the maximum power tracking is met under the wind speed is determined, the total output power of the wind power plant is optimal, and then the primary frequency modulation of a power grid is completed.
According to the fan control method, when the system frequency changes, the optimal output value and the optimal power output of each fan are determined according to the working state information of each fan, so that each fan can participate in the adjustment of the system, the primary frequency modulation of the system is met, the stability of the whole system is ensured, and the control accuracy of the fans is improved.
The control method provided by the invention is a control technology based on a model, and achieves the function of primary frequency modulation of the whole power system by optimizing the output of each fan of the wind power plant. As shown in fig. 4, the control method is proposed based on a kalman filter and a model predictive control technique, wherein the kalman filter is used to estimate the wind speed, which also introduces a core control of the system based on the optimal control of each fan, and by minimizing a cost function including the boundary condition limit of the system, the optimal working area of each fan can be found and the implementation of the primary frequency modulation function of the system can be satisfied.
The control method comprises the following steps: 1) regarding the whole wind farm as a whole, as shown in fig. 4, the Control method includes a core Controller (MPC Controller) and a core kalman filter (Central KF), wherein the core Controller includes a plurality of local kalman filters (local KFs) and a maximum power tracking Control (MPT), and each local kalman filter controls a wind turbine; 2) with the adoption of wind energy, wind farms are increasingly required to meet different requirements of the system, including the control of active power, and an effective value of the active power is distributed to each wind turbine (as an input quantity) through a core controller according to a wind farm control algorithm; 3) the core controller receives rotor angular velocity measurements, pitch angle angles and deviations (variations) in system frequency and power values delivered to the grid by the entire wind farm. The pitch angle control is independently controlled by a PI controller, which enables the angular speed and the active power to be controlled within a normal range; 4) the control method of the local fan and the local Kalman filter is maximum power tracking, so that the power transmitted to the power grid at a specific rotating speed is an optimal value. Under the condition of normal operation, the core controller is not put into use, the core controller inputs a power reference value for each fan, and the power reference value can be correspondingly changed when in failure; 5) when the system frequency changes, the variable quantity of the input quantity is determined according to the maximum power tracking signal so as to meet the primary frequency modulation of the system. And then, the input signals are transmitted to each local fan according to the calculation result of the wind speed, and the stability of the whole system needs to be ensured. The control strategy can realize that each fan can participate in the regulation of the system disturbance when the system is disturbed. When a large amount of wind power is connected to the system, the control of the power system becomes more and more important. On the other hand, when the system is disturbed and the frequency is too low or too high, the wind power plant can also adjust the system frequency by sending out active power. A model-based optimization control is studied, which utilizes a model predictive control system and effectively combines the judgment of wind conditions to define the influence of the fan on the system frequency control. Different technologies such as a Kalman Filter (KF) and a Model Predictive Control (MPC) are combined to predict the load change of the power system and an actual wind speed range determined by tracking the angle of each fan pitch angle so as to find out the optimal working point of each fan, and then the fan is enabled to adjust the system frequency and reduce the change of the system frequency under the condition of not touching the working limit. The core Kalman filter is used for judging the change of external load, and the local Kalman filter is used for estimating the wind speed and evaluating the transient characteristic of the wind turbine. How the fans in the wind power plant are coupled and coordinated and the output of active power is controlled can be further analyzed through the fan control model shown in fig. 4, so as to improve the influence of disturbance or fault on the system frequency. It can also be seen from fig. 4 that when variables such as wind speed or rotor angular velocity and pitch angle, which cannot be directly measured, occur, the MPC is combined to obtain an estimated value of the above variables and an estimated value of the external power variation by introducing KF, where KF functions to introduce an estimated value whose deviation from the real value can be processed by the system of the KF link when some parameters of the system cannot be directly measured, and finally the error between the estimated value and the real value is within an acceptable range.
The flexibility and the effectiveness of the control method are verified through the simulation condition of the operation of 20 fans, and the stability of the system can still be ensured when the parameters are changed. FIG. 5 is a schematic diagram of the effect of a wind turbine generator set on primary frequency modulation under overload conditions; fig. 6 is a schematic diagram of the power transfer capacity of a wind power plant in an overload situation. As can be seen from fig. 5, the system with coordinated control of the wind farm MPC contributes much less to the primary frequency modulation of the power system than a wind farm without coordinated control between wind turbines when a sudden 50MW overload occurs in the system 30 s. Fig. 6 shows that the wind turbine with the MPC coordination control of the wind farm transmits more power under the overload condition than the wind turbine without the coordination control, and then the wind curtailment rate is reduced.
