Wind power fire extinguishing system processing method
Through the area division of wind farms and multi-sensor monitoring, the environment and wind motor parameters are analyzed, and the fire risk index model is established, which solves the problems of inaccurate fire risk prediction and rigid response in the existing technology, and realizes the flexibility of the wind power fire protection system. Accurate prevention and control and real-time management reduce the risk of accidents.
Patent Information
- Application Number
- CN202411444144.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-16
- Publication Date
- 2025-01-10
AI Technical Summary
The existing wind power fire protection system has shortcomings in fire prevention and control, and lacks comprehensive acquisition and in-depth analysis of environmental parameters and wind turbine operating status parameters, resulting in inaccurate fire risk prediction and rigid response methods, which increases the risk of fire accidents and harm.
By dividing the wind farm area, using multi-sensor fusion technology to monitor the fire situation, analyzing the environment and wind turbine operating status parameters, establishing a fire risk coefficient model, calculating the comprehensive fire risk index, and automatically activate corresponding fire protection measures according to the risk level to achieve Flexible and precise fire prevention and control.
It improves the accuracy of fire risk prediction, reduces false alarms and underreports, shortens response time, reduces maintenance costs of wind power projects and safety risks of technicians, and realizes real-time monitoring and efficient management of fire risks in wind farms.
Smart Images
Figure CN119294822A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of wind power fire protection, and in particular to a wind power fire protection system processing method. Background Art
[0002] With the global transformation of energy structures and the development of renewable energy, wind power, as a clean, renewable energy source, has seen widespread application and rapid growth. However, wind farm sites are often located in remote areas with inconvenient transportation. Furthermore, wind turbines are complex, tall, and often located at high altitudes. Once a fire occurs, it can spread rapidly and have serious consequences. Therefore, the research and application of wind power fire protection systems is particularly important.
[0003] The wind power fire protection system is a comprehensive system that integrates advanced fire monitoring, early warning and intelligent fire extinguishing technologies. It is designed to monitor the fire risks of wind power sites in real time, promptly detect and quickly respond to fire incidents, effectively curb the spread of fire through intelligent fire extinguishing devices, and ensure the safe operation of wind power facilities.
[0004] Existing wind power fire protection system approaches often rely on traditional fire detection methods, such as smoke detectors and temperature sensors. While these methods can provide a certain level of early warning, they still suffer from numerous deficiencies in practical application. For example, existing wind power fire protection system approaches have significant shortcomings in fire prevention and control. Specifically, they often lack comprehensive acquisition and in-depth analysis of environmental parameters (such as temperature, humidity, and wind speed) and wind turbine operating parameters (such as turbine power, turbine speed, and turbine vibration amplitude), resulting in inaccurate prediction and assessment of fire risks. Furthermore, existing systems also have significant limitations in fire response. They are typically limited to simple alarms or the initiation of pre-set fire extinguishing procedures based on fixed preset thresholds, without the ability to flexibly and precisely adjust and respond to the actual fire risk situation. This undoubtedly increases the risk and harm of fire accidents. Summary of the Invention
[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a wind power fire protection system processing method to solve the problems raised in the above-mentioned background technology.
[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: A wind power fire protection system processing method, comprising the following steps: step S1: dividing the wind farm into regions, step S2: monitoring the wind farm for fires, step S3: analyzing the environmental parameters of the wind farm, step S4: judging and optimizing the environmental fire risk coefficient, step S5: analyzing the operating status parameters of the wind turbine, step S6: judging and optimizing the wind turbine failure fire risk coefficient, step S7: establishing a comprehensive fire risk index model for the wind farm, step S8: judging the level of the comprehensive fire risk, and step S9: establishing a user interface module.
