Method, device and electronic equipment for processing inverter operation data

Abstract

The application provides a method and device for processing inverter operation data and an electronic device. The method comprises: obtaining historical operation data of a target inverter; dividing the historical operation data into at least one data group based on abnormal time information; obtaining astronomical data corresponding to a date, determining a start time of the target inverter on the date based on the astronomical data; and updating time information of the historical operation data in the data group corresponding to the date based on the start time. In this way, the time information corresponding to the historical operation data of the inverter during the network interruption period can be accurately inferred. Based on the accurate time information, the operation data during the network interruption period can accurately reflect the operation state of the photovoltaic module.

Description

Technical Field

[0001] This application relates to the field of power communication technology, and in particular to a method, apparatus and electronic device for processing inverter operating data. Background Technology

[0002] Inverters can monitor photovoltaic (PV) modules and generate relevant operational data during the monitoring process. When the inverter is connected to the network, it synchronizes its time with the network, and the operational data carries the correct time information before being uploaded to the cloud system. However, if the network is disconnected after the inverter has started, it cannot synchronize its time through the network, resulting in incorrect time information in the operational data. Consequently, the operational data during the network outage period cannot accurately reflect the operating status of the PV modules. Summary of the Invention

[0003] In view of this, the purpose of this application is to provide a method, apparatus and electronic device for processing inverter operating data, so that the operating data during grid outages can also accurately reflect the operating status of photovoltaic modules.

[0004] In a first aspect, embodiments of this application provide a method for processing inverter operating data. The method includes: acquiring historical operating data of a target inverter; wherein the historical operating data is operating data generated by the target inverter during a grid outage, and the historical operating data carries abnormal time information; the abnormal time information is uncalibrated time information; based on the abnormal time information, dividing the historical operating data into at least one data group; wherein the operating data in the same data group belongs to the same date; acquiring astronomical data corresponding to the date, and determining the start-up time of the target inverter on the date based on the astronomical data; and updating the time information of the historical operating data in the data group corresponding to the date based on the start-up time.

[0005] Following the step of dividing historical operating data into at least one data group based on abnormal time information, the method further includes: acquiring first operating data and second operating data of the target inverter; wherein, the first operating data is the last operating data received by the target inverter before the start of the grid outage period; the second operating data is the first operating data received by the target inverter after the end of the grid outage period; the first operating data and the second operating data carry normal time information; the normal time information is calibrated time information; based on the first operating data and the second operating data, determining the number of dates during the grid outage period; if the number of dates matches the number of data groups, determining that the historical operating data is valid.

[0006] The above method also includes the following steps: if the number of dates does not match the number of data groups, determine that the historical operating data is invalid; stop the process of obtaining the astronomical data corresponding to the date, determine the start-up time of the target inverter on the date based on the astronomical data, and update the time information of the historical operating data in the data group corresponding to the date based on the start-up time.

[0007] After the steps of obtaining the first operating data and the second operating data of the target inverter, the method further includes: determining the date information corresponding to the data group based on the first operating data and / or the second operating data.

[0008] The steps described above for determining the start-up time of the target inverter on a given date based on astronomical data include: determining the sunrise time on the given date based on astronomical data; and determining the start-up time of the target inverter on the given date based on the sunrise time.

[0009] The historical running data in the same data group are arranged in chronological order, and there is a specified time interval between adjacent running data. The step of updating the time information of the historical running data in the data group corresponding to the start time includes: updating the time information of the first historical running data in the data group in chronological order based on the start time; and updating the time information of the subsequent historical running data of the first historical running data in the data group based on the specified time interval and the time information of the first historical running data.

[0010] Following the steps of updating the time information of historical operating data in the data group corresponding to the startup time, the method further includes: determining the shutdown time of the target inverter on the date based on astronomical data; determining whether the updated time information of the historical operating data in the data group matches the shutdown time; and if they match, determining that the historical operating data in the data group is valid data.

[0011] The steps described above for determining whether the updated time information of historical running data in the data group matches the shutdown time include: obtaining the updated time information of the last sorted historical running data in the data group; if the time interval between the updated time information of the last sorted historical running data and the shutdown time is less than a specified interval threshold, determining that the updated time information of the historical running data in the data group matches the shutdown time; if the time interval between the updated time information of the last sorted historical running data and the shutdown time is greater than or equal to the specified interval threshold, determining that the updated time information of the historical running data in the data group does not match the shutdown time.

