CN118653962B - Network flow control method suitable for home-made fan master control - Google Patents

Abstract

The present invention provides a network traffic control method applicable to a domestically produced wind turbine master control, and relates to the technical field of network traffic control. The method comprises: obtaining predicted wind speed data and predicted wind direction data of the target location of the wind turbine through weather forecast data, and obtaining the first yaw angle of the windward surface and the theoretical yaw angles at multiple moments of the next control cycle at the end of the control cycle, and then determining the adjustment mode at multiple moments, and then distinguishing the node moment of the adjustment mode through the node discrimination condition, and performing default settings on the adjustment mode at multiple moments, obtaining the adjustment mode at the node moment and the adjustment change mode of the time period between adjacent node moments, thereby generating a wind turbine control signal and sending it to the wind turbine controller. According to the present invention, the amount of data transmitted in communication can be reduced, so that the wind turbine control signal after the default setting can accurately express the complete adjustment mode at multiple moments using a smaller amount of data, and reduce the burden of data transmission.

Description

A network traffic control method suitable for domestically produced wind turbine master control

Technical Field

The present invention relates to the technical field of network traffic control, and in particular to a network traffic control method suitable for a domestically produced wind turbine master control.

Background Art

In the related art, CN109245884B provides a data communication method and device for a wind turbine generator set. The data communication method for a wind turbine generator set includes: obtaining communication data of the wind turbine generator set; splitting the communication data, and arranging the split communication data to form a linear data structure; performing any number of transformations on data elements at any position in the linear data structure to obtain encrypted communication data for transmission. This solution can increase the complexity of data encoding and encryption by arranging the split communication data to form a linear data structure, and performing any number of transformations on data elements at any position in the linear data structure, thereby achieving coding protection for communication data and improving the confidentiality and security of communication data.

CN105471992B provides a terminal device and communication system for use in a wind farm, the terminal device comprising: a data collector and a communication module. The solution, by setting up a communication module and a data acquisition module, realizes the use of an IP phone and/or a smart terminal connected to WiFi to establish a communication connection with the outside of the wind turbine, and realizes communication between the wind turbine site and remote technical support personnel, which can effectively solve the problem of poor instant communication at the wind farm site, accurately locate a specific wind turbine for dialogue, or conduct dialogue between wind turbines, significantly improve the operation and maintenance efficiency of the wind farm, and form an operation and maintenance mode in which one operation and maintenance expert provides remote technical support for the operation and maintenance of multiple operation and maintenance teams.

Therefore, in the current relevant technologies, although the communication between wind turbines and other equipment can be realized, the working location of wind turbines is generally in remote areas, and the command post that controls the operation of the wind turbines is also far away from the wind turbines. In addition, the amount of data is very large, resulting in slow data transmission speed between the command post and the wind turbines, and the control of the yaw angle of the windward side of the wind turbine is not precise enough, which in turn affects the utilization efficiency of wind resources.

The information disclosed in the background technology section of this application is only intended to deepen the understanding of the general background technology of this application, and should not be regarded as an admission or any form of suggestion that the information constitutes the prior art already known to those skilled in the art.

Summary of the invention

The present invention provides a network traffic control method applicable to a domestically produced wind turbine master control, which can solve the technical problem that a large amount of data leads to transmission difficulties, thereby affecting the working efficiency of the wind turbine.

According to a first aspect of the present invention, there is provided a method comprising:

At the end of the current control cycle, based on the weather forecast data of the target location where the wind turbine is located, the predicted wind speed data and predicted wind direction data of the target location at multiple times in the next control cycle are obtained;

Acquire a first yaw angle of the windward surface of the wind turbine at the end time of the current control cycle;

Determining theoretical yaw angles of the windward surface of the wind turbine at multiple moments in the next control cycle according to the predicted wind direction data;

Determining a mode for adjusting the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle according to the theoretical yaw angle, the predicted wind speed data, the first yaw angle and the maximum adjustment speed of the yaw angle of the windward surface of the wind turbine;

Determining node moments of the adjustment method according to the adjustment method of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle;

According to the node moment, a default setting is made for the adjustment mode of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle, and the adjustment mode of the yaw angle of the windward surface of the wind turbine at the node moment and the adjustment change mode in the time period between adjacent node moments are obtained;

Generate a wind turbine control signal according to the adjustment mode of the yaw angle of the windward surface of the wind turbine at the node moment and the adjustment change mode in the time period between adjacent node moments;

Sends fan control signals to the fan controller.

According to a second aspect of the present invention, a network traffic control system suitable for domestically produced wind turbine master control is provided.

