Wind power plant efficient operation management system based on intelligent monitoring

Abstract

The invention discloses a wind power plant efficient operation management system based on intelligent monitoring, particularly relates to the technical field of intelligent monitoring, and comprises a survey area division module, a wind power plant information acquisition module, a wind power plant information preprocessing module, a wind power plant information analysis module, a comprehensive information analysis module, a comprehensive judgment module and a man-machine interaction module. Performing data acquisition on any sub-region of the target region through various survey devices; a physical performance coefficient value, an energy storage equipment coefficient value, an equipment operation coefficient value and an engineering benefit coefficient value are imported into a comprehensive analysis model to obtain a comprehensive monitoring rationality index value, and the comprehensive monitoring rationality index value is compared with a preset monitoring rationality threshold value and fed back. And the accuracy and comprehensiveness of efficient operation management of the wind power plant can be improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent monitoring technology, and more specifically, to a wind farm efficient operation management system based on intelligent monitoring. Background Art

[0002] With the rapid advancement of intelligent monitoring technology, the scale of various industries continues to expand. For example, the installed capacity of wind farms in the energy industry continues to rise, the number of equipment has increased significantly, and the operating environment has become increasingly complex and changeable. In this context, the demand for accurate monitoring, timely maintenance, and optimized management of equipment operating status has become more urgent. Traditional monitoring methods can no longer meet the requirements of large-scale and refined management, and a more advanced and efficient monitoring solution is urgently needed.

[0003] An existing wind farm efficient operation management system based on intelligent monitoring includes a data acquisition module, a data analysis module and a risk assessment module. The data acquisition module uses sensors throughout the wind farm to comprehensively collect various types of data closely related to the operation of the wind farm. The data analysis module conducts in-depth analysis of the data collected by the data acquisition module. The risk assessment module helps to accurately determine the error range and deviation direction by evaluating each type of data, efficiently guide subsequent targeted calibration and maintenance work, and effectively ensure the accuracy and reliability of data in the wind farm area.

[0004] However, in actual application, the system still shows many shortcomings, such as: in the data acquisition module, the collected information data is not comprehensive enough. In the data analysis module, the analysis of various types of data is not accurate enough, resulting in data loss and errors. The system lacks a comprehensive model and cannot integrate various types of information data into one indicator to reduce time and labor costs, which helps to accurately determine the error range and deviation direction, and effectively ensure the accuracy and reliability of data in the wind farm area.

[0005] Therefore, there is an urgent need for an efficient wind farm operation management system based on intelligent monitoring to solve the above problems. Summary of the invention

[0006] In order to overcome the above defects of the prior art, an embodiment of the present invention provides a wind farm efficient operation management system based on intelligent monitoring, which solves the problems raised in the above background technology through the field of intelligent monitoring technology.

[0007] To achieve the above object, the present invention provides the following technical solution: an efficient operation management system for a wind farm based on intelligent monitoring, comprising a survey area division module, a wind farm information collection module, a wind farm information preprocessing module, a wind farm information analysis module, a comprehensive information analysis module, a comprehensive judgment module and a human-computer interaction module:

[0008] Survey area division module: used to set up multiple groups of high-definition cameras in the target survey area, divide the target survey area into sub-areas according to equal area through multiple groups of high-definition cameras, and number the sub-areas in the target area as 1, 2, ..., i, ..., n in sequence;

[0009] Wind farm information collection module: used to collect data from any sub-area of ​​the target area through various survey equipment, obtain data from each sub-area, and transmit the data to the wind farm preprocessing module; including physical performance collection unit, energy storage equipment collection unit, equipment operation collection unit and engineering benefit collection unit;

[0010] Wind farm preprocessing module: receives data transmitted by the wind farm information acquisition module, performs preprocessing operations on the transmitted data, and transmits the data to the wind farm information analysis module;

[0011] Wind farm information analysis module: receives data transmitted by the wind farm preprocessing module, is used to obtain a data analysis model, and transmits the data to the data analysis model to obtain the physical performance coefficient value, energy storage equipment coefficient value, equipment operation coefficient value and engineering benefit coefficient value; includes a physical performance analysis unit, an energy storage equipment analysis unit, an equipment operation analysis unit and an engineering benefit analysis unit;