[0012] The above method also includes: if there is a mismatch, determining that the historical running data in the data group is invalid data.

[0013] After determining the start-up time of the target inverter on a given date based on astronomical data, the method further includes: identifying a first inverter that is within a specified distance range from the target inverter; wherein the first inverter is connected to the network during the period when the target inverter is offline; obtaining the start-up time of the first inverter on a given date; and updating the start-up time of the target inverter on a given date based on the start-up time of the first inverter on a given date.

[0014] After determining the start-up time of the target inverter on a given date based on astronomical data, the method further includes: obtaining the geographical information of the target inverter; and updating the start-up time of the target inverter on a given date based on the geographical information.

[0015] Secondly, embodiments of this application provide an inverter operation data processing apparatus, comprising: a historical operation data acquisition module, used to acquire historical operation data of a target inverter; wherein the historical operation data is operation data generated by the target inverter during a grid outage, and the historical operation data carries abnormal time information; the abnormal time information is uncalibrated time information; a data group division module, used to divide the historical operation data into at least one data group based on the abnormal time information; wherein the operation data in the same data group belongs to the same date; a start-up time determination module, used to acquire astronomical data corresponding to the date, and determine the start-up time of the target inverter on the date based on the astronomical data; and a time information update module, used to update the time information of the historical operation data in the data group corresponding to the date based on the start-up time.

[0016] Thirdly, embodiments of this application provide an electronic device, characterized in that it includes a processor and a memory, the memory storing computer-executable instructions that can be executed by the processor, and the processor executing the computer-executable instructions to implement the above-described method for processing inverter operating data.

[0017] The aforementioned electronic devices do not include clock circuits.

[0018] Fourthly, embodiments of this application provide a computer-readable storage medium, characterized in that the computer-readable storage medium stores computer-executable instructions, which, when called and executed by a processor, cause the processor to implement the above-described method for processing inverter operating data.

[0019] The aforementioned method, apparatus, and electronic equipment for processing inverter operating data acquire historical operating data of the target inverter. This historical operating data is generated during grid outages and carries abnormal time information; the abnormal time information is uncalibrated time information. Based on the abnormal time information, the historical operating data is divided into at least one data group; the operating data within the same data group belongs to the same date. Astronomical data corresponding to the date is acquired, and based on the astronomical data, the start-up time of the target inverter on that date is determined. Based on the start-up time, the time information of the historical operating data in the data group corresponding to that date is updated. In this method, the start-up time of the inverter on that date is determined based on the astronomical data, and then the time information of the historical operating data in the data group is updated based on the start-up time. This method can accurately infer the time information corresponding to the historical operating data of the inverter during grid outages. Based on accurate time information, the operating data during grid outages can also accurately reflect the operating status of the photovoltaic modules.

[0020] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0021] To more clearly illustrate the specific embodiments of this application or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the monitoring methods provided in related technologies;

[0023] Figure 2 A flowchart illustrating a method for processing inverter operating data provided in this application embodiment;

[0024] Figure 3 A schematic diagram of the historical operational data before and after the update, provided in an embodiment of this application;

[0025] Figure 4 A flowchart illustrating the time information of a target inverter processing operating data is provided in an embodiment of this application.

[0026] Figure 5 A flowchart illustrating the updating of historical runtime data by a cloud-based controller is provided as an embodiment of this application.

[0027] Figure 6A schematic diagram of an inverter operation data processing device provided in an embodiment of this application;

[0028] Figure 7 This is a schematic diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0030] Taking residential applications as an example, photovoltaic systems often use micro-inverter devices, also known as miniature grid-connected photovoltaic inverters. Micro-inverter devices are small in size, have low DC-side voltage, and small single-unit power capacity. They can perform independent MPPT (Maximum Power Point Tracking) monitoring on each photovoltaic module, and have module-level monitoring and shutdown functions. Currently, there are two main monitoring methods for micro-inverter devices:

[0031] In one approach, a single DTU (Data Transfer Unit) is used to centrally monitor multiple micro-reverse devices, either locally or remotely. Figure 1 As shown in (a), each micro-inverter is connected to a corresponding photovoltaic module. Multiple micro-inverters are connected in parallel, and the multiple micro-inverters connected in parallel are connected to the power grid and electrical equipment. Multiple micro-inverters are connected to a DTU, which can connect to a router via Wi-Fi, and then the router connects to cloud devices. The DTU can also connect to a base station via a mobile network, and then the base station connects to cloud devices.

