A wind turbine generator water cooling control method, system, device and medium

Abstract

The present application relates to the technical field of water cooling control, and in particular to a method, system, device and medium for water cooling control of a wind turbine. The present application first obtains the operating parameters and temperature rise prediction information of the wind turbine, then calculates the flow rate adjustment requirements based on the coolant characteristic parameters, and then dynamically adjusts the flow rate through a variable frequency water pump, thereby starting preventive cooling before the temperature reaches the peak value; more precise temperature control is achieved, and the flow rate control strategy is optimized by considering the coolant characteristics, which significantly improves the cooling efficiency.

Description

Technical Field

[0001] The present application relates to the technical field of water cooling control, and in particular to a method, system, equipment and medium for water cooling control of a wind turbine generator. Background Art

[0002] With the rapid development of the new energy industry, wind power generation, as an important component of clean energy, plays an increasingly important role in the transformation of the global energy structure. Wind turbines will generate a lot of heat during long-term operation. If the heat is not dissipated in time, it is easy to cause overheating and damage to key components, affecting the operating efficiency and service life of the generator set.

[0003] The currently commonly used cooling solution for wind turbines is to set a fixed speed water pump in the cooling circuit and cool the key components of the generator through a water cooling system. The system monitors the temperature of each component in real time through a temperature sensor. When it detects that the temperature exceeds the preset threshold, the water pump is started for cooling and stops when the temperature drops to a safe range. However, the cooling method of the traditional fixed speed water pump has a lag, and often starts cooling only when the temperature of the component has reached a high value, and cannot prevent the temperature from being too high in advance; at the same time, because the actual cooling needs are not taken into account, it is easy to cause energy waste and cannot achieve accurate temperature control; this situation needs to be further improved. Summary of the invention

[0004] In order to solve the problem that the existing cooling method has hysteresis, easily causes energy waste, and cannot achieve accurate temperature control, the present application provides a wind turbine water cooling control method, system, equipment and medium, which adopts the following technical solutions: In a first aspect, the present application provides a wind turbine water cooling control method, comprising the following steps: Obtaining the operating parameters, key part identifications and current operating time of the wind turbine generator, and based on the operating parameters, predicting the temperature rise information of the generator, the temperature rise information including the predicted temperature value and the time when the temperature peak occurs; Acquiring a current temperature value of the coolant and coolant characteristic parameters, wherein the coolant characteristic parameters include specific heat capacity, thermal conductivity, and flow viscosity; Based on the current temperature value, the predicted temperature value and the key part identifier, determining the flow rate adjustment information of the coolant, wherein the flow rate adjustment information includes the flow rate that needs to be adjusted and the flow rate adjustment value or the flow rate that does not need to be adjusted; When the flow rate adjustment information indicates that the flow rate needs to be adjusted, the speed power of the variable frequency water pump is determined based on the pre-cooling time, the coolant characteristic parameter and the flow rate adjustment value, and the pre-cooling time is the time difference between the temperature peak time and the current operation time; A water pump control signal is generated based on the pre-cooling time and the speed power to control the variable frequency water pump to adjust the coolant flow rate. The variable frequency water pump is arranged in a cooling circuit of the wind turbine.

[0005] By adopting the above technical solution, the existing water cooling system usually uses a fixed speed water pump for cooling, but this method often starts cooling when the components have heated to a relatively high temperature. For example, when the generator set is running at full load for a long time, the temperature of the key components may exceed 80°C before cooling is triggered, which not only affects the life of the equipment, but also causes unnecessary energy consumption. The present application first obtains the operating parameters and temperature rise prediction information of the wind turbine, and then accurately calculates the flow rate adjustment requirements based on the coolant characteristic parameters, and then realizes dynamic adjustment of the flow rate through a variable frequency water pump, so as to start preventive cooling before the temperature reaches the peak value. More precise temperature control is achieved, and the cooling efficiency is significantly improved by optimizing the flow rate control strategy by considering the coolant characteristics.

[0006] Optionally, the operating parameters include real-time operating status information, load status data and temperature monitoring data, and obtaining the operating parameters and key part identifications of the wind turbine specifically includes the following steps: Obtain generator speed, output power and wind speed data to obtain real-time operating status information; According to the real-time operation status information, corresponding load status data is acquired; Based on the load status data, determining key part identifiers, the key part identifiers including stator windings, rotor windings, bearings and power electronic devices; According to the key part identification, the temperature monitoring data of each part is obtained.

