New energy side end equipment data simulation reporting and query method and device

Abstract

The invention relates to the field of new energy, and particularly provides a new energy side end equipment data simulation reporting and querying method and device.Firstly, a seed data importing module allows a user to customize and import seed data, and the seed data comprises a timestamp and corresponding generating capacity data; then, the time range verification module firstly verifies the queried time range before carrying out data query; and finally, the data query calculation module enters a data query calculation link after the system successfully completes verification of the query time range and confirms that the query request conforms to the seed data time range limitation. Compared with the prior art, the method has the advantages that the seed data of the incremental generating capacity can be imported in a self-defined mode, the query time range is strictly controlled, accurate and efficient data simulation and query are achieved, and powerful support is provided for optimization and management of a new energy power generation system.

Description

TECHNICAL FIELD

[0001] The application relates to the field of new energy, and particularly provides a new energy edge device data simulation reporting and querying method and device. BACKGROUND

[0002] In the field of new energy, edge devices bear the heavy responsibility of collecting key data, and among them, inverter devices are particularly important. As the core hub connecting new energy power generation devices (such as solar panels, wind turbines, etc.) and the power grid, inverters not only convert the direct current generated by power generation devices into alternating current, but also continuously collect a large amount of data closely related to the power generation process. These data cover key information such as real-time power generation, power generation efficiency, and device operating status. For power generation system performance evaluation, the data collected by the inverter is like a precise "diagnostic report". By analyzing the long-term accumulated power generation data, the power generation capacity of the power generation system under different seasons and weather conditions can be intuitively understood, so as to evaluate whether the system achieves the expected power generation efficiency and judge whether there are potential fault hazards in the equipment. In terms of optimizing power generation efficiency, based on the power generation efficiency data collected by the inverter, combined with the device operating status data, technical personnel can accurately locate the energy loss link in the power generation process, and then adjust the device parameters or perform device maintenance and upgrade to maximize the improvement of power generation efficiency.

[0003] However, in actual application scenarios, data simulation and querying face many difficult challenges. In terms of data simulation, the traditional seed data import method is extremely limited. Many existing systems only support fixed format and fixed range data import, which is difficult to meet the diversified actual business needs.

[0004] For example, in some new new energy power generation projects, due to the uniqueness of geographical environment, climate conditions and other factors, the data to be simulated should reflect the special trend of power generation capacity changing with time.

[0005] However, the existing technology cannot flexibly generate such data that conforms to the actual scene, which makes it difficult to have reliable data support in the pre-project testing and scheme analysis stage, seriously affecting the feasibility study and scheme optimization of the project. SUMMARY

[0006] The present application is aimed at the deficiencies of the prior art, and provides a new energy edge device data simulation reporting and querying method with strong practicality.

[0007] The further technical task of the present application is to provide a new energy edge device data simulation reporting and querying device with reasonable design, safety and applicability.

[0008] The technical scheme adopted by the present application to solve its technical problems is:

[0009] A method for simulating reporting and querying data from new energy edge devices: First, the seed data import module allows users to customize the import of seed data, which includes timestamps and corresponding power generation data.

[0010] Then, before performing a data query, the time range verification module first verifies the time range of the query.

[0011] Finally, once the system successfully verifies the query time range and confirms that the query request complies with the seed data time range limit, the data query and calculation module will proceed to the data query and calculation stage.

[0012] Furthermore, in the seed data import module, the power generation data is set according to an increasing pattern, so that the simulated data conforms to the actual power generation trend.

[0013] Furthermore, in the time range verification module, the difference between the maximum and minimum time of the seed data is calculated to ensure that the query time length does not exceed this difference.

[0014] If the minimum time for seed data is t min The maximum time is t max The query starts at time t. start The end time is t end Then t must be satisfied. end -t start ≤t max -t min ;

[0015] If this condition is not met, the system will prompt the user to adjust the query time range.

[0016] Furthermore, in the data query and calculation module, based on the return time calculation and the return power generation calculation, data that meets the user's query requirements is extracted and calculated from the imported and stored seed data. When receiving a user's data query request, the system first clarifies the query start time t entered by the user. start With end time t end It is then converted into an internal time representation that is consistent with the seed data time format and is easy to compute.

[0017] Furthermore, in the calculation of the return time, the formula for calculating the return time T is as follows:

[0018] T = Seed time + (start date of query - start date of seed data) offset in days;

[0019] Seed time is the raw time value in the seed data corresponding to the time to be calculated. The start date for the query must be the start time t entered by the user. startExtract the corresponding date portion. Similarly, the start date of the seed data is the earliest recorded date in the seed data set. Let t be the start date of the query in the offset days. start The seed data starts on date t. min Then, the offset days n1 (start date of query - start date of seed data) = t start -t min This difference reflects the time offset of the query start point relative to the seed data start point.

