Resource coordinated control method and system for power system considering distributed units

Abstract

The present disclosure relates to the field of electric power technology, and discloses a resource collaborative control method and system for an electric power system taking into account distributed units. The specific scheme is as follows: based on the bubble movement characteristics and volume characteristics of the hydraulic oil in the pitch system of each wind generator set in the electric power system at the current moment, the bubble content of the hydraulic oil of each wind generator set at the current moment is determined; based on the blade force of each wind generator set at the current moment, the bubble content of the hydraulic oil in its pitch system at the current moment is determined, and the dynamic response characteristics of its pitch system are determined; based on the dynamic response characteristics of the pitch system in each wind generator set, the predicted power generation of each wind generator set is determined; when the predicted power generation of any wind generator set does not meet the preset conditions, the hydraulic oil in the pitch system of the wind generator set is subjected to bubble purification treatment to adjust the power generation of each wind generator set in the electric power system.

Description

Technical Field

[0001] The present disclosure relates to the field of electric power technology, and in particular to a resource collaborative control method, system, electronic device and storage medium for an electric power system taking into account distributed units. Background Art

[0002] In the power system of distributed units, wind turbines are one of the important distributed energy sources. Among them, the hydraulic oil in the variable pitch system of wind turbines is very easy to generate bubbles under high pressure and high-speed flow conditions. The microbubbles in the hydraulic oil will affect the dynamic response characteristics of the hydraulic system, resulting in a decrease in the variable pitch speed and accuracy of the variable pitch system. The higher the bubble content, the greater the compressibility of the hydraulic oil, the lower the system stiffness, the lower the damping ratio, and the dynamic response speed and control accuracy of the hydraulic actuator will deteriorate. In addition, the bubbles burst under high pressure to produce impact loads, accelerating the fatigue failure of hydraulic components. Fluctuations in the bubble content will also cause instability in the dynamic characteristics of the system.

[0003] Since wind turbines are one of the important distributed energy sources in the distributed unit power system, the dynamic response characteristics of the wind turbine pitch system directly affect the active and reactive output of the unit, and thus affect the stability and control performance of the entire power system. Therefore, studying and revealing the intrinsic relationship between the microbubble content of hydraulic oil and the dynamic response of the pitch system is of great significance to improving the control performance and reliability of wind turbines, and is also crucial to achieving resource coordinated control of the distributed unit power system. Summary of the invention

[0004] The present disclosure provides a resource collaborative control method, system, electronic device and storage medium for an electric power system taking into account distributed units, which can solve at least one of the above problems.

[0005] The present disclosure provides a resource collaborative control method for a power system taking into account distributed units, comprising:

[0006] Determine the bubble content of the hydraulic oil in the pitch system of each wind generator set in the power system at the current moment based on the bubble movement characteristics and volume characteristics of the hydraulic oil in the pitch system of each wind generator set at the current moment;

[0007] For each of the wind turbine generator sets, based on the blade force of the wind turbine generator set at the current moment and the bubble content of the hydraulic oil of the pitch system in the wind turbine generator set at the current moment, the dynamic response characteristics of the pitch system in the wind turbine generator set are determined;

[0008] Determining the predicted power generation of each wind turbine generator set based on the dynamic response characteristics of the pitch system in each wind turbine generator set;

[0009] For any of the wind turbine generator sets, when the predicted power generation of the wind turbine generator set does not meet the preset conditions, a bubble purification operation is performed on the hydraulic oil in the variable pitch system of the wind turbine generator set to adjust the power generation of each of the wind turbine generator sets in the power system.

[0010] According to another aspect of the present disclosure, there is provided a resource coordination control system of a power system taking into account distributed units, comprising:

[0011] A bubble content prediction module, for determining the bubble content of the hydraulic oil in the pitch system of each wind turbine in the power system at the current moment based on the bubble movement characteristics and volume characteristics of the hydraulic oil in the pitch system of each wind turbine in the power system at the current moment;

[0012] a response characteristic determination module, for determining the dynamic response characteristics of the variable pitch system in the wind generator set for each wind generator set, based on the blade force of the wind generator set at the current moment and the bubble content of the hydraulic oil of the variable pitch system in the wind generator set at the current moment;

[0013] A power generation determination module, used to determine the predicted power generation of each wind turbine generator set based on the dynamic response characteristics of the pitch system in each wind turbine generator set;

[0014] The power generation adjustment module is used to perform bubble purification operation on the hydraulic oil in the pitch system of any wind turbine generator set when the predicted power generation of the wind turbine generator set does not meet the preset conditions, so as to adjust the power generation of each wind turbine generator set in the power system.