[0007] By adopting the above technical scheme, since the heating characteristics of various components of wind turbines under different operating conditions are significantly different, traditional water cooling control methods often adopt a unified control strategy and fail to perform differentiated control according to the actual cooling needs of different components; the present application first obtains real-time operating status information, and then analyzes the load status based on this information, and then determines the key parts that need to be monitored, and finally collects the temperature data of each part in a targeted manner, thereby establishing a complete operating parameter collection system; it realizes accurate identification of the operating status of each component of the generator, and provides a reliable data basis for subsequent differentiated cooling control.

[0008] Optionally, based on the operating parameters, predicting the temperature rise information of the generator specifically includes the following steps: Obtain wind farm weather forecast data and grid load data to obtain environmental prediction information; Obtaining temperature change trends based on the environmental prediction information and historical operating data; The predicted temperature value and the time when the temperature peak occurs are determined according to the temperature change trend.

[0009] By adopting the above technical solution, during the peak period of electricity consumption in summer, the temperature of the generator may rise sharply in a short period of time due to the dual influence of weather and load, and traditional methods cannot provide early warning and response; this application first obtains environmental forecast information, including weather changes and electricity load forecasts for future periods, and then correlates and analyzes this information with historical operating data to obtain temperature change trends, and finally determines the predicted temperature value and the time when the temperature peak occurs through data modeling; through the collaborative analysis of multi-dimensional data, accurate prediction of temperature changes is achieved, providing a reliable decision-making basis for active cooling control.

[0010] Optionally, based on the current temperature value, the predicted temperature value and the key part identifier, determining the flow rate adjustment information of the coolant specifically comprises the following steps: Based on the preset correspondence between the key part identification and the standard temperature and the key part identification, determining the standard temperature limit value corresponding to the key part identification; Determine a temperature difference between the standard temperature limit and the predicted temperature value, and determine whether the temperature difference is greater than a preset temperature difference threshold; If the temperature difference is greater than a preset temperature difference threshold, determining that the flow rate adjustment information of the coolant is the flow rate that needs to be adjusted; When the flow rate adjustment information of the coolant is the flow rate that needs to be adjusted, the flow rate adjustment value of the coolant is determined based on the standard temperature limit value and the current temperature value.

[0011] By adopting the above technical scheme, since different components of wind turbines have significant differences in temperature sensitivity and tolerance, existing cooling control methods usually use a unified temperature threshold to determine whether the coolant flow rate needs to be adjusted, which cannot meet the differentiated temperature control requirements of various components; the present application first determines the standard temperature limit of each component according to a preset corresponding relationship, and then determines whether the flow rate needs to be adjusted by calculating the difference between the predicted temperature value and the standard temperature limit. When the difference exceeds the threshold, the required flow rate adjustment value is accurately calculated based on the current temperature value; accurate temperature control of each component is achieved, avoiding the problem of over-cooling or insufficient cooling.

[0012] Optionally, the method further comprises the following steps: Get external environment temperature data; Calculate the difference between the external environment temperature data and the preset antifreeze critical temperature value; Based on the difference, determining a control parameter of the heating device; A heating control signal is generated according to the control parameter to control the heating device to heat the coolant.

[0013] By adopting the above-mentioned technical scheme, the present application first obtains the external ambient temperature data, then calculates the difference between the external ambient temperature and the preset antifreeze critical temperature, determines the optimal heating control parameters based on the difference, and finally realizes precise control of the heating device through the heating control signal; by establishing a correlation mechanism between ambient temperature and heating control, precise regulation of the coolant temperature is achieved, which not only ensures the safe operation of the system, but also avoids energy waste.

[0014] Optionally, the method further comprises the following steps: Acquire temperature data of each key part according to the key part identification, and calculate the temperature change rate; Determining whether the temperature change rate exceeds a preset threshold value; Determine the emergency response level based on the judgment results; According to the emergency response level, calculate the maximum speed value of the variable frequency water pump; Based on the maximum rotation speed value, an emergency control signal is generated, and a fault warning message is sent to a control center.

[0015] By adopting the above technical scheme, since the temperature of wind turbines may rise sharply under abnormal operating conditions, the traditional water-cooling control system lacks a rapid emergency response mechanism and can only take simple shutdown protection measures. For example, when the temperature of the bearing rises rapidly in a short period of time due to poor lubrication, if effective cooling measures are not taken in time, it may cause serious damage to the equipment; the application first calculates the temperature change rate of each key part, and then determines the severity of the event by comparing with the preset threshold, and then determines the emergency response level based on the severity, and finally calculates the maximum cooling capacity required according to the response level and issues a warning message at the same time; it achieves rapid and accurate cooling under abnormal conditions, which not only avoids equipment damage but also ensures reliable operation of the system.