[0032] In practical applications, in order to store the operating data of the micro inverter device at accurate times during network outages, the DTU uses an independent power supply or adds a button battery, but this increases the cost.

[0033] In another approach, the micro-reversing device has a built-in Wi-Fi module, enabling local and remote monitoring of the device, such as... Figure 1 As shown in (b), each micro-inverter is connected to a corresponding photovoltaic module. Multiple micro-inverters are connected in parallel, and the parallel micro-inverters are connected to the power grid and electrical equipment. The multiple micro-inverters are connected to a router via Wi-Fi, and then the router is connected to a cloud device.

[0034] In practical applications, microinverter equipment has a long warranty period and uses a potting process in its production, making it impossible to disassemble. Therefore, it is currently impossible to use battery modules inside microinverter equipment. This results in the inability to store the operating data of microinverter equipment at an accurate time for an extended period during grid outages. Specifically, microinverter equipment shuts down daily, and if the equipment is disconnected from the grid when it restarts, it cannot synchronize the time via the network. The time information carried in the operating data is incorrect, causing the operating data during grid outages to fail to accurately reflect the operating status of the photovoltaic modules. This operating data cannot be displayed accurately either.

[0035] Based on this, the inverter operation data processing method, apparatus and electronic device provided in the embodiments of this application can be applied to photovoltaic systems.

[0036] To facilitate understanding of this embodiment, a method for processing inverter operating data disclosed in this application will first be described in detail, such as... Figure 2 As shown, this method can be executed by the inverter's controller, etc., and includes the following steps:

[0037] Step S201: Obtain historical operating data of the target inverter; wherein, the historical operating data is the operating data generated by the target inverter during the grid outage, and the historical operating data carries abnormal time information; the abnormal time information is time information that has not been calibrated.

[0038] Even during a grid outage, the target inverter will still generate operating data. This data can include the inverter's own operating data, as well as the operating data of the photovoltaic modules connected to it, such as current, voltage, and power data. The operating data generated by the target inverter during the grid outage is called historical operating data; this historical operating data can be stored in the target inverter during the outage.

[0039] During the network outage, the target inverter cannot synchronize its time with the network. Therefore, the time on the target inverter is uncalibrated time information, and the time information carried by the historical operating data is also uncalibrated time information, i.e., abnormal time information.

[0040] Target inverters typically have a default start time set, such as January 1, 1970, 00:00. If the inverter is connected to the network after startup, it can obtain the network time and operate according to the network time. If the target inverter is disconnected from the network after startup and cannot obtain the network time, the target inverter will operate according to the aforementioned start time, resulting in a significant difference between the time running in the target inverter and the actual time.

[0041] After the target inverter is connected to the network, it can upload the above-mentioned historical operating data to the controller and other devices, and the controller can then obtain the historical operating data.

[0042] Step S202: Based on the abnormal time information, divide the historical operation data into at least one data group; wherein the operation data in the same data group belongs to the same date;

[0043] When the controller obtains historical operating data carrying abnormal time information, it can automatically trigger the calibration logic, that is, automatically execute steps S202-S204.

[0044] During a grid outage, the abnormal time information generated by the target inverter also changes at the normal rate of time flow; that is, the date is updated by one day every 24 hours. Therefore, based on the abnormal time information, it is also possible to distinguish which data belong to the same day from historical operating data.

[0045] The abnormal time information includes information such as year, month, day, hour, minute, and second. Based on the historical operation data of the same year, month, and day in the abnormal time information, it is divided into a data group.

[0046] Step S203: Obtain the astronomical data corresponding to the date, and determine the start-up time of the target inverter on the date based on the astronomical data;

[0047] Considering that the dates carried in the abnormal time information are inaccurate, the dates corresponding to the network outage period can be determined based on the network outage date and network connection date of the target inverter. The dates corresponding to the network outage period can be assigned to each data group in sequence to obtain the real date corresponding to each data group.

[0048] Once the actual date is obtained, the corresponding astronomical data can be acquired. This astronomical data can include latitude and longitude, the time zone of the target inverter, solar declination, and other data. The sunrise time for that date can be obtained by calculating the astronomical data using a preset astronomical formula.