[0015] According to another aspect of the present disclosure, there is provided an electronic device, comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute any resource collaborative control method of the power system taking into account distributed units in the embodiments of the present disclosure.

[0019] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute any resource collaborative control method of an electric power system taking into account distributed units in any embodiment of the present disclosure.

[0020] According to the technical solution disclosed in the present invention, based on the bubble movement characteristics and volume characteristics of the hydraulic oil in the pitch system of each wind generator set in the power system at the current moment, the bubble content of the hydraulic oil in the pitch system of each wind generator set at the current moment is determined; then, for each wind generator set, based on the blade force of the wind generator set at the current moment and the bubble content of the hydraulic oil in the pitch system of the wind generator set at the current moment, the dynamic response characteristics of the pitch system in the wind generator set are determined. Furthermore, based on the dynamic response characteristics of the pitch system in each wind generator set, the predicted power generation of each wind generator set is determined. For any wind generator set, if the predicted power generation of the wind generator set does not meet the preset conditions, the hydraulic oil in the pitch system of the wind generator set is subjected to bubble purification treatment to adjust the power generation of each wind generator set in the power system. In this way, whether the power generation of the wind generator set is affected is predicted by the bubble content of the hydraulic oil, and if it is affected, the hydraulic oil is subjected to bubble purification treatment, thereby realizing the coordinated adjustment of the power generation of the wind generator set. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is a flow chart of a resource cooperative control method of a power system taking into account distributed units according to an embodiment of the present disclosure;

[0022] Figure 2 is a structural block diagram of a resource coordination control system of a power system taking into account distributed units according to an embodiment of the present disclosure;

[0023] Figure 3 is a block diagram of an electronic device for implementing an embodiment of the present disclosure. DETAILED DESCRIPTION

[0024] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0025] Figure 1 It is a flowchart of a resource cooperative control method of an electric power system taking into account distributed units according to an embodiment of the present disclosure.

[0026] like Figure 1 As shown, the control method includes:

[0027] S110, determining the bubble content of the hydraulic oil in the pitch system of each wind turbine generator set at the current moment based on the bubble movement characteristics and volume characteristics of the hydraulic oil in the pitch system of each wind turbine generator set in the power system at the current moment;

[0028] S120, for each wind turbine generator set, determining the dynamic response characteristics of the variable pitch system in the wind turbine generator set based on the blade force of the wind turbine generator set at the current moment and the bubble content of the hydraulic oil of the variable pitch system in the wind turbine generator set at the current moment;

[0029] S130, determining the predicted power generation of each wind turbine generator set based on the dynamic response characteristics of the variable pitch system in each wind turbine generator set;

[0030] S140, for any wind turbine generator set, when the predicted power generation of the wind turbine generator set does not meet the preset conditions, a bubble purification operation is performed on the hydraulic oil in the pitch system of the wind turbine generator set to adjust the power generation of each wind turbine generator set in the power system.

[0031] It is understandable that the power system may include multiple wind turbines, each of which has a pitch system. When the pitch system is working, hydraulic oil is required to assist. However, bubbles will be generated in the hydraulic oil as the pitch system rotates, and these bubbles will also affect the working efficiency of the pitch system, such as the pitch speed and pitch angle.

[0032] It can be understood that a fan composed of multiple blades is provided in the wind turbine generator set. When the blades are subjected to wind force, the fan rotates and drives the variable pitch system to work, thereby driving the magnetic generator to generate electricity, generating magnetic current and voltage.

[0033] Exemplarily, the bubble motion feature may include the bubble motion trajectory, such as information such as the position, velocity, and acceleration of each trajectory point.

[0034] For example, the volume feature may include the average volume of bubbles, the total volume, or may also include the state of bubbles.

[0035] Exemplarily, the dynamic response characteristics may include pitch speed, pitch angle, etc.

[0036] For example, the slower the bubble movement, the less bubble content. The faster the bubble movement, the faster the bubble content. When the bubble movement speed reaches a certain threshold and continues to accelerate, the growth rate of the bubble content slows down.