[0007] Step S1: Divide the wind farm into regions: Divide the target wind farm into i monitoring sub-regions, where i=1, 2, 3, ...n; Step S2: Fire monitoring of the wind farm: using multi-sensor fusion technology to monitor the fire situation in each monitoring sub-area, and obtain wind farm environmental parameters and wind turbine operating status parameters; Step S3: Analyzing the wind farm environmental parameters: Analyzing the wind farm environmental parameters obtained in step S2, establishing an environmental fire risk coefficient model, and calculating the environmental fire risk coefficient of each monitoring sub-area; Step S4: Determine and optimize the environmental fire risk coefficient: Determine the environmental fire risk of each monitoring sub-area based on the environmental fire risk coefficient in S3, and optimize the fire risk of the sub-area with abnormal determination results; Step S5: Analyzing the wind turbine operating state parameters: Analyzing the wind turbine operating state parameters obtained in step S2, establishing a wind turbine failure fire risk coefficient model, and calculating the wind turbine failure fire risk coefficient of each monitoring sub-area; Step S6: Determine and optimize the wind turbine failure fire risk coefficient: Determine the wind turbine operation failure risk of each monitoring sub-area based on the wind turbine failure fire risk coefficient in S5, and optimize the failure risk of the sub-area where the determination result is abnormal; Step S7: Establishing a comprehensive fire risk index model for a wind farm: Establishing a comprehensive fire risk index model for a wind farm based on the environmental fire risk coefficient and the wind turbine failure fire risk coefficient determined and optimized in steps S4 and S6, and calculating a comprehensive fire risk index for the wind farm; Step S8: Determine the comprehensive fire risk level: Compare the wind farm comprehensive fire risk index of each monitoring sub-area calculated in step S7 with a preset fire risk level range, and initiate fire fighting measures corresponding to the fire risk level based on the determination result; Step S9: Establishing a user interface module: Using Internet technology to achieve remote operation and control of the wind farm fire protection system, so that operation and maintenance personnel can understand the fire safety status inside the unit and the wind farm in real time.
[0008] Preferably, the specific division method of the wind farm is: determining the entire wind farm as a target area, and on this basis dividing each wind turbine in the wind farm into i independent monitoring sub-areas, where i=1, 2, 3, ...n.
[0009] Preferably, the multiple sensors include a temperature sensor, a flame sensor and a smoke sensor, which are used to monitor abnormal temperature, flame and smoke conditions in the wind power generation site in real time.
[0010] Preferably, the environmental parameters include temperature, wind speed and humidity; the wind turbine operating state parameters include wind turbine power, wind turbine speed and wind turbine vibration amplitude.
[0011] Preferably, the steps for calculating the environmental fire risk coefficient of each monitoring sub-area are as follows: Step S31: Calculate wind speed probability distribution function F ( v ), the expression is as follows: ,in, exp Expressed as a natural exponential function, v Expressed as wind speed, k It is expressed as a shape parameter with a value range of 1.5-2.5. c It is expressed as a scale parameter, indicating the average wind speed in the area where the wind farm is located, with a value range of 5-10m / s; Step S32: According to the wind speed probability distribution function F ( v ) Calculate wind speed v , the calculation model is as follows: , where x is A random variable uniformly distributed on Step S33: Calculate the environmental fire risk coefficient of each monitoring sub-area. The calculation model is as follows: ,in, FRC i Expressed as the environmental fire risk coefficient of each monitoring sub-area, T i Indicates the wind farm ambient temperature value of each monitoring sub-area, T max It is expressed as the maximum temperature value of the wind farm environment. T minIt is expressed as the lowest temperature value of the wind farm environment. v i It is represented by the wind speed of each monitoring sub-area, H i It is represented by the wind farm environmental humidity of each monitoring sub-area, H max It is expressed as the maximum humidity value of the wind farm environment, and e is expressed as a natural constant.
[0012] Preferably, the specific content of judging and optimizing the environmental fire risk factor in step S4 is: Step S41: Compare the environmental fire risk coefficient of each monitoring sub-area with a preset fire risk threshold. If the environmental fire risk coefficient is less than or equal to the preset fire risk threshold, it is determined that there is no fire risk in the wind farm environment. If the environmental fire risk coefficient is greater than the preset fire risk threshold, it is determined that there is a fire risk in the wind farm environment. Step S42: Fire risk optimization is performed on the monitoring sub-area where the wind farm environment is judged to have a fire risk, an early warning message is issued, and the number of the abnormal wind turbine is sent to the operation and maintenance manager. The operation and maintenance manager initiates the wind farm environment fire risk optimization strategy and displays it visually on the administrator's mobile device.
