Operation control method and device of grid-connected system, computer equipment, readable storage medium and program product

Abstract

The invention relates to an operation control method and device of a grid-connected system, computer equipment, a readable storage medium and a program product, which are applied to the technical field of data processing, and the method comprises the following steps: obtaining grid-connected power data of the grid-connected system, and screening target power data from the grid-connected power data; a transformation step: carrying out wavelet transformation updating on partial data including the target power data in the grid-connected power data, and if the target power data can be screened out from the grid-connected power data, returning to the transformation step; generating a first target grid-connected feature according to the grid-connected power data of which the target power data cannot be screened out; according to at least one pair of detail coefficients of the grid-connected power data in the wavelet transformation process, a second target grid-connected feature is generated, and the second grid-connected device is used for compensating the charge and discharge missing amount of the first grid-connected device; and controlling the operation of the grid-connected system according to the first target grid-connected feature and the second target grid-connected feature. By adopting the method, the operation control accuracy of the grid-connected system can be improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to an operation control method, apparatus, computer equipment, computer-readable storage medium, and computer program product for a grid-connected system. Background Art

[0002] With the widespread application of grid-connected systems, in order to meet the interaction requirements during the configuration of the grid-connected systems, there may be a situation where the configured grid-connected power data does not meet the power fluctuation limit conditions of the grid-connected systems. Therefore, it is necessary to smooth the grid-connected power data to generate grid-connected characteristics, thereby realizing the control of the grid-connected systems.

[0003] At present, sine-type transformation is usually used to smooth the grid-connected power data. However, this type of method can only process the global grid-connected power data, which is prone to over-smoothing, resulting in low accuracy in generating the grid-connected characteristics of the grid-connected system, that is, low control accuracy of the grid-connected system. Summary of the Invention

[0004] Based on this, it is necessary to provide an operation control method, device, computer equipment, computer-readable storage medium and computer program product for a grid-connected system that can improve the control accuracy of the grid-connected system in order to address the above technical problems.

[0005] In a first aspect, the present application provides an operation control method for a grid-connected system, wherein the grid-connected system includes a first grid-connected device and a second grid-connected device; the method includes:

[0006] acquiring grid-connected power data of the grid-connected system, and screening target power data that does not meet the power fluctuation restriction condition corresponding to the first grid-connected device from the grid-connected power data;

[0007] A first transformation step: performing wavelet transformation on a portion of the grid-connected power data including the target power data to update the data; if the target power data can be filtered out from the updated grid-connected power data, returning to the first transformation step until the target power data can no longer be filtered out from the grid-connected power data;

[0008] generating a first target grid-connected feature of the first grid-connected device based on the grid-connected power data from which the target power data cannot be filtered out;

[0009] generating a second target grid-connected feature of the second grid-connected device according to at least one pair of detail coefficients of the grid-connected power data in the wavelet transform process, wherein the second grid-connected device is used to compensate for the missing charge and discharge amount of the first grid-connected device;

[0010] The operation of the grid-connected system is controlled according to the first target grid-connected characteristic and the second target grid-connected characteristic.

[0011] In a second aspect, the present application further provides an operation control device for a grid-connected system, the grid-connected system comprising a first grid-connected device and a second grid-connected device; comprising:

[0012] a screening module, configured to obtain grid-connected power data of the grid-connected system and screen target power data that does not meet the power fluctuation restriction condition corresponding to the first grid-connected device from the grid-connected power data;

[0013] a transformation module configured to perform a first transformation step of performing a wavelet transformation on a portion of the grid-connected power data containing the target power data, and if the target power data can be filtered out from the updated grid-connected power data, return to the first transformation step until the target power data can no longer be filtered out from the grid-connected power data;

[0014] a generating module, configured to generate a first target grid-connected characteristic of the first grid-connected device based on the grid-connected power data from which the target power data cannot be filtered out; and to generate a second target grid-connected characteristic of the second grid-connected device based on at least one pair of detail coefficients of the grid-connected power data in the wavelet transform process, wherein the second grid-connected device is configured to compensate for a missing charge and discharge amount of the first grid-connected device;

[0015] A control module is used to control the operation of the grid-connected system according to the first target grid-connected characteristic and the second target grid-connected characteristic.

[0016] In a third aspect, the present application further provides a computer device, wherein the grid-connected system includes a first grid-connected device and a second grid-connected device; the computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0017] acquiring grid-connected power data of the grid-connected system, and screening target power data that does not meet the power fluctuation restriction condition corresponding to the first grid-connected device from the grid-connected power data;

[0018] A first transformation step: performing wavelet transformation on a portion of the grid-connected power data including the target power data to update the data; if the target power data can be filtered out from the updated grid-connected power data, returning to the first transformation step until the target power data can no longer be filtered out from the grid-connected power data;

[0019] generating a first target grid-connected feature of the first grid-connected device based on the grid-connected power data from which the target power data cannot be filtered out;

[0020] generating a second target grid-connected feature of the second grid-connected device according to at least one pair of detail coefficients of the grid-connected power data in the wavelet transform process, wherein the second grid-connected device is used to compensate for the missing charge and discharge amount of the first grid-connected device;

[0021] The operation of the grid-connected system is controlled according to the first target grid-connected characteristic and the second target grid-connected characteristic.

[0022] In a fourth aspect, the present application further provides a computer-readable storage medium, wherein the grid-connected system includes a first grid-connected device and a second grid-connected device; a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the following steps are implemented:

[0023] acquiring grid-connected power data of the grid-connected system, and screening target power data that does not meet the power fluctuation restriction condition corresponding to the first grid-connected device from the grid-connected power data;

[0024] A first transformation step: performing wavelet transformation on a portion of the grid-connected power data including the target power data to update the data; if the target power data can be filtered out from the updated grid-connected power data, returning to the first transformation step until the target power data can no longer be filtered out from the grid-connected power data;

[0025] generating a first target grid-connected feature of the first grid-connected device based on the grid-connected power data from which the target power data cannot be filtered out;

[0026] generating a second target grid-connected feature of the second grid-connected device according to at least one pair of detail coefficients of the grid-connected power data in the wavelet transform process, wherein the second grid-connected device is used to compensate for the missing charge and discharge amount of the first grid-connected device;

[0027] The operation of the grid-connected system is controlled according to the first target grid-connected characteristic and the second target grid-connected characteristic.