[0037] Illustratively, the greater the ratio of the total volume of bubbles to the total volume of the hydraulic oil, the greater the bubble content.

[0038] Therefore, the accurate bubble content of hydraulic oil can be predicted based on both the bubble movement characteristics and the volume characteristics.

[0039] For example, a pre-trained model can be used to process the blade force of the wind turbine at the current moment and the hydraulic oil bubble content of the pitch system in the wind turbine at the current moment, so as to obtain the dynamic response characteristics of the pitch system in the wind turbine.

[0040] For example, the pitch speed and pitch angle in the dynamic response characteristics of the pitch system can be used to calculate the generator excitation current and DC bus voltage, and then the power generation power of the wind turbine generator set can be calculated using the two.

[0041] For example, the bubble purification operation for the hydraulic oil in the pitch control system of the wind turbine generator set can be to start the vacuum degassing device and adjust the speed of the vacuum pump through the PID controller to absorb the bubbles of the hydraulic oil in the hydraulic oil circulation pump. The hydraulic oil circulation pump can deliver the purified hydraulic oil to the pitch control system.

[0042] According to the above embodiment, whether the power generation of the wind turbine is affected is predicted by the bubble content of the hydraulic oil, and if affected, the hydraulic oil is subjected to bubble purification operation, thereby achieving coordinated adjustment of the power generation of the wind turbine.

[0043] In one embodiment, based on the bubble movement characteristics and volume characteristics of the hydraulic oil in the pitch system of each wind turbine in the power system at the current moment, the bubble content of the hydraulic oil in the pitch system of each wind turbine in the power system at the current moment is determined, including: performing bubble recognition on the hydraulic oil image of the pitch system at the current moment to determine a first bubble shape distribution, a first bubble total volume and a first hydraulic oil total volume; determining a first bubble content based on a ratio between the first bubble total volume and the first hydraulic oil total volume; determining a first bubble movement feature vector based on the average velocity and acceleration of the bubbles in the hydraulic oil in the pitch system at the current moment, and the first bubble shape distribution; determining a second bubble content corresponding to the first bubble movement feature vector based on a mapping relationship between the bubble content and the bubble movement characteristics; and determining the hydraulic oil bubble content of the pitch system at the current moment from the first bubble content and the second bubble content.

[0044] Exemplarily, a high-speed camera is used to continuously shoot the hydraulic oil of the variable pitch system and record the bubble movement video, the video frames are segmented by an image processing algorithm to extract the bubble contours, the watershed algorithm is used to segment the overlapping bubbles, and the total volume of the bubbles in a single frame image is calculated based on the area of ​​the segmented bubble contours. At the same time, the total volume of the hydraulic oil is calculated to obtain the bubble content data.

[0045] For example, for the bubble motion video acquired by high-speed camera, the three-dimensional reconstruction technology is used to convert the two-dimensional image sequence into the bubble motion trajectory in three-dimensional space, and the Kalman filter algorithm is used to smooth the trajectory to improve the trajectory accuracy and obtain the trajectory data of the three-dimensional coordinates of the bubble center point changing with time.

[0046] Exemplarily, the bubble velocity and acceleration may be calculated based on the bubble motion trajectory data.

[0047] Exemplarily, the bubble shape distribution can be characterized by roundness, for example (roundness 0.8-1).

[0048] Exemplarily, the bubble shape distribution may also include bubble distribution states, for example, classified into uniform distribution, aggregated distribution, and laminar distribution.

[0049] For example, a multiple regression analysis method can be used, and data is used in advance to construct a mapping relationship between bubble content and bubble motion characteristics based on the data. For example, the independent variables are bubble motion characteristics such as speed, acceleration, size and shape, and the dependent variable is bubble content. During the construction process, 10-fold cross validation is used to evaluate model performance, and the root mean square error is 0.002%, and the model parameters with the smallest validation error are selected.

[0050] Exemplarily, either the first bubble content or the second bubble content is selected as the hydraulic oil bubble content of the pitch system at the current moment. Alternatively, the larger one is selected from the first bubble content and the second bubble content as the hydraulic oil bubble content of the pitch system at the current moment.