[0016] In a second aspect, the present application provides a wind turbine water cooling control system, comprising: A temperature rise information acquisition module is used to acquire the operating parameters, key part identification and current operating time of the wind turbine generator, and based on the operating parameters, predict the temperature rise information of the generator, the temperature rise information including the predicted temperature value and the time when the temperature peak occurs; A coolant information acquisition module, used to acquire the current temperature value of the coolant and coolant characteristic parameters, wherein the coolant characteristic parameters include specific heat capacity, thermal conductivity and flow viscosity; A flow rate adjustment information determination module, used to determine the flow rate adjustment information of the coolant based on the current temperature value, the predicted temperature value and the key part identifier, the flow rate adjustment information including the flow rate that needs to be adjusted and the flow rate adjustment value or the flow rate that does not need to be adjusted; A speed and power determination module, for determining the speed and power of the variable frequency water pump based on the pre-cooling time, the coolant characteristic parameter and the flow rate adjustment value when the flow rate adjustment information indicates that the flow rate needs to be adjusted, wherein the pre-cooling time is the time difference between the time when the temperature peak occurs and the current operation time; The water pump control signal generating module is used to generate a water pump control signal based on the pre-cooling time and the speed power to control the variable frequency water pump to adjust the coolant flow rate. The variable frequency water pump is arranged in the cooling circuit of the wind turbine.

[0017] In a third aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned wind turbine water cooling control method when executing the computer program.

[0018] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-mentioned wind turbine water cooling control method.

[0019] In summary, the present application includes at least one of the following beneficial technical effects: 1. This application first obtains the operating parameters and temperature rise prediction information of the wind turbine, then accurately calculates the flow rate adjustment requirements based on the coolant characteristic parameters, and then dynamically adjusts the flow rate through a variable frequency water pump, so as to start preventive cooling before the temperature reaches the peak; more precise temperature control is achieved, and the flow rate control strategy is optimized by considering the coolant characteristics, which significantly improves the cooling efficiency; 2. Since the heating characteristics of various components of wind turbines under different operating conditions are significantly different, traditional water cooling control methods often adopt a unified control strategy and fail to perform differentiated control according to the actual cooling needs of different components. This application first obtains real-time operating status information, then analyzes the load status based on this information, and then determines the key parts that need to be monitored, and finally collects temperature data of each part in a targeted manner, thereby establishing a complete operating parameter collection system; it realizes accurate identification of the operating status of each component of the generator, and provides a reliable data basis for subsequent differentiated cooling control; 3. Since different components of wind turbines have significant differences in their sensitivity and tolerance to temperature, existing cooling control methods usually use a unified temperature threshold to determine whether the coolant flow rate needs to be adjusted, which cannot meet the differentiated temperature control requirements of various components; the present application first determines the standard temperature limit of each component based on a preset correspondence, and then determines whether the flow rate needs to be adjusted by calculating the difference between the predicted temperature value and the standard temperature limit. When the difference exceeds the threshold, the required flow rate adjustment value is accurately calculated based on the current temperature value; accurate temperature control of each component is achieved, avoiding the problem of over-cooling or insufficient cooling. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flow chart of a water cooling control method for a wind turbine generator according to an embodiment of the present application; Figure 2 This is a schematic diagram of the process of step S110 in a wind turbine water cooling control method according to an embodiment of the present application. Figure 1 ; Figure 3 This is a schematic diagram of the process of step S110 in a wind turbine water cooling control method according to an embodiment of the present application. Figure 2 ; Figure 4 It is a flow chart of step S130 in a wind turbine water cooling control method according to an embodiment of the present application; Figure 5 It is a schematic diagram of the process of antifreeze in a water cooling control method for a wind turbine generator according to an embodiment of the present application; Figure 6 It is a schematic diagram of the process of emergency response in a wind turbine water cooling control method according to an embodiment of the present application; Figure 7 This is a module schematic diagram of a wind turbine water cooling control system according to an embodiment of the present application; Figure 8 It is a diagram of the internal structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0021] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more listed items.

[0022] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0023] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0024] In a first aspect, the present application provides a wind turbine water cooling control method, referring to Figure 1 , including the following steps: S110, obtaining the operating parameters, key part identifications and current operating time of the wind turbine generator, and predicting the temperature rise information of the generator based on the operating parameters, the temperature rise information including the predicted temperature value and the time when the temperature peak occurs.

[0025] In this embodiment, the operating parameters and current time information are obtained through the SCADA system of the wind turbine, and the key part identification information is read from the control system database. The operating parameters mainly include the real-time operation data of the generator, which is used to reflect the current working status of the equipment; the key part identification is used to determine the key areas for temperature monitoring, which are usually parts of the generator that are prone to high temperatures; the current operating time is used for subsequent calculation of the pre-cooling time. The temperature rise prediction adopts an analysis method based on historical data, and predicts the temperature change trend in the future by establishing a temperature change model, including the highest temperature value that may be reached and the specific time when the temperature is reached.