[0028] In a fifth aspect, the present application further provides a computer program product. The grid-connected system includes a first grid-connected device and a second grid-connected device; and includes a computer program. When the computer program is executed by a processor, the following steps are implemented:

[0029] acquiring grid-connected power data of the grid-connected system, and screening target power data that does not meet the power fluctuation restriction condition corresponding to the first grid-connected device from the grid-connected power data;

[0030] A first transformation step: performing wavelet transformation on a portion of the grid-connected power data including the target power data to update the data; if the target power data can be filtered out from the updated grid-connected power data, returning to the first transformation step until the target power data can no longer be filtered out from the grid-connected power data;

[0031] generating a first target grid-connected feature of the first grid-connected device based on the grid-connected power data from which the target power data cannot be filtered out;

[0032] generating a second target grid-connected feature of the second grid-connected device according to at least one pair of detail coefficients of the grid-connected power data in the wavelet transform process, wherein the second grid-connected device is used to compensate for the missing charge and discharge amount of the first grid-connected device;

[0033] The operation of the grid-connected system is controlled according to the first target grid-connected characteristic and the second target grid-connected characteristic.

[0034] The above-mentioned operation control method, device, computer equipment, computer-readable storage medium and computer program product of the grid-connected system, the grid-connected system includes a first grid-connected device and a second grid-connected device; grid-connected power data of the grid-connected system is obtained, and target power data that does not meet the power fluctuation limit condition corresponding to the first grid-connected device is filtered out from the grid-connected power data; a first transformation step: performing a wavelet transform on a portion of the grid-connected power data containing the target power data to update; if the target power data can be filtered out from the updated grid-connected power data, returning to the first transformation step until the target power data can no longer be filtered out from the grid-connected power data; generating a first target grid-connected characteristic of the first grid-connected device based on the grid-connected power data that cannot be filtered out; generating a second target grid-connected characteristic of the second grid-connected device based on at least one pair of detail coefficients of the grid-connected power data in the wavelet transform process, wherein the second grid-connected device is used to compensate for the missing charge and discharge amount of the first grid-connected device; and controlling the operation of the grid-connected system based on the first target grid-connected characteristic and the second target grid-connected characteristic.

[0035] In this way, considering that the grid-connected power data of the grid-connected system is configured to meet the interaction requirements, but there is a situation where the configured grid-connected power data does not meet the power fluctuation limit conditions of the grid-connected devices in the grid-connected system, therefore, the target power data that does not meet the power fluctuation limit conditions corresponding to the first grid-connected device is screened from the grid-connected power data, and based on the power data distribution type of the target power data, the grid-connected power data is subjected to local wavelet transform, and at least one expansion coefficient obtained after the local wavelet transform is used to characterize the power data after smoothing, and at least one pair of detail coefficients obtained after the local wavelet transform is used to characterize the compensated power data after smoothing. Therefore, according to the grid-connected power data in the wavelet transform process The first target grid-connected characteristic of the first grid-connected device is generated based on at least one expansion coefficient. When the first grid-connected device is operated and controlled, it can be ensured that the control process of the first grid-connected device complies with the power fluctuation limit condition of the first grid-connected device. The second target grid-connected characteristic of the second grid-connected device is generated based on at least one pair of detail coefficients of the grid-connected power data in the wavelet transform process. When the second grid-connected device is operated and controlled, it can achieve compensation for the smoothing amount of the first grid-connected device, that is, the charging and discharging missing amount of the first grid-connected device, thereby ensuring that the grid-connected system combining the first grid-connected device and the second grid-connected device can meet the interaction requirements, thereby improving the operation control accuracy of the grid-connected system. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0037] Figure 1 2. It is an application environment diagram of an operation control method of a grid-connected system in one embodiment;

[0038] Figure 2 1 is a flow chart of an operation control method of a grid-connected system in one embodiment;

[0039] Figure 3 1 is a flow chart of a step of performing wavelet transform update on a portion of the grid-connected power data including the target power data in one embodiment;

[0040] Figure 4 FIG1 is a flow chart of a step of generating a second target grid-connected characteristic of the second grid-connected device according to at least one pair of detail coefficients of the grid-connected power data in the wavelet transform process in one embodiment;

[0041] Figure 5is a structural block diagram of an operation control device of a grid-connected system in one embodiment;

[0042] Figure 6 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0044] It should be noted that the information and data involved in this application (including but not limited to data for analysis, stored data, displayed data, etc.) are all information and data authorized by the user or fully authorized by all parties, and the acquisition, transmission, storage, use and processing of relevant data are in compliance with the relevant provisions of national laws and regulations. The content pushed to the user (for example, target power data, grid-connected power data that cannot be filtered out of the target power data, the first target grid-connected characteristics and the second target grid-connected characteristics, etc.) can be rejected by the user or can be easily rejected by the content push, etc. In the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of the implementation of the technical solution of this application, but it does not mean that the applicant has or will necessarily use the solution.

[0045] The operation control method of the grid-connected system provided in the embodiment of the present application can be applied to Figure 1In the application environment shown, the grid-connected system 102 and the terminal 104 communicate with the server 106 via a network. The data storage system can store data that the server 106 needs to process. The data storage system can be integrated on the server 106, or placed on a cloud or other network server. The server 106 receives the grid-connected power data of the grid-connected system 102 sent by the grid-connected system 102, and filters the target power data that does not meet the power fluctuation restriction condition corresponding to the first grid-connected device from the grid-connected power data; performs wavelet transform update on the portion of the grid-connected power data containing the target power data, and returns to the screening step until the target power data cannot be filtered out from the grid-connected power data; generates a first target grid-connected characteristic of the first grid-connected device based on the grid-connected power data that cannot filter out the target power data; generates a second target grid-connected characteristic of the second grid-connected device based on at least one pair of detail coefficients of the grid-connected power data during the wavelet transform process, wherein the second grid-connected device is used to compensate for the missing charge and discharge amount of the first grid-connected device; and controls the operation of the grid-connected system 102 based on the first target grid-connected characteristic and the second target grid-connected characteristic. Server 106 can push target power data, grid-connected power data for which target power data cannot be filtered out, and at least one of the first target grid-connected feature and the second target grid-connected feature to terminal 104. Terminal 104 can include, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart car devices, and projectors. Portable wearable devices can include smart watches, smart bracelets, and head-mounted devices. Head-mounted devices can include virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, and the like. Server 106 can be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server providing cloud computing services.

[0046] In an exemplary embodiment, Figure 2 As shown, a method for controlling the operation of a grid-connected system is provided. Figure 1 The server 106 in FIG. 1 is used as an example to illustrate the process, including the following steps 202 to 210. In which:

[0047] Step 202 : Obtain grid-connected power data of the grid-connected system, and filter target power data that does not meet the power fluctuation restriction condition corresponding to the first grid-connected device from the grid-connected power data.