[0051] Exemplarily, according to the difference between the first bubble content and the second bubble content, the bubble content of the hydraulic oil of the pitch system at the current moment is determined from the first bubble content and the second bubble content. For example, if the difference is greater than the first threshold value, the first bubble content is used as the bubble content of the hydraulic oil of the pitch system at the current moment; if the difference is less than the first threshold value, the second bubble content is used as the bubble content of the hydraulic oil of the pitch system at the current moment.

[0052] According to the above embodiment, the bubble content of the hydraulic oil at the current moment can be accurately calculated by utilizing the bubble movement characteristics and volume characteristics at the current moment.

[0053] In one embodiment, based on the blade force of the wind turbine at the current moment and the hydraulic oil bubble content of the pitch system in the wind turbine at the current moment, the dynamic response characteristics of the pitch system in the wind turbine are determined, including: obtaining a first mathematical model for reflecting the influence of the hydraulic oil bubble content on the dynamic response characteristics of the pitch system; inputting the blade force of the wind turbine at the current moment and the hydraulic oil bubble content of the pitch system in the wind turbine at the current moment into the first mathematical model, and obtaining the dynamic response characteristics of the pitch system in the wind turbine output by the first mathematical model.

[0054] Exemplarily, the dynamic response characteristics may include pitch speed and pitch angle, etc.

[0055] Exemplarily, the first mathematical model is a pre-trained model. The model may adopt a support vector machine algorithm. In this way, a mathematical model of nonlinear mapping may be constructed.

[0056] It can be understood that under different blade stress conditions, the dynamic response characteristics affected by the same hydraulic oil bubble content are different.

[0057] It can be understood that under the same blade force condition, the dynamic response characteristics are different for different hydraulic oil bubble contents.

[0058] According to the above implementation, a model can be used to predict the blade force of the wind turbine at the current moment and the hydraulic oil bubble content of the pitch system in the wind turbine at the current moment, so as to obtain the dynamic response characteristics of the pitch system in the wind turbine and improve the accuracy of determining the dynamic response characteristics of the pitch system.

[0059] In one embodiment, a first mathematical model is obtained to reflect the influence of the bubble content of hydraulic oil on the dynamic response characteristics of the pitch system, including: for each historical moment, based on the bubble movement characteristics and volume characteristics of the hydraulic oil in the pitch system of the wind turbine at the historical moment, determining the estimated value of the bubble content of the pitch system at the historical moment; constructing the first mathematical model based on the blade force of the wind turbine at each historical moment, and the estimated value of the bubble content and the dynamic response characteristics of the pitch system at each historical moment.

[0060] It can be understood that the first mathematical model is trained using training samples at multiple historical moments. For example, each training sample includes blade force, bubble content estimation value and corresponding pitch dynamic response characteristics.

[0061] For example, according to the relationship data of blade force, bubble content and pitch dynamic response characteristics at each historical moment, the data is normalized, and the characteristic values ​​such as blade force, bubble content, pitch speed and pitch accuracy are uniformly scaled to the range of 0-1 to eliminate the dimension effect and improve the data quality. The principal component analysis method is used to reduce the dimension of the preprocessed data, retain the principal components with a cumulative contribution rate of 95%, construct a new feature space, and use the reduced dimension blade force and bubble content as the input of the support vector machine, and select the pitch dynamic response characteristics as the output variable. The nonlinear mapping model is constructed using the support vector machine algorithm, and the radial basis kernel function is selected as the kernel function. The grid search combined with 5-fold cross validation is used to determine the optimal penalty factor C and kernel function parameter γ. The dual problem of the support vector machine is solved using the sequential minimum optimization algorithm to obtain the optimal Lagrange multiplier, calculate the bias term b and the decision function, and use the root mean square error and determination coefficient R² to evaluate the model performance, and obtain a mathematical model that accurately reflects the influence of bubble content on the pitch dynamic response characteristics.

[0062] For example, the support vector machine uses the radial basis kernel function K(x,y)=exp(-γ||xy||²), and the grid search range is set to C∈[2 -5 , 2¹ 5 ],γ∈[2 - ¹ 5 , 2³], with a step size of 2.

[0063] For example, when the sequential minimum optimization algorithm iteratively solves the dual problem, the convergence threshold is set to 1e -3 , the maximum number of iterations is 1000. 100 non-zero Lagrange multipliers are obtained, the corresponding number of support vectors is 100, the bias term b=-0.247, and the decision function f(x)=sign(∑αiyiK(xi,x)+b). Through the test of the model, it can be seen that with the root mean square error RMSE=0.035 and the determination coefficient R²=0.928, the model has good fitting effect and prediction ability.