[0012] Comprehensive analysis module: used to obtain a comprehensive analysis model, import the physical performance coefficient value, energy storage equipment coefficient value, equipment operation coefficient value and engineering benefit coefficient value into the comprehensive analysis model to obtain a comprehensive monitoring rationality index value, and transmit the data to a comprehensive judgment module; including a comprehensive analysis unit;

[0013] Comprehensive judgment module: obtains a preset monitoring rationality threshold, obtains a digital signal based on the comparison between the comprehensive monitoring rationality index value and the preset monitoring rationality threshold, and transmits the digital signal to the human-computer interaction module;

[0014] Human-computer interaction module: used to receive danger signals from the comprehensive judgment module and managers will make corresponding adjustments and optimizations, and display them to relevant managers in a visual manner.

[0015] Preferably, the physical property collection unit includes: soil resistance value recorded as Wr, foundation soil bearing capacity recorded as Wn, and solar radiation intensity recorded as Wt; the energy storage equipment collection unit includes: the number of discharge cycles recorded as Cf, the number of charging cycles recorded as Ca, the energy storage content recorded as Cn, and the transformer loss recorded as Cb; the equipment operation collection unit includes: the fan blade rotation speed recorded as Sv, the number of power equipment failures recorded as Sd, and the transformer oil temperature value recorded as Sw; the engineering benefit collection unit includes: the land use area recorded as Gs, the fan power generation recorded as Gd, and the electricity consumption amount recorded as Gj.

[0016] Preferably, the specific method of the pre-processing operation includes:

[0017] The calculation formula for soil resistivity is:

[0018] WR represents soil resistivity, Wr i represents the soil resistance value of the ith area, and n represents the total number of sub-areas;

[0019] The calculation formula for the average intensity of solar radiation is:

[0020] WT represents the average intensity of solar radiation, Wt i represents the solar radiation intensity of the ith region, and n represents the total number of sub-regions;

[0021] The calculation formula for discharge cycle efficiency is:

[0022] CF represents the discharge cycle efficiency, Cf i represents the number of discharge cycles in the ith region, Ca i represents the number of charging cycles of the ith region, and n represents the total number of sub-regions;

[0023] The calculation formula of the fan blade rotation speed change rate is:

[0024] SV represents the rate of change of the fan blade rotation speed, Sv i represents the rotation speed of the fan blades in the ith region. When Sv i-1 and Sv i For equal exclusion treatment, n represents the total number of sub-regions;

[0025] The calculation formula of land resource utilization rate is:

[0026] GS represents land resource utilization rate, Gs i represents the land use area of ​​the ith region, Ga represents the total area of ​​the target region, and n represents the total number of sub-regions;

[0027] The calculation formula for the total electricity consumption is:

[0028] GJ represents the total amount of electricity consumed, Gj i Represents the electricity consumption amount of the i-th area.

[0029] Preferably, the physical performance analysis unit is used to establish a physical performance analysis model, import the data processed by the preprocessing module into the physical performance analysis model, and calculate the physical fluctuation coefficient value, which is specifically expressed as:

[0030] W represents the physical fluctuation coefficient value, Wn i represents the bearing capacity of the foundation soil in the ith sub-region, WR represents the soil resistivity, and Wr i represents the soil resistance value of the ith region, WT represents the average intensity of solar radiation, and Wt i represents the solar radiation intensity of the ith region, e represents a natural constant, and n represents the total number of sub-regions.

[0031] Preferably, the energy storage device analysis unit is used to establish an energy storage device analysis model, import the data processed by the preprocessing module into the energy storage device analysis model, and calculate the energy storage device coverage coefficient value, which is specifically expressed as:

[0032] C represents the coverage factor of the energy storage device, CF represents the discharge cycle efficiency, Cn i represents the energy storage content of the ith sub-region, Cb i represents the transformer loss of the ith sub-region, e represents a natural constant, and n represents the total number of sub-regions.

[0033] Preferably, the equipment operation analysis unit is used to establish an equipment operation analysis model, import the data processed by the preprocessing module into the equipment operation analysis model, and calculate the equipment operation coefficient value, which is specifically expressed as:

[0034] S represents the equipment operation coefficient value, SV represents the rate of change of the fan blade rotation speed, Sd i represents the number of power equipment failures in the ith sub-area, Sw i represents the oil temperature value of the transformer in the i-th sub-area, and n represents the total number of sub-areas.