[0013] Preferably, the calculation steps of the wind turbine fault fire risk coefficient of each monitoring sub-area are as follows: Step S51: Standardize the wind turbine power, wind turbine speed, and wind turbine vibration amplitude respectively. The calculation model of linear standardization is as follows: , Among them, X represents the standardized parameters, X0 represents the initial acquisition parameters, and X min Represents the minimum value of the initial acquisition parameter, X max It is expressed as the maximum value of the initial acquisition parameters; Step S52: Calculate the wind turbine fault fire risk coefficient. The calculation model is as follows: ,in, FFC i It is expressed as the wind turbine failure fire risk coefficient of each monitoring sub-area, Rs i It is represented by the wind turbine speed of each monitoring sub-area, Rs max It is the maximum value allowed for the wind turbine speed. Va i It is expressed as the vibration amplitude of wind turbine in each monitoring sub-area, Va 0 represents the preset standard wind turbine vibration amplitude, P iExpressed as the wind turbine power of each monitoring sub-area, P 0 represents the rated power of the wind turbine. It is expressed as the standard deviation of the wind turbine rated power, and e is expressed as a natural constant.
[0014] Preferably, the specific content of judging and optimizing the wind turbine fault fire risk factor in step S6 is: Step S61: Compare the wind turbine failure fire risk coefficient of each monitoring sub-area with a preset failure fire risk threshold. If the wind turbine failure fire risk coefficient is less than or equal to the preset failure fire risk threshold, it is determined that there is no fire risk due to the wind turbine failure. If the wind turbine failure fire risk coefficient is greater than the preset failure fire risk threshold, it is determined that there is a fire risk due to the wind turbine failure. Step S62: Optimize the fault risk of the monitoring sub-area where the judgment result is that there is a fire risk due to wind turbine failure, issue a warning message, and send the number of the abnormal wind turbine to the operation and maintenance manager. The operation and maintenance manager initiates the wind turbine operation fault risk optimization strategy and visually displays it on the manager's mobile device.
[0015] Preferably, the calculation model of the wind farm comprehensive fire risk index is as follows: ,in, CFRI Expressed as the comprehensive fire risk index of wind farms, FRC i Expressed as the environmental fire risk coefficient of each monitoring sub-area, FFC i It is represented as the wind turbine failure fire risk coefficient of each monitoring sub-area, k1 and k2 are constants, and n is the total number of wind turbines in the wind farm.
[0016] Preferably, the specific content of judging the level of comprehensive fire risk in step S8 is: The comprehensive fire risk index of the wind farm is extracted and compared with the preset fire risk level range. If the comprehensive fire risk index of the wind farm is within the preset fire risk level A range, it means that the comprehensive fire risk of the wind farm has reached level one, and the level one response measures are initiated to carry out fire fighting in the wind farm; if the comprehensive fire risk index of the wind farm is within the preset fire risk level B range, it means that the comprehensive fire risk of the wind farm has reached level two, and the level two response measures are initiated to carry out fire fighting in the wind farm; if the comprehensive fire risk index of the wind farm is within the preset fire risk level C range, it means that the comprehensive fire risk of the wind farm has reached level three, and the level three response measures are initiated to carry out fire fighting in the wind farm.
[0017] Technical effects and advantages of the present invention: 1. The present invention obtains wind farm environmental parameters and wind turbine operating status parameters, analyzes and obtains environmental fire risk factors and wind turbine fault fire risk factors, and improves the accuracy of fire risk prediction through risk factor analysis and fire optimization adjustment. The present invention also obtains a comprehensive fire risk index for the wind farm through comprehensive analysis of the risk factors and compares it with a preset fire risk level range. Based on the comparison results, the present invention can automatically select and initiate fire prevention measures corresponding to the fire risk level, thereby achieving more flexible and accurate fire prevention and control. 2. This invention combines advanced data processing technology to improve the accuracy and response speed of fire detection, reduce false alarms and missed alarms, thereby reducing the maintenance costs of wind power projects and the safety risks of technicians; 3. The present invention achieves accurate positioning of early-stage fires and shortens response time through risk factor analysis and fire optimization adjustment; and achieves real-time monitoring and efficient management of wind farm fire risks through advanced sensing technology, automated control technology and data analysis methods. BRIEF DESCRIPTION OF THE DRAWINGS
[0018] The present invention is further described with reference to the accompanying drawings. However, the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without inventive effort.
