Wind power consumption processing method and device, equipment and storage medium

Abstract

The invention provides a wind power consumption processing method and device, equipment and a storage medium. The method comprises the steps that wind power resource data of a to-be-processed sub-region are collected, wind power plant operation data of the to-be-processed sub-region are collected, the to-be-processed sub-region belongs to a to-be-processed wind power plant region, and the to-be-processed wind power plant region is divided into a plurality of to-be-processed sub-regions; performing first calculation processing according to the wind power resource data to obtain a wind power resource characterization value of the to-be-processed sub-region; performing second calculation processing according to the wind power plant operation data to obtain a power generation adjustment index and an energy storage adjustment index of the to-be-processed sub-region; according to the wind power resource characterization value and the power generation adjustment index, outputting a first target operation parameter so as to regulate and control the wind power equipment of the to-be-processed sub-region; and outputting a second target operation parameter according to the wind power resource characterization value and the energy storage adjustment index so as to regulate and control the energy storage system of the to-be-processed sub-region. According to the method provided by the invention, the accuracy and management efficiency of wind power consumption are improved.

Description

Technical Field

[0001] The present application relates to the technical field of wind power equipment, and in particular to a processing method, device, equipment and storage medium for wind power consumption. Background Art

[0002] Wind power consumption refers to the process of connecting the electricity generated by wind farms to the power grid and effectively transmitting it to other power-consuming areas. This process is of great significance for improving the utilization rate of wind power, ensuring the stable operation of the power system, and promoting the sustainable development of renewable energy. Unreasonable offshore wind power consumption management will directly affect the stability of the power system and may cause grid frequency fluctuations. Timely and accurate monitoring and regulation can reduce the risk of grid frequency fluctuations.

[0003] In the related technology, usually only the operating status of the wind farm is considered, for example, the power receiving parameters of the power grid and the charge status data of the energy storage power station are directly obtained, and the dispatching management of wind power consumption is realized by analyzing the above data.

[0004] However, existing technologies cannot achieve accurate scheduling of wind power consumption, and the utilization rate of wind resources is low. Summary of the invention

[0005] The present application provides a processing method, device, equipment and storage medium for wind power consumption, which are used to solve the problem that accurate scheduling of wind power consumption cannot be achieved in the prior art, resulting in low utilization rate of wind resources.

[0006] In a first aspect, the present application provides a method for processing wind power consumption, comprising:

[0007] Collecting wind resource data of the sub-area to be processed and collecting wind farm operation data of the sub-area to be processed, wherein the sub-area to be processed belongs to the wind farm area to be processed, and the wind farm area to be processed is divided into a plurality of sub-areas to be processed;

[0008] Performing a first calculation process according to the wind resource data to obtain a wind resource characterization value of the sub-area to be processed;

[0009] Performing a second calculation process according to the wind farm operation data to obtain a power generation adjustment index and an energy storage adjustment index of the sub-area to be processed;

[0010] Outputting a first target operating parameter according to the wind resource characterization value and the power generation adjustment index to regulate the wind power equipment in the sub-area to be processed;

[0011] According to the wind resource characterization value and the energy storage adjustment index, a second target operating parameter is output to regulate the energy storage system of the sub-area to be processed.

[0012] In a possible implementation, the wind resource data includes wind speed data and air density data;

[0013] Accordingly, a first calculation process is performed according to the wind resource data to obtain a wind resource characterization value of the sub-area to be processed, including:

[0014] The wind energy density of the sub-area to be processed is calculated based on the wind speed data and air density data;

[0015] According to the wind speed data, the turbulence intensity of the sub-area to be processed is calculated;

[0016] The wind resource characterization value of the sub-area to be processed is determined based on wind speed data, wind energy density and turbulence intensity.

[0017] In a possible implementation, determining the wind resource characterization value of the sub-area to be processed according to the wind speed data, wind energy density and turbulence intensity includes:

[0018] Obtaining a preset reference wind energy density, an influence factor corresponding to the preset wind energy density, a preset reference turbulence intensity, an influence factor corresponding to the preset turbulence intensity, a preset reference wind speed, and an influence factor corresponding to the preset wind speed;

[0019] According to the preset reference wind energy density, the influencing factor corresponding to the preset wind energy density, the preset reference turbulence intensity, the influencing factor corresponding to the preset turbulence intensity, the preset reference wind speed and the influencing factor corresponding to the preset wind speed, as well as the wind speed data, wind energy density and turbulence intensity, the wind resource characterization value of the sub-area to be processed is calculated.

[0020] In a possible implementation, the wind farm operation data includes power generation adjustment data and energy storage adjustment data; the power generation adjustment data includes the output power, rated power and power generation of the wind power equipment; the energy storage adjustment data includes the remaining battery power, total energy input and total energy output of the energy storage system, and the charging energy and discharging energy of the sub-area to be processed;

[0021] According to the wind farm operation data, a second calculation process is performed to obtain a power generation adjustment index and an energy storage adjustment index of the sub-area to be processed, including:

[0022] According to the output power and rated power, the power factor of the wind power equipment is calculated;

[0023] According to the power generation, the total power generation of the sub-area to be processed is calculated;

[0024] According to the power coefficient and the total power generation, the power generation adjustment index of the sub-area to be processed is calculated;

[0025] The energy conversion efficiency of the sub-area to be processed is calculated based on the total energy input and the total energy output;

[0026] According to the charging energy and the discharging energy, the average energy storage flow of the sub-area to be processed is calculated;

[0027] According to the remaining battery capacity, energy conversion efficiency and average energy storage flow, the energy storage adjustment index of the sub-area to be processed is calculated.

[0028] In a possible implementation, outputting a first target operating parameter according to the wind resource characterization value and the power generation adjustment index includes:

[0029] Obtaining a preset reference power generation adjustment index, a weight factor corresponding to the preset power generation adjustment index, a preset reference wind resource characterization value, and a weight factor corresponding to the preset wind resource characterization value;

[0030] Calculate the power generation scheduling optimization index value of the sub-area to be processed according to the power generation adjustment index, the preset reference power generation adjustment index, the weight factor corresponding to the preset power generation adjustment index, the wind resource characterization value, the preset reference wind resource characterization value and the weight factor corresponding to the preset wind resource characterization value;

[0031] According to the power generation dispatch optimization index value, matching is performed in a mapping table of preset power generation dispatch optimization index value intervals and power generation dispatch parameters to determine the power generation dispatch parameters of the sub-area to be processed, wherein the power generation dispatch parameters include the rotor speed and output power of the wind power equipment;

[0032] According to the power generation dispatching parameters, the first target operating parameters are output to adjust the rotor speed and output power of the wind power equipment in the sub-area to be processed.