A first data acquisition module, at the end time of the current control cycle, acquires predicted wind speed data and predicted wind direction data of the target location at multiple times of the next control cycle according to the weather forecast data of the target location where the wind turbine is located;

A first yaw angle acquisition module, which acquires a first yaw angle of the windward surface of the wind turbine at the end time of the current control cycle;

A theoretical yaw angle acquisition module, which determines the theoretical yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle according to the predicted wind direction data;

A first adjustment mode acquisition module determines an adjustment mode of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle according to the theoretical yaw angle, the predicted wind speed data, the first yaw angle and the maximum adjustment speed of the yaw angle of the windward surface of the wind turbine;

A node time acquisition module determines the node time of the adjustment method according to the adjustment method of the yaw angle of the windward surface of the wind turbine at multiple times in the next control cycle;

an adjustment change mode acquisition module, which performs default settings on the adjustment modes of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle according to the node moment, and obtains the adjustment mode of the yaw angle of the windward surface of the wind turbine at the node moment, and the adjustment change mode in the time period between adjacent node moments;

A control signal generating module, generating a fan control signal according to the adjustment mode of the yaw angle of the windward surface of the fan at the node moment and the adjustment change mode of the time period between adjacent node moments;

The control signal sending module sends the fan control signal to the fan controller.

Technical effect: According to the present invention, the predicted wind speed data and predicted wind direction data of the target position of the wind turbine can be obtained through weather forecast data, and at the end of the control cycle, the first yaw angle of the windward surface is obtained, and the theoretical yaw angles at multiple moments of the next control cycle are determined, and then the adjustment method of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle is determined, and the node moments of the adjustment method are determined, and then the adjustment method of the yaw angle of the windward surface of the wind turbine at multiple moments is defaulted, and the adjustment method at the node moment and the adjustment change method in the time period between adjacent node moments are obtained, so as to generate a wind turbine control signal and send it to the wind turbine controller, which can reduce the amount of data transmitted in communication, so that the fan control signal after the default setting can accurately express the complete adjustment method at multiple moments with a smaller amount of data, so that the fan control signal is concise and representative, which improves the utilization rate of wind resources while reducing the burden of data transmission. When determining the demand adjustment coefficient, the predicted wind speed data, the predicted wind direction data, the first yaw angle of the windward side of the wind turbine and the theoretical yaw angles at multiple moments in the next control cycle can be obtained, and then the adjustment demand coefficient can be determined in combination with the angle difference between the first yaw angle of the windward side of the wind turbine and the ideal yaw angle, and then it can be judged whether the adjustment demand function is higher than the preset coefficient threshold, and the yaw angle of the windward side of the wind turbine is adjusted in the next control cycle to avoid low work efficiency caused by the large angle difference between the yaw angle of the windward side of the wind turbine and the ideal yaw angle, thereby improving the utilization rate of wind resources and providing a data basis for reducing the pressure of data transmission. When determining the windward surface adjustment speed, the wind flux between each moment can be determined by predicting wind speed data, ideal yaw angle, first yaw angle and the area of the windward surface of the wind turbine, and according to the change rate of the yaw angle of the windward surface of the wind turbine and the maximum adjustment speed of the windward surface of the wind turbine, the constraint conditions are set in a targeted manner to reasonably set the adjustment speed of the windward surface of the wind turbine, and determine the adjustment mode optimization model to maximize the wind volume passing through the windward surface of the wind turbine in the next control cycle, and solve the optimal solution of the windward surface adjustment speed between each adjacent moment of the next control cycle, so as to improve the utilization rate of wind resources. When determining the node moment, three discrimination conditions can be set. By judging whether there is a step change in the adjustment speed of the windward surface of the wind turbine, the moment that meets the node discrimination conditions is set as the node moment. Taking into account various factors, the node moment after discrimination is more representative, and the volume of the wind turbine control data is reduced, thereby providing an accurate data basis for reducing the burden of data transmission. When determining the adjustment change mode, the adjustment mode of the previous moment of other node moments except the first node moment can be obtained, and then the adjustment speed of the two node moments and the time difference between the two node moments can be combined to determine the adjustment change mode between the two node moments, that is, the rate of change of the angular velocity, so that the adjustment speed of the windward surface of the fan at each moment between the two node moments can be solved by the rate of change, thereby reducing the amount of data that needs to be transmitted, alleviating the pressure of data transmission, and improving the efficiency of data transmission.

It should be understood that the above general description and the following detailed description are exemplary and explanatory only and do not limit the present invention. Other features and aspects of the present invention will become more apparent from the following detailed description of exemplary embodiments with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other embodiments can be obtained based on these drawings without creative work.

FIG1 exemplarily shows a flow chart of a network traffic control method applicable to a domestically produced wind turbine master control according to an embodiment of the present invention;

FIG2 exemplarily shows a schematic diagram of a network traffic control system applicable to a domestically produced wind turbine master control according to an embodiment of the present invention.