[0026] S120, obtaining the current temperature value of the coolant and the coolant characteristic parameters, where the coolant characteristic parameters include specific heat capacity, thermal conductivity, and flow viscosity.

[0027] In this embodiment, the current temperature value of the coolant is collected in real time by a temperature sensor installed in the cooling system, and the coolant characteristic parameters are read from the system configuration file. The current temperature value reflects the immediate working status of the cooling system and is an important basis for judging whether the cooling capacity needs to be adjusted. The coolant characteristic parameters include three key physical quantities: specific heat capacity, thermal conductivity, and flow viscosity. These parameters directly affect the cooling effect. Different types of coolants have different characteristic parameter values, and need to be configured accordingly according to the actual coolant used.

[0028] Specifically, the configuration file contains a matrix of characteristic parameters of different types of coolants in different temperature ranges. The system can automatically select the corresponding parameter values ​​according to the type of coolant currently in use and the operating temperature range. The system pre-tests the performance of the coolant in a laboratory environment using high-precision physical property testing equipment, and then inputs the test data into a parameter fitting program to generate a functional relationship between each characteristic parameter and temperature. Finally, these functional relationships are converted into discrete parameter matrices and stored in the configuration file.

[0029] S130. Determine flow rate adjustment information of the coolant based on the current temperature value, the predicted temperature value and the key part identifier, where the flow rate adjustment information includes the flow rate that needs to be adjusted and the flow rate adjustment value or the flow rate that does not need to be adjusted.

[0030] In this embodiment, the coolant flow rate adjustment strategy is determined based on the current temperature value, the predicted temperature value and the key part identification. The system first queries the corresponding standard temperature limit from the preset temperature limit data table according to the key part identification. These limits are the safe operating temperature range determined based on the temperature resistance characteristics of each component. By comparing the difference between the predicted temperature value and the standard temperature limit, combined with the current measured temperature, the system can determine whether the coolant flow rate needs to be adjusted and calculate the specific adjustment value. The specific calculation parameters and thresholds can be optimized and adjusted based on actual operating experience.

[0031] S140. When the flow rate adjustment information indicates that the flow rate needs to be adjusted, the speed power of the variable frequency water pump is determined based on the pre-cooling time, the coolant characteristic parameters and the flow rate adjustment value. The pre-cooling time is the time difference between the temperature peak time and the current operating time.

[0032] In this embodiment, after determining that the flow rate needs to be adjusted, the system combines the precooling time, coolant characteristic parameters and flow rate adjustment value to calculate the optimal operating parameters of the variable frequency water pump. The precooling time reflects how long in advance the system needs to start adjusting the cooling capacity, and this time window directly affects the cooling effect. The speed power calculation of the variable frequency water pump comprehensively considers the fluid resistance and heat exchange efficiency, and determines the most economical and effective operating power by establishing a mathematical model.

[0033] Specifically, when it is predicted that a temperature peak may occur in 2 hours, the system will calculate the required pre-cooling time in advance. For example, if the current time is 14:00 and the temperature peak is predicted to occur at 16:00, the pre-cooling time is 2 hours. Based on this duration, combined with the previously determined flow rate adjustment value (such as increasing from 2m / s to 2.5m / s), the system uses fluid mechanics formulas to calculate the required water pump speed and power. The calculation takes into account the effect of changes in the viscosity of the coolant on power consumption. For example, at 20°C, increasing the flow rate by 0.5m / s may require an increase in the water pump power by 0.5kW. The system will select a combination of operating parameters that can meet the flow rate requirements with minimal power consumption.

[0034] S150, generating a water pump control signal based on the pre-cooling time and the speed power to control the variable frequency water pump to adjust the coolant flow rate, the variable frequency water pump being arranged in the cooling circuit of the wind turbine.

[0035] In this embodiment, the calculated speed power parameters are converted into a standard water pump control signal format. It includes the start time, running time and speed curve. The system adopts a segmented control strategy, dividing the pre-cooling time into several control cycles, each cycle has a corresponding speed setting value. This segmented control method can achieve a smooth transition of the water pump speed and avoid sudden changes causing impact on the system.

[0036] Specifically, a time-based piecewise function is used to implement it. The system divides the pre-cooling time T into n control cycles, and the duration of each cycle is T / n. The speed curve is generated by piecewise linear interpolation to ensure a smooth transition of speed changes between adjacent control cycles to avoid shocks to the water pump. First, the initial speed S0 and the target speed S1 are determined, and the total speed change ΔS=S1-S0 is calculated. Then, the pre-cooling time T is divided into n equal-length cycles. For the i-th cycle (i from 1 to n), the speed setting value Si=S0+(ΔS×i) / n. Furthermore, in order to achieve a smooth transition, a buffer zone can be added between adjacent cycles, and a quadratic function can be used for curve fitting. The duration of the buffer zone is 20% of a single cycle.