[0019] Figure 1 It is a schematic diagram of the structural flow of the method of the present invention. DETAILED DESCRIPTION
[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.
[0021] See also Figure 1 As shown, the present invention provides a wind power fire protection system processing method, comprising the following steps: step S1: dividing the wind farm into regions, step S2: monitoring the wind farm for fire, step S3: analyzing the environmental parameters of the wind farm, step S4: judging and optimizing the environmental fire risk coefficient, step S5: analyzing the operating status parameters of the wind turbine, step S6: judging and optimizing the wind turbine failure fire risk coefficient, step S7: establishing a comprehensive fire risk index model for the wind farm, step S8: judging the level of the comprehensive fire risk, and step S9: establishing a user interface module.
[0022] Step S1: Divide the wind farm into regions: Divide the target wind farm into i monitoring sub-regions, where i=1, 2, 3, ...n; In this embodiment, it should be specifically explained that the specific division method of the wind farm is: the entire wind farm is determined as a target area, and on this basis, each wind turbine in the wind farm is divided into i independent monitoring sub-areas, where i=1, 2, 3, ...n.
[0023] Step S2: Fire monitoring of the wind farm: using multi-sensor fusion technology to monitor the fire situation in each monitoring sub-area, and obtain wind farm environmental parameters and wind turbine operating status parameters; In this embodiment, it should be specifically explained that the multiple sensors include a temperature sensor, a flame sensor, and a smoke sensor, which are used to monitor abnormal conditions of temperature, flame, and smoke in the wind power generation site in real time.
[0024] In this embodiment, it should be specifically explained that the environmental parameters include temperature, wind speed and humidity; and the wind turbine operating state parameters include wind turbine power, wind turbine speed and wind turbine vibration amplitude.
[0025] Step S3: Analyzing the wind farm environmental parameters: Analyzing the wind farm environmental parameters obtained in step S2, establishing an environmental fire risk coefficient model, and calculating the environmental fire risk coefficient of each monitoring sub-area; In this embodiment, it should be specifically explained that the steps for calculating the environmental fire risk coefficient of each monitoring sub-area are as follows: Step S31: Calculate wind speed probability distribution function F ( v ), the expression is as follows: ,in, exp Expressed as a natural exponential function, v Expressed as wind speed, k It is expressed as a shape parameter with a value range of 1.5-2.5. c It is expressed as a scale parameter, indicating the average wind speed in the area where the wind farm is located, with a value range of 5-10m / s; In this embodiment, it should be specifically noted that c and k in the expression can be actually measured according to the grid-connected position of the wind farm.
[0026] Step S32: According to the wind speed probability distribution function F ( v ) Calculate wind speed v , the calculation model is as follows: , where x is A random variable uniformly distributed on Step S33: Calculate the environmental fire risk coefficient of each monitoring sub-area. The calculation model is as follows: ,in, FRC i Expressed as the environmental fire risk coefficient of each monitoring sub-area, T i Indicates the wind farm ambient temperature value of each monitoring sub-area, T max It is expressed as the maximum temperature value of the wind farm environment. T min It is expressed as the lowest temperature value of the wind farm environment. v i It is represented by the wind speed of each monitoring sub-area, H i It is represented by the wind farm environmental humidity of each monitoring sub-area, H max It is expressed as the maximum humidity value of the wind farm environment, and e is expressed as a natural constant.
[0027] In this embodiment, it should be specifically noted that by obtaining wind farm environmental parameters including temperature, humidity and wind speed, the parameters are analyzed and calculated using a data analysis method to obtain the wind farm environmental fire risk coefficient. By calculating the environmental fire risk coefficient, the fire hazard level of the wind farm under different environmental conditions can be accurately assessed; this helps wind farm operators to take targeted preventive measures in periods and areas with higher fire risks, such as strengthening patrols, increasing monitoring frequency, etc., thereby effectively reducing the occurrence of fire accidents.