DETAILED DESCRIPTION

In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

The technical solution of the present invention is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

FIG1 exemplarily shows a flow chart of a network traffic control method applicable to a domestically produced wind turbine master control according to an embodiment of the present invention, wherein the method comprises:

Step S101, at the end of the current control cycle, according to the weather forecast data of the target location where the wind turbine is located, obtain the predicted wind speed data and predicted wind direction data of the target location at multiple moments in the next control cycle;

Step S102, obtaining a first yaw angle of the windward surface of the wind turbine at the end time of the current control cycle;

Step S103, determining the theoretical yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle according to the predicted wind direction data;

Step S104, determining a method for adjusting the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle according to the theoretical yaw angle, the predicted wind speed data, the first yaw angle, and the maximum adjustment speed of the yaw angle of the windward surface of the wind turbine;

Step S105, determining the node time of the adjustment method according to the adjustment method of the yaw angle of the windward surface of the wind turbine at multiple times in the next control cycle;

Step S106, according to the node moment, default settings are made for the adjustment methods of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle, and the adjustment method of the yaw angle of the windward surface of the wind turbine at the node moment and the adjustment change method in the time period between adjacent node moments are obtained;

Step S107, generating a fan control signal according to the adjustment mode of the yaw angle of the windward surface of the fan at the node moment and the adjustment change mode in the time period between adjacent node moments;

Step S108, sending the fan control signal to the fan controller.

According to the network traffic control method applicable to the domestically produced wind turbine master control of the present invention, the predicted wind speed data and predicted wind direction data of the target position of the wind turbine can be obtained through weather forecast data, and at the end of the control cycle, the first yaw angle of the windward side is obtained, and the theoretical yaw angles at multiple moments of the next control cycle are determined, and then the adjustment method of the yaw angle of the windward side of the wind turbine at multiple moments of the next control cycle is determined, and the node moments of the adjustment method are determined, and then the adjustment method of the yaw angle of the windward side of the wind turbine at multiple moments is defaulted, and the adjustment method at the node moment and the adjustment change method in the time period between adjacent node moments are obtained, so as to generate a wind turbine control signal and send it to the wind turbine controller, which can reduce the amount of data transmitted in communication, so that the wind turbine control signal after the default setting can accurately express the complete adjustment method at multiple moments with a smaller amount of data, so that the wind turbine control signal is concise and representative, and the utilization rate of wind resources is improved while reducing the burden of data transmission.

According to an embodiment of the present invention, in step S101, at the end of the current control cycle, the predicted wind speed data and predicted wind direction data of the target location at multiple moments in the next control cycle are obtained according to the weather forecast data of the target location where the wind turbine is located. That is, at the end of the current control cycle, the predicted wind speed data and predicted wind direction data of multiple moments are obtained according to the weather forecast data of the location where the wind turbine is located, and the theoretical yaw angles of multiple moments in the next cycle can be obtained based on this, and subsequent calculation steps are performed.

According to an embodiment of the present invention, in step S102, the first yaw angle of the windward surface of the wind turbine at the end time of the current control cycle is obtained. The first yaw angle of the windward surface of the wind turbine can represent the orientation of the wind turbine. For example, when the windward surface of the wind turbine faces due north, the yaw angle of the windward surface of the current wind turbine can be set to 0°. When the windward surface of the wind turbine faces due east, the yaw angle of the windward surface of the current wind turbine can be set to 90°. The first yaw angle is the yaw angle of the windward surface of the wind turbine at the end of the current control cycle, and can also be used as the yaw angle of the windward surface of the wind turbine at the beginning of the next control cycle.

According to an embodiment of the present invention, in step S103, the theoretical yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle is determined based on the predicted wind direction data, wherein the theoretical yaw angle is the yaw angle that makes the windward surface of the wind turbine face the wind direction. In the example, the predicted wind direction data at a certain moment is a direction angle that can be used to describe the wind force, for example, the direction angle of the wind force is , then the yaw angle facing the wind direction, that is, the theoretical yaw angle is .

According to an embodiment of the present invention, in step S104, the adjustment method of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle is determined according to the theoretical yaw angle, the predicted wind speed data, the first yaw angle and the maximum adjustment speed of the yaw angle of the windward surface of the wind turbine, including: determining whether it is necessary to adjust the yaw angle of the windward surface of the wind turbine according to the theoretical yaw angle, the predicted wind speed data and the first yaw angle; if it is necessary to adjust the yaw angle of the windward surface of the wind turbine, adjusting the yaw angle according to the theoretical yaw angle, the predicted wind speed data and the first yaw angle; The constraint conditions of the adjustment mode optimization model are determined according to the predicted wind speed data and the theoretical yaw angle, and the objective function of the adjustment mode optimization model is determined; the adjustment speed of the windward surface of the yaw angle of the windward surface of the wind turbine between each adjacent moment in the next control cycle is determined according to the constraint conditions and objective function of the adjustment mode optimization model; the adjustment speed of the windward surface between the i-th moment and the i+1-th moment in the next control cycle is determined as the adjustment mode at the i-th moment.

According to an embodiment of the present invention, based on the theoretical yaw angle, the predicted wind speed data and the first yaw angle, it is determined whether it is necessary to adjust the yaw angle of the windward surface of the wind turbine, and then combined with the maximum adjustment speed of the yaw angle of the windward surface of the wind turbine, the constraint conditions of the adjustment mode optimization model are determined, and the objective function of the adjustment mode optimization model is determined, and then the optimization model is solved to determine the optimal solution of the windward surface adjustment speed of the yaw angle of the windward surface of the wind turbine between each adjacent moment in the next control cycle, and the windward surface adjustment speed between the i-th moment to the i+1-th moment in the next control cycle is determined as the adjustment mode at the i-th moment, wherein the optimization model may be a nonlinear programming model or a genetic algorithm model, and the present invention does not impose any limitation on this.