[0033] In a possible implementation, outputting a second target operating parameter according to the wind resource characterization value and the energy storage adjustment index includes:

[0034] Obtaining a preset reference energy storage adjustment index, a compensation factor corresponding to the preset energy storage adjustment index, a preset reference wind resource characterization value, and a compensation factor corresponding to the preset wind resource characterization value;

[0035] Calculate the energy storage scheduling optimization index value of the sub-area to be processed according to the energy storage adjustment index, the preset reference energy storage adjustment index, the compensation factor corresponding to the preset energy storage adjustment index, the wind resource characterization value, the preset reference wind resource characterization value and the compensation factor corresponding to the preset wind resource characterization value;

[0036] According to the energy storage scheduling optimization index value, a mapping table of preset energy storage scheduling optimization index value intervals and energy storage scheduling parameters is matched to determine the energy storage scheduling parameters of the sub-area to be processed, wherein the energy storage scheduling parameters include the charging and discharging frequency and power of the energy storage system;

[0037] According to the energy storage scheduling parameters, the second target operating parameters are output to regulate the charging and discharging frequency and power of the energy storage system in the sub-area to be processed.

[0038] In a possible implementation manner, before collecting the wind resource data of the sub-area to be processed and collecting the wind farm operation data of the sub-area to be processed, the method further includes:

[0039] Obtaining distribution information of wind power equipment in the wind farm area to be processed;

[0040] According to the distribution information, the wind farm area to be processed is divided into a plurality of sub-areas to be processed.

[0041] In a second aspect, an embodiment of the present application provides a processing device for wind power consumption, including:

[0042] A collection module, used for collecting wind resource data of a sub-area to be processed and collecting wind farm operation data of the sub-area to be processed, wherein the sub-area to be processed belongs to a wind farm area to be processed, and the wind farm area to be processed is divided into a plurality of sub-areas to be processed;

[0043] A first calculation module, used for performing a first calculation process according to the wind resource data to obtain a wind resource characterization value of the sub-area to be processed;

[0044] A second calculation module is used to perform a second calculation process according to the wind farm operation data to obtain a power generation adjustment index and an energy storage adjustment index of the sub-area to be processed;

[0045] A first control module, configured to output a first target operating parameter according to the wind resource characterization value and the power generation adjustment index, so as to regulate the wind power equipment in the sub-area to be processed;

[0046] The second control module is used to output a second target operating parameter according to the wind resource characterization value and the energy storage adjustment index to regulate the energy storage system of the sub-area to be processed.

[0047] In a third aspect, the present application provides a processing device for wind power consumption, including:

[0048] at least one processor; and

[0049] a memory communicatively connected to at least one processor; wherein,

[0050] The memory stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor so that the at least one processor can execute the first aspect or various possible implementations of the first aspect as described above.

[0051] In a fourth aspect, the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the above first aspect or various possible implementations of the first aspect.

[0052] The present application provides a processing method, device, equipment and storage medium for wind power consumption. By collecting wind resource data and wind farm operation data of the sub-area to be processed, calculating and processing, the wind resource characterization value, the power generation adjustment index and the energy storage adjustment index of the sub-area to be processed are obtained; according to the wind resource characterization value and the power generation adjustment index, the first target operating parameter is output to regulate the wind power equipment in the sub-area to be processed; according to the wind resource characterization value and the energy storage adjustment index, the second target operating parameter is output to regulate the energy storage system in the sub-area to be processed. In this way, accurate regulation of wind power consumption is achieved. Compared with the prior art that only analyzes the operating status of the wind farm to achieve the dispatching management of wind power consumption, the present application divides the area to obtain the sub-area to be processed, and calculates and processes the wind resource data and wind farm operation data in the sub-area to be processed, respectively, to obtain the first target operating parameter and the second target operating parameter, and regulates the energy storage system in the sub-area to be processed, thereby improving the accuracy of wind power consumption management. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0054] Figure 1 A wind power consumption processing system architecture diagram provided in an embodiment of the present application;

[0055] Figure 2 A schematic diagram of a process for processing wind power consumption provided in an embodiment of the present application;

[0056] Figure 3 A schematic diagram of a process for processing wind power consumption provided in an embodiment of the present application;

[0057] Figure 4 A schematic diagram of a process for processing wind power consumption provided in an embodiment of the present application;

[0058] Figure 5 A schematic diagram of a process for processing wind power consumption provided in an embodiment of the present application;

[0059] Figure 6 A schematic diagram of a process for processing wind power consumption provided in an embodiment of the present application;

[0060] Figure 7 A schematic diagram of a process for processing wind power consumption provided in an embodiment of the present application;

[0061] Figure 8 An example diagram of energy storage scheduling optimization index values ​​provided in an embodiment of the present application;

[0062] Fig. 9 A schematic diagram of a process for processing wind power consumption provided in an embodiment of the present application;

[0063] Fig.10 A schematic diagram of the structure of a wind power consumption processing device provided in an embodiment of the present application;

[0064] Fig.11 A schematic diagram of the structure of a wind power consumption processing device provided in an embodiment of the present application.

[0065] The above drawings show the embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0066] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0067] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0068] Offshore wind power consumption management refers to the process of effectively utilizing and managing the electricity generated by offshore wind power generation. Due to the instability and intermittent nature of offshore wind power, offshore wind power consumption management is needed to ensure that the electricity generated by offshore wind power generation can be efficiently absorbed and utilized to avoid energy waste.

[0069] In the prior art, the operation status of the wind farm is usually analyzed, such as the power receiving parameters of the power grid and the state of charge data of the energy storage station, to achieve the dispatch management of wind power consumption. However, the prior art lacks analysis of wind resource data, and the analysis angle is relatively single, which may lead to insufficient accuracy of the analysis results and reduce the efficiency of wind power consumption.

[0070] Based on this, in the existing technology, there is a problem that accurate scheduling of wind power consumption cannot be achieved and the utilization rate of wind resources is low.