[0064] According to the above implementation, a first mathematical model can be trained to accurately reflect the influence of the hydraulic oil bubble content on the dynamic response characteristics of the pitch control system.

[0065] In one embodiment, based on the bubble movement characteristics and volume characteristics of the hydraulic oil in the pitch system of the wind turbine generator set at a historical moment, an estimated value of the bubble content of the pitch system at a historical moment is determined, including: performing bubble recognition on the hydraulic oil image of the pitch system at a historical moment to determine a second bubble shape distribution, a second bubble total volume, and a second hydraulic oil total volume; determining a third bubble content based on a ratio between the second bubble total volume and the second hydraulic oil total volume; determining a second bubble movement feature vector based on an average velocity and acceleration of bubbles in the hydraulic oil in the pitch system at a historical moment, and the second bubble shape distribution; determining a fourth bubble content corresponding to the second bubble movement feature vector based on a mapping relationship between the bubble content and the bubble movement characteristics; and determining the hydraulic oil bubble content of the pitch system at a historical moment from the third bubble content and the fourth bubble content.

[0066] Exemplarily, a high-speed camera is used to continuously shoot the hydraulic oil of the variable pitch system and record the bubble movement video, the video frames are segmented by an image processing algorithm to extract the bubble contours, the watershed algorithm is used to segment the overlapping bubbles, and the total volume of the bubbles in a single frame image is calculated based on the area of ​​the segmented bubble contours. At the same time, the total volume of the hydraulic oil is calculated to obtain the bubble content data.

[0067] For example, for the bubble motion video acquired by high-speed camera, the three-dimensional reconstruction technology is used to convert the two-dimensional image sequence into the bubble motion trajectory in three-dimensional space, and the Kalman filter algorithm is used to smooth the trajectory to improve the trajectory accuracy and obtain the trajectory data of the three-dimensional coordinates of the bubble center point changing with time.

[0068] Exemplarily, the bubble velocity and acceleration may be calculated based on the bubble motion trajectory data.

[0069] Exemplarily, the bubble shape distribution can be characterized by roundness, for example (roundness 0.8-1).

[0070] Exemplarily, the bubble shape distribution may also include a bubble distribution state, for example, classified into uniform distribution, aggregated distribution, and laminar distribution.

[0071] For example, a multiple regression analysis method can be used, and data is used in advance to construct a mapping relationship between bubble content and bubble motion characteristics based on the data. For example, the independent variables are bubble motion characteristics such as speed, acceleration, size and shape, and the dependent variable is bubble content. During the construction process, 10-fold cross validation is used to evaluate model performance, and the root mean square error is 0.002%, and the model parameters with the smallest validation error are selected.

[0072] Exemplarily, either the first bubble content or the second bubble content is selected as the hydraulic oil bubble content of the pitch system at a historical moment. Alternatively, the larger one is selected from the first bubble content and the second bubble content as the hydraulic oil bubble content of the pitch system at a historical moment.

[0073] Exemplarily, according to the difference between the first bubble content and the second bubble content, the bubble content of the hydraulic oil of the pitch system at the historical moment is determined from the first bubble content and the second bubble content. For example, if the difference is greater than the first threshold, the first bubble content is used as the bubble content of the hydraulic oil of the pitch system at the historical moment, and if the difference is less than the first threshold, the second bubble content is used as the bubble content of the hydraulic oil of the pitch system at the historical moment.

[0074] According to the above implementation, the bubble content of the hydraulic oil at the historical moment can be accurately calculated by utilizing the bubble movement characteristics and volume characteristics at the historical moment.

[0075] In one embodiment, based on the dynamic response characteristics of the pitch system in each wind turbine, the predicted power generation of each wind turbine is determined, including: determining the generator excitation current and DC bus voltage of the wind turbine corresponding to the pitch system based on the pitch speed and pitch angle of the pitch system; determining the predicted power generation of the wind turbine based on the generator excitation current and DC bus voltage.

[0076] For example, different pitch speeds and pitch angles correspond to different generator excitation currents. Therefore, the pitch speed and pitch angle can be used to determine the corresponding generator excitation current. Thus, based on the generator excitation current and the total resistance, the DC bus voltage can be obtained.