According to an embodiment of the present invention, determining whether it is necessary to adjust the yaw angle of the windward surface of the wind turbine according to the theoretical yaw angle, the predicted wind speed data and the first yaw angle includes:

According to formula (1), the adjustment demand coefficient D is:

(1),

in, is the predicted wind speed data at the i-th moment of the next control cycle, is the theoretical yaw angle of the windward side of the wind turbine at the i-th moment in the next control cycle, is the first yaw angle, and n is the number of moments in the next control cycle; if the adjustment demand coefficient is greater than or equal to the preset coefficient threshold, it is determined that the yaw angle of the windward surface of the wind turbine needs to be adjusted.

According to an embodiment of the present invention, in formula (1), It can represent the wind flux when the windward side of the fan always faces the predicted wind direction in the next control cycle (i.e. the wind flux when the windward side of the fan works at the theoretical yaw angle). is the windward surface area of the fan, It can be expressed as the wind flux when the windward side of the fan works at the first yaw angle in the next control cycle. It can represent the difference between the wind flux when the windward side of the fan always faces the predicted wind direction and the wind flux obtained when the windward side of the fan works at the first yaw angle in the next control cycle. Therefore, is the relative difference between the wind flux obtained when the windward side of the wind turbine always works at the theoretical yaw angle and works at the first yaw angle. and the theoretical yaw angle When the difference is small, Approaching 1, the adjustment demand coefficient D approaches 0, indicating that the utilization rate of wind resources in the next cycle is high, and there is no need to adjust the yaw angle of the windward side of the wind turbine. On the contrary, when the first yaw angle and the theoretical yaw angle When the difference is large, it means that the utilization rate of wind resources in the next cycle is low, and it is necessary to adjust the yaw angle of the windward side of the wind turbine. Therefore, the higher the adjustment demand coefficient, the lower the utilization rate of wind resources in the next cycle, and the more necessary it is to adjust the yaw angle of the windward side of the wind turbine in the next cycle; the lower the adjustment demand coefficient, the less necessary it is to adjust the yaw angle of the windward side of the wind turbine in the next cycle. In this way, while maintaining a high working efficiency of the wind turbine, there is no need to adjust the yaw angle, thereby reducing the burden of data transmission.

In this way, the predicted wind speed data, the predicted wind direction data, the first yaw angle of the windward side of the wind turbine and the theoretical yaw angles at multiple moments in the next control cycle can be obtained, and then the adjustment demand coefficient can be determined in combination with the angle difference between the first yaw angle of the windward side of the wind turbine and the ideal yaw angle, and then it can be judged whether the adjustment demand function is higher than the preset coefficient threshold, and the yaw angle of the windward side of the wind turbine is adjusted in the next control cycle to avoid low work efficiency caused by the large angle difference between the yaw angle of the windward side of the wind turbine and the ideal yaw angle, thereby improving the utilization rate of wind resources and providing a data basis for reducing the pressure of data transmission.

If the yaw angle of the windward surface of the wind turbine needs to be adjusted, the constraint conditions of the adjustment mode optimization model are determined according to the theoretical yaw angle, the predicted wind speed data, the first yaw angle and the maximum adjustment speed of the yaw angle of the windward surface of the wind turbine, including: determining the constraint conditions of the adjustment mode optimization model according to formula (2),

(2),

(3),

(4),

in, is the predicted average wind flux between the i-th moment and the i+1-th moment in the next control cycle, is the predicted wind speed data at the i-th moment of the next control cycle, is the predicted wind speed data at the i+1th moment of the next control cycle, is the theoretical yaw angle of the windward side of the wind turbine at the i-th moment in the next control cycle, is the theoretical yaw angle of the windward side of the wind turbine at the i+1th moment in the next control cycle, is the predicted yaw angle of the windward side of the wind turbine at the i-th moment in the next control cycle. When i=1, is the first yaw angle, is the predicted yaw angle of the windward side of the wind turbine at the i+1th moment in the next control cycle, is the windward surface adjustment speed of the fan between the i-th moment and the i+1-th moment in the next control cycle, is the time interval between adjacent moments of the next control cycle, is the maximum adjustment speed of the yaw angle of the windward side of the wind turbine, is the windward surface area of the fan.

According to an embodiment of the present invention, in formula (2), It can represent the theoretical wind flux on the windward side of the fan at the i-th moment. Similarly, It can represent the theoretical wind flux on the windward side of the fan at the i+1th moment, so, It can represent the average wind flux between the i-th moment and the i+1-th moment in the next control cycle. In formula (3), The angle difference between the yaw angle of the windward side of the wind turbine at the i-th moment and the predicted yaw angle at the i+1-th moment in the next control cycle can be calculated, and the ratio of the angle difference to the time interval between two adjacent moments can be solved to obtain the adjustment speed of the windward side of the wind turbine between the two moments (i.e., the change speed of the yaw angle). In formula (4), It means that the absolute value of the adjustment speed of the windward surface of the wind turbine between two moments (ie, the adjustment rate) is lower than the maximum adjustment speed of the yaw angle of the windward surface of the wind turbine.