[0071] In order to solve the above problems, the core concept of the present application is to collect wind resource data and wind farm operation data in the sub-area to be processed respectively for calculation and processing to obtain first target operating parameters and second target operating parameters, and to regulate the energy storage system in the sub-area to be processed based on the first target operating parameters and the second target operating parameters, thereby comprehensively considering the impact of wind resource data and wind farm operation data on wind power consumption, thereby improving the accuracy of wind power consumption management.

[0072] Optionally, Figure 1 The present invention provides a wind power consumption processing system architecture schematic diagram, the wind power consumption processing system is a computer device. Figure 1 In the above framework, the above framework includes at least one of a data acquisition device 101, a processing device 102, and a display device 103.

[0073] It is understandable that the structure illustrated in the embodiment of the present application does not constitute a specific limitation on the architecture of the processing system for wind power consumption. In other feasible implementations of the present application, the above architecture may include more or fewer components than shown in the figure, or combine certain components, or split certain components, or arrange the components differently, which can be determined according to the actual application scenario and is not limited here. Figure 1 The components shown may be implemented in hardware, software, or a combination of software and hardware.

[0074] In a specific implementation process, the data acquisition device 101 may include an input / output interface and may also include a communication interface. The data acquisition device 101 may be connected to the processing device via the input / output interface or the communication interface.

[0075] The processing device 102 can perform a first calculation process on the wind resource data and a second calculation process on the wind farm operation data, respectively, to obtain a wind resource characterization value, a power generation adjustment index, and an energy storage adjustment index for the sub-area to be processed; based on the wind resource characterization value and the power generation adjustment index, obtain a first target operating parameter to regulate the wind power equipment in the sub-area to be processed; based on the wind resource characterization value and the energy storage adjustment index, obtain a second target operating parameter to regulate the energy storage system in the sub-area to be processed, so as to achieve accurate scheduling of wind power consumption and improve the utilization rate of wind resources.

[0076] The display device 103 may also be a touch display screen or a screen of a terminal device, which is used to receive user instructions while displaying the above content to achieve interaction with the user.

[0077] It should be understood that the above-mentioned processing device can be implemented by a processor reading instructions in a memory and executing the instructions, or it can be implemented by a chip circuit.

[0078] In addition, the network architecture and business scenarios described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Ordinary technicians in this field can know that with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0079] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0080] Figure 2 A schematic diagram of a process for processing wind power consumption provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, the method includes:

[0081] S201 , collecting wind resource data of a sub-region to be processed, and collecting wind farm operation data of the sub-region to be processed, wherein the sub-region to be processed belongs to a wind farm region to be processed, and the wind farm region to be processed is divided into a plurality of sub-regions to be processed.

[0082] In this embodiment, the preset monitoring period is divided into a plurality of monitoring time periods.

[0083] Optionally, the wind resource data includes wind speed data and air density data.

[0084] The wind speed data in the sub-area to be processed is collected in real time through the anemometer.

[0085] Arrange multiple monitoring points in the sub-area to be processed, install air pressure sensors and temperature sensors in each monitoring point, collect air pressure data and temperature data of each monitoring point in the sub-area to be processed through the air pressure sensors and temperature sensors installed in each monitoring point in each monitoring time period, and use the ratio of the air pressure data P of each monitoring point to the product of the dry air gas constant R and the temperature data T as the air density data ρ. The calculation formula is as follows:

[0086]

[0087] Optionally, the wind farm operation data includes power generation adjustment data and energy storage adjustment data; the power generation adjustment data includes the output power, rated power and power generation of the wind power equipment; the energy storage adjustment data includes the remaining battery power, total energy input and total energy output of the energy storage system, as well as the charging energy and discharging energy of the sub-area to be processed.

[0088] Output power refers to the actual power generated by the wind turbine during the monitoring period. The output power is collected in real time through sensors and data recorders in the wind turbine control system. Rated power refers to the maximum power that the wind turbine can continuously generate under optimal wind speed conditions.

[0089] Power generation refers to the total electrical energy generated by the wind turbine during the monitoring period.

[0090] S202: Perform a first calculation process according to the wind resource data to obtain a wind resource characterization value of the sub-area to be processed.

[0091] In this embodiment, the wind resource characterization value is used to evaluate the power generation capacity of the wind turbine and adjust the power generation strategy of the wind turbine, thereby improving the power generation efficiency of the wind farm.

[0092] S203: Perform a second calculation process according to the wind farm operation data to obtain a power generation adjustment index and an energy storage adjustment index of the sub-area to be processed.

[0093] In this embodiment, by performing a second calculation process on the wind farm operation data, the power generation adjustment index and energy storage adjustment index of the area to be processed are obtained to clarify the power generation situation, energy demand and supply situation of the area to be processed, thereby improving the accuracy of wind power consumption management.

[0094] S204: Output a first target operating parameter according to the wind resource characterization value and the power generation adjustment index to regulate the wind power equipment in the sub-area to be processed.

[0095] In this embodiment, corresponding calculations are performed through the wind resource characterization value and the power generation adjustment index, and the first target operating parameters are output. The wind power equipment in the sub-area to be processed is regulated based on the first target operating parameters, and the wind energy potential of the sub-area to be processed is accurately evaluated, thereby optimizing the operating strategy of the wind power equipment, thereby improving the power generation efficiency of the wind farm.

[0096] S205. Output a second target operating parameter according to the wind resource characterization value and the energy storage adjustment index to regulate the energy storage system of the sub-area to be processed.

[0097] In this embodiment, corresponding calculations are performed through the wind resource characterization value and the energy storage adjustment index, and the second target operating parameters are output. The energy storage system of the sub-area to be processed is regulated based on the second target operating parameters, and corresponding energy storage regulation is accurately and timely performed according to different needs, thereby improving the rationality of the energy storage system of the sub-area to be processed.

[0098] In this embodiment, wind resource data and wind farm operation data of the sub-area to be processed are collected and corresponding calculations and processing are performed to obtain wind resource characterization values, power generation adjustment indexes and energy storage adjustment indexes. According to the wind resource characterization values, power generation adjustment indexes and energy storage adjustment indexes, first target operation parameters and second target operation parameters are obtained, thereby achieving precise control of wind power equipment and energy storage systems in the sub-area to be processed and improving the wind energy utilization rate of the wind farm.