[0020] Furthermore, in the calculation of the returned power generation, the formula for calculating the returned power generation P is:

[0021] P = current value + [(start date of query - start date of seed data) / (maximum date of seed data - minimum date of seed data + 1)] * (maximum value of seed data - minimum value of seed data);

[0022] The current value p is the power generation value at the moment corresponding to the calculation return time T in the seed data, and the maximum value P in the seed data is... max With minimum value P min These are the maximum and minimum power generation values ​​recorded in the seed dataset, respectively.

[0023] Furthermore, the seed data is traversed in chronological order, and calculations are performed on the data corresponding to each time point to filter out the data that is at the start time t of the user query. start With end time t end All data points within the range are used to calculate time and power generation data, which are then organized into a user-friendly format. The complete data results are returned to the user, completing the entire data query, calculation, and feedback process.

[0024] A data simulation reporting and querying device for new energy edge devices includes: at least one memory and at least one processor;

[0025] The at least one memory is used to store a machine-readable program;

[0026] The at least one processor is used to call the machine-readable program to execute a method for simulating and reporting data from new energy edge devices.

[0027] Compared with the prior art, the data simulation reporting and querying method and apparatus for new energy edge devices of the present invention have the following outstanding advantages:

[0028] This invention, by importing custom seed data of incremental power generation, can more realistically simulate the actual operation of new energy power generation systems, providing a reliable data foundation for subsequent data processing and analysis. Using the simulation data of this invention makes the model more realistic and improves the accuracy of the assessment.

[0029] By strictly controlling the query time range and calculating the returned data using specific formulas, we ensure that the query results obtained by users not only meet their actual needs but also fall within a reasonable data range, avoiding data bias caused by unreasonable query time ranges. This helps users utilize data more efficiently and make quick decisions, such as accurately obtaining the necessary data for analysis when analyzing changes in power generation efficiency over a specific time period.

[0030] It supports the import of custom seed data, which can adapt to the needs of different new energy power generation scenarios. Users can adjust the seed data according to the actual project characteristics to meet diverse data simulation and query needs, thereby improving the system's versatility and flexibility. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a schematic diagram of the seed data import process in a method for simulating and reporting data from new energy edge devices;

[0033] Figure 2 This is a flowchart illustrating the time offset process in a data simulation reporting and query method for new energy edge devices.

[0034] Figure 3 This is a breakdown diagram of the dynamic calculation process of power generation in a data simulation reporting and query method for new energy edge equipment. Detailed Implementation

[0035] To enable those skilled in the art to better understand the present invention, the present invention will be further described in detail below with reference to specific embodiments. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] The following is a preferred embodiment:

[0037] like Figure 1As shown in this embodiment, a method for simulating, reporting, and querying data from new energy edge devices involves several steps. First, the seed data import module allows users to customize and import seed data, which includes a timestamp and corresponding power generation data. The power generation data is set according to an increasing pattern to ensure that the simulated data conforms to actual power generation trends. For example, users can import seed data into the system using a specific file format (such as a CSV file). The system performs format verification and parsing on the imported data to ensure its accuracy and completeness.

[0038] Then, before performing a data query, the time range verification module first verifies the time range of the query.

[0039] Calculate the difference between the maximum and minimum times of the seed data, ensuring that the query time does not exceed this difference. For example, if the minimum time of the seed data is t... min The maximum time is t max The query starts at time t. start The end time is t end Then t must be satisfied. end -t start ≤t max -t min If this condition is not met, the system will prompt the user to adjust the query time range.

[0040] Finally, once the system successfully verifies the query time range and confirms that the query request complies with the seed data time range restrictions, the data query and calculation module proceeds to the data query and calculation stage. Based on the returned time calculation and returned power generation calculation, it extracts and calculates data that meets the user's query requirements from the imported and stored seed data. When receiving a user's data query request, it first clarifies the user-input query start time t. start With end time t end It is then converted into an internal time representation that is consistent with the seed data time format and is easy to compute.

[0041] When receiving a user's data query request, the system first determines the query start time t entered by the user. start With end time t end It is then converted into an internal time representation that is consistent with the seed data time format and is easy to calculate, such as converting it into milliseconds starting from a fixed start time point (e.g., January 1, 1970, 00:00:00).

[0042] The return time T is calculated using the following formula:

[0043] T = Seed time + (start date of query - start date of seed data) offset in days.

[0044] Seed time is the original time value in the seed data corresponding to the time to be calculated, providing a basic time reference point for the calculation.

[0045] like Figure 2 As shown, the start date for the query must be the start time t entered by the user. start Extract the corresponding date portion. Similarly, the start date of the seed data is the earliest recorded date in the seed data set. Calculating the offset in days is crucial. Let the start date of the query be t. start The seed data starts on date t. min Then, the offset days n1 (start date of query - start date of seed data) = t start -t min This difference reflects the time offset of the query start point relative to the seed data start point.

[0046] To illustrate with a specific example, let's assume the seed data starts on date t. min For "January 1, 2023", the maximum date is t. max The user query starts on the date "January 10, 2023". start If the seed time t is "January 3, 2023", then n1 = 3 - 1 = 2 days. If a seed time t is "January 1, 2023, 08:00:00", according to the formula, the offset of the return time T on the time axis is 2 days. After converting this offset into a time unit (such as seconds, milliseconds, etc., depending on the system's internal time precision setting), it is added to the seed time t to obtain the return time T that meets the query conditions.