[0035] Preferably, the engineering benefit analysis unit is used to establish an engineering benefit analysis model, import the data processed by the preprocessing module into the engineering benefit analysis model, and calculate the benefit proportional coefficient value, which is specifically expressed as:

[0036] G represents the value of the benefit ratio coefficient, GS represents the land resource utilization rate, GJ represents the total amount of electricity consumption, and Gj i represents the electricity consumption amount of the ith area, Gd irepresents the wind turbine power generation in the ith sub-region, e represents a natural constant, and n represents the total number of sub-regions.

[0037] Preferably, the comprehensive analysis unit is used to establish a comprehensive analysis model, import the physical performance coefficient value, the energy storage equipment coefficient value, the equipment operation coefficient value and the engineering benefit coefficient value into the comprehensive analysis model, and calculate the comprehensive monitoring rationality index value, which is specifically expressed as:

[0038] Among them, P represents the comprehensive monitoring rationality index value, W represents the physical fluctuation coefficient value, C represents the energy storage equipment coverage coefficient value, S represents the equipment operation coefficient value, G represents the benefit ratio coefficient value, α1, α2, α3, α4 represent weight coefficients and are all greater than zero, and the sum of α1, α2, α3, α4 is equal to one, among which β represents other influencing factors of the comprehensive monitoring rationality index value, and n represents the total number of sub-areas.

[0039] Preferably, the preset monitoring rationality threshold is an average value obtained by evaluating the historical data in the system database; the specific determination is as follows:

[0040] The digital signals include: danger signals and safety signals;

[0041] B1: If the comprehensive monitoring rationality index value is greater than the preset monitoring rationality threshold, a danger signal is issued;

[0042] B2: If the comprehensive monitoring rationality index value is less than the preset monitoring rationality threshold, a safety signal is issued and the data is stored in the system database.

[0043] Technical effects and advantages of the present invention:

[0044] 1. The present invention uses a wind farm information collection module to collect data from any sub-area of ​​the target area through various survey equipment, which helps to improve the accuracy of the collection area; the wind farm preprocessing module cleans, denoises, and unifies the format of the information text, which helps to improve the accuracy of the wind farm operation status assessment in the future and effectively eliminate abnormal data interference; the wind farm information analysis module obtains the physical performance coefficient value, energy storage equipment coefficient value, equipment operation coefficient value, and engineering benefit coefficient value through the data analysis model, which helps to comprehensively refine the wind farm information analysis and greatly reduce the risk level;

[0045] 2. The comprehensive analysis module of the present invention obtains the comprehensive monitoring rationality index value through the comprehensive analysis model, which helps to present a more intuitive effect to the management personnel, realizes the systematic analysis of the overall operation data of the wind farm, and can carry out a more detailed analysis of the operation status. Comparing the comprehensive monitoring rationality index value with the preset monitoring rationality threshold value helps to improve the accuracy of wind farm operation risk management;

[0046] 3. Human-computer interaction module: after receiving danger signals, the system will immediately feed back the processing results to the management personnel, and optimize and adjust the system in a targeted manner based on the feedback, so as to timely discover the risk situations in the operation of the wind farm, greatly improve the accuracy and completeness of management, and ensure the stability of the wind farm. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a schematic diagram of the system structure of the present invention.

[0048] Figure 2 It is a structural schematic diagram of the wind farm information analysis module of the present invention. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] As attached Figure 1 The figure shows a schematic diagram of the structure of a wind farm efficient operation management system based on intelligent monitoring, including a survey area division module, a wind farm information acquisition module, a wind farm information preprocessing module, a wind farm information analysis module, a comprehensive information analysis module, a comprehensive judgment module and a human-computer interaction module.

[0051] As attached Figure 2 Shown is a schematic diagram of the structure of the wind farm information analysis module.

[0052] Survey area division module: used to set up multiple groups of high-definition cameras in the target survey area, divide the target survey area into sub-areas of equal area through multiple groups of high-definition cameras, and number the sub-areas in the target area as 1, 2, ..., i, ..., n.