[0037] In one embodiment, the operating parameters include real-time operating status information, load status data and temperature monitoring data. Figure 2 In step S110, the operation parameters and key part identifications of the wind turbine are obtained, which specifically includes the following steps: S111. Obtain generator speed, output power and wind speed data to obtain real-time operating status information.

[0038] In this embodiment, the wind turbine SCADA monitoring system collects the unit operation data in real time. The system is equipped with a high-precision sensor network, including a Hall speed sensor, a power analyzer, and an anemometer. The data collected by these sensors are initially filtered and transmitted to the data acquisition unit through the industrial field bus to form a real-time operation status information data stream.

[0039] S112. Obtain corresponding load status data according to the real-time operation status information.

[0040] In this embodiment, the load characteristic curve is used to calculate the load status data based on the real-time operation status information. The system has multiple sets of load characteristic curves built in, which reflect the load distribution under different operating conditions. The load status data includes three dimensions: mechanical load, electrical load, and thermal load. The system extracts key features from the real-time operation status information through a feature extraction algorithm and maps them to the corresponding load status space.

[0041] S113. Based on the load status data, determine the key part identification, where the key part identification includes the stator winding, the rotor winding, the bearing and the power electronic device.

[0042] Among them, the key parts that need to be monitored are dynamically determined based on the load status data, and the parts that are most likely to have temperature abnormalities under the current load conditions are identified. The key parts are determined using a multi-level weight scoring mechanism that comprehensively considers the load rate, historical failure frequency, and component importance.

[0043] S114. Obtain temperature monitoring data of each part according to the key part identification.

[0044] In this embodiment, a multi-point temperature acquisition system is used to obtain temperature data of each key part. Multiple temperature measurement points are arranged at each key part according to its characteristics to form a temperature field distribution monitoring network. The system uses real-time data stream processing technology to ensure the timeliness and continuity of temperature data.

[0045] In one embodiment, referring to Figure 3 In step S110, based on the operating parameters, the temperature rise information of the generator is predicted, which specifically includes the following steps: S115. Obtaining wind farm weather forecast data and power grid load data to obtain environmental prediction information.

[0046] In this embodiment, environmental forecast information is obtained through the meteorological data collection system of the wind farm and the power grid dispatching center. The meteorological forecast data includes the predicted values ​​of wind speed, wind direction, temperature and humidity in the next 24 hours, which are provided by the meteorological station in the wind farm and the surrounding meteorological departments. The power grid load data includes the power grid dispatching plan and the load forecast curve, which reflects the possible operating conditions of the unit in the future period.

[0047] Specifically, the wind farm weather station collects real-time weather data every 10 minutes and receives numerical weather forecast results from the meteorological department at the same time; the system weights and fuses the forecast results of the two data sources to obtain more accurate local forecast values. For example, the forecast data for the next 4 hours obtained at a certain moment is: wind speed 11-13m / s, dominant wind direction northeast, temperature 22-25℃, relative humidity 65%. The grid load forecast shows that the unit needs to maintain 80-90% of the rated power output during this period.

[0048] S116. Obtain temperature change trends based on environmental prediction information and historical operation data.

[0049] In this embodiment, a deep learning model is used to analyze historical operating data and environmental prediction information to establish a temperature change trend model. The deep learning model uses a long short-term memory network structure to capture the temporal characteristics of temperature changes. The system extracts the operating data of the last 30 days from the database as training samples, including environmental parameters, operating status, and temperature records for each period. The model establishes a mapping relationship between environmental factors and temperature changes by learning from these historical data.

[0050] S117. Determine the predicted temperature value and the time when the temperature peak occurs according to the temperature change trend.

[0051] In this embodiment, based on the temperature change trend, a peak recognition algorithm is used to determine the predicted temperature value and the time when the temperature peak occurs. The system uses a numerical differentiation method to analyze the temperature change curve and identify possible extreme points. Furthermore, considering the inertial characteristics of temperature change, the system also calculates the change in the temperature rise rate to correct the peak prediction result. The influence of heat conduction between different parts is also considered in the prediction process, which improves the accuracy of the prediction.

[0052] In one embodiment, referring to Figure 4 In step S130, based on the current temperature value, the predicted temperature value and the key part identification, the flow rate adjustment information of the coolant is determined, which specifically includes the following steps: S131. Based on the preset correspondence between the key part identification and the standard temperature and the key part identification, determine the standard temperature limit value corresponding to the key part identification.