[0099] Figure 3 A schematic diagram of a process for processing wind power consumption provided in an embodiment of the present application is provided. Figure 2 Based on the embodiment shown, Figure 3 As shown, the first calculation process in the above step S202 is performed according to the wind resource data to obtain the wind resource characterization value of the sub-area to be processed, including:

[0100] S301. Calculate the wind energy density of the sub-area to be processed based on wind speed data and air density data.

[0101] In this embodiment, the air density data ρ in each monitoring point is averaged to obtain the average air density ρ′ of each sub-area to be processed.

[0102] The calculation formula of wind energy density A in the sub-area to be processed is as follows:

[0103]

[0104] Wherein, C represents the wind speed data of the sub-area to be processed.

[0105] S302: Calculate the turbulence intensity of the sub-area to be processed based on the wind speed data.

[0106] In this embodiment, turbulence intensity refers to an indicator for measuring wind speed fluctuations. The wind speed standard deviation σ and the average wind speed C′ are calculated through wind speed data. The calculation formula for the turbulence intensity B of the sub-area to be processed is as follows:

[0107]

[0108] S303: Determine the wind resource characterization value of the sub-area to be processed according to the wind speed data, wind energy density and turbulence intensity.

[0109] In this embodiment, for example, if the wind energy density of the sub-area to be processed is greater, the wind speed of the sub-area to be processed is greater, which indicates that the sub-area to be processed has higher wind resources, and the wind resource characterization value of the sub-area to be processed is higher; the turbulence intensity of the sub-area to be processed reflects the stability of the wind speed. If the wind speed is more stable, it indicates that the sub-area to be processed has higher wind resources, and the wind resource characterization value of the sub-area to be processed is higher.

[0110] In this embodiment, by calculating the wind resource characterization value, the accuracy of evaluating the wind turbine power generation capacity can be improved, the wind turbine power generation strategy can be optimized, and thus the power generation efficiency of the wind farm can be improved.

[0111] Figure 4 A schematic diagram of a process for processing wind power consumption provided in an embodiment of the present application is provided. Figure 3 Based on the embodiment shown, Figure 4 As shown, the above step S303 determines the wind resource characterization value of the sub-area to be processed according to the wind speed data, wind energy density and turbulence intensity, including:

[0112] S401, obtaining a preset reference wind energy density, an influence factor corresponding to the preset wind energy density, a preset reference turbulence intensity, an influence factor corresponding to the preset turbulence intensity, a preset reference wind speed, and an influence factor corresponding to the preset wind speed.

[0113] In this embodiment, i represents the identifier of the sub-area to be processed, j represents the identifier of the monitoring time period, and τ i represents the wind resource characterization value of the i-th sub-area to be processed;

[0114] A ij represents the wind energy density of the i-th sub-region to be processed in the j-th monitoring time period, ΔA represents the preset reference wind energy density, Θ1 represents the influence factor corresponding to the preset reference wind energy density ΔA, which refers to the numerical value of the influence degree of the wind energy density on the wind resource characterization value of the sub-region to be processed, and is obtained through the preset first mapping relationship;

[0115] B ijrepresents the turbulence intensity of the i-th sub-area to be processed in the j-th monitoring time period, ΔB represents the preset reference turbulence intensity, Θ2 represents the influence factor corresponding to the preset reference turbulence intensity ΔB, which refers to the numerical value of the influence degree of the turbulence intensity on the wind resource characterization value of the sub-area to be processed, and is obtained through the preset second mapping relationship;

[0116] C ij represents the wind speed data of the i-th sub-area to be processed in the j-th monitoring time period, ΔC represents the preset reference wind speed data, θ3 represents the influence factor corresponding to the preset reference wind speed data ΔC, which refers to the numerical value of the influence degree of the wind speed data on the wind resource characterization value of the sub-area to be processed, and is obtained through the preset third mapping relationship;

[0117] Among them, i is greater than or equal to 1 and less than or equal to the total number of sub-areas to be processed n; j is greater than or equal to 1 and less than or equal to the total number of monitoring time periods m; Θ1, Θ2, and Θ3 are all greater than 0 and less than 1, and ΔA, ΔB, ΔB, Θ1, Θ2, and Θ3 are all obtained from the preset offshore wind power consumption database.

[0118] S402. Calculate the wind resource characterization value of the sub-area to be processed based on the preset reference wind energy density, the influencing factor corresponding to the preset wind energy density, the preset reference turbulence intensity, the influencing factor corresponding to the preset turbulence intensity, the preset reference wind speed and the influencing factor corresponding to the preset wind speed, as well as the wind speed data, wind energy density and turbulence intensity.

[0119] In this embodiment, the wind resource characterization value τ of the sub-region to be processed i The calculation formula is as follows:

[0120]

[0121] In this embodiment, the wind resource characterization value of the sub-area to be processed is obtained by calculation, which accurately reflects the wind energy situation, thereby adjusting the wind power consumption in time and improving the power generation efficiency of the wind farm.

[0122] Figure 5 A schematic diagram of a process for processing wind power consumption provided in an embodiment of the present application is provided. Figure 2 Based on the embodiment shown, Figure 5 As shown, the second calculation process in the above step S203 is performed according to the wind farm operation data to obtain the power generation adjustment index and energy storage adjustment index of the sub-region to be processed, including:

[0123] S501. Calculate the power factor of the wind power equipment according to the output power and the rated power.

[0124] In this embodiment, the power coefficient of the wind power equipment is used to measure the efficiency of the wind turbine in converting wind energy into electrical energy. The calculation formula of the power coefficient F of the wind power equipment is as follows:

[0125]

[0126] Where D is the output power and P is the rated power.

[0127] S502: Calculate the total power generation of the sub-area to be processed based on the power generation.

[0128] In this embodiment, the sub-area to be processed includes at least one wind turbine, and the total power generation of the sub-area to be processed is the cumulative value of the power generation of each wind turbine in the sub-area to be processed, wherein the power generation of the wind turbine refers to the total electric energy generated by the wind turbine during the monitoring time period, which is monitored and collected by the energy meter of the wind turbine.

[0129] S503: Calculate the power generation adjustment index of the sub-region to be processed according to the power coefficient and the total power generation.