[0048] The grid-connected system in step 202 includes a first grid-connected device and a second grid-connected device. The first grid-connected device includes a power grid device; the second grid-connected device includes an energy storage device, specifically including at least one energy storage device. The grid-connected power data is used to characterize the operating power status of the grid-connected system at multiple times (time periods or time points). The grid-connected power data may include multiple energy storage power sub-data, each energy storage power sub-data including a specific operating power value of the grid-connected system at a specific operating time. For example, energy storage power sub-data a is (t1, p1). The grid-connected power data may also include a grid-connected system power curve. The grid-connected system power curve characterizes the correspondence between time and the operating power value of the grid-connected system. For example, a curve drawn from multiple coordinate points (consisting of multiple time periods or frequency bands and corresponding operating power values) with a time period or frequency band as the horizontal axis and the operating power value of the grid-connected system as the vertical axis serves as the power curve of the grid-connected system.

[0049] The power fluctuation limit condition in step 202 includes a power fluctuation limit range within at least one time range. For example, the power fluctuation limit range within 1 minute is 0-3, meaning the power fluctuation amount within 1 minute cannot exceed 3. Alternatively, the power fluctuation limit range within 10 minutes is 0-10, meaning the power fluctuation amount within 10 minutes cannot exceed 10. The power fluctuation limit condition corresponds to the capacity of the first grid-connected device; a larger capacity corresponds to a larger power fluctuation limit range. The target power data includes at least one target power sub-data, each of which does not meet the power fluctuation limit condition corresponding to the first grid-connected device.

[0050] As an embodiment, obtaining grid-connected power data of the grid-connected system includes: sending an energy storage power query request to the grid-connected system, and obtaining the grid-connected power data of the grid-connected system sent by the grid-connected system when receiving the energy storage power query request.

[0051] As another embodiment, obtaining grid-connected power data of a grid-connected system includes: obtaining grid demand information of a power grid system interacting with the grid-connected system, wherein the grid demand information is used to characterize the power supply demand at each time; generating grid-connected power data of the grid-connected system based on the grid demand information, wherein the discharge power of the grid-connected power data of the grid-connected system at each time matches the power supply demand characterized by the grid demand information at the corresponding time.

[0052] In this way, it can be ensured that the grid-connected power data of the grid-connected system is compatible with the corresponding interactive power grid system, and the grid-connected power data is the basis for subsequent control of the operation of the grid-connected system. Therefore, to a certain extent, it can be ensured that the operation of the grid-connected system matches the requirements of the power grid system, thereby improving the operation accuracy of the grid-connected system.

[0053] Exemplarily, target power data that does not meet the power fluctuation limit condition corresponding to the first grid-connected device is screened out from the grid-connected power data, including: obtaining the power fluctuation amount between each pair of energy storage power sub-data in the grid-connected power data, and screening target power data whose corresponding power fluctuation amount does not meet the power fluctuation limit condition corresponding to the first grid-connected device from the grid-connected power data.

[0054] The power fluctuation amount may be a power difference, a power change rate, a power fluctuation index, or a sampling loss rate, which is not limited here.

[0055] Furthermore, target power data whose corresponding power fluctuation amount does not meet the power fluctuation limit condition corresponding to the first grid-connected device is screened from the grid-connected power data, including: screening at least one power data pair whose corresponding power fluctuation amount is not within the power fluctuation limit range corresponding to the power fluctuation limit condition corresponding to the first grid-connected device from the grid-connected power data; for each power data pair, if the time difference of the power data pair is within the time range corresponding to the power fluctuation limit condition corresponding to the first grid-connected device, the power data pair is added to the target power data; if the time difference of the power data pair is outside the time range corresponding to the power fluctuation limit condition corresponding to the first grid-connected device, the next power data pair is detected until all power data pairs are detected to obtain the target power data.

[0056] It should be noted that the power data in the grid-connected power data will not be counted repeatedly in the target power data.

[0057] For example, the grid-connected power data is (5, 9, 1, 3), the time interval between each power data is 1 minute, and the power fluctuation limit condition corresponding to the first grid-connected device is that the power fluctuation limit range within 1 minute is 0-3, and the power fluctuation limit range within 2 minutes is 0-7; the power data pairs include: 1: (5, 9), 2: (5, 1), 3: (9, 1), 4: (9, 3); for the first power data pair, the power fluctuation amount is 4, and the corresponding time difference is 1, so 5 and 9 are counted into the target power data; for the second power data pair, the power fluctuation amount is 4, and the corresponding time difference is 2, which is outside the time range of 1 minute, so the next power data is detected; for the third power data pair, the power fluctuation amount is 8, and the corresponding time difference is 1, so 1 is counted into the target power data (9 has been counted in the first power data pair and is not counted again here); for the fourth power data pair, the power fluctuation amount is 6, and the corresponding time difference is 2, which is outside the time range of 1 minute; in summary, 5, 9, and 1 in the grid-connected power data are counted into the target power data.

[0058] Step 204 : performing wavelet transformation update on a portion of the grid-connected power data including the target power data.

[0059] As an embodiment, step 204 includes: selecting partial data including target power data from the grid-connected power data, and performing wavelet transform on the partial data; and updating the partial data according to at least one expansion coefficient in the wavelet transform process.

[0060] Furthermore, wavelet transform is performed on part of the data, including: determining the average value between every two adjacent data in the part of the data as at least one expansion coefficient in the wavelet transform process; determining the mean difference value between every two adjacent data in the part of the data (half of the two differences between every two adjacent data is the mean difference value, for example, 5 and 9 are adjacent, then the mean difference value is (5-9) / 2=-2, and, (9-5) / 2=2) as a pair of detail coefficients in the time interval corresponding to the two adjacent data.

[0061] For example, partial data includes (5, 9, 1, 3), at least one expansion coefficient obtained by wavelet transform includes: (7, 2), and at least one pair of detail coefficients obtained by wavelet transform includes (-2, 2, -1, 1).

[0062] As an embodiment, updating the portion of data according to at least one expansion coefficient in the wavelet transform process includes: replacing the portion of data with each expansion coefficient in the wavelet transform process.

[0063] If the target power data can be filtered out from the updated grid-connected power data, the process returns to step 204 until the target power data cannot be filtered out from the grid-connected power data.

[0064] Optionally, the specific implementation content of determining whether the target power data can be filtered out from the updated grid-connected power data may refer to the specific implementation steps of filtering out the target power data that does not meet the power fluctuation limit conditions corresponding to the first grid-connected device from the grid-connected power data in step 202, which will not be elaborated here.

[0065] Optionally, until the target power data cannot be filtered out from the grid-connected power data, the method further includes: updating the grid-connected power data according to the number of rounds of wavelet transformation.

[0066] Step 206 : generating a first target grid-connected characteristic of the first grid-connected device according to the grid-connected power data from which the target power data cannot be filtered out.