[0053] In this embodiment, a configuration database is used to store the correspondence between key part identifiers and standard temperature limits. The configuration database is built based on the technical specifications and long-term operating experience provided by the equipment manufacturer, and contains the safe temperature thresholds of each key part under different working conditions. The system uses key-value pairs to store these correspondences to ensure query efficiency. The database is updated regularly to adapt to changes in equipment performance over time.

[0054] S132: Determine the temperature difference between the standard temperature limit and the predicted temperature value, and determine whether the temperature difference is greater than a preset temperature difference threshold.

[0055] S133: If the temperature difference is greater than a preset temperature difference threshold, determine that the flow rate adjustment information of the coolant requires flow rate adjustment.

[0056] In this embodiment, the flow rate adjustment decision is made based on the temperature difference judgment result. The system adopts a fuzzy logic controller, which takes the temperature difference as an input variable and outputs flow rate adjustment suggestions. The controller's rule base is built based on a large amount of experimental data and can give appropriate adjustment suggestions based on different temperature difference levels.

[0057] S134. When the flow rate adjustment information of the coolant indicates that the flow rate needs to be adjusted, the flow rate adjustment value of the coolant is determined based on the standard temperature limit and the current temperature value.

[0058] In one embodiment, referring to Figure 5 , the method further comprises the steps of: S510: Acquire external environment temperature data.

[0059] S520: Calculate the difference between the external environment temperature data and the preset antifreeze critical temperature value.

[0060] In this embodiment, the system pre-establishes a temperature difference calculation model for evaluating antifreeze risk. The system presets the critical antifreeze temperature value based on the physical properties of the coolant, while taking into account the safety margin. The model uses real-time calculation to continuously monitor the difference between the ambient temperature and the critical value, and predicts future antifreeze risks based on the trend of the difference.

[0061] S530: Determine control parameters of the heating device based on the difference.

[0062] In this embodiment, the system uses an intelligent control algorithm to determine the control parameters of the heating device. The control parameters include heating power, heating time, target temperature, etc. The system uses a fuzzy PID controller to dynamically adjust the control parameters according to the size and change rate of the temperature difference.

[0063] Specifically, the system first selects the basic heating power level according to the temperature difference. For example, when the difference is between -5℃ and -8℃, the heating power is set to 5kW. Then, based on the specific heat capacity and flow rate of the coolant, the time required for temperature rise is calculated and the required heating time is estimated. The system will generate a control instruction set containing these parameters for subsequent heating control.

[0064] S540: Generate a heating control signal according to the control parameter to control the heating device to heat the coolant.

[0065] In one embodiment, referring to Figure 6 , the method further comprises the steps of: S610, acquiring temperature data of each key part according to the key part identifier, and calculating the temperature change rate.

[0066] S620: Determine whether the temperature change rate exceeds a preset threshold value based on the temperature change rate.

[0067] Among them, this embodiment constructs a multi-level threshold judgment system to evaluate the dangerousness of temperature changes. The system sets personalized temperature change rate thresholds for different key parts based on equipment characteristics and historical operation data. These thresholds take into account the thermal capacity, heat dissipation characteristics and safety margin of the equipment. The judgment process adopts fuzzy logic methods to improve the adaptability of the system.

[0068] Specifically, the threshold judgment execution process is as follows: the system preset temperature change rate threshold is divided into three levels, taking the stator winding as an example: the first threshold is 0.1℃ / second, the second threshold is 0.15℃ / second, and the third threshold is 0.2℃ / second. When the temperature change rate is detected to be 0.2℃ / second, the system determines that the third threshold has been reached. At the same time, the system will consider the duration of the temperature change. If the high temperature change rate lasts for more than 30 seconds, the warning level will be increased.

[0069] S630. Determine the emergency response level based on the judgment result.

[0070] Specifically, the emergency response level determination process is as follows: The system sets three emergency response levels, each corresponding to a different processing strategy. When the temperature change rate reaches 0.2℃ / second (third-level threshold) and lasts for more than 30 seconds, the system determines it as a first-level emergency response.

[0071] S640. Calculate the maximum speed of the variable frequency water pump according to the emergency response level.

[0072] Specifically, the basic speed range is first determined according to the emergency response level, and then optimized calculations are performed in combination with current system parameters (such as pipeline pressure, flow, etc.).

[0073] S650: Generate an emergency control signal based on the maximum speed value, and send a fault warning message to a control center.

[0074] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0075] In a second aspect, the present application provides a wind turbine water cooling control system. The wind turbine water cooling control system of the present application is described below in conjunction with the above-mentioned wind turbine water cooling control method.