According to an embodiment of the present invention, determining the objective function of the adjustment mode optimization model according to the predicted wind speed data and the theoretical yaw angle includes: determining the objective function of the adjustment mode optimization model according to formula (5),

(5),

Among them, n is the number of moments in the next control cycle, and max is the maximization function.

According to an embodiment of the present invention, in formula (5), represents the predicted average wind flux between two moments in the next control cycle. The objective function maximizes the sum of the predicted average wind flux between multiple moments in the next control cycle to improve the utilization of wind resources.

According to an embodiment of the present invention, the adjustment mode optimization model can be solved through the constraint conditions of the adjustment mode optimization model determined above and the objective function of the adjustment mode optimization model to determine the optimal solution for the windward surface adjustment speed of the wind turbine between each adjacent moment in the next control cycle.

In this way, the wind flux between each moment can be determined by predicting wind speed data, ideal yaw angle, first yaw angle and the area of the windward surface of the wind turbine, and according to the changing speed of the yaw angle of the windward surface of the wind turbine and the maximum adjustment speed of the windward surface of the wind turbine, the constraint conditions are set in a targeted manner to reasonably set the adjustment speed of the windward surface of the wind turbine, and determine the optimization model of the adjustment method to maximize the wind volume passing through the windward surface of the wind turbine in the next control cycle, solve the optimal solution of the windward surface adjustment speed between each adjacent moment of the next control cycle, and improve the utilization rate of wind resources.

According to an embodiment of the present invention, in step S105, determining the node moments of the adjustment method according to the adjustment method of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle includes: determining the node judgment conditions C1, C2 and C3 according to formula (6),

(6),

in, is the windward surface adjustment speed of the fan between the i+1th moment and the i+2th moment in the next control cycle, is the windward adjustment speed of the fan between the i-1th moment and the i+1th moment in the next control cycle, is a first preset coefficient greater than 1, is a first preset coefficient less than 1; when any one of the node judgment conditions C1, C2 and C3 is met, the i+1th moment of the next control cycle is determined as the node moment, and the 1st moment and the n-1th moment of the next control cycle are determined as the node moments.

According to an embodiment of the present invention, in the node discrimination condition C1 in formula (6), is the adjustment mode of the windward side of the fan at the i-th moment in the next control cycle, is the adjustment mode of the windward side of the fan at the i+1th moment of the next control cycle. When , it can be indicated that the directions of the above two adjustment methods are opposite. For example, the adjustment methods of the windward side of the fan at two moments are respectively adjusted in the clockwise direction and adjusted in the counterclockwise direction, resulting in opposite signs of the windward side adjustment speed at the above two moments. At this time, the node judgment condition C1 is satisfied, and the i+1th moment can be set as the node moment. In the node judgment condition C2 in formula (6), is the difference between the adjustment mode of the windward side of the fan at the i+1th moment and the adjustment mode at the ith moment, and is the difference between the adjustment mode of the windward side of the fan at the i-th moment in the next control cycle and the adjustment mode at the i-1-th moment. Therefore, It indicates that the predicted wind direction changes greatly, and the adjustment speed of the windward side of the fan needs to be increased stepwise. For example, the adjustment speed of the windward side of the fan from the i-th moment to the i+1th moment in the next control cycle is 2 rad/s, the adjustment speed of the windward side of the fan from the i-1th moment to the i-th moment in the next control cycle is 1 rad/s, and the adjustment speed of the windward side of the fan from the i+1th moment to the i+2th moment in the next control cycle is 5 rad/s. ,but , at this time, the adjustment mode of the windward side of the fan is neither uniform acceleration nor uniform speed. At this time, the i+1th moment can be set as the node moment. Similarly, in the node judgment condition C3 in formula (6), It can indicate that the predicted wind direction change is small, and the adjustment speed of the windward side of the fan needs to be reduced stepwise. The adjustment method of the windward side of the fan is neither uniform deceleration motion nor uniform speed motion. At this time, the i+1th moment can be set as the node moment, and when any one of the above three node judgment conditions is met, the 1st moment and the n-1th moment of the next control cycle are determined as node moments, so that each node moment is more representative, providing an accurate data basis for the optimization of fan control data.

In this way, three judgment conditions can be set. By judging whether there is a step change in the adjustment speed of the windward side of the fan, the moment that meets the node judgment conditions is set as the node moment. By comprehensively considering various factors, the node moment after judgment is more representative, reducing the volume of the fan control data, thereby providing an accurate data basis for reducing the burden of data transmission.