The embodiment further provides a fan control system, which is used for implementing the implementation manner in the embodiment, and the description of the system is omitted. The term "module" as used below may be a combination of software and/or hardware that implements a predetermined function. While the system described in the embodiments below is preferably implemented in software, implementations in hardware, or a combination of software and hardware are also possible and contemplated.
As shown in fig. 7, in the fan control system provided in this embodiment, a first obtaining module 71 is configured to collect current-time system parameters transmitted to a power grid by a whole wind farm, current-time working state information of each fan in the wind farm, and a system rated frequency; the first processing module 72 is configured to output a fan output value of each fan at a next moment according to the current-moment system parameter, the current-moment working state information, and the system rated frequency; the second processing module 73 is configured to output a power output value of each fan at a next moment according to the fan output value of each fan at the next moment; and the third processing module 74 is configured to control the working state of each fan at the next time according to the power output value of each fan at the next time.
Wherein, the first processing module 72 includes: the first processing unit 721 is configured to establish a wind farm model of the whole wind farm; the second processing unit 722 is configured to input the system parameter at the current time, the working state information at the current time, and the system rated frequency into the wind farm model for processing, so as to obtain a fan output value of each fan at the next time.
The second processing module 73 includes: a third processing unit 731, configured to establish a transient model of each wind turbine; the fourth processing unit 732 is configured to input the fan output value at the next time into the transient model for processing, so as to obtain a power output value of each fan at the next time.
Further functional descriptions of the modules are the same as those of the above embodiments, and are not repeated herein.
The fan control system has the advantage of high control accuracy.
The present embodiment provides a terminal, as shown in fig. 8, including: at least one processor 801, such as a CPU (Central Processing Unit), at least one communication interface 803, memory 804, at least one communication bus 802. Wherein a communication bus 802 is used to enable connective communication between these components. The communication interface 803 may include a Display (Display) and a Keyboard (Keyboard), and the optional communication interface 803 may also include a standard wired interface and a standard wireless interface. The Memory 704 may be a RAM (random Access Memory) or a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The memory 804 may optionally be at least one memory device located remotely from the processor 801 as previously described. Wherein the processor 801 may be in connection with the system described in fig. 7, a set of program codes is stored in the memory 804, and the processor 801 calls the program codes stored in the memory 804 for executing a fan control method, i.e. for executing the fan control method as in the embodiments of fig. 1 and 2.
The communication bus 802 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The communication bus 802 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 8, but this is not intended to represent only one bus or type of bus.
The memory 804 may include a volatile memory (RAM), such as a random-access memory (RAM); the memory may also include a non-volatile memory (english: non-volatile memory), such as a flash memory (english: flash memory), a hard disk (english: hard disk drive, abbreviated: HDD) or a solid-state drive (english: SSD); the memory 804 may also comprise a combination of the above-described types of memory.
The processor 801 may be a Central Processing Unit (CPU), a Network Processor (NP), or a combination of a CPU and an NP.
The processor 801 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a Programmable Logic Device (PLD), or a combination thereof. The PLD may be a Complex Programmable Logic Device (CPLD), a field-programmable gate array (FPGA), a General Array Logic (GAL), or any combination thereof.
Optionally, the memory 804 is also used for storing program instructions. The processor 801 may invoke program instructions to implement the fan control method as shown in the embodiments of fig. 1 and 2 of the present application.