[0053] In this embodiment, it should be specifically explained that multiple groups of high-definition cameras are provided to survey the target survey area and divide the area into equal areas.

[0054] Wind farm information collection module: used to collect data from any sub-area of ​​the target area through various survey equipment, obtain data from each sub-area, and transmit the data to the wind farm preprocessing module; including physical performance collection unit, energy storage equipment collection unit, equipment operation collection unit and engineering benefit collection unit.

[0055] In this embodiment, it should be specifically explained that the data of the sub-areas are as follows: the physical performance collection unit includes: soil resistance value recorded as Wr, foundation soil bearing capacity recorded as Wn, and solar radiation intensity recorded as Wt; the energy storage equipment collection unit includes: the number of discharge cycles recorded as Cf, the number of charging cycles recorded as Ca, the energy storage content recorded as Cn, and the transformer loss recorded as Cb; the equipment operation collection unit includes: the fan blade rotation speed recorded as Sv, the number of power equipment failures recorded as Sd, and the transformer oil temperature value recorded as Sw; the engineering benefit collection unit includes: the land use area recorded as Gs, the fan power generation recorded as Gd, and the electricity consumption amount recorded as Gj.

[0056] Wind farm preprocessing module: receives data transmitted by the wind farm information acquisition module, performs preprocessing operations on the transmitted data, and transmits the data to the wind farm information analysis module.

[0057] In this example, it should be specifically noted that the specific method of preprocessing the data of the sub-region includes:

[0058] The calculation formula for soil resistivity is:

[0059] WR represents soil resistivity, Wr i represents the soil resistance value of the ith area, and n represents the total number of sub-areas;

[0060] The calculation formula for the average intensity of solar radiation is:

[0061] WT represents the average intensity of solar radiation, Wt i represents the solar radiation intensity of the ith region, and n represents the total number of sub-regions;

[0062] The calculation formula for discharge cycle efficiency is:

[0063] CF represents the discharge cycle efficiency, Cf i represents the number of discharge cycles in the ith region, Ca i represents the number of charging cycles of the ith region, and n represents the total number of sub-regions;

[0064] The calculation formula of the fan blade rotation speed change rate is:

[0065] SV represents the rate of change of the fan blade rotation speed, Sv i represents the rotation speed of the fan blades in the ith region. When Sv i-1 and Sv i For equal exclusion treatment, n represents the total number of sub-regions;

[0066] The calculation formula of land resource utilization rate is:

[0067] GS represents land resource utilization rate, Gs i represents the land use area of ​​the ith region, Ga represents the total area of ​​the target region, and n represents the total number of sub-regions;

[0068] The calculation formula for the total electricity consumption is:

[0069] GJ represents the total amount of electricity consumed, Gj i Represents the electricity consumption amount of the i-th area.

[0070] Wind farm information analysis module: receives data transmitted by the wind farm preprocessing module, is used to obtain the data analysis model, and transmits the data to the data analysis model to obtain the physical performance coefficient value, energy storage equipment coefficient value, equipment operation coefficient value and engineering benefit coefficient value; includes physical performance analysis unit, energy storage equipment analysis unit, equipment operation analysis unit and engineering benefit analysis unit.

[0071] In this embodiment, it should be specifically explained that the data analysis model specifically includes: a physical performance analysis model, an energy storage equipment analysis model, an equipment operation analysis model and an engineering benefit analysis model.

[0072] In this embodiment, it should be specifically explained that the physical performance analysis unit is used to establish a physical performance analysis model, import the data processed by the preprocessing module into the physical performance analysis model, and calculate the physical fluctuation coefficient value, which is specifically expressed as:

[0073] W represents the physical fluctuation coefficient value, Wn i represents the bearing capacity of the foundation soil in the ith sub-region, WR represents the soil resistivity, and Wr i represents the soil resistance value of the ith region, WT represents the average intensity of solar radiation, and Wt i represents the solar radiation intensity of the ith region, e represents a natural constant, and n represents the total number of sub-regions.