[0130] In this embodiment, i represents the identifier of the sub-area to be processed, j represents the identifier of the monitoring time period, and k represents the identifier of the wind power equipment in the sub-area to be processed;

[0131] D ij→k represents the output power of the kth wind turbine in the ith to-be-processed sub-area during the jth monitoring period, ΔD represents the preset reference output power, and ε1 represents the impact factor corresponding to the preset reference output power;

[0132] F ij→k represents the power coefficient of the kth wind turbine in the ith to-be-processed sub-area within the jth monitoring time period, ΔF represents the preset reference power coefficient, and ε2 represents the influencing factor corresponding to the preset reference power coefficient;

[0133] H ij represents the total power generation of the i-th sub-area to be processed in the j-th monitoring time period, ΔH represents the preset reference total power generation, and ε3 represents the influencing factor corresponding to the preset reference total power generation;

[0134] Among them, i is greater than or equal to 1 and less than or equal to the total number of sub-areas to be processed n; j is greater than or equal to 1 and less than or equal to the total number of monitoring time periods m; k is greater than or equal to 1 and less than or equal to the total number of wind power equipment h; ε1, ε2, and ε3 are all greater than 0 and less than 1, and ΔD, ΔF, ΔH, ε1, ε2, and ε3 are all obtained from the preset offshore wind power consumption database.

[0135] Then the power generation adjustment index P of the i-th sub-region to be processed is i The calculation formula is as follows:

[0136]

[0137] In this embodiment, the power generation adjustment index of the sub-region to be processed is a numerical quantification result obtained by analyzing the power coefficient and the total power generation of the sub-region to be processed.

[0138] S504: Calculate the energy conversion efficiency of the sub-region to be processed according to the total energy input and the total energy output.

[0139] In this embodiment, the total energy input E1 refers to the total energy received by the energy storage system during the charging process, and the total energy output E2 refers to the total energy released by the energy storage system during the discharging process; the calculation formula of the energy conversion efficiency M is as follows:

[0140]

[0141] The current and voltage are measured by a current sensor and a voltage sensor, and the total energy input E1 and the total energy output E2 are calculated based on the current and voltage.

[0142] S505. Calculate the average energy storage flow of the sub-area to be processed according to the charging energy and the discharging energy.

[0143] In this embodiment, the charging energy and the discharging energy of the sub-area to be processed are added to obtain the total energy storage flow of the sub-area to be processed, and the total energy storage flow of the sub-area to be processed is divided by the length of the monitoring time period to obtain the average energy storage flow of the sub-area to be processed.

[0144] S506: Calculate the energy storage adjustment index of the sub-area to be processed according to the remaining battery power, energy conversion efficiency and average energy storage flow.

[0145] In this embodiment, i represents the identifier of the sub-area to be processed, and j represents the identifier of the monitoring time period;

[0146] M ij represents the energy conversion efficiency in the i-th sub-region to be processed in the j-th monitoring time period, ΔM represents the preset reference energy conversion efficiency, and ω1 represents the weight factor corresponding to the preset reference energy conversion efficiency;

[0147] P ij represents the average energy storage flow in the i-th sub-area to be processed in the j-th monitoring time period, ΔP represents the preset reference average energy storage flow, and ω2 represents the weight factor corresponding to the preset reference average energy storage flow;

[0148] Q jrepresents the remaining battery capacity of the energy storage system in the jth monitoring time period, ΔQ represents the preset reference battery remaining capacity, and ω3 represents the weight factor corresponding to the preset reference battery remaining capacity;

[0149] Among them, i is greater than or equal to 1 and less than or equal to the total number of sub-areas to be processed n; j is greater than or equal to 1 and less than or equal to the total number of monitoring time periods m; ω1, ω2, and ω3 are all greater than 0 and less than 1, and ΔM, ΔP, ΔQ, ω1, ω2, and ω3 are all obtained from the preset offshore wind power consumption database.

[0150] Then the energy storage adjustment index ρ of the i-th sub-region to be processed is i The calculation formula is as follows:

[0151]

[0152] For example, if the energy conversion efficiency of the sub-area to be processed is higher, it means that wind energy can be more effectively converted into electrical energy, thereby improving the charging efficiency of the energy storage system, and the energy storage adjustment index is smaller; the higher the average energy storage flow, the higher the utilization rate of the energy storage system during charging and discharging, which effectively regulates the fluctuations in electricity supply and demand; the remaining battery power reflects the current charging state and energy reserve level of the energy storage system, which facilitates precise adjustment of the energy storage system, thereby improving the energy storage efficiency.

[0153] In this embodiment, by calculating the energy storage adjustment index of the sub-area to be processed, an overall performance evaluation can be performed for the energy storage system of the sub-area to be processed, thereby achieving accurate scheduling of the energy storage system and improving energy storage efficiency.

[0154] Figure 6 A schematic diagram of a process for processing wind power consumption provided in an embodiment of the present application is provided. Figure 2 Based on the embodiment shown, Figure 6 As shown, the output of the first target operating parameter according to the wind resource characterization value and the power generation adjustment index in the above step S204 includes:

[0155] S601: Obtain a preset reference power generation adjustment index, a weight factor corresponding to the preset power generation adjustment index, a preset reference wind resource characterization value, and a weight factor corresponding to the preset wind resource characterization value.

[0156] In this embodiment, i represents the identifier of the sub-region to be processed, Δβ represents a preset reference power generation adjustment index, represents the weight factor corresponding to the preset power generation adjustment index, Δτ represents the preset reference wind resource representation value, represents the weight factor corresponding to the preset wind resource characterization value; wherein i is greater than or equal to 1 and less than or equal to the total number of sub-areas to be processed n, is greater than 0 and less than 1, and Δβ, Δτ, as well as All of them are obtained from the preset offshore wind power consumption database.

[0157] S602. Calculate the power generation scheduling optimization index value of the sub-area to be processed according to the power generation adjustment index, the preset reference power generation adjustment index, the weight factor corresponding to the preset power generation adjustment index, the wind resource characterization value, the preset reference wind resource characterization value and the weight factor corresponding to the preset wind resource characterization value.

[0158] In this embodiment, β i represents the power generation adjustment index of the i-th sub-region to be processed, τ i represents the wind resource characterization value of the i-th sub-region to be processed; then the power generation scheduling optimization index value α of the i-th sub-region to be processed i The calculation formula is as follows:

[0159]

[0160] S603. According to the power generation dispatch optimization index value, a match is performed in a mapping table of a preset power generation dispatch optimization index value interval and a power generation dispatch parameter to determine the power generation dispatch parameter of the sub-area to be processed, wherein the power generation dispatch parameter includes the rotor speed and output power of the wind power equipment.