The embodiment of the invention also provides a computer-readable storage medium, wherein computer-executable instructions are stored on the computer-readable storage medium and can execute the fan control method in any method embodiment. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (9)
1. A fan control method is characterized by comprising the following steps:
collecting system parameters of the whole wind power plant transmitted to a power grid at the current moment, working state information of each fan in the wind power plant at the current moment and rated frequency of the system;
outputting the fan output value of each fan at the next moment according to the current moment system parameters, the current moment working state information and the system rated frequency;
outputting the power output value of each fan at the next moment according to the fan output value of each fan at the next moment;
controlling the working state of each fan at the next moment according to the power output value of each fan at the next moment;
controlling the working state of each fan at the next moment according to the maximum power tracking algorithm, wherein the working state at the next moment is the optimal output power state of the fan under the maximum power tracking algorithm, obtaining the output value of the fan at the next moment by enabling the following objective function to obtain the optimal value, namely the system frequency is closest to the rated system frequency, and then determining the optimal power output of the fan,
ui(k+1)＝f[gmin|yi(k+1)-y*|，ui(k)]
wherein u isi(k +1) is a fan output value at the next moment of the ith fan; u. ofi(k) The current fan output value of the ith fan at the current moment is obtained; y isi(k +1) is the system frequency of the ith fan at the next moment; y is*Is the rated frequency of the system;
when the frequency changes, the power of each local wind power plant can be controlled to determine that the maximum power tracking is met under the wind speed, so that the total output power of the wind power plant is optimal, and then primary frequency modulation of a power grid is completed;
the relationship between the primary frequency, i.e. frequency f(s), and power p(s) of the power system can be expressed as:
wherein, Δ f is the frequency change of the power system; the delta P is a power change value of the power system; tau is a system first order differential coefficient; k is a radical offIs the first-order integral coefficient of the system; omeganSynchronizing generator angular speed for the power system; δ is the power factor angle.
2. The wind turbine control method of claim 1, wherein the system parameters include a system power output value and a system frequency output value.
3. The wind turbine control method of claim 1, wherein the operating state information comprises a wind turbine rotor angular speed, a wind turbine final angular speed, a pitch angle speed, a linear speed of wind speed, and a tip speed ratio.
4. The fan control method according to any one of claims 1 to 3, wherein the step of outputting the fan output value of each fan at the next time according to the current-time system parameter, the current-time operating state information, and the system rated frequency comprises:
establishing a wind power plant model of the whole wind power plant;
and inputting the current-time system parameters, the current-time working state information and the system rated frequency into the wind power plant model for processing to obtain the fan output value of each fan at the next time.
5. The fan control method according to any one of claims 1 to 3, wherein the step of outputting the power output value of each fan at the next time according to the fan output value of each fan at the next time comprises:
establishing a transient model of each fan;
and inputting the fan output value of the next moment into the transient model for processing to obtain the power output value of each fan at the next moment.
6. The wind turbine control method of claim 5, wherein the transient model is obtained by the equation,
wherein i is the ith fan; j. the design is a squarerIs the rotational inertia of the fan motor; j. the design is a squaregIs the rotational inertia of the fan impeller; pa,iThe power of the fan of the ith fan at the current moment; omegar,iThe speed of a fan rotor of the ith fan at the current moment; omegag,iThe final fan angular speed of the ith fan at the current moment;
the fan rotor speed of the ith fan at the next moment;
the final fan angular speed of the ith fan at the next moment; mu is an integral coefficient of a fan model PI controller; k is a proportional coefficient of the fan model PI controller; thetad,iThe pitch angle speed of the ith fan at the current moment;
the pitch angle speed of the ith fan at the next moment; ρ is the air density; r is the fan blade radius; v. ofiThe linear velocity is the linear velocity of the wind speed of the ith fan at the current moment; cP(βi,λi) The wind energy utilization rate of the ith fan at the current moment is a function of the blade tip speed ratio and the pitch angle.
7. A fan control system based on the fan control method of any one of claims 1 to 6, the fan control system comprising:
the system comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for acquiring current-time system parameters transmitted to a power grid by a whole wind power plant, current-time working state information of each fan in the wind power plant and system rated frequency;
the first processing module is used for outputting a fan output value of each fan at the next moment according to the current moment system parameter, the current moment working state information and the system rated frequency;
the second processing module is used for outputting the power output value of each fan at the next moment according to the fan output value of each fan at the next moment;
and the third processing module is used for controlling the working state of each fan at the next moment according to the power output value of each fan at the next moment.