[0077] Exemplarily, the predicted power generation of the wind turbine generator set may be obtained by multiplying the generator excitation current by the DC bus voltage.

[0078] According to the above embodiment, the predicted power generation of each wind turbine generator set can be accurately determined by utilizing the dynamic response characteristics of the pitch control system in each wind turbine generator set.

[0079] Figure 2 A resource coordination control system of an electric power system taking into account distributed units according to an embodiment of the present disclosure.

[0080] like Figure 2 As shown, the resource coordination control system of the power system taking into account the distributed units may include:

[0081] The bubble content prediction module 210 is used to determine the bubble content of the hydraulic oil in the pitch system of each wind turbine in the power system at the current moment based on the bubble movement characteristics and volume characteristics of the hydraulic oil in the pitch system of each wind turbine in the power system at the current moment;

[0082] A response characteristic determination module 220 is used to determine the dynamic response characteristics of the pitch system in the wind generator set for each wind generator set based on the blade force of the wind generator set at the current moment and the bubble content of the hydraulic oil of the pitch system in the wind generator set at the current moment;

[0083] A power generation determination module 230, configured to determine the predicted power generation of each wind turbine generator set based on the dynamic response characteristics of the pitch control system in each wind turbine generator set;

[0084] The power generation adjustment module 240 is used to perform bubble purification operations on the hydraulic oil in the pitch system of any of the wind turbines when the predicted power generation of the wind turbine does not meet the preset conditions, so as to adjust the power generation of each of the wind turbines in the power system.

[0085] In one embodiment, the bubble content prediction module 210 includes:

[0086] an image recognition unit, configured to perform bubble recognition on the hydraulic oil image of the pitch system at a current moment to determine a first bubble shape distribution, a first bubble total volume, and a first hydraulic oil total volume;

[0087] a first content calculation unit, configured to determine a first bubble content based on a ratio between the first bubble total volume and the first hydraulic oil total volume;

[0088] A first vector determination unit, configured to determine a first bubble motion characteristic vector based on an average velocity and acceleration of bubbles of hydraulic oil in the pitch control system at a current moment, and a shape distribution of the first bubbles;

[0089] a second content calculation unit, configured to determine a second bubble content corresponding to the first bubble motion feature vector based on a mapping relationship between the bubble content and the bubble motion feature;

[0090] The third content determination unit is used to determine the hydraulic oil bubble content of the pitch system at the current moment from the first bubble content and the second bubble content.

[0091] In one implementation, the response characteristic determination module 220 includes:

[0092] A model acquisition unit, used to acquire a first mathematical model for reflecting the influence of the hydraulic oil bubble content on the dynamic response characteristics of the pitch control system;

[0093] The model calculation unit is used to input the blade force of the wind turbine generator set at the current moment and the hydraulic oil bubble content of the variable pitch system in the wind turbine generator set at the current moment into the first mathematical model to obtain the dynamic response characteristics of the variable pitch system in the wind turbine generator set output by the first mathematical model.

[0094] In one implementation, the model acquisition unit is specifically used to:

[0095] For each historical moment, based on the bubble movement characteristics and volume characteristics of the hydraulic oil in the pitch system of the wind turbine generator set at the historical moment, determine the estimated value of the bubble content of the pitch system at the historical moment;

[0096] The first mathematical model is constructed based on the blade forces of the wind turbine generator set at each historical moment, and the estimated bubble content and pitch dynamic response characteristics of the pitch system at each historical moment.

[0097] In one embodiment, determining the estimated value of the bubble content of the pitch system at the historical moment based on the bubble movement characteristics and volume characteristics of the hydraulic oil in the pitch system of the wind turbine generator set at the historical moment includes:

[0098] performing bubble recognition on the hydraulic oil image of the pitch system at the historical moment to determine a second bubble shape distribution, a second bubble total volume, and a second hydraulic oil total volume;

[0099] determining a third bubble content based on a ratio between the second bubble total volume and the second hydraulic oil total volume;

[0100] Determining a second bubble motion characteristic vector based on an average velocity and acceleration of bubbles of hydraulic oil in the pitch system at the historical moment and a shape distribution of the second bubbles;

[0101] determining a fourth bubble content corresponding to the second bubble motion feature vector based on a mapping relationship between the bubble content and the bubble motion feature;

[0102] The bubble content of the hydraulic oil of the pitch system at the historical moment is determined in the third bubble content and the fourth bubble content.