[0161] In this embodiment, the power generation scheduling parameter includes positive values ​​and negative values.

[0162] S604: Output a first target operating parameter according to the power generation dispatching parameter to adjust the rotor speed and output power of the wind power equipment in the sub-area to be processed.

[0163] In this embodiment, the actual operating parameters of the wind power equipment are obtained, the sum of the power generation scheduling parameters and the actual operating parameters is used as the first target operating parameter, and the first target operating parameter is used as the target operating parameter of the wind power equipment, thereby realizing the regulation of the rotor speed and output power of the wind power equipment.

[0164] In this embodiment, the first target operating parameter is obtained by performing corresponding calculations based on the wind resource characterization value and the power generation adjustment index, thereby achieving accurate regulation of the rotor speed and output power of the wind power equipment to improve power generation efficiency.

[0165] Figure 7 A schematic diagram of a process for processing wind power consumption provided in an embodiment of the present application is provided. Figure 2 Based on the embodiment shown, Figure 7 As shown, the output of the second target operating parameter according to the wind resource characterization value and the energy storage adjustment index in the above step S205 includes:

[0166] S701. Obtain a preset reference energy storage adjustment index, a compensation factor corresponding to the preset energy storage adjustment index, a preset reference wind resource characterization value, and a compensation factor corresponding to the preset wind resource characterization value.

[0167] In this embodiment, i represents the identifier of the sub-area to be processed, Δρ represents the preset reference energy storage adjustment index, μ1 represents the compensation factor corresponding to the preset energy storage adjustment index, Δτ represents the preset reference wind resource characterization value, and μ2 represents the compensation factor corresponding to the preset wind resource characterization value; wherein, i is greater than or equal to 1 and less than or equal to the total number n of sub-areas to be processed, μ1 and μ2 are greater than 0 and less than 1, and Δρ, Δτ, μ1, and μ2 are all obtained from a preset offshore wind power consumption database.

[0168] S702. Calculate the energy storage scheduling optimization index value of the sub-area to be processed according to the energy storage adjustment index, the preset reference energy storage adjustment index, the compensation factor corresponding to the preset energy storage adjustment index, the wind resource characterization value, the preset reference wind resource characterization value and the compensation factor corresponding to the preset wind resource characterization value.

[0169] In this embodiment, i represents the energy storage adjustment index of the i-th sub-region to be processed, τ i represents the wind resource characterization value of the i-th sub-region to be processed, then the energy storage scheduling optimization index value δ of the i-th sub-region to be processed i The calculation formula is as follows:

[0170]

[0171] Among them, e is a natural constant.

[0172] In this embodiment, for example, i is 1, 2, 3, and 4, Δρ is 1.3, μ1 is 0.7, Δτ is 1.4, and μ2 is 0.3; the energy storage adjustment index and wind resource characterization value of each sub-region to be processed and the energy storage scheduling optimization index value corresponding to the sub-region to be processed can be shown in the following table:

[0173]

[0174] like Figure 8As shown, the x-axis is the wind resource characterization value, and the y-axis is the energy storage scheduling optimization index value. When the energy storage index is 1.3, the functional relationship between the wind resource characterization value and the energy storage scheduling optimization index value is shown in curve a; when the energy storage index is 1.6, the functional relationship between the wind resource characterization value and the energy storage scheduling optimization index value is shown in curve b; when the energy storage index is 1.9, the functional relationship between the wind resource characterization value and the energy storage scheduling optimization index value is shown in curve c.

[0175] It should be noted that as the energy storage adjustment index of each sub-region to be processed increases, the energy storage scheduling optimization index value increases accordingly; as the difference between the wind resource characterization value of each sub-region to be processed and the preset reference wind resource characterization value increases, the energy storage scheduling optimization index value increases accordingly.

[0176] S703: According to the energy storage scheduling optimization index value, a mapping table of preset energy storage scheduling optimization index value intervals and energy storage scheduling parameters is matched to determine the energy storage scheduling parameters of the sub-area to be processed, wherein the energy storage scheduling parameters include the charging and discharging frequency and power of the energy storage system.

[0177] In this embodiment, the energy storage scheduling parameter includes positive values ​​and negative values.

[0178] S704: Output a second target operating parameter according to the energy storage scheduling parameter to adjust the charge and discharge frequency and power of the energy storage system in the sub-area to be processed.

[0179] In this embodiment, the actual energy storage operating parameters in the sub-area to be processed are obtained, the sum of the energy storage scheduling parameters and the actual energy storage operating parameters is used as the second target operating parameters, and the second target operating parameters are used as the target operating parameters of the energy storage system in the sub-area to be processed, thereby realizing the regulation of the charging and discharging frequency and power of the energy storage system in the sub-area to be processed.

[0180] In this embodiment, the wind resource characterization value and the energy storage adjustment index are used for corresponding calculations, thereby improving the accuracy of the energy storage scheduling optimization index value and obtaining the second target operating parameters, thereby achieving precise control of the charging and discharging frequency and power of the energy storage system in the sub-area to be processed.

[0181] Fig. 9 A schematic diagram of a process for processing wind power consumption provided in an embodiment of the present application is provided. Figure 2 Based on the embodiment shown, Fig. 9 As shown, before collecting the wind resource data of the sub-area to be processed and collecting the wind farm operation data of the sub-area to be processed in the above step S201, it also includes:

[0182] S901. Obtain distribution information of wind power equipment in a wind farm area to be processed.

[0183] In this embodiment, the wind power equipment may refer to a wind turbine. A plane image of the offshore wind farm area is extracted by using geographic information system software and image processing technology, and the position of each wind turbine in the plane image is marked.

[0184] S902: Divide the wind farm area to be processed into a plurality of sub-areas to be processed according to the distribution information.

[0185] In this embodiment, according to the preset number of wind turbines and the position of each wind turbine in the plane image, the Delaunay triangulation algorithm is used to divide the wind farm area to be processed to obtain a plurality of sub-areas to be processed.

[0186] In this embodiment, by dividing the wind farm area to be processed into multiple sub-areas to be processed, the accuracy of the data analysis results can be improved, thereby achieving accurate scheduling of wind power consumption.

[0187] Fig.10 A schematic diagram of a wind power processing device provided in an embodiment of the present application is shown in FIG. Fig.10 As shown, the wind power consumption processing device includes:

[0188] The collection module 1001 is used to collect wind resource data of the sub-area to be processed and collect wind farm operation data of the sub-area to be processed, wherein the sub-area to be processed belongs to the wind farm area to be processed, and the wind farm area to be processed is divided into multiple sub-areas to be processed.