[0028] Step S4: Determine and optimize the environmental fire risk coefficient: Determine the environmental fire risk of each monitoring sub-area based on the environmental fire risk coefficient in S3, and optimize the fire risk of the sub-area with abnormal determination results; In this embodiment, it should be specifically explained that the specific content of judging and optimizing the environmental fire risk factor in step S4 is: Step S41: Compare the environmental fire risk coefficient of each monitoring sub-area with a preset fire risk threshold. If the environmental fire risk coefficient is less than or equal to the preset fire risk threshold, it is determined that there is no fire risk in the wind farm environment. If the environmental fire risk coefficient is greater than the preset fire risk threshold, it is determined that there is a fire risk in the wind farm environment. Step S42: Fire risk optimization is performed on the monitoring sub-area where the wind farm environment is judged to have a fire risk, an early warning message is issued, and the number of the abnormal wind turbine is sent to the operation and maintenance manager. The operation and maintenance manager initiates the wind farm environment fire risk optimization strategy and displays it visually on the administrator's mobile device.
[0029] Step S5: Analyzing the wind turbine operating state parameters: Analyzing the wind turbine operating state parameters obtained in step S2, establishing a wind turbine failure fire risk coefficient model, and calculating the wind turbine failure fire risk coefficient of each monitoring sub-area; In this embodiment, it should be specifically explained that the calculation steps of the wind turbine fault fire risk coefficient of each monitoring sub-area are as follows: Step S51: Standardize the wind turbine power, wind turbine speed, and wind turbine vibration amplitude respectively. The calculation model of linear standardization is as follows: , Among them, X represents the standardized parameters, X0 represents the initial acquisition parameters, and X min Represents the minimum value of the initial acquisition parameter, X max It is expressed as the maximum value of the initial acquisition parameters; Step S52: Calculate the wind turbine fault fire risk coefficient. The calculation model is as follows: ,in, FFC i It is expressed as the wind turbine failure fire risk coefficient of each monitoring sub-area, Rs i It is represented by the wind turbine speed of each monitoring sub-area, Rs max It is the maximum value allowed for the wind turbine speed. Va i It is expressed as the vibration amplitude of wind turbine in each monitoring sub-area, Va 0 represents the preset standard wind turbine vibration amplitude, P i Expressed as the wind turbine power of each monitoring sub-area, P 0 represents the rated power of the wind turbine. It is expressed as the standard deviation of the wind turbine rated power, and e is expressed as a natural constant.
[0030] In this embodiment, it should be specifically noted that the wind turbine speed has a positive impact on the risk of fire caused by wind turbine failure. If the wind turbine speed exceeds the maximum allowable speed of the wind turbine, it may cause excessive mechanical stress, resulting in wear or damage to mechanical components, such as bearing failure, gear wear, etc.; these failures may cause overheating, and then cause fire; the wind turbine vibration amplitude has a positive impact on the risk of fire caused by wind turbine failure. Excessive vibration amplitude may be the result of imbalance or wear of mechanical components; for example, blade imbalance, bearing damage, etc., these situations will cause local temperature rise and increase the risk of fire; the wind turbine power has a positive impact on the risk of fire caused by wind turbine failure. If the motor is in an overloaded state for a long time, that is, the actual power exceeds the rated power, the motor windings and internal components may overheat, which increases the risk of electrical failure and fire.