[0067] The first target grid-connected characteristic in step 206 is used to characterize the operating power distribution status of each first energy storage device in the first grid-connected device at various times. The first target grid-connected characteristic may include operating power values ​​of multiple first energy storage devices at various times. The first target grid-connected characteristic may also include multiple decomposed power linear graphs, each power linear graph corresponding to a first energy storage device, and each power linear graph characterizing the correspondence between time and the operating power value of the corresponding first energy storage device. For example, with time as the horizontal axis and the operating power value of the corresponding first energy storage device as the vertical axis, a line drawn from multiple coordinate points (coordinate points consisting of multiple times and corresponding operating power values) serves as a power linear graph. The power linear graph may be a broken line graph or a curve graph, without limitation herein.

[0068] As an embodiment, step 206 includes: determining the grid-connected power data from which the target power data cannot be filtered out as the first target grid-connected feature of the first grid-connected device, wherein each energy storage power sub-data of the grid-connected power data from which the target power data cannot be filtered out is respectively used to characterize the operating power distribution status of the first grid-connected device at each time.

[0069] As another embodiment, step 206 includes: constructing a power matrix based on the grid-connected power data from which the target power data cannot be filtered out, wherein the elements in each row of the power matrix are fused to form the grid-connected power data from which the target power data cannot be filtered out; and generating a first target grid-connected feature of the first grid-connected device based on the power matrix, wherein the elements in each row of the power matrix are respectively used to characterize the operating power distribution status of each first energy storage device in the first grid-connected device at each time.

[0070] Step 208 : generating a second target grid-connected feature of a second grid-connected device based on at least one pair of detail coefficients of the grid-connected power data during the wavelet transform process, wherein the second grid-connected device is used to compensate for the missing charge and discharge amount of the first grid-connected device.

[0071] The second target grid-connected characteristic in step 208 is used to characterize the operating power distribution of each of the two energy storage devices in the second grid-connected device at various times. The second target grid-connected characteristic may include the operating power values ​​of multiple energy storage devices at various times. The second target grid-connected characteristic may also include multiple decomposed power linear graphs, each power linear graph corresponding to two types of energy storage devices, and each of the two power linear graphs characterizing the correspondence between time and the operating power value of the corresponding energy storage device. For example, with time as the horizontal axis and the operating power value of the corresponding energy storage device as the vertical axis, a line drawn from multiple coordinate points (coordinate points consisting of multiple times and corresponding operating power values) serves as a power linear graph. The power linear graph may be a broken line graph or a curve graph, without limitation herein.

[0072] Exemplarily, step 208 includes: generating a second target grid-connected feature of the second grid-connected device according to at least one pair of detail coefficients of the grid-connected power data in each round of wavelet transform.

[0073] It can be understood that since each round of wavelet transform is actually an update process for the grid-connected power data, after each round of wavelet transform, at least one pair of detail coefficients of each round of wavelet transform process can be used to characterize the updated power difference during the update of that round. Therefore, the superposition of the detail coefficients of each round is the grid-connected power data that cannot filter out the target power data and the corresponding charging and discharging missing amount that needs to be compensated.

[0074] Step 210: Control the operation of the grid-connected system according to the first target grid-connected characteristic and the second target grid-connected characteristic.

[0075] Exemplarily, step 210 includes: controlling the operation of a first grid-connected device in the grid-connected system according to a first target grid-connected characteristic; and controlling the operation of a second grid-connected device in the grid-connected system according to a second target grid-connected characteristic.

[0076] As an embodiment, step 210 includes: controlling the operation of the first grid-connected device in the grid-connected system according to the operating power distribution status at each time represented by the first target grid-connected characteristic; and controlling the operation of the second grid-connected device in the grid-connected system according to the operating power distribution status at each time represented by the second target grid-connected characteristic.

[0077] In the above-mentioned operation control method of the grid-connected system, it is considered that the grid-connected power data of the grid-connected system is configured to meet the interaction requirements, but there is a situation where the configured grid-connected power data does not meet the power fluctuation limit conditions of the grid-connected devices in the grid-connected system. Therefore, the target power data that does not meet the power fluctuation limit conditions corresponding to the first grid-connected device is screened from the grid-connected power data, and the grid-connected power data is subjected to local wavelet transform based on the power data distribution type of the target power data. The at least one expansion coefficient obtained after the local wavelet transform is used to characterize the power data after smoothing, and the at least one pair of detail coefficients obtained after the local wavelet transform is used to characterize the compensated power data after smoothing. Therefore, according to the grid-connected power data in the wavelet transform, the target power data that does not meet the power fluctuation limit conditions corresponding to the first grid-connected device is selected. Based on at least one expansion coefficient in the transformation process, a first target grid-connected characteristic of the first grid-connected device is generated. When the first grid-connected device is operated and controlled, it can be ensured that the control process of the first grid-connected device complies with the power fluctuation limit condition of the first grid-connected device. Based on at least one pair of detail coefficients of the grid-connected power data in the wavelet transformation process, a second target grid-connected characteristic of the second grid-connected device is generated. When the second grid-connected device is operated and controlled, the smoothing amount of the first grid-connected device, that is, the charging and discharging missing amount of the first grid-connected device is compensated, thereby ensuring that the grid-connected system combining the first grid-connected device and the second grid-connected device can meet the interaction requirements, thereby improving the operation control accuracy of the grid-connected system.

[0078] In an exemplary embodiment, Figure 3 As shown, a method for accurately performing wavelet transform update is provided, and wavelet transform update is performed on the part of the grid-connected power data including the target power data, including steps 302 to 306. In which:

[0079] Step 302 : dividing the grid-connected power data into at least one transformed data set according to the power data distribution type of at least one target power sub-data, wherein the transformed data set includes at least one target power data.

[0080] The power data included in each transformed data set in step 302 is continuously distributed in time series.

[0081] Exemplarily, step 302 includes: dividing the grid-connected power data into at least one transformation data set according to a power data distribution type of at least one target power sub-data and a preset number of transformations corresponding to a wavelet transformation method.

[0082] The preset number of transformations corresponding to the wavelet transform is a power of 2, for example, 2 n , n is a positive integer, so the normal wavelet transform can be guaranteed.

[0083] As an embodiment, step 302 includes: if there is at least one first-category target power sub-data belonging to a sparse distribution type in the target power data, determining a first division number according to a preset transformation number corresponding to the wavelet transformation method, and dividing the first-category power data and the first-category target power sub-data into the same transformation data set according to the first division number, wherein the first-category power data is adjacent to the first-category target power sub-data, and the number of the first-category power data is consistent with the first division number; if there are multiple second-category target power sub-data belonging to a tight distribution type in the target power data, determining a second division number according to the number of the second target power data and the preset transformation number, and dividing the second-category power data and the multiple second-category target power sub-data into the same transformation data set according to the second division number, wherein the second-category power data is adjacent to the first second-category target power sub-data and the last second-category target power sub-data in the multiple second-category target power sub-data, respectively, and the number of the second-category power data is consistent with the second division number.