[0076] Reference Figure 7 , a wind turbine water cooling control system, comprising: The temperature rise information acquisition module is used to obtain the operating parameters, key part identification and current operating time of the wind turbine generator, and predict the temperature rise information of the generator based on the operating parameters. The temperature rise information includes the predicted temperature value and the time when the temperature peak occurs; A coolant information acquisition module is used to obtain the current temperature value and coolant characteristic parameters of the coolant, the coolant characteristic parameters including specific heat capacity, thermal conductivity and flow viscosity; A flow rate adjustment information determination module, used to determine the flow rate adjustment information of the coolant based on the current temperature value, the predicted temperature value and the key part identification, the flow rate adjustment information including the flow rate that needs to be adjusted and the flow rate adjustment value or the flow rate that does not need to be adjusted; The speed and power determination module is used to determine the speed and power of the variable frequency water pump based on the pre-cooling time, the coolant characteristic parameters and the flow rate adjustment value when the flow rate adjustment information indicates that the flow rate needs to be adjusted. The pre-cooling time is the time difference between the temperature peak time and the current operation time; The water pump control signal generating module is used to generate a water pump control signal based on the pre-cooling time and the speed power to control the variable frequency water pump to adjust the coolant flow rate. The variable frequency water pump is arranged in the cooling circuit of the wind turbine.

[0077] In one embodiment, the temperature rise information acquisition module includes: An operation status acquisition unit is used to acquire generator speed, output power and wind speed data to obtain real-time operation status information; A load data acquisition unit, used to acquire corresponding load status data according to real-time operation status information; A key part determination unit, used for determining key part identification based on load state data, where the key part identification includes stator winding, rotor winding, bearing and power electronic device; The temperature monitoring unit is used to obtain temperature monitoring data of each part according to the key part identification.

[0078] In one embodiment, the temperature rise information acquisition module further includes: An environmental information acquisition unit is used to acquire wind farm weather forecast data and power grid load data to obtain environmental prediction information; Trend analysis unit, used to obtain temperature change trends based on environmental prediction information and historical operation data; The temperature rise prediction unit is used to determine the predicted temperature value and the time when the temperature peak occurs according to the temperature change trend.

[0079] In one embodiment, the flow rate adjustment information determination module includes: A standard temperature determination unit, used for determining a standard temperature limit value corresponding to the key part identifier based on a preset correspondence relationship between the key part identifier and the standard temperature and the key part identifier; A temperature difference judgment unit is used to determine the temperature difference between the standard temperature limit and the predicted temperature value, and to judge whether the temperature difference is greater than a preset temperature difference threshold; A flow rate adjustment information determining unit, configured to determine that the flow rate adjustment information of the coolant is that the flow rate needs to be adjusted when the temperature difference is greater than a preset temperature difference threshold; The flow rate adjustment value determining unit is used to determine the flow rate adjustment value of the coolant based on the standard temperature limit value and the current temperature value when the flow rate adjustment information of the coolant indicates that the flow rate needs to be adjusted.

[0080] In one embodiment, the system further comprises: Ambient temperature acquisition module, used to obtain external ambient temperature data; A difference calculation module is used to calculate the difference between the external environment temperature data and the preset antifreeze critical temperature value; A control parameter determination module, used to determine the control parameters of the heating device based on the difference; The heating control module is used to generate a heating control signal according to the control parameters to control the heating device to heat the coolant.

[0081] In one embodiment, the system further comprises: The temperature change rate calculation module is used to obtain the temperature data of each key part according to the key part identification and calculate the temperature change rate; A threshold judgment module is used to judge whether the temperature exceeds a preset threshold according to the temperature change rate; A response level determination module, used to determine the emergency response level based on the judgment result; The maximum speed calculation module is used to calculate the maximum speed value of the variable frequency water pump according to the emergency response level; The emergency control module is used to generate an emergency control signal based on the maximum speed value and send a fault warning message to the control center.

[0082] In one embodiment, the present application provides an electronic device, which may be a server, and its internal structure diagram may be as follows: Figure 8As shown. The electronic device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the electronic device is used to store data. The network interface of the electronic device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a wind turbine water cooling control method is implemented.