[0103] In one implementation, the power generation determination module 230 includes:

[0104] A current and voltage determination unit, configured to determine a generator excitation current and a DC bus voltage of a wind turbine generator set corresponding to the pitch system based on a pitch speed and a pitch angle of the pitch system;

[0105] A power determination unit is used to determine the predicted power generation power of the wind turbine generator set based on the generator excitation current and the DC bus voltage.

[0106] According to an embodiment of the present disclosure, the above method of the present disclosure may be applied to an electronic device and a readable storage medium.

[0107] Figure 3 A schematic block diagram of an example electronic device 600 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0108] like Figure 3 As shown, the device 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the device 600 can also be stored. The computing unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0109] A number of components in the device 600 are connected to the I / O interface 605, including: an input unit 606, such as a keyboard, a mouse, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a disk, an optical disk, etc.; and a communication unit 609, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0110] The computing unit 601 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 601 performs the various methods and processes described above, such as a resource collaborative control method for a power system taking into account distributed units. For example, in some embodiments, a resource collaborative control method for a power system taking into account distributed units may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 600 via the ROM 602 and / or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of a resource collaborative control method for a power system taking into account distributed units described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured in any other appropriate manner (eg, by means of firmware) to execute a resource coordinated control method for a power system taking into account distributed units.

[0111] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0112] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0113] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0114] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0115] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0116] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0117] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0118] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the principles of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A resource collaborative control method for a power system taking into account distributed units, characterized in that: include: Determine the bubble content of the hydraulic oil in the pitch system of each wind generator set in the power system at the current moment based on the bubble movement characteristics and volume characteristics of the hydraulic oil in the pitch system of each wind generator set at the current moment; For each of the wind turbine generator sets, based on the blade force of the wind turbine generator set at the current moment and the bubble content of the hydraulic oil of the pitch system in the wind turbine generator set at the current moment, the dynamic response characteristics of the pitch system in the wind turbine generator set are determined; Determining the predicted power generation of each wind turbine generator set based on the dynamic response characteristics of the pitch system in each wind turbine generator set; For any of the wind turbine generator sets, when the predicted power generation of the wind turbine generator set does not meet the preset conditions, a bubble purification operation is performed on the hydraulic oil in the pitch system of the wind turbine generator set to adjust the power generation of each of the wind turbine generator sets in the power system; Wherein, the bubble content of the hydraulic oil in the pitch system of each wind turbine generator set in the power system at the current moment is determined based on the bubble movement characteristics and volume characteristics of the hydraulic oil in the pitch system of each wind turbine generator set in the power system at the current moment, including: Performing bubble recognition on the hydraulic oil image of the pitch system at the current moment to determine a first bubble shape distribution, a first bubble total volume, and a first hydraulic oil total volume; determining a first bubble content based on a ratio between the first bubble total volume and the first hydraulic oil total volume; Determine a first bubble motion characteristic vector based on an average velocity and acceleration of bubbles of hydraulic oil in the pitch control system at a current moment and a shape distribution of the first bubbles; determining a second bubble content corresponding to the first bubble motion feature vector based on a mapping relationship between the bubble content and the bubble motion feature; Determining the hydraulic oil bubble content of the pitch system at the current moment from the first bubble content and the second bubble content; Wherein, determining the dynamic response characteristics of the variable pitch system in the wind generator set based on the blade force of the wind generator set at the current moment and the bubble content of the hydraulic oil of the variable pitch system in the wind generator set at the current moment includes: Acquire a first mathematical model for reflecting the influence of the bubble content of hydraulic oil on the dynamic response characteristics of the pitch control system; Inputting the blade force of the wind generator set at the current moment and the bubble content of the hydraulic oil of the variable pitch system in the wind generator set at the current moment into the first mathematical model, and obtaining the dynamic response characteristics of the variable pitch system in the wind generator set output by the first mathematical model; Wherein, determining the predicted power generation of each wind turbine generator set based on the dynamic response characteristics of the pitch system in each wind turbine generator set includes: Based on the pitch speed and pitch angle of the pitch system, determining the generator excitation current and DC bus voltage of the wind turbine generator set corresponding to the pitch system; The predicted power generation power of the wind turbine generator set is determined based on the generator excitation current and the DC bus voltage.