[0084] The amount of data in the transformed data set containing the first type of target power sub-data is less than or equal to the amount of data in the transformed data set containing the second type of target power sub-data.

[0085] For example, the grid-connected power data includes (1, 1, 5, 1, 2, 7, 5, 7, 1, 1, 6, 1), among which 5, 6, and 7 are target power data, and the first 5 is sparsely distributed, that is, the first type of target power sub-data. Then, the 1 adjacent to the first 5 can be the first type of power data; the latter part (7, 5, 7, 6) is densely distributed, that is, the second type of target power sub-data. Then, the 2 adjacent to the first 7 can be the second type of power data, and the 1 adjacent to 6 can also be the second type of power data. Therefore, (1, 1, 5, 1) can be divided into the same transformation data set, and (2, 7, 5, 7, 1, 1, 6, 1) can be divided into the same transformation data set.

[0086] In this way, considering the sparse distribution type of the first-category target power sub-data, it means that there is no target power data near the first-category target power sub-data, or the number of target power data is small. At this time, the smaller first-category power data are divided into a transformation data set, which can avoid wavelet transform updating of more first-category power data (that is, power data that meets the power fluctuation restriction conditions), that is, reducing the over-smoothing degree of the grid-connected power data to a certain extent.

[0087] Moreover, considering that the second-category target power sub-data of the tightly distributed type may include more data, multiple second-category target power sub-data and second-category power data of the tightly distributed type are divided into the same transformation data set, which reduces the number of divisions of the transformation data set to a certain extent. Therefore, the smoothing efficiency of the grid-connected power data can be improved, that is, the update efficiency of the grid-connected power data can be improved.

[0088] Optionally, as an embodiment, the above method also includes: if there is a target power sub-data and the interval duration between it and other target power sub-data is greater than a first preset interval duration threshold, then the power data distribution type of the target power sub-data is determined to be a sparse distribution type; if there is a target power sub-data and the interval duration between it and other target power sub-data is not greater than the first preset interval duration threshold, then the power data distribution type of the target power sub-data is determined to be a tight distribution type.

[0089] As another embodiment, the above method also includes: if there is a target power sub-data in the target power data whose corresponding interval duration is greater than the second preset interval duration threshold and the number of the target power sub-data is less than the preset number threshold, then the power data distribution type of the target power sub-data is determined to be a sparse distribution type; if there is a target power sub-data in the target power data whose corresponding interval duration is greater than the second preset interval duration threshold and the number of the power sub-data is not less than the preset number threshold, then the power data distribution type of the target power sub-data is determined to be a tight distribution type.

[0090] For example, the grid-connected power data is (5, 9, 1, 3, 2, 9, 4, 3), the time interval between each power data is 1 minute, 5, 9, 1 and 9 parts are target power data, the second preset interval time threshold is 2 minutes, and the preset number threshold is 2. Then, it is considered that parts 5, 9, and 1 are target power sub-data with a tight distribution type of power data distribution, and the remaining 9 parts are target power sub-data with a sparse distribution type of power data distribution.

[0091] The first preset interval duration, the second preset interval duration and the preset quantity threshold may be set by the user as needed, and may also correspond to the time series distribution of each target power sub-data.

[0092] Among them, the number of data contained in each transformation data set matches the preset transformation number corresponding to the wavelet transformation method. For example, the number of data contained in one transformation data set is 4, the number of data contained in another transformation data set is 8, the number of data contained in another transformation data set is 16, and so on; specifically, the sum of the first division number and the number of first-category target power sub-data matches the preset transformation number corresponding to the wavelet transformation method; the sum of the number of data between the first second-category target power sub-data and the last second-category target power sub-data (including the first second-category target power sub-data and the last second-category target power sub-data) and the second division number matches the preset transformation number corresponding to the wavelet transformation method.

[0093] For example, the grid-connected power data is (5, 9, 1, 3, 2, 9, 4, 3), where 5, 9, and 1 are target power sub-data with a tight distribution type of power data distribution, and the remaining 9 are target power sub-data with a sparse distribution type of power data distribution. Therefore, (5, 9, 1, 3) can be divided into one transformation data set, and (2, 9, 4, 3) can be divided into another transformation data set (or (3, 2, 9, 4) can be divided into one transformation data set).

[0094] Step 304 : Perform at least one round of wavelet transform on the transformed data set to obtain wavelet transform information of the transformed data set in the final round.

[0095] As an embodiment, step 304 includes: for each transformed data set, executing a second transformation step: performing a round of wavelet transform on the transformed data set to obtain the wavelet transform information of the transformed data set in the current round; updating the transformed data set according to at least one expansion coefficient in the wavelet transform information of the transformed data set in the current round; if the target power data can be filtered out in the transformed data set, returning to execute the second transformation step until the target power data can no longer be filtered out in the transformed data set, and then determining the wavelet transform information of the transformed data set in the current round as the wavelet transform information of the final round.

[0096] In this way, each transformed data set is guaranteed to be wavelet transformed separately, thereby minimizing the degree of over-smoothing.

[0097] Furthermore, a round of wavelet transform is performed on the transformed data set to obtain wavelet transform information of the transformed data set in the current round, including: determining the average value between every two adjacent data in the transformed data set as at least one expansion coefficient of the transformed data set in the current round; and determining the absolute mean difference between every two adjacent data in the transformed data set as at least one pair of detail coefficients of the transformed data set in the current round.

[0098] As an embodiment, updating the transformed dataset according to at least one expansion coefficient in the wavelet transform information of the transformed dataset in the current round includes: replacing the transformed dataset with at least one expansion coefficient in the wavelet transform information of the current round.

[0099] Step 306 : updating the transformed data set in the grid-connected power data according to at least one expansion coefficient in the wavelet transform information of the transformed data set in the final round.

[0100] Exemplarily, step 306 includes: replacing the transformed data set with at least one expansion coefficient in the wavelet transform information of the final round, specifically, copying each expansion coefficient in the wavelet transform information of the final round according to the number of rounds of wavelet transform corresponding to the transformed data set, to obtain multiple copy coefficients, wherein the number of rounds is the same as the number of copies, and the number of copy coefficients is based on 2 as the base, and the number of rounds is the power under the exponent; replacing the transformed data set with the multiple copy coefficients.