[0031] Step S6: Determine and optimize the wind turbine failure fire risk coefficient: Determine the wind turbine operation failure risk of each monitoring sub-area based on the wind turbine failure fire risk coefficient in S5, and optimize the failure risk of the sub-area where the determination result is abnormal; In this embodiment, it should be specifically explained that the specific content of judging and optimizing the wind turbine fault fire risk factor in step S6 is: Step S61: Compare the wind turbine failure fire risk coefficient of each monitoring sub-area with a preset failure fire risk threshold. If the wind turbine failure fire risk coefficient is less than or equal to the preset failure fire risk threshold, it is determined that there is no fire risk due to the wind turbine failure. If the wind turbine failure fire risk coefficient is greater than the preset failure fire risk threshold, it is determined that there is a fire risk due to the wind turbine failure. Step S62: Optimize the fault risk of the monitoring sub-area where the judgment result is that there is a fire risk due to wind turbine failure, issue a warning message, and send the number of the abnormal wind turbine to the operation and maintenance manager. The operation and maintenance manager initiates the wind turbine operation fault risk optimization strategy and visually displays it on the manager's mobile device.
[0032] Step S7: Establishing a comprehensive fire risk index model for a wind farm: Establishing a comprehensive fire risk index model for a wind farm based on the environmental fire risk coefficient and the wind turbine failure fire risk coefficient determined and optimized in steps S4 and S6, and calculating a comprehensive fire risk index for the wind farm; In this embodiment, it should be specifically explained that the calculation model of the wind farm comprehensive fire risk index is as follows: ,in, CFRI Expressed as the comprehensive fire risk index of wind farms, FRC i Expressed as the environmental fire risk coefficient of each monitoring sub-area, FFC iIt is represented as the wind turbine failure fire risk coefficient of each monitoring sub-area, k1 and k2 are constants, and n is the total number of wind turbines in the wind farm.
[0033] Step S8: Determine the comprehensive fire risk level: Compare the wind farm comprehensive fire risk index of each monitoring sub-area calculated in step S7 with a preset fire risk level range, and initiate fire fighting measures corresponding to the fire risk level based on the determination result; In this embodiment, it should be specifically explained that the specific content of judging the level of comprehensive fire risk in step S8 is: The comprehensive fire risk index of the wind farm is extracted and compared with the preset fire risk level range. If the comprehensive fire risk index of the wind farm is within the preset fire risk level A range, it means that the comprehensive fire risk of the wind farm has reached level one, and the level one response measures are initiated to carry out fire fighting in the wind farm; if the comprehensive fire risk index of the wind farm is within the preset fire risk level B range, it means that the comprehensive fire risk of the wind farm has reached level two, and the level two response measures are initiated to carry out fire fighting in the wind farm; if the comprehensive fire risk index of the wind farm is within the preset fire risk level C range, it means that the comprehensive fire risk of the wind farm has reached level three, and the level three response measures are initiated to carry out fire fighting in the wind farm.
[0034] In this embodiment, it is important to specify that in the wind power fire protection system, the fire prevention measures corresponding to the fire level are as follows: For a level 1 fire risk, a prevention-first strategy is typically adopted, including regular inspections of electrical equipment and cable connections to ensure there is no overheating, and the installation of temperature and smoke sensors for environmental monitoring. Furthermore, fire isolation measures, fire safety training for operators, and the provision of portable fire extinguishers are used to reduce the risk of fire.
[0035] At the Level 2 fire risk level, in addition to strengthening continuous temperature and smoke monitoring, an automatic fire extinguishing system will be installed to activate immediately upon fire detection. A detailed emergency response plan will be developed, and regular emergency drills will be conducted to ensure personnel are familiar with emergency procedures. Furthermore, fire barriers will be installed around critical equipment, and firefighting equipment will be regularly maintained to ensure it is always operational.
[0036] Targeting the third-level fire risk, a comprehensive fire monitoring network was established and a multi-stage automatic fire extinguishing system was deployed to ensure comprehensive coverage. Furthermore, an emergency command center was established, equipped with an advanced emergency management system, and employee fire safety training was strengthened. Finally, fire prevention engineering improvements and a collaborative mechanism with local fire departments ensured rapid response and effective fire control in emergencies.
[0037] Step S9: Establishing a user interface module: Using Internet technology to achieve remote operation and control of the wind farm fire protection system, so that operation and maintenance personnel can understand the fire safety status inside the unit and the wind farm in real time.
[0038] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.
[0039] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.