[0083] Those skilled in the art will understand that Figure 8 The structure shown in the figure is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the electronic device to which the scheme of the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0084] In one embodiment, an electronic device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0085] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the above-mentioned computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0086] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A wind turbine water cooling control method, characterized in that: The steps include: Obtaining the operating parameters, key part identifications and current operating time of the wind turbine generator, and based on the operating parameters, predicting the temperature rise information of the generator, the temperature rise information including the predicted temperature value and the time when the temperature peak occurs; Acquiring a current temperature value of the coolant and coolant characteristic parameters, wherein the coolant characteristic parameters include specific heat capacity, thermal conductivity, and flow viscosity; Based on the current temperature value, the predicted temperature value and the key part identifier, determining the flow rate adjustment information of the coolant, wherein the flow rate adjustment information includes the flow rate that needs to be adjusted and the flow rate adjustment value or the flow rate that does not need to be adjusted; When the flow rate adjustment information indicates that the flow rate needs to be adjusted, the speed power of the variable frequency water pump is determined based on the pre-cooling time, the coolant characteristic parameter and the flow rate adjustment value, and the pre-cooling time is the time difference between the temperature peak time and the current operation time; A water pump control signal is generated based on the pre-cooling time and the speed power to control the variable frequency water pump to adjust the coolant flow rate. The variable frequency water pump is arranged in a cooling circuit of the wind turbine.

2. The wind turbine water cooling control method according to claim 1, characterized in that: The operating parameters include real-time operating status information, load status data and temperature monitoring data. Obtaining the operating parameters and key part identifications of the wind turbine specifically includes the following steps: Obtain generator speed, output power and wind speed data to obtain real-time operating status information; According to the real-time operation status information, corresponding load status data is acquired; Based on the load status data, determining key part identifiers, the key part identifiers including stator windings, rotor windings, bearings and power electronic devices; According to the key part identification, the temperature monitoring data of each part is obtained.

3. The wind turbine water cooling control method according to claim 1, characterized in that: Based on the operating parameters, predicting the temperature rise information of the generator specifically includes the following steps: Obtain wind farm weather forecast data and grid load data to obtain environmental prediction information; Obtaining temperature change trends based on the environmental prediction information and historical operating data; The predicted temperature value and the time when the temperature peak occurs are determined according to the temperature change trend.

4. The wind turbine water cooling control method according to claim 1, characterized in that: Based on the current temperature value, the predicted temperature value and the key part identifier, determining the flow rate adjustment information of the coolant specifically includes the following steps: Based on the preset correspondence between the key part identification and the standard temperature and the key part identification, determining the standard temperature limit value corresponding to the key part identification; Determine a temperature difference between the standard temperature limit and the predicted temperature value, and determine whether the temperature difference is greater than a preset temperature difference threshold; If the temperature difference is greater than a preset temperature difference threshold, determining that the flow rate adjustment information of the coolant is the flow rate that needs to be adjusted; When the flow rate adjustment information of the coolant is the flow rate that needs to be adjusted, the flow rate adjustment value of the coolant is determined based on the standard temperature limit value and the current temperature value.

5. The wind turbine water cooling control method according to claim 1, characterized in that: The method further comprises the steps of: Get external environment temperature data; Calculate the difference between the external environment temperature data and the preset antifreeze critical temperature value; Based on the difference, determining a control parameter of the heating device; A heating control signal is generated according to the control parameter to control the heating device to heat the coolant.

6. The wind turbine water cooling control method according to claim 1, characterized in that: The method further comprises the steps of: Acquire temperature data of each key part according to the key part identification, and calculate the temperature change rate; Determining whether the temperature change rate exceeds a preset threshold value; Determine the emergency response level based on the judgment results; According to the emergency response level, calculate the maximum speed value of the variable frequency water pump; Based on the maximum rotation speed value, an emergency control signal is generated, and a fault warning message is sent to a control center.

7. A wind turbine water cooling control system, characterized in that: include: A temperature rise information acquisition module is used to acquire the operating parameters, key part identification and current operating time of the wind turbine generator, and based on the operating parameters, predict the temperature rise information of the generator, the temperature rise information including the predicted temperature value and the time when the temperature peak occurs; A coolant information acquisition module, used to acquire the current temperature value of the coolant and coolant characteristic parameters, wherein the coolant characteristic parameters include specific heat capacity, thermal conductivity and flow viscosity; A flow rate adjustment information determination module, used to determine the flow rate adjustment information of the coolant based on the current temperature value, the predicted temperature value and the key part identifier, the flow rate adjustment information including the flow rate that needs to be adjusted and the flow rate adjustment value or the flow rate that does not need to be adjusted; A speed and power determination module, for determining the speed and power of the variable frequency water pump based on the pre-cooling time, the coolant characteristic parameter and the flow rate adjustment value when the flow rate adjustment information indicates that the flow rate needs to be adjusted, wherein the pre-cooling time is the time difference between the time when the temperature peak occurs and the current operation time; The water pump control signal generating module is used to generate a water pump control signal based on the pre-cooling time and the speed power to control the variable frequency water pump to adjust the coolant flow rate. The variable frequency water pump is arranged in the cooling circuit of the wind turbine.

8. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the wind turbine water cooling control method according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the wind turbine water cooling control method according to any one of claims 1 to 6 are implemented.

Images