[0101] For example, the transformed data set includes (5, 9, 1, 3), and at least one expansion coefficient obtained by one round of wavelet transform includes: (7, 2). At this time, the transformed data set can filter out the target power data. Then another round of wavelet transform is performed, and the obtained expansion coefficient includes 4.5. At this time, the transformed data set cannot filter out the target power data. The number of rounds of wavelet transform is 2, so the expansion coefficient is copied twice, that is, (4.5, 4.5, 4.5, 4.5), and the updated transformed data set is also (4.5, 4.5, 4.5, 4.5).

[0102] In this embodiment, the grid-connected power data is divided into data sets based on the power data distribution type of at least one target power sub-data to obtain at least one transformed data set, and then the transformed data set is subjected to wavelet transform, thereby realizing targeted local wavelet transform, and thus obtaining updated grid-connected power data with the smallest possible range of wavelet transform. Therefore, the amount of data subjected to wavelet transform is reduced as much as possible, thereby reducing the degree of smoothing of the grid-connected power data and improving the smoothing accuracy of the grid-connected power data.

[0103] In an exemplary embodiment, Figure 4 As shown, a method for accurately generating a second target grid-connected characteristic of a second grid-connected device is provided, wherein the second target grid-connected characteristic of the second grid-connected device is generated based on at least one pair of detail coefficients in a wavelet transform process of grid-connected power data, including steps 402 to 406.

[0104] Step 402: Determine a target detail coefficient for each category based on at least one pair of detail coefficients of the grid-connected power data during the wavelet transform process.

[0105] Among them, the at least one pair of detail coefficients of the grid-connected power data in the wavelet transform process in step 402 includes at least one pair of detail coefficients obtained through each round of wavelet transform when executing the first transform step, and at least one pair of detail coefficients obtained through each round of wavelet transform when executing the second transform step.

[0106] As an embodiment, step 402 includes: determining the statistical characteristic value of at least one pair of detail coefficients in each round of wavelet transform as the target detail coefficient of each category.

[0107] In this way, the statistical characteristic value of at least one pair of detail coefficients in each round of wavelet transform process is directly determined as the target detail coefficient, thereby improving the efficiency of determining the target detail coefficient.

[0108] As another embodiment, step 402 includes: determining the statistical characteristic values ​​of at least one pair of detail coefficients corresponding to each transformed data set in each round of wavelet transform as target detail coefficients of each category.

[0109] In this way, the statistical characteristic values ​​corresponding to each transformed data set are determined as the target detail coefficients of each category, and at least one target detail coefficient corresponding to each transformed data set actually represents the charge and discharge compensation value in the corresponding time interval, which can improve the accuracy of determining the target detail coefficients to a certain extent.

[0110] As another embodiment, step 402 includes: determining each detail coefficient in each round of wavelet transform as a target detail coefficient of each category.

[0111] In this way, each detail coefficient in each round of wavelet transform is further divided into the charge and discharge compensation value in each time interval, further improving the accuracy of determining the target detail coefficient.

[0112] In which, at least one pair of detail coefficients obtained by the first transformation step and the second transformation step corresponding to the same round of wavelet transform is determined as at least one pair of detail coefficients in one round of wavelet transform process. For example, at least one pair of detail coefficients obtained by the first round of wavelet transform in the first transformation step and at least one pair of detail coefficients obtained by the first round of wavelet transform in the second transformation step are regarded as at least one pair of detail coefficients in the first round of wavelet transform process.

[0113] The statistical characteristic value may be a maximum value or an average value, which is not limited here.

[0114] Step 404 : Allocate target detail coefficients of all categories to a plurality of energy storage devices.

[0115] As an embodiment, step 404 includes: obtaining the rated power of each energy storage device; and distributing target detail coefficients of all categories to multiple energy storage devices according to the rated power of each energy storage device, wherein the higher the rated power of the energy storage device, the larger the allocated target detail coefficient.

[0116] In this way, the distribution of the target detail coefficient is ensured to be compatible with the energy storage capacity of the energy storage device, thereby improving the accuracy of the target detail coefficient obtained by the corresponding distribution of the energy storage device.

[0117] Step 406 : For each energy storage device, generate a second target grid-connected characteristic of the energy storage device according to the target detail coefficient correspondingly allocated to the energy storage device.

[0118] Exemplarily, generating a second target grid-connected characteristic of the energy storage device based on the target detail coefficients corresponding to the energy storage device includes: distributing the target detail coefficients corresponding to the energy storage device to the time intervals corresponding to the target detail coefficients, and padding the undistributed time intervals with zeros to obtain the second target grid-connected characteristic of the energy storage device.

[0119] For example, the target detail coefficients 1 and -1 allocated to the energy storage device are from the 3rd minute to the 4th minute, and the target detail coefficients -2 and 2 are from the 5th minute to the 6th minute. Then, the second target grid-connected characteristics of the energy storage device are (0, 0, 1, -1, -2, 2, 0, 0).

[0120] In this embodiment, the target detail coefficients of each category are determined based on at least one pair of detail coefficients obtained during the wavelet transform of the grid-connected power data. The target detail coefficients of each category are then matched with the energy storage devices, thereby ensuring that the second target grid-connected feature can accurately characterize the operating power distribution status of each energy storage device, thereby improving the accuracy of generating the second target grid-connected feature.

[0121] As a detailed embodiment, grid-connected power data of a grid-connected system is obtained, and target power data that does not meet the power fluctuation restriction condition corresponding to the first grid-connected device is screened from the grid-connected power data; a first transformation step is performed: if the target power data contains at least one first-category target power sub-data of a sparse distribution type, a first division number is determined based on a preset transformation number corresponding to a wavelet transform method, and the first-category power data and the first-category target power sub-data are divided into the same transformation data set according to the first division number, wherein the first-category power data are adjacent to the first-category target power sub-data, and the number of the first-category power data is consistent with the first division number; if the target power data contains multiple second-category target power sub-data of a dense distribution type, a second division number is determined based on the number of the second target power data and the preset transformation number, and the second-category power data and the multiple second-category target power sub-data are divided into the same transformation data set according to the second division number, wherein the second-category power data are adjacent to the first and last second-category target power sub-data of the multiple second-category target power sub-data, respectively, and the number of the second-category power data is consistent with the second division number.