2. The method according to claim 1, characterized in that: The obtaining of a first mathematical model for reflecting the influence of the hydraulic oil bubble content on the dynamic response characteristics of the pitch control system comprises: For each historical moment, based on the bubble movement characteristics and volume characteristics of the hydraulic oil in the pitch system of the wind turbine generator set at the historical moment, determine the estimated value of the bubble content of the pitch system at the historical moment; The first mathematical model is constructed based on the blade forces of the wind turbine generator set at each historical moment, and the estimated bubble content and pitch dynamic response characteristics of the pitch system at each historical moment.

3. The method according to claim 2, characterized in that The step of determining an estimated value of bubble content in the pitch system at the historical moment based on bubble movement characteristics and volume characteristics of hydraulic oil in the pitch system of the wind turbine generator set at the historical moment comprises: performing bubble recognition on the hydraulic oil image of the pitch system at the historical moment to determine a second bubble shape distribution, a second bubble total volume, and a second hydraulic oil total volume; determining a third bubble content based on a ratio between the second bubble total volume and the second hydraulic oil total volume; Determining a second bubble motion characteristic vector based on an average velocity and acceleration of bubbles of hydraulic oil in the pitch system at the historical moment and a shape distribution of the second bubbles; determining a fourth bubble content corresponding to the second bubble motion feature vector based on a mapping relationship between the bubble content and the bubble motion feature; The bubble content of the hydraulic oil of the pitch system at the historical moment is determined in the third bubble content and the fourth bubble content.

4. A resource coordination control system for a power system taking into account distributed units, characterized in that: include: A bubble content prediction module, for determining the bubble content of the hydraulic oil in the pitch system of each wind turbine in the power system at the current moment based on the bubble movement characteristics and volume characteristics of the hydraulic oil in the pitch system of each wind turbine in the power system at the current moment; a response characteristic determination module, for determining the dynamic response characteristics of the variable pitch system in the wind generator set for each wind generator set, based on the blade force of the wind generator set at the current moment and the bubble content of the hydraulic oil of the variable pitch system in the wind generator set at the current moment; A power generation determination module, used to determine the predicted power generation of each wind turbine generator set based on the dynamic response characteristics of the pitch system in each wind turbine generator set; A power generation adjustment module, for any of the wind generator sets, when the predicted power generation of the wind generator set does not meet the preset conditions, to perform bubble purification operation on the hydraulic oil in the pitch system of the wind generator set, so as to adjust the power generation of each of the wind generator sets in the power system; Wherein, the bubble content prediction module includes: an image recognition unit, configured to perform bubble recognition on the hydraulic oil image of the pitch system at a current moment to determine a first bubble shape distribution, a first bubble total volume, and a first hydraulic oil total volume; a first content calculation unit, configured to determine a first bubble content based on a ratio between the first bubble total volume and the first hydraulic oil total volume; A first vector determination unit, configured to determine a first bubble motion characteristic vector based on an average velocity and acceleration of bubbles of hydraulic oil in the pitch control system at a current moment, and a shape distribution of the first bubbles; a second content calculation unit, configured to determine a second bubble content corresponding to the first bubble motion feature vector based on a mapping relationship between the bubble content and the bubble motion feature; a third content determination unit, configured to determine, from the first bubble content and the second bubble content, a bubble content of the hydraulic oil of the pitch system at the current moment; Wherein, the response characteristic determination module includes: A model acquisition unit, used to acquire a first mathematical model for reflecting the influence of the hydraulic oil bubble content on the dynamic response characteristics of the pitch control system; a model calculation unit, configured to input the blade force of the wind generator set at a current moment and the bubble content of the hydraulic oil of the variable pitch system in the wind generator set at a current moment into the first mathematical model, and obtain the dynamic response characteristics of the variable pitch system in the wind generator set output by the first mathematical model; Wherein, the power generation determination module includes: A current and voltage determination unit, configured to determine a generator excitation current and a DC bus voltage of a wind turbine generator set corresponding to the pitch system based on a pitch speed and a pitch angle of the pitch system; A power determination unit is used to determine the predicted power generation power of the wind turbine generator set based on the generator excitation current and the DC bus voltage.

5. An electronic device comprising: at least one processor; as well as a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described in any one of claims 1 to 3.

6. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-3.

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