According to an embodiment of the present invention, in step S106, according to the node moment, the adjustment mode of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle is set by default, and the adjustment mode of the yaw angle of the windward surface of the wind turbine at the node moment and the adjustment change mode of the time period between adjacent node moments are obtained, including: obtaining the adjustment mode of each node moment; obtaining the adjustment mode of the previous moment of other node moments except the first node moment; determining the adjustment change mode between the kth node moment and the k+1th node moment according to formula (7). ,

(7),

in, is the adjustment method at the kth node moment, is the adjustment method of the moment before the k+1th node moment, is the k+1th node moment, is the k-th node moment.

According to an embodiment of the present invention, in formula (7), is the difference between the adjustment mode at the moment before the k+1th node moment and the adjustment mode at the kth node moment, which can be expressed as the difference between the angular velocities corresponding to the above two adjustment modes, and It represents the time difference between the kth node moment and the moment before the k+1th node moment. By comparing the speed difference and the time difference, the adjustment change mode between the kth node moment and the k+1th node moment can be obtained. , which can be expressed as the rate of change of the angular velocity between two node moments. Since the angular velocity corresponding to the adjustment mode of the moment between two node moments is constant, or increases or decreases at a uniform speed, when the command post server communicates with the fan controller, it can only send the adjustment mode of the node moment and the adjustment change mode between the node moments to the fan controller. After receiving the adjustment mode of the node moment and the adjustment change mode between the node moments, the fan controller can use the adjustment change mode and the time interval between adjacent moments. By multiplying, the adjustment methods for each moment between the kth node moment and the k+1th node moment are obtained, so as to improve the utilization rate of wind resources while alleviating the transmission pressure and improving the efficiency of data transmission.

In this way, the adjustment mode of the previous moment of other node moments except the first node moment can be obtained, and then the adjustment speed of the two node moments and the time difference between the two node moments can be combined to determine the adjustment change mode between the two node moments, that is, the rate of change of the angular velocity, so that the adjustment speed of the windward surface of the fan at each moment between the two node moments can be solved by the rate of change, thereby reducing the amount of data that needs to be transmitted, alleviating the pressure of data transmission, and improving the efficiency of data transmission.

According to an embodiment of the present invention, in step S107, a wind turbine control signal is generated according to the adjustment mode of the yaw angle of the windward surface of the wind turbine at the node moment and the adjustment change mode in the time period between adjacent node moments.

According to an embodiment of the present invention, in step S108 , the fan control signal is sent to the fan controller.

According to an embodiment of the present invention, as described above, after determining the adjustment mode of the yaw angle of the windward surface of the wind turbine at the node moment and the adjustment change mode in the time period between adjacent node moments (i.e., the adjustment speed of the windward surface of the wind turbine and the rate of change between two node moments), a wind turbine control signal is generated and sent to the wind turbine controller. After receiving the adjustment mode at the node moment and the adjustment change mode between the node moments, the wind turbine controller can use the adjustment change mode and the time interval between adjacent moments to determine the windward surface of the wind turbine. Multiply them together to obtain the adjustment method for each moment between the kth node moment and the k+1th node moment.

According to the network traffic control method applicable to the domestically produced wind turbine master control of the present invention, the predicted wind speed data and predicted wind direction data of the target position of the wind turbine can be obtained through weather forecast data, and at the end of the control cycle, the first yaw angle of the windward side is obtained, and the theoretical yaw angles at multiple moments of the next control cycle are determined, and then the adjustment method of the yaw angle of the windward side of the wind turbine at multiple moments of the next control cycle is determined, and the node moments of the adjustment method are determined, and then the adjustment method of the yaw angle of the windward side of the wind turbine at multiple moments is defaulted, and the adjustment method at the node moment and the adjustment change method in the time period between adjacent node moments are obtained, so as to generate a wind turbine control signal and send it to the wind turbine controller, which can reduce the amount of data transmitted in communication, so that the wind turbine control signal after the default setting can accurately express the complete adjustment method at multiple moments with a smaller amount of data, so that the wind turbine control signal is concise and representative, and the utilization rate of wind resources is improved while reducing the burden of data transmission. When determining the demand adjustment coefficient, the predicted wind speed data, the predicted wind direction data, the first yaw angle of the windward side of the wind turbine and the theoretical yaw angles at multiple moments in the next control cycle can be obtained, and then the adjustment demand coefficient can be determined in combination with the angle difference between the first yaw angle of the windward side of the wind turbine and the ideal yaw angle, and then it can be judged whether the adjustment demand function is higher than the preset coefficient threshold, and the yaw angle of the windward side of the wind turbine is adjusted in the next control cycle to avoid low work efficiency caused by the large angle difference between the yaw angle of the windward side of the wind turbine and the ideal yaw angle, thereby improving the utilization rate of wind resources and providing a data basis for reducing the pressure of data transmission. When determining the windward surface adjustment speed, the wind flux between each moment can be determined by predicting wind speed data, ideal yaw angle, first yaw angle and the area of the windward surface of the wind turbine, and according to the change rate of the yaw angle of the windward surface of the wind turbine and the maximum adjustment speed of the windward surface of the wind turbine, the constraint conditions are set in a targeted manner to reasonably set the adjustment speed of the windward surface of the wind turbine, and determine the adjustment mode optimization model to maximize the wind volume passing through the windward surface of the wind turbine in the next control cycle, and solve the optimal solution of the windward surface adjustment speed between each adjacent moment of the next control cycle, so as to improve the utilization rate of wind resources. When determining the node moment, three discrimination conditions can be set. By judging whether there is a step change in the adjustment speed of the windward surface of the wind turbine, the moment that meets the node discrimination conditions is set as the node moment. Taking into account various factors, the node moment after discrimination is more representative, and the volume of the wind turbine control data is reduced, thereby providing an accurate data basis for reducing the burden of data transmission. When determining the adjustment change mode, the adjustment mode of the previous moment of other node moments except the first node moment can be obtained, and then the adjustment speed of the two node moments and the time difference between the two node moments can be combined to determine the adjustment change mode between the two node moments, that is, the rate of change of the angular velocity, so that the adjustment speed of the windward surface of the fan at each moment between the two node moments can be solved by the rate of change, thereby reducing the amount of data that needs to be transmitted, alleviating the pressure of data transmission, and improving the efficiency of data transmission.