[0122] Furthermore, for each transformed data set, a second transformation step is performed: a round of wavelet transform is performed on the transformed data set to obtain the wavelet transform information of the transformed data set in the current round; the transformed data set is updated according to at least one expansion coefficient in the wavelet transform information of the transformed data set in the current round; if the target power data can be filtered out from the transformed data set, the second transformation step is returned to be performed until the target power data can no longer be filtered out from the transformed data set, and the wavelet transform information of the transformed data set in the current round is determined as the wavelet transform information of the final round; the transformed data set in the grid-connected power data is updated according to at least one expansion coefficient in the wavelet transform information of the transformed data set in the final round, and if the target power data can be filtered out from the updated grid-connected power data, rate data, then returns to the first transformation step until the target power data cannot be filtered out from the grid-connected power data; generating a first target grid-connected feature of the first grid-connected device based on the grid-connected power data that cannot be filtered out; determining the statistical characteristic value of at least one pair of detail coefficients corresponding to each transformed data set in each round of wavelet transform as the target detail coefficient of each category; assigning the target detail coefficients of all categories to multiple energy storage devices; for each energy storage device, generating a second target grid-connected feature of the energy storage device based on the target detail coefficient corresponding to the energy storage device, wherein the second grid-connected device is used to compensate for the charging and discharging missing amount of the first grid-connected device; and controlling the operation of the grid-connected system based on the first target grid-connected feature and the second target grid-connected feature.

[0123] In this way, considering that the grid-connected power data of the grid-connected system is configured to meet the interaction requirements, but there is a situation where the configured grid-connected power data does not meet the power fluctuation limit conditions of the grid-connected devices in the grid-connected system, therefore, the target power data that does not meet the power fluctuation limit conditions corresponding to the first grid-connected device is screened from the grid-connected power data, and based on the power data distribution type of the target power data, the grid-connected power data is subjected to local wavelet transform, and at least one expansion coefficient obtained after the local wavelet transform is used to characterize the power data after smoothing, and at least one pair of detail coefficients obtained after the local wavelet transform is used to characterize the compensated power data after smoothing. Therefore, according to the grid-connected power data in the wavelet transform process The first target grid-connected characteristic of the first grid-connected device is generated based on at least one expansion coefficient. When the first grid-connected device is operated and controlled, it can be ensured that the control process of the first grid-connected device complies with the power fluctuation limit condition of the first grid-connected device. The second target grid-connected characteristic of the second grid-connected device is generated based on at least one pair of detail coefficients of the grid-connected power data in the wavelet transform process. When the second grid-connected device is operated and controlled, it can achieve compensation for the smoothing amount of the first grid-connected device, that is, the charging and discharging missing amount of the first grid-connected device, thereby ensuring that the grid-connected system combining the first grid-connected device and the second grid-connected device can meet the interaction requirements, thereby improving the operation control accuracy of the grid-connected system.

[0124] Furthermore, the grid-connected power data is divided into data sets based on the power data distribution type of at least one target power sub-data to obtain at least one transformed data set, and then the transformed data set is subjected to wavelet transform, thereby achieving targeted local wavelet transform, thereby obtaining updated grid-connected power data while minimizing the scope of wavelet transform. Therefore, the amount of data subjected to wavelet transform is minimized, thereby reducing the degree of smoothing of the grid-connected power data and improving the smoothing accuracy of the grid-connected power data. Alternatively, by determining the target detail coefficient for each category based on at least one pair of detail coefficients of the grid-connected power data during the wavelet transform process, and matching the target detail coefficients of each category with the energy storage device, it is ensured that the second target grid-connected feature can accurately characterize the operating power distribution status of each energy storage device, thereby improving the generation accuracy of the second target grid-connected feature.

[0125] It should be understood that, although the steps in the flowcharts of the above embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts of the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily to be performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0126] Based on the same inventive concept, embodiments of the present application further provide a grid-connected system operation control device for implementing the aforementioned grid-connected system operation control method. The implementation solution provided by this device is similar to the implementation solution described in the aforementioned method. Therefore, the specific limitations of one or more grid-connected system operation control device embodiments provided below can be found in the above-mentioned limitations of the grid-connected system operation control method, and will not be further elaborated here.

[0127] In an exemplary embodiment, Figure 5 As shown, an operation control device 500 for a grid-connected system is provided, comprising: a screening module 502, a transformation module 504, a generation module 506 and a control module 508, wherein:

[0128] A screening module 502 is configured to obtain grid-connected power data of the grid-connected system and screen target power data that does not meet the power fluctuation restriction condition corresponding to the first grid-connected device from the grid-connected power data;

[0129] The transformation module 504 is configured to perform a first transformation step of performing a wavelet transform on a portion of the grid-connected power data containing the target power data, and if the target power data can be filtered out from the updated grid-connected power data, return to the first transformation step until the target power data can no longer be filtered out from the grid-connected power data;

[0130] A generating module 506 is configured to generate a first target grid-connected characteristic for a first grid-connected device based on the grid-connected power data from which target power data cannot be filtered out; and to generate a second target grid-connected characteristic for a second grid-connected device based on at least one pair of detail coefficients obtained during a wavelet transform of the grid-connected power data, wherein the second grid-connected device is configured to compensate for a missing charge and discharge amount of the first grid-connected device.

[0131] The control module 508 is configured to control the operation of the grid-connected system according to the first target grid-connected characteristic and the second target grid-connected characteristic.

[0132] In one embodiment, the target power data includes at least one target power sub-data; the transformation module 504 is further used to divide at least one transformation data set from the grid-connected power data according to the power data distribution type of the at least one target power sub-data, wherein the transformation data set includes at least one target power data; perform at least one round of wavelet transform on the transformation data set to obtain wavelet transform information of the transformation data set in the final round; and update the transformation data set in the grid-connected power data according to at least one expansion coefficient in the wavelet transform information of the transformation data set in the final round.

[0133] In one embodiment, the transformation module 504 is also used to execute a second transformation step for each transformed data set: perform a round of wavelet transform on the transformed data set to obtain the wavelet transform information of the transformed data set in the current round; update the transformed data set according to at least one expansion coefficient in the wavelet transform information of the transformed data set in the current round; if the target power data can be filtered out in the transformed data set, return to execute the second transformation step until the target power data can no longer be filtered out in the transformed data set, and then determine the wavelet transform information of the transformed data set in the current round as the wavelet transform information of the final round.

[0134] In one embodiment, the second grid-connected device includes multiple energy storage devices; the generation module 506 is further used to determine the target detail coefficient of each category based on at least one pair of detail coefficients of the grid-connected power data during the wavelet transform process; the target detail coefficients of all categories are respectively allocated to the multiple energy storage devices; for each energy storage device, the second target grid-connected feature of the energy storage device is generated according to the target detail coefficient corresponding to the energy storage device.

[0135] In one embodiment, the generation module 506 is further used for one of the following: determining the statistical characteristic value of at least one pair of detail coefficients in each round of wavelet transform as the target detail coefficient of each category; determining the statistical characteristic value of at least one pair of detail coefficients corresponding to each transformed data set in each round of wavelet transform as the target detail coefficient of each category; determining each detail coefficient in each round of wavelet transform as the target detail coefficient of each category.