[0189] The first calculation module 1002 is used to perform a first calculation process according to the wind resource data to obtain a wind resource characterization value of the sub-area to be processed.

[0190] The second calculation module 1003 is used to perform a second calculation process according to the wind farm operation data to obtain a power generation adjustment index and an energy storage adjustment index of the sub-area to be processed.

[0191] The first control module 1004 is used to output a first target operating parameter according to the wind resource characterization value and the power generation adjustment index to regulate the wind power equipment in the sub-area to be processed.

[0192] The second control module 1005 is used to output a second target operating parameter according to the wind resource characterization value and the energy storage adjustment index to regulate the energy storage system of the sub-area to be processed.

[0193] Optionally, the first calculation module 1002 is further configured to:

[0194] The wind energy density of the sub-area to be processed is calculated based on the wind speed data and air density data;

[0195] According to the wind speed data, the turbulence intensity of the sub-area to be processed is calculated;

[0196] The wind resource characterization value of the sub-area to be processed is determined based on wind speed data, wind energy density and turbulence intensity.

[0197] Optionally, the first calculation module 1002 is further configured to:

[0198] Obtaining a preset reference wind energy density, an influence factor corresponding to the preset wind energy density, a preset reference turbulence intensity, an influence factor corresponding to the preset turbulence intensity, a preset reference wind speed, and an influence factor corresponding to the preset wind speed;

[0199] According to the preset reference wind energy density, the influencing factor corresponding to the preset wind energy density, the preset reference turbulence intensity, the influencing factor corresponding to the preset turbulence intensity, the preset reference wind speed and the influencing factor corresponding to the preset wind speed, as well as the wind speed data, wind energy density and turbulence intensity, the wind resource characterization value of the sub-area to be processed is calculated.

[0200] Optionally, the second calculation module 1003 is further configured to:

[0201] According to the output power and rated power, the power factor of the wind power equipment is calculated;

[0202] According to the power generation, the total power generation of the sub-area to be processed is calculated;

[0203] According to the power coefficient and the total power generation, the power generation adjustment index of the sub-area to be processed is calculated;

[0204] The energy conversion efficiency of the sub-area to be processed is calculated based on the total energy input and the total energy output;

[0205] According to the charging energy and the discharging energy, the average energy storage flow of the sub-area to be processed is calculated;

[0206] According to the remaining battery capacity, energy conversion efficiency and average energy storage flow, the energy storage adjustment index of the sub-area to be processed is calculated.

[0207] Optionally, the second calculation module 1003 is further configured to:

[0208] Obtaining a preset reference power generation adjustment index, a weight factor corresponding to the preset power generation adjustment index, a preset reference wind resource characterization value, and a weight factor corresponding to the preset wind resource characterization value;

[0209] Calculate the power generation scheduling optimization index value of the sub-area to be processed according to the power generation adjustment index, the preset reference power generation adjustment index, the weight factor corresponding to the preset power generation adjustment index, the wind resource characterization value, the preset reference wind resource characterization value and the weight factor corresponding to the preset wind resource characterization value;

[0210] According to the power generation dispatch optimization index value, matching is performed in a mapping table of preset power generation dispatch optimization index value intervals and power generation dispatch parameters to determine the power generation dispatch parameters of the sub-area to be processed, wherein the power generation dispatch parameters include the rotor speed and output power of the wind power equipment;

[0211] According to the power generation dispatching parameters, the first target operating parameters are output to adjust the rotor speed and output power of the wind power equipment in the sub-area to be processed.

[0212] Optionally, the second calculation module 1003 is further configured to:

[0213] Obtaining a preset reference energy storage adjustment index, a compensation factor corresponding to the preset energy storage adjustment index, a preset reference wind resource characterization value, and a compensation factor corresponding to the preset wind resource characterization value;

[0214] Calculate the energy storage scheduling optimization index value of the sub-area to be processed according to the energy storage adjustment index, the preset reference energy storage adjustment index, the compensation factor corresponding to the preset energy storage adjustment index, the wind resource characterization value, the preset reference wind resource characterization value and the compensation factor corresponding to the preset wind resource characterization value;

[0215] According to the energy storage scheduling optimization index value, a mapping table of preset energy storage scheduling optimization index value intervals and energy storage scheduling parameters is matched to determine the energy storage scheduling parameters of the sub-area to be processed, wherein the energy storage scheduling parameters include the charging and discharging frequency and power of the energy storage system;

[0216] According to the energy storage scheduling parameters, the second target operating parameters are output to regulate the charging and discharging frequency and power of the energy storage system in the sub-area to be processed.

[0217] Optionally, before the collection module 1001 is used to collect wind resource data of the sub-area to be processed and collect wind farm operation data of the sub-area to be processed, the above-mentioned device further includes:

[0218] The division module is used to obtain the distribution information of the wind power equipment in the wind farm area to be processed; and divide the wind farm area to be processed into a plurality of sub-areas to be processed according to the distribution information.

[0219] Fig.11 This is a schematic diagram of the structure of a wind power processing device provided in an embodiment of the present application. Fig.11 As shown, the processing equipment for wind power consumption provided in this embodiment includes:

[0220] At least one processor 1101 and a memory 1102. Optionally, the device further includes a communication component 1103. The processor 1101, the memory 1102 and the communication component 1103 are connected via a bus 1104.

[0221] In a specific implementation process, at least one processor 1101 executes the computer-executable instructions stored in the memory 1102, so that at least one processor 1101 executes the above method.

[0222] The specific implementation process of the processor 1101 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0223] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0224] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (Non-volatile Memory, NVM), such as at least one disk memory.

[0225] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0226] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0227] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0228] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in a dedicated integrated circuit. Of course, the processor and the readable storage medium can also exist in a device as discrete components.

[0229] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0230] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0231] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0232] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a disk or an optical disk, and other media that can store program codes.