[0074] In this embodiment, it should be specifically explained that the energy storage device analysis unit is used to establish an energy storage device analysis model, import the data processed by the preprocessing module into the energy storage device analysis model, and calculate the energy storage device coverage coefficient value, which is specifically expressed as:

[0075] C represents the coverage factor of the energy storage device, CF represents the discharge cycle efficiency, Cn i represents the energy storage content of the ith sub-region, Cb i represents the transformer loss of the ith sub-region, e represents a natural constant, and n represents the total number of sub-regions.

[0076] In this embodiment, it should be specifically explained that the equipment operation analysis unit is used to establish an equipment operation analysis model, import the data processed by the preprocessing module into the equipment operation analysis model, and calculate the equipment operation coefficient value, which is specifically expressed as: ,

[0077] S represents the equipment operation coefficient value, SV represents the rate of change of the fan blade rotation speed, Sd i represents the number of power equipment failures in the ith sub-area, Sw i represents the oil temperature value of the transformer in the i-th sub-area, and n represents the total number of sub-areas.

[0078] In this embodiment, it should be specifically explained that the engineering benefit analysis unit is used to establish an engineering benefit analysis model, import the data processed by the preprocessing module into the engineering benefit analysis model, and calculate the benefit proportional coefficient value, which is specifically expressed as:

[0079] G represents the value of the benefit ratio coefficient, GS represents the land resource utilization rate, GJ represents the total amount of electricity consumption, and Gj i represents the electricity consumption amount of the ith area, Gd i represents the wind turbine power generation in the ith sub-region, e represents a natural constant, and n represents the total number of sub-regions.

[0080] Comprehensive analysis module: used to obtain a comprehensive analysis model, import the physical performance coefficient value, energy storage equipment coefficient value, equipment operation coefficient value and engineering benefit coefficient value into the comprehensive analysis model to obtain a comprehensive monitoring rationality index value, and transmit the data to a comprehensive judgment module; including a comprehensive analysis unit.

[0081] In this embodiment, it should be specifically explained that the comprehensive analysis unit is used to establish a comprehensive analysis model, import the physical performance coefficient value, the energy storage equipment coefficient value, the equipment operation coefficient value and the engineering benefit coefficient value into the comprehensive analysis model, and calculate the comprehensive monitoring rationality index value, which is specifically expressed as:

[0082] Among them, P represents the comprehensive monitoring rationality index value, W represents the physical fluctuation coefficient value, C represents the energy storage equipment coverage coefficient value, S represents the equipment operation coefficient value, G represents the benefit ratio coefficient value, α1, α2, α3, α4 represent weight coefficients and are all greater than zero, and the sum of α1, α2, α3, α4 is equal to one, among which β represents other influencing factors of the comprehensive monitoring rationality index value, and n represents the total number of sub-areas.

[0083] Comprehensive judgment module: obtains the preset monitoring rationality threshold, obtains a digital signal after comparing the comprehensive monitoring rationality index value with the preset monitoring rationality threshold, and transmits the digital signal to the human-computer interaction module.

[0084] In this embodiment, it should be specifically explained that the preset monitoring rationality threshold is an average value obtained by evaluating the historical data in the system database; the specific determination is as follows:

[0085] The digital signals include: danger signals and safety signals;

[0086] B1: If the comprehensive monitoring rationality index value is greater than the preset monitoring rationality threshold, a danger signal is issued;

[0087] B2: If the comprehensive monitoring rationality index value is less than the preset monitoring rationality threshold, a safety signal is issued and the data is stored in the system database.

[0088] Human-computer interaction module: used to receive danger signals from the comprehensive judgment module and managers will make corresponding adjustments and optimizations, and display them to relevant managers in a visual manner.

[0089] In this embodiment, it is specifically necessary to explain that the visualization methods include text, image and audio.