Claims
1. A wind power fire protection system processing method, characterized in that: The following steps are involved: Step S1: Divide the wind farm into regions: divide the target wind farm into i monitoring sub-regions, where i=1, 2, 3, ...n; Step S2: Fire monitoring of the wind farm: using multi-sensor fusion technology to monitor the fire situation in each monitoring sub-area, and obtaining wind farm environmental parameters and wind turbine operating status parameters; Step S3: Analyze the environmental parameters of the wind farm: Analyze the environmental parameters of the wind farm obtained in step S2, establish an environmental fire risk coefficient model, and calculate the environmental fire risk coefficient of each monitoring sub-area; Step S4: judging and optimizing the environmental fire risk coefficient: judging the environmental fire risk of each monitoring sub-area according to the environmental fire risk coefficient in S3, and optimizing the fire risk of the sub-area with abnormal judgment results; Step S5: analyzing the wind turbine operating state parameters: analyzing the wind turbine operating state parameters obtained in step S2, establishing a wind turbine failure fire risk coefficient model, and calculating the wind turbine failure fire risk coefficient of each monitoring sub-area; Step S6: judging and optimizing the wind turbine failure fire risk coefficient: judging the wind turbine operation failure risk of each monitoring sub-area according to the wind turbine failure fire risk coefficient in S5, and optimizing the failure risk of the sub-area with abnormal judgment results; Step S7: Establishing a comprehensive fire risk index model for a wind farm: establishing a comprehensive fire risk index model for a wind farm according to the environmental fire risk coefficient and the wind turbine failure fire risk coefficient determined and optimized in step S4 and step S6, and calculating a comprehensive fire risk index for the wind farm; Step S8: making a level judgment on the comprehensive fire risk: comparing the wind farm comprehensive fire risk index of each monitoring sub-area calculated in step S7 with a preset fire risk level range, and starting fire fighting measures corresponding to the fire risk level according to the judgment result; Step S9: Establishing a user interface module: Using Internet technology to achieve remote operation and control of the wind farm fire protection system, so that operation and maintenance personnel can understand the fire safety status of the unit and the wind farm in real time.
2. A wind power fire protection system processing method according to claim 1, characterized in that: The specific division method of the wind farm area division is: the entire wind farm is determined as a target area, and on this basis, each wind turbine in the wind farm is divided into i independent monitoring sub-areas, where i=1, 2, 3, . . . n.
3. A wind power fire protection system processing method according to claim 1, characterized in that: The multi-sensor comprises a temperature sensor, a flame sensor and a smoke sensor, which are used to monitor the temperature, flame and smoke abnormalities of the wind power generation site in real time.
4. A wind power fire protection system processing method according to claim 1, characterized in that: The environmental parameters include temperature, wind speed and humidity; the wind turbine operating state parameters include wind turbine power, wind turbine speed and wind turbine vibration amplitude.
5. A wind power fire protection system processing method according to claim 1, characterized in that: The calculation steps of the environmental fire risk coefficient of each monitoring sub-area are as follows: Step S31: Calculate wind speed probability distribution function F ( v ), the expression is as follows: ,in, exp Expressed as a natural exponential function, v Expressed as wind speed, k It is expressed as a shape parameter, with a value range of 1.5-2.
5. c It is expressed as a scale parameter, indicating the average wind speed in the area where the wind farm is located, with a value range of 5-10m / s; Step S32: According to the wind speed probability distribution function F ( v ) Calculate wind speed v , the calculation model is as follows: , where x is A random variable uniformly distributed on Step S33: Calculate the environmental fire risk coefficient of each monitoring sub-area, and the calculation model is as follows: ,in, FRC i It is expressed as the environmental fire risk coefficient of each monitoring sub-area, T i Indicates the wind farm ambient temperature value of each monitoring sub-area, T max It is expressed as the maximum temperature of the wind farm environment. T min It is expressed as the minimum temperature value of the wind farm environment. v i It is represented by the wind speed of each monitoring sub-area, H i It is represented by the wind farm environmental humidity of each monitoring sub-area, H max It is expressed as the maximum humidity value of the wind farm environment, and e is expressed as a natural constant.