[0233] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0234] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for processing wind power consumption, characterized in that: include: Collecting wind resource data of a sub-region to be processed and collecting wind farm operation data of the sub-region to be processed, wherein the sub-region to be processed belongs to a wind farm region to be processed, and the wind farm region to be processed is divided into a plurality of sub-regions to be processed; Performing a first calculation process according to the wind resource data to obtain a wind resource characterization value of the sub-area to be processed; Performing a second calculation process according to the wind farm operation data to obtain a power generation adjustment index and an energy storage adjustment index of the sub-area to be processed; Outputting a first target operating parameter according to the wind resource characterization value and the power generation adjustment index to regulate the wind power equipment in the sub-area to be processed; According to the wind resource characterization value and the energy storage adjustment index, a second target operating parameter is output to regulate the energy storage system of the sub-area to be processed.

2. The method according to claim 1, characterized in that The wind resource data includes wind speed data and air density data; Accordingly, performing a first calculation process according to the wind resource data to obtain a wind resource characterization value of the sub-area to be processed includes: Calculating the wind energy density of the sub-area to be processed according to the wind speed data and the air density data; Calculating the turbulence intensity of the sub-area to be processed according to the wind speed data; A wind resource characterization value of the sub-area to be processed is determined according to the wind speed data, the wind energy density and the turbulence intensity.

3. The method according to claim 2, characterized in that Determining the wind resource characterization value of the sub-area to be processed according to the wind speed data, the wind energy density and the turbulence intensity includes: Obtaining a preset reference wind energy density, an influence factor corresponding to the preset wind energy density, a preset reference turbulence intensity, an influence factor corresponding to the preset turbulence intensity, a preset reference wind speed, and an influence factor corresponding to the preset wind speed; The wind resource characterization value of the sub-area to be processed is calculated based on the preset reference wind energy density, the influencing factor corresponding to the preset wind energy density, the preset reference turbulence intensity, the influencing factor corresponding to the preset turbulence intensity, the preset reference wind speed and the influencing factor corresponding to the preset wind speed, as well as the wind speed data, the wind energy density and the turbulence intensity.

4. The method according to any one of claims 1 to 3, characterized in that: The wind farm operation data includes power generation adjustment data and energy storage adjustment data; the power generation adjustment data includes the output power, rated power and power generation of the wind power equipment; the energy storage adjustment data includes the remaining battery power, total energy input and total energy output of the energy storage system, and the charging energy and discharging energy of the sub-area to be processed; The performing a second calculation process according to the wind farm operation data to obtain a power generation adjustment index and an energy storage adjustment index of the sub-region to be processed includes: Calculating the power coefficient of the wind power equipment according to the output power and the rated power; According to the power generation, the total power generation of the sub-area to be processed is calculated; Calculating a power generation adjustment index of the sub-area to be processed according to the power coefficient and the total power generation; Calculating the energy conversion efficiency of the sub-region to be processed according to the total energy input and the total energy output; According to the charging energy and the discharging energy, an average energy storage flow rate of the sub-area to be processed is calculated; The energy storage adjustment index of the sub-area to be processed is calculated according to the remaining battery power, the energy conversion efficiency and the average energy storage flow.

5. The method according to claim 4, characterized in that The step of outputting a first target operating parameter according to the wind resource characterization value and the power generation adjustment index comprises: Obtaining a preset reference power generation adjustment index, a weight factor corresponding to the preset power generation adjustment index, a preset reference wind resource characterization value, and a weight factor corresponding to the preset wind resource characterization value; The power generation scheduling optimization index value of the sub-area to be processed is calculated according to the power generation adjustment index, the preset reference power generation adjustment index, the weight factor corresponding to the preset power generation adjustment index, the wind resource characterization value, the preset reference wind resource characterization value and the weight factor corresponding to the preset wind resource characterization value; According to the power generation dispatch optimization index value, matching is performed in a mapping table of preset power generation dispatch optimization index value intervals and power generation dispatch parameters to determine the power generation dispatch parameters of the sub-area to be processed, wherein the power generation dispatch parameters include the rotor speed and output power of the wind power equipment; According to the power generation scheduling parameter, a first target operating parameter is output to adjust the rotor speed and output power of the wind power equipment in the sub-area to be processed.

6. The method according to claim 4, characterized in that The outputting a second target operating parameter according to the wind resource characterization value and the energy storage adjustment index comprises: Obtaining a preset reference energy storage adjustment index, a compensation factor corresponding to the preset energy storage adjustment index, a preset reference wind resource characterization value, and a compensation factor corresponding to the preset wind resource characterization value; The energy storage scheduling optimization index value of the sub-area to be processed is calculated according to the energy storage adjustment index, the preset reference energy storage adjustment index, the compensation factor corresponding to the preset energy storage adjustment index, the wind resource characterization value, the preset reference wind resource characterization value and the compensation factor corresponding to the preset wind resource characterization value; According to the energy storage scheduling optimization index value, matching is performed in a mapping table of preset energy storage scheduling optimization index value intervals and energy storage scheduling parameters to determine the energy storage scheduling parameters of the sub-area to be processed, wherein the energy storage scheduling parameters include the charging and discharging frequency and power of the energy storage system; According to the energy storage scheduling parameters, second target operating parameters are output to regulate the charging and discharging frequency and power of the energy storage system in the sub-area to be processed.

7. The method according to any one of claims 1 to 3, characterized in that: Before collecting the wind resource data of the sub-area to be processed and collecting the wind farm operation data of the sub-area to be processed, the method further includes: Obtaining distribution information of wind power equipment in the wind farm area to be processed; According to the distribution information, the wind farm area to be processed is divided into a plurality of sub-areas to be processed.

8. A wind power consumption processing device, characterized in that: include: A collection module, used for collecting wind resource data of a sub-region to be processed and collecting wind farm operation data of the sub-region to be processed, wherein the sub-region to be processed belongs to a wind farm region to be processed, and the wind farm region to be processed is divided into a plurality of sub-regions to be processed; A first calculation module, configured to perform a first calculation process according to the wind resource data to obtain a wind resource characterization value of the sub-area to be processed; A second calculation module is used to perform a second calculation process according to the wind farm operation data to obtain a power generation adjustment index and an energy storage adjustment index of the sub-area to be processed; A first control module, configured to output a first target operating parameter according to the wind resource characterization value and the power generation adjustment index, so as to regulate the wind power equipment in the sub-area to be processed; The second control module is used to output a second target operating parameter according to the wind resource characterization value and the energy storage adjustment index to regulate the energy storage system of the sub-area to be processed.

9. A wind power consumption processing device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the processing method for wind power consumption according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the processing method for wind power consumption according to any one of claims 1 to 7.

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