FIG2 exemplarily shows a schematic diagram of a network traffic control system applicable to a domestically produced wind turbine master control according to an embodiment of the present invention, wherein the system comprises:

A first data acquisition module, at the end time of the current control cycle, acquires predicted wind speed data and predicted wind direction data of the target location at multiple times of the next control cycle according to the weather forecast data of the target location where the wind turbine is located;

A first yaw angle acquisition module, which acquires a first yaw angle of the windward surface of the wind turbine at the end time of the current control cycle;

A theoretical yaw angle acquisition module, which determines the theoretical yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle according to the predicted wind direction data;

A first adjustment mode acquisition module determines an adjustment mode of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle according to the theoretical yaw angle, the predicted wind speed data, the first yaw angle and the maximum adjustment speed of the yaw angle of the windward surface of the wind turbine;

A node time acquisition module determines the node time of the adjustment method according to the adjustment method of the yaw angle of the windward surface of the wind turbine at multiple times in the next control cycle;

an adjustment change mode acquisition module, which performs default settings on the adjustment modes of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle according to the node moment, and obtains the adjustment mode of the yaw angle of the windward surface of the wind turbine at the node moment, and the adjustment change mode in the time period between adjacent node moments;

A control signal generating module, generating a fan control signal according to the adjustment mode of the yaw angle of the windward surface of the fan at the node moment and the adjustment change mode of the time period between adjacent node moments;

The control signal sending module sends the fan control signal to the fan controller.

The present invention may be a method, an apparatus, a system and/or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for executing various aspects of the present invention.

It should be understood by those skilled in the art that the embodiments of the present invention described above and shown in the accompanying drawings are only examples and do not limit the present invention. The purpose of the present invention has been fully and effectively achieved. The functional and structural principles of the present invention have been demonstrated and explained in the embodiments, and the embodiments of the present invention may be deformed or modified in any way without departing from the principles.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims (2)