[0090] The present invention uses a wind farm information collection module to collect data from any sub-area of ​​the target area through various survey equipment, which helps to improve the accuracy of the collection area; the wind farm preprocessing module cleans, denoises, and unifies the format of the information text, which helps to improve the accuracy of the wind farm operation status assessment in the future and effectively eliminate the interference of abnormal data; the wind farm information analysis module obtains the physical performance coefficient value, energy storage equipment coefficient value, equipment operation coefficient value, and engineering benefit coefficient value through the data analysis model, which helps to refine the wind farm information analysis in all aspects and greatly reduce the risk; the comprehensive analysis module obtains the comprehensive monitoring rationality index value through the comprehensive analysis model, which helps to present a more intuitive effect to the management personnel, realizes the systematic analysis of the overall operation data of the wind farm, and can carry out a more refined analysis of the operation status analysis results. Comparing the comprehensive monitoring rationality index value with the preset monitoring rationality threshold value helps to improve the accuracy of wind farm operation risk management. The human-computer interaction module, upon receiving danger signals, the system immediately feeds back the processing results to the management personnel, and optimizes and adjusts the system in a targeted manner based on the feedback, so as to timely discover the risk situations in the operation of the wind farm, greatly improving the accuracy and completeness of management and ensuring the stability of the wind farm.

[0091] Secondly, in the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0092] 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 principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An efficient operation management system for a wind farm based on intelligent monitoring, characterized in that: include: Survey area division module: used to set up multiple groups of high-definition cameras in the target survey area, divide the target survey area into sub-areas according to equal area through multiple groups of high-definition cameras, and number the sub-areas in the target area as 1, 2, ..., i, ..., n in sequence; Wind farm information collection module: used to collect data from any sub-area of ​​the target area through various survey equipment, obtain data from each sub-area, and transmit the data to the wind farm pre-processing module; It includes physical performance collection unit, energy storage equipment collection unit, equipment operation collection unit and engineering benefit collection unit; Wind farm preprocessing module: receives data transmitted by the wind farm information acquisition module, performs preprocessing operations on the transmitted data, and transmits the data to the wind farm information analysis module; Wind farm information analysis module: receives data transmitted by the wind farm preprocessing module, is used to obtain a data analysis model, and transmits the data to the data analysis model to obtain the physical performance coefficient value, energy storage equipment coefficient value, equipment operation coefficient value and engineering benefit coefficient value; It includes physical performance analysis unit, energy storage equipment analysis unit, equipment operation analysis unit and engineering benefit analysis unit; Comprehensive analysis module: used to obtain a comprehensive analysis model, import the physical performance coefficient value, energy storage equipment coefficient value, equipment operation coefficient value and engineering benefit coefficient value into the comprehensive analysis model to obtain a comprehensive monitoring rationality index value, and transmit the data to a comprehensive judgment module; Includes comprehensive analysis unit; Comprehensive judgment module: obtains a preset monitoring rationality threshold, obtains a digital signal based on the comparison between the comprehensive monitoring rationality index value and the preset monitoring rationality threshold, and transmits the digital signal to the human-computer interaction module; Human-computer interaction module: used to receive danger signals from the comprehensive judgment module and managers will make corresponding adjustments and optimizations, and display them to relevant managers in a visual manner.

2. According to claim 1, a wind farm efficient operation management system based on intelligent monitoring is characterized by: The physical property collection unit includes: soil resistance value recorded as Wr, foundation soil bearing capacity recorded as Wn, and solar radiation intensity recorded as Wt; the energy storage equipment collection unit includes: discharge cycle number recorded as Cf, charging cycle number recorded as Ca, energy storage content recorded as Cn, and transformer loss recorded as Cb; the equipment operation collection unit includes: fan blade rotation speed recorded as Sv, power equipment failure number recorded as Sd, and transformer oil temperature value recorded as Sw; the engineering benefit collection unit includes: land use area recorded as Gs, fan power generation recorded as Gd, and electricity consumption amount recorded as Gj.

3. The wind farm efficient operation management system based on intelligent monitoring according to claim 1 is characterized by: The pre-processing operation includes: The calculation formula for soil resistivity is: WR represents soil resistivity, Wr i represents the soil resistance value of the ith area, and n represents the total number of sub-areas; The calculation formula for the average intensity of solar radiation is: WT represents the average intensity of solar radiation, Wt i represents the solar radiation intensity of the ith region, and n represents the total number of sub-regions; The calculation formula of discharge cycle efficiency is: CF represents the discharge cycle efficiency, Cf i represents the number of discharge cycles in the ith region, Ca i represents the number of charging cycles of the ith region, and n represents the total number of sub-regions; The calculation formula of the fan blade rotation speed change rate is: SV represents the rate of change of the fan blade rotation speed, Sv i represents the rotation speed of the fan blades in the i-th region. When Sv i-1 and Sv i For equal exclusion treatment, n represents the total number of sub-regions; The calculation formula of land resource utilization rate is: GS represents land resource utilization rate, Gs i represents the land use area of ​​the ith region, Ga represents the total area of ​​the target region, and n represents the total number of sub-regions; The calculation formula for the total electricity consumption is: GJ represents the total amount of electricity consumed, Gj i Represents the electricity consumption amount of the i-th area.