8. A terminal, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method of any one of claims 1-6.
9. A computer-readable storage medium having stored thereon computer instructions, which when executed by a processor, perform the steps of the method of any of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711235449.6A CN107979112B (en) | 2017-11-30 | 2017-11-30 | Fan control method, system, terminal and readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711235449.6A CN107979112B (en) | 2017-11-30 | 2017-11-30 | Fan control method, system, terminal and readable storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107979112A CN107979112A (en) | 2018-05-01 |
| CN107979112B true CN107979112B (en) | 2021-08-27 |
Family
ID=62008548
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711235449.6A Active CN107979112B (en) | 2017-11-30 | 2017-11-30 | Fan control method, system, terminal and readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107979112B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108711885A (en) * | 2018-06-05 | 2018-10-26 | 重庆大学 | One kind cooperateing with method of estimation for field of wind-force state |
| CN109343448B (en) * | 2018-09-18 | 2020-09-08 | 国电联合动力技术有限公司 | Programming system and programming method for fan integrated control system |
| CN112529373B (en) * | 2020-11-26 | 2022-04-26 | 国网宁夏电力有限公司电力科学研究院 | Power grid frequency stability evaluation method under simultaneous fault of multiple loops of direct current |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103034764A (en) * | 2012-12-12 | 2013-04-10 | 上海市电力公司 | Modeling and simulation method for doubly-fed variable speed constant frequency wind generation set system |
| CN105048499A (en) * | 2015-07-24 | 2015-11-11 | 中国农业大学 | Wind power integration real-time scheduling method and device based on model prediction and control |
-
2017
- 2017-11-30 CN CN201711235449.6A patent/CN107979112B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103034764A (en) * | 2012-12-12 | 2013-04-10 | 上海市电力公司 | Modeling and simulation method for doubly-fed variable speed constant frequency wind generation set system |
| CN105048499A (en) * | 2015-07-24 | 2015-11-11 | 中国农业大学 | Wind power integration real-time scheduling method and device based on model prediction and control |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107979112A (en) | 2018-05-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109494769B (en) | Wind field participating frequency modulation method and system | |
| US9822765B2 (en) | Wind power plant control system | |
| CN111801493B (en) | Determining control settings for a wind turbine | |
| EP2896099B1 (en) | A method of determining individual set points in a power plant controller, and a power plant controller | |
| CN108475929B (en) | Method for controlling a wind power plant | |
| CN104538980B (en) | Self-balanced quick load-reducing control method for microgrid | |
| CN110829487B (en) | Dynamic frequency prediction method for power system | |
| CN107689638B (en) | Transient coordination control method for wind power-containing power system based on phase trajectory analysis | |
| CN107979112B (en) | Fan control method, system, terminal and readable storage medium | |
| CN107317345A (en) | It is a kind of to be electrolysed the method that type load participates in island network FREQUENCY CONTROL | |
| CN105794067A (en) | A wind power plant with improved rise time | |
| CN113507137B (en) | Wind power plant model construction method based on DigSILENT/PF and related device | |
| CN110492524A (en) | Active-control method for frequency and system without the communication soft direct join net of marine wind electric field | |
| CN109038613A (en) | A kind of adaptive low frequency deloading method counted and wind-powered electricity generation virtual inertia/primary frequency modulation responds | |
| CN110518632B (en) | Quantitative calculation method for weakening power grid inertia by wind power plant grid connection | |
| CN105934862A (en) | Wind farm control having improved target-value jump behavior | |
| CN115833111A (en) | Minimum inertia demand evaluation method, device, system and medium for high-proportion new energy power system | |
| CN115940148A (en) | Minimum inertia requirement evaluation method and device, electronic equipment and storage medium | |
| CN110445171A (en) | A kind of active power and frequency control method and system based on the soft lineal system of marine wind electric field | |
| CN110661270B (en) | Coordination control method for voltage stability of power system containing wind power | |
| CN116845886A (en) | Multi-port autonomous photovoltaic system network construction control method based on model prediction | |
| CN115313499A (en) | Fan frequency control parameter calculation method, device, terminal and medium | |
| CN109657380A (en) | A kind of double-fed fan motor field Dynamic Equivalence based on Extended Kalman filter | |
| CN114421490A (en) | Method for constructing rapid simulation model for wind power participating in power grid frequency support | |
| CN113013913B (en) | Reactive voltage control system and method for wind farm |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP03 | Change of name, title or address |
Address after: 18 Binhe Avenue, future science and Technology City, Changping District, Beijing 102200 Patentee after: State Grid Smart Grid Research Institute Co.,Ltd. Country or region after: China Address before: 102209 18 Riverside Avenue, Changping District science and Technology City, Beijing Patentee before: GLOBAL ENERGY INTERCONNECTION RESEARCH INSTITUTE Co.,Ltd. Country or region before: China |