[0047] The calculation of the returned power generation, P, is calculated using the following formula:

[0048] P = current value + [(start date of query - start date of seed data) / (maximum date of seed data - minimum date of seed data + 1)] * (maximum value of seed data - minimum value of seed data).

[0049] The current value p here is the power generation value at the moment corresponding to the calculation return time T in the seed data. The maximum value P in the seed data. max With minimum value P min These are the maximum and minimum power generation values ​​recorded in the seed dataset, respectively.

[0050] Continuing with the example above, let's assume the minimum power generation value P in the seed data. min =10.0kWh, maximum value P max=20.0kWh, and the current power generation value p corresponding to the seed time "January 1, 2023, 08:00:00" is 12.0kWh. According to the formula, the returned power generation P = 12.0 + [(3-1 / (9+1)]*(20-10) = 14kWh.

[0051] Through the above calculation process, the seed data is traversed in chronological order, and the data corresponding to each time point is calculated to filter out the data at the user query start time t. start With end time t end All data points within the specified range. The calculated time and power generation data are then organized into a user-friendly format, such as a table, with each row recording a time point and its corresponding power generation. The complete data results are then returned to the user, completing the entire data query, calculation, and feedback process, providing users with accurate and tailored simulation data query results. Figure 3 As shown.

[0052] Based on the above method, a new energy edge device data simulation reporting and querying device in this embodiment includes: at least one memory and at least one processor;

[0053] The at least one memory is used to store a machine-readable program;

[0054] The at least one processor is used to call the machine-readable program to execute a method for simulating and reporting data from new energy edge devices.

[0055] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for simulating data reporting and querying from new energy edge devices, characterized in that, First, the seed data import module allows users to import custom seed data, which includes timestamps and corresponding power generation data. Then, before performing a data query, the time range verification module first verifies the time range of the query. Finally, once the system successfully verifies the query time range and confirms that the query request complies with the seed data time range limit, the data query and calculation module proceeds to the data query and calculation stage.

2. The method for simulating, reporting, and querying data from new energy edge devices according to claim 2, characterized in that, In the seed data import module, the power generation data is set according to an increasing pattern, so that the simulated data conforms to the actual power generation trend.

3. The method for simulating reporting and querying data from new energy edge devices according to claim 2, characterized in that, In the time range verification module, the difference between the maximum and minimum time of the seed data is calculated to ensure that the query time length does not exceed this difference. If the minimum time for seed data is t min The maximum time is t max The query starts at time t. start The end time is t end Then t must be satisfied. end -t start ≤t max -t min ; If this condition is not met, the system will prompt the user to adjust the query time range.

4. The method for simulating, reporting, and querying data from new energy edge devices according to claim 3, characterized in that, In the data query and calculation module, based on the return time calculation and the return power generation calculation, data that meets the user's query requirements is extracted and calculated from the imported and stored seed data. When receiving a user's data query request, the system first determines the query start time t entered by the user. start With end time t end It is then converted into an internal time representation that is consistent with the seed data time format and is easy to compute.

5. The method for simulating, reporting, and querying data from new energy edge devices according to claim 4, characterized in that, In the calculation of the return time, the formula for calculating the return time T is as follows: T = Seed time + (Start date of query - Start date of seed data) offset in days; Seed time is the raw time value in the seed data corresponding to the time to be calculated. The start date for the query must be from the start time t entered by the user. start Extract the corresponding date portion. Similarly, the start date of the seed data is the earliest recorded date in the seed data set. Let t be the start date of the query in the offset days. start The seed data starts on date t. min Then, the offset days n1 (start date of query - start date of seed data) = t start -t min This difference reflects the time offset of the query start point relative to the seed data start point.

6. The method for simulating reporting and querying data from new energy edge devices according to claim 5, characterized in that, In the calculation of the returned power generation, the formula for calculating the returned power generation P is: P = current value + [(start date of query - start date of seed data) / (maximum date of seed data - minimum date of seed data + 1)] * (maximum value of seed data - minimum value of seed data); The current value p is the power generation value at the moment corresponding to the calculation return time T in the seed data, and the maximum value P in the seed data is... max With minimum value P min These are the maximum and minimum power generation values ​​recorded in the seed dataset, respectively.

7. The method for simulating, reporting, and querying data from new energy edge devices according to claim 6, characterized in that, Iterate through the seed data in chronological order, calculate the data corresponding to each time point, and filter out the data that is at the start time t of the user query. start With end time t end All data points within the range are used to calculate time and power generation data, which are then organized into a user-friendly format. The complete data results are returned to the user, completing the entire data query, calculation, and feedback process.

8. A data simulation reporting and query device for new energy edge devices, characterized in that, include: At least one memory and at least one processor; The at least one memory is used to store a machine-readable program; The at least one processor is configured to invoke the machine-readable program to perform the method according to any one of claims 1 to 7.

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