4. The wind farm efficient operation management system based on intelligent monitoring according to claim 1 is characterized by: The physical performance analysis unit is used to establish a physical performance analysis model, import the data processed by the preprocessing module into the physical performance analysis model, and calculate the physical fluctuation coefficient value, which is specifically expressed as: W represents the physical fluctuation coefficient value, Wn i represents the bearing capacity of the foundation soil in the ith sub-region, WR represents the soil resistivity, and Wr i represents the soil resistance value of the ith region, WT represents the average intensity of solar radiation, and Wt i represents the solar radiation intensity of the ith region, e represents a natural constant, and n represents the total number of sub-regions.

5. The wind farm efficient operation management system based on intelligent monitoring according to claim 1 is characterized by: The energy storage device analysis unit is used to establish an energy storage device analysis model, import the data processed by the preprocessing module into the energy storage device analysis model, and calculate the energy storage device coverage coefficient value, which is specifically expressed as: C represents the coverage factor of the energy storage device, CF represents the discharge cycle efficiency, Cn i represents the energy storage content of the ith sub-region, Cb i represents the transformer loss of the ith sub-region, e represents a natural constant, and n represents the total number of sub-regions.

6. The wind farm efficient operation management system based on intelligent monitoring according to claim 1 is characterized by: The equipment operation analysis unit is used to establish an equipment operation analysis model, import the data processed by the preprocessing module into the equipment operation analysis model, and calculate the equipment operation coefficient value, which is specifically expressed as: S represents the equipment operation coefficient value, SV represents the rate of change of the fan blade rotation speed, Sd i represents the number of power equipment failures in the ith sub-area, Sw i represents the oil temperature of the transformer in the ith sub-area, and n represents the total number of sub-areas.

7. The wind farm efficient operation management system based on intelligent monitoring according to claim 1 is characterized by: The engineering benefit analysis unit is used to establish an engineering benefit analysis model, import the data processed by the preprocessing module into the engineering benefit analysis model, and calculate the benefit ratio coefficient value, which is specifically expressed as: G represents the value of the benefit ratio coefficient, GS represents the land resource utilization rate, GJ represents the total amount of electricity consumption, and Gj i represents the electricity consumption amount of the ith area, Gd i represents the wind turbine power generation in the ith sub-region, e represents a natural constant, and n represents the total number of sub-regions.

8. The wind farm efficient operation management system based on intelligent monitoring according to claim 1 is characterized by: The comprehensive analysis unit is used to establish a comprehensive analysis model, import the physical performance coefficient value, the energy storage equipment coefficient value, the equipment operation coefficient value and the engineering benefit coefficient value into the comprehensive analysis model, and calculate the comprehensive monitoring rationality index value, which is specifically expressed as: Among them, P represents the comprehensive monitoring rationality index value, W represents the physical fluctuation coefficient value, C represents the energy storage equipment coverage coefficient value, S represents the equipment operation coefficient value, G represents the benefit ratio coefficient value, α1, α2, α3, α4 represent weight coefficients and are all greater than zero, and the sum of α1, α2, α3, α4 is equal to one, among which β represents other influencing factors of the comprehensive monitoring rationality index value, and n represents the total number of sub-areas.

9. The wind farm efficient operation management system based on intelligent monitoring according to claim 1 is characterized by: The preset monitoring rationality threshold is an average value obtained by evaluating the historical data in the system database; The specific judgment is as follows: The digital signals include: danger signals and safety signals; B1: If the comprehensive monitoring rationality index value is greater than the preset monitoring rationality threshold, a danger signal is issued; B2: If the comprehensive monitoring rationality index value is less than the preset monitoring rationality threshold, a safety signal is issued and the data is stored in the system database.

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