6. A wind power fire protection system processing method according to claim 1, characterized in that: The specific contents of judging and optimizing the environmental fire risk factor in step S4 are as follows: Step S41: Compare the environmental fire risk coefficient of each monitoring sub-area with a preset fire risk threshold. If the environmental fire risk coefficient is less than or equal to the preset fire risk threshold, the result of the judgment is that there is no fire risk in the wind farm environment. If the environmental fire risk coefficient is greater than the preset fire risk threshold, the result of the judgment is that there is a fire risk in the wind farm environment. Step S42: Optimize the fire risk of the monitoring sub-area where the judgment result is that the wind farm environment has a fire risk, issue a warning message, send the number of the abnormal wind turbine to the operation and maintenance manager, and the operation and maintenance manager initiates the wind farm environment fire risk optimization strategy and visualizes it on the administrator's mobile device.
7. A wind power fire protection system processing method according to claim 1, characterized in that: The calculation steps of the wind turbine failure fire risk coefficient of each monitoring sub-area are as follows: Step S51: Standardize the wind turbine power, wind turbine speed, and wind turbine vibration amplitude respectively. The calculation model of linear standardization is as follows: ， Among them, X represents the standardized parameters, X0 represents the initial acquisition parameters, and X min Represents the minimum value of the initial acquisition parameters, X max It is expressed as the maximum value of the initial acquisition parameters; Step S52: Calculate the wind turbine fault fire risk coefficient, the calculation model is as follows: ,in, FFC i It is expressed as the wind turbine failure fire risk coefficient of each monitoring sub-area, Rs i It is represented by the wind turbine speed of each monitoring sub-area, Rs max It is expressed as the maximum value allowed for the wind turbine speed. V i It is expressed as the vibration amplitude of wind turbines in each monitoring sub-area, V 0 represents the preset standard wind turbine vibration amplitude. P i It is represented by the wind turbine power of each monitoring sub-area, P 0 represents the rated power of the wind turbine. It is expressed as the standard deviation of the rated power of the wind turbine, and e is expressed as a natural constant.
8. A wind power fire protection system processing method according to claim 1, characterized in that: The specific contents of judging and optimizing the wind turbine fault fire risk factor in step S6 are as follows: Step S61: Compare the wind turbine failure fire risk coefficient of each monitoring sub-area with the preset failure fire risk threshold. If the wind turbine failure fire risk coefficient is less than or equal to the preset failure fire risk threshold, the judgment result is that there is no fire risk due to the wind turbine failure. If the wind turbine failure fire risk coefficient is greater than the preset failure fire risk threshold, the judgment result is that there is a fire risk due to the wind turbine failure. Step S62: Optimize the fault risk of the monitoring sub-area where the judgment result is that there is a fire risk due to wind turbine fault, issue a warning message, send the number of the abnormal wind turbine to the operation and maintenance manager, and the operation and maintenance manager initiates the wind turbine operation fault risk optimization strategy and visualizes it on the manager's mobile device.
9. A wind power fire protection system processing method according to claim 1, characterized in that: The calculation model of the wind farm comprehensive fire risk index is as follows: ,in, CFRI Expressed as the comprehensive fire risk index of wind farms, FRC i It is expressed as the environmental fire risk coefficient of each monitoring sub-area, FFC i It is represented as the wind turbine failure fire risk coefficient of each monitoring sub-area, k1 and k2 are constants, and n is the total number of wind turbines in the wind farm.
10. A wind power fire protection system processing method according to claim 1, characterized in that: The specific content of judging the level of comprehensive fire risk in step S8 is: Extract the wind farm comprehensive fire risk index and compare it with the preset fire risk level range. If the wind farm comprehensive fire risk index is within the preset fire risk level A range, it means that the wind farm comprehensive fire risk reaches level one, and the level one response measures are initiated to carry out fire fighting in the wind farm; If the wind farm comprehensive fire risk index is within the preset fire risk level B range, it means that the wind farm comprehensive fire risk has reached level 2, and the level 2 response measures are initiated to carry out fire fighting in the wind farm; If the comprehensive fire risk index of the wind farm is within the preset fire risk C level range, it means that the comprehensive fire risk of the wind farm has reached level three, and the level three response measures are initiated to carry out fire fighting in the wind farm.