1. A network traffic control method applicable to a domestically produced wind turbine master control, characterized by comprising: At the end of the current control cycle, based on the weather forecast data of the target location where the wind turbine is located, the predicted wind speed data and predicted wind direction data of the target location at multiple times in the next control cycle are obtained; Acquire a first yaw angle of the windward surface of the wind turbine at the end time of the current control cycle; Determine the theoretical yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle according to the predicted wind direction data, the theoretical yaw angle being the yaw angle that makes the windward surface of the wind turbine face the wind direction; Determining a mode for adjusting the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle according to the theoretical yaw angle, the predicted wind speed data, the first yaw angle and the maximum adjustment speed of the yaw angle of the windward surface of the wind turbine; Determining node moments of the adjustment method according to the adjustment method of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle; According to the node moment, a default setting is made for the adjustment mode of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle, and the adjustment mode of the yaw angle of the windward surface of the wind turbine at the node moment and the adjustment change mode in the time period between adjacent node moments are obtained; Generate a wind turbine control signal according to the adjustment mode of the yaw angle of the windward surface of the wind turbine at the node moment and the adjustment change mode in the time period between adjacent node moments; Sending fan control signals to fan controllers; According to the theoretical yaw angle, the predicted wind speed data, the first yaw angle and the maximum adjustment speed of the yaw angle of the windward surface of the wind turbine, determining the adjustment method of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle, including: Determining whether it is necessary to adjust the yaw angle of the windward surface of the wind turbine according to the theoretical yaw angle, the predicted wind speed data and the first yaw angle; If it is necessary to adjust the yaw angle of the windward surface of the wind turbine, determine the constraint conditions of the adjustment mode optimization model according to the theoretical yaw angle, the predicted wind speed data, the first yaw angle and the maximum adjustment speed of the yaw angle of the windward surface of the wind turbine; Determining an objective function of a regulation mode optimization model according to the predicted wind speed data and the theoretical yaw angle; According to the constraint conditions and objective function of the adjustment mode optimization model, determining the windward surface adjustment speed of the yaw angle of the windward surface of the wind turbine between each adjacent moment in the next control cycle; The windward surface adjustment speed between the i-th moment and the i+1-th moment in the next control cycle is determined as the adjustment mode at the i-th moment; Determining whether it is necessary to adjust the yaw angle of the windward surface of the wind turbine according to the theoretical yaw angle, the predicted wind speed data and the first yaw angle includes: According to the formula , Obtain the adjustment demand coefficient D, where is the predicted wind speed data at the i-th moment of the next control cycle, is the theoretical yaw angle of the windward side of the wind turbine at the i-th moment in the next control cycle, is the first yaw angle, n is the number of moments in the next control cycle; If the adjustment demand coefficient is greater than or equal to the preset coefficient threshold, it is determined that the yaw angle of the windward surface of the wind turbine needs to be adjusted; If the yaw angle of the windward surface of the wind turbine needs to be adjusted, the constraint conditions of the adjustment mode optimization model are determined according to the theoretical yaw angle, the predicted wind speed data, the first yaw angle and the maximum adjustment speed of the yaw angle of the windward surface of the wind turbine, including: According to the formula , , , Determine the constraints of the adjustment mode optimization model, where: is the predicted average wind flux between the i-th moment and the i+1-th moment in the next control cycle, is the predicted wind speed data at the i-th moment of the next control cycle, is the predicted wind speed data at the i+1th moment of the next control cycle, is the theoretical yaw angle of the windward side of the wind turbine at the i-th moment in the next control cycle, is the theoretical yaw angle of the windward side of the wind turbine at the i+1th moment in the next control cycle, is the predicted yaw angle of the windward side of the wind turbine at the i-th moment in the next control cycle. When i=1, is the first yaw angle, is the predicted yaw angle of the windward side of the wind turbine at the i+1th moment in the next control cycle, is the windward surface adjustment speed of the fan between the i-th moment and the i+1-th moment in the next control cycle, is the time interval between adjacent moments of the next control cycle, is the maximum adjustment speed of the yaw angle of the windward side of the wind turbine, is the area of the windward side of the fan; According to the predicted wind speed data and the theoretical yaw angle, determining the objective function of the adjustment mode optimization model includes: According to the formula , Determine the objective function of the regulation mode optimization model, where n is the number of moments in the next control cycle and max is the maximization function; According to the adjustment method of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle, determining the node moment of the adjustment method includes: According to the formula , Determine the node discrimination conditions C1, C2 and C3, where: is the windward surface adjustment speed of the fan between the i+1th moment and the i+2th moment in the next control cycle, is the windward adjustment speed of the fan between the i-1th moment and the i+1th moment in the next control cycle, is a first preset coefficient greater than 1, is a first preset coefficient less than 1; When any one of the node determination conditions C1, C2 and C3 is satisfied, the i+1th moment of the next control cycle is determined as the node moment, and the 1st moment and the n-1th moment of the next control cycle are determined as the node moments; According to the node moment, a default setting is performed on the adjustment mode of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle, and the adjustment mode of the yaw angle of the windward surface of the wind turbine at the node moment and the adjustment change mode of the time period between adjacent node moments are obtained, including: Get the adjustment method of each node moment; Get the adjustment method of the previous moment of other node moments except the first node moment; According to the formula , Determine the adjustment change mode between the kth node time and the k+1th node time ,in, is the adjustment method at the kth node moment, is the adjustment method of the moment before the k+1th node moment, is the k+1th node moment, is the kth node moment, and the adjustment change mode between the kth node moment and the k+1th node moment It represents the rate of change of angular velocity between the kth node time and the k+1th node time. 2. A network traffic control system applicable to a domestically produced wind turbine master control for executing the method according to claim 1, characterized in that it comprises: A first data acquisition module, at the end time of the current control cycle, acquires predicted wind speed data and predicted wind direction data of the target location at multiple times of the next control cycle according to the weather forecast data of the target location where the wind turbine is located; A first yaw angle acquisition module, which acquires a first yaw angle of the windward surface of the wind turbine at the end time of the current control cycle; A theoretical yaw angle acquisition module, which determines the theoretical yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle according to the predicted wind direction data; A first adjustment mode acquisition module determines an adjustment mode of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle according to the theoretical yaw angle, the predicted wind speed data, the first yaw angle and the maximum adjustment speed of the yaw angle of the windward surface of the wind turbine; A node time acquisition module determines the node time of the adjustment method according to the adjustment method of the yaw angle of the windward surface of the wind turbine at multiple times in the next control cycle; an adjustment change mode acquisition module, which performs default settings on the adjustment modes of the yaw angle of the windward surface of the wind turbine at multiple moments in the next control cycle according to the node moment, and obtains the adjustment mode of the yaw angle of the windward surface of the wind turbine at the node moment, and the adjustment change mode in the time period between adjacent node moments; A control signal generating module, generating a fan control signal according to the adjustment mode of the yaw angle of the windward surface of the fan at the node moment and the adjustment change mode of the time period between adjacent node moments; The control signal sending module sends the fan control signal to the fan controller.