[0136] In one embodiment, the transformation module 504 is also used to determine a first division number according to a preset transformation number corresponding to the wavelet transformation method if there is at least one first-class target power sub-data belonging to a sparse distribution type in the target power data, and divide the first-class power data and the first-class target power sub-data into the same transformation data set according to the first division number, wherein the first-class power data is adjacent to the first-class target power sub-data, and the number of the first-class power data is consistent with the first division number; if there are multiple second-class target power sub-data belonging to a tight distribution type in the target power data, then determine a second division number according to the number of the second target power data and the preset transformation number, and divide the second-class power data and the multiple second-class target power sub-data into the same transformation data set according to the second division number, wherein the second-class power data is adjacent to the first second-class target power sub-data and the last second-class target power sub-data in the multiple second-class target power sub-data, respectively, and the number of the second-class power data is consistent with the second division number.

[0137] Each module in the aforementioned grid-connected system operation control device may be implemented in whole or in part through software, hardware, or a combination thereof. Each module may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0138] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 6As shown. The computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via wired or wireless means, and the wireless means can be implemented via Wi-Fi, a mobile cellular network, near-field communication (NFC), or other technologies. When executed by the processor, the computer program implements a method for controlling the operation of a grid-connected system. The display unit of the computer device is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0139] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0140] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0141] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0142] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0143] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0144] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0145] The above embodiments merely illustrate several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art may make various modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for controlling the operation of a grid-connected system, characterized in that: The grid-connected system includes a first grid-connected device and a second grid-connected device; the method includes: acquiring grid-connected power data of the grid-connected system, and screening target power data that does not meet the power fluctuation restriction condition corresponding to the first grid-connected device from the grid-connected power data; A first transformation step: performing wavelet transformation on a portion of the grid-connected power data including the target power data to update the data; if the target power data can be filtered out from the updated grid-connected power data, returning to the first transformation step until the target power data can no longer be filtered out from the grid-connected power data; generating a first target grid-connected feature of the first grid-connected device based on the grid-connected power data from which the target power data cannot be filtered out; generating a second target grid-connected feature of the second grid-connected device according to at least one pair of detail coefficients of the grid-connected power data in the wavelet transform process, wherein the second grid-connected device is used to compensate for the missing charge and discharge amount of the first grid-connected device; The operation of the grid-connected system is controlled according to the first target grid-connected characteristic and the second target grid-connected characteristic.

2. The method according to claim 1, characterized in that The target power data includes at least one target power sub-data; performing wavelet transform update on a portion of the grid-connected power data including the target power data, comprising: dividing at least one transformed data set from the grid-connected power data according to the power data distribution type of the at least one target power sub-data, wherein the transformed data set includes at least one target power data; Performing at least one round of wavelet transform on the transformed data set to obtain wavelet transform information of the transformed data set in a final round; The transformed data set in the grid-connected power data is updated according to at least one expansion coefficient in the wavelet transform information of the transformed data set in the final round.

3. The method according to claim 2, characterized in that The performing at least one round of wavelet transform on the transformed data set to obtain wavelet transform information of the transformed data set in the final round includes: For each of the transformed data sets, performing a second transform step: performing a round of wavelet transform on the transformed data set to obtain wavelet transform information of the transformed data set in the current round; updating the transformed data set according to at least one expansion coefficient in the wavelet transform information of the transformed data set in the current round; If the target power data can be filtered out from the transformed data set, the second transformation step is returned to be executed until the target power data can no longer be filtered out from the transformed data set, and the wavelet transformation information of the transformed data set in the current round is determined as the wavelet transformation information of the final round.

4. The method according to claim 2, characterized in that The second grid-connected device includes a plurality of energy storage devices; and generating a second target grid-connected feature of the second grid-connected device according to at least one pair of detail coefficients of the grid-connected power data in the wavelet transform process includes: determining a target detail coefficient for each category based on at least one pair of detail coefficients of the grid-connected power data in the wavelet transform process; Allocating target detail coefficients of all categories to the plurality of energy storage devices respectively; For each of the energy storage devices, a second target grid-connected characteristic of the energy storage device is generated according to the target detail coefficient correspondingly allocated to the energy storage device.

5. The method according to claim 4, characterized in that Determining a target detail coefficient for each category based on at least one pair of detail coefficients of the grid-connected power data in the wavelet transform process includes one of the following: Determine the statistical characteristic value of at least one pair of detail coefficients in each round of wavelet transform as the target detail coefficient of each category; Determine the statistical characteristic value of at least one pair of detail coefficients corresponding to each transformed data set in each round of wavelet transform as the target detail coefficient of each category; Each detail coefficient in each round of wavelet transform is determined as the target detail coefficient of each category.

6. The method according to any one of claims 2 to 5, characterized in that The dividing of the at least one transformed data set from the grid-connected power data according to the power data distribution type of the at least one target power sub-data comprises: If there is at least one first-category target power sub-data belonging to a sparse distribution type in the target power data, determining a first division number according to a preset transformation number corresponding to the wavelet transformation method, and dividing the first-category power data and the first-category target power sub-data into the same transformation data set according to the first division number, wherein the first-category power data is adjacent to the first-category target power sub-data, and the number of the first-category power data is consistent with the first division number; If there are multiple second-category target power sub-data of a tightly distributed type in the target power data, the second division number is determined based on the number of the second target power data and the preset transformation number, and according to the second division number, the second-category power data and the multiple second-category target power sub-data are divided into the same transformation data set, wherein the second-category power data are respectively adjacent to the first second-category target power sub-data and the last second-category target power sub-data in the multiple second-category target power sub-data, and the number of the second-category power data is consistent with the second division number.

7. An operation control device for a grid-connected system, characterized in that: The grid-connected system includes a first grid-connected device and a second grid-connected device; the devices include: a screening module, configured to obtain grid-connected power data of the grid-connected system and screen target power data that does not meet the power fluctuation restriction condition corresponding to the first grid-connected device from the grid-connected power data; a transformation module configured to perform a first transformation step of performing a wavelet transformation on a portion of the grid-connected power data containing the target power data, and if the target power data can be filtered out from the updated grid-connected power data, return to the first transformation step until the target power data can no longer be filtered out from the grid-connected power data; a generating module, configured to generate a first target grid-connected characteristic of the first grid-connected device based on the grid-connected power data from which the target power data cannot be filtered out; and to generate a second target grid-connected characteristic of the second grid-connected device based on at least one pair of detail coefficients of the grid-connected power data in the wavelet transform process, wherein the second grid-connected device is configured to compensate for a missing charge and discharge amount of the first grid-connected device; A control module is used to control the operation of the grid-connected system according to the first target grid-connected characteristic and the second target grid-connected characteristic.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

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

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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