[0049] Since the target inverter starts up at sunrise and shuts down at sunset, the startup time of the target inverter on that date can be determined.

[0050] Step S204: Based on the startup time, update the time information of historical running data in the data group corresponding to the date.

[0051] After the target inverter starts up, it will generate operating data at specified time intervals. Historical operating data in the same data group belong to the same date, are arranged in chronological order under that date, and there is a specified time interval between adjacent operating data. The cloud can update the time information of the first historical operating data in the data group corresponding to the start time, and update the time information of the historical operating data after the first historical operating data in the data group at specified time intervals.

[0052] The above-mentioned method for processing inverter operating data involves obtaining historical operating data of the target inverter; wherein, the historical operating data is the operating data generated by the target inverter during a grid outage, and the historical operating data carries abnormal time information; the abnormal time information is uncalibrated time information; based on the abnormal time information, the historical operating data is divided into at least one data group; wherein, the operating data in the same data group belongs to the same date; obtaining the astronomical data corresponding to the date, and determining the start-up time of the target inverter on the date based on the astronomical data; and updating the time information of the historical operating data in the data group corresponding to the date based on the start-up time.

[0053] In this method, the start-up time of the inverter on the corresponding date is determined based on the astronomical data. Then, the time information of the historical operating data in the data group is updated based on the start-up time. This method can more accurately infer the time information corresponding to the historical operating data of the inverter during the grid outage. Based on the accurate time information, the operating data during the grid outage can also accurately reflect the operating status of the photovoltaic module.

[0054] In one specific implementation, first operating data and second operating data of the target inverter are obtained; wherein, the first operating data is the last operating data received by the target inverter before the start of the grid outage period; the second operating data is the first operating data received by the target inverter after the end of the grid outage period; the first operating data and the second operating data carry normal time information; the normal time information is calibrated time information; based on the first operating data and the second operating data, the number of dates during the grid outage period is determined; if the number of dates matches the number of data groups, the historical operating data is determined to be valid.

[0055] The first operating data is the last operating data received by the target inverter before the start of the network outage period, such as... Figure 3 T0 is shown in (a); the second operating data is the first operating data received by the target inverter after the grid outage period ends, such as... Figure 3 T1 is shown in (a); as shown in (a) Figure 3 As shown in (a), 'Day 1 Tstart' represents the start-up time of the target inverter on the first day of the grid outage, 'Day 2 Tstart' represents the start-up time of the target inverter on the second day of the grid outage, and 'Day m Tstart' represents the start-up time of the target inverter on the m-th day of the grid outage.

[0056] Specifically, the cloud obtains the first and second operating data of the target inverter, calculates the number of days during the network outage based on the first and second operating data, and then determines whether the number of days matches the number of data groups. If the number of days matches the number of data groups, the historical operating data is determined to be valid, and the subsequent steps are executed.

[0057] In one example, if the number of dates does not match the number of data groups, the historical running data is determined to be invalid; the process of obtaining the astronomical data corresponding to the date, determining the startup time of the target inverter on the date based on the astronomical data, and updating the time information of the historical running data in the data group corresponding to the date based on the startup time is stopped.

[0058] When the cloud determines whether the number of dates matches the number of data groups, if the number of dates does not match the number of data groups, it determines that the historical running data is invalid and then stops executing the aforementioned steps S203 and S204.

[0059] Furthermore, based on the first running data and / or the second running data, the date information corresponding to the data group is determined.

[0060] like Figure 3 As shown in (b), N1 to N7 represent a 7-day data set. There are three ways to determine the date information corresponding to the data set:

[0061] Method 1: Determine the date information corresponding to the data group based on the first running data. That is, calculate the date information corresponding to the data group forward based on the first running data. For example, the date of N1 is determined by adding one day to the date of T0.

[0062] Method 2: Determine the date information corresponding to the data group based on the second running data. That is, calculate the date information corresponding to the data group in reverse based on the second running data. For example, the date of N6 is determined by subtracting one day from the date of T1.

[0063] Method 3: Determine the date information corresponding to the data group based on the first and second running data. That is, calculate the date information corresponding to the data group forward based on the first running data, and verify it by calculating the date information corresponding to the data group backward based on the second running data. For example, add one day to the date of T0 to get the date of N1, and then verify it by subtracting six days from the date of T1. If they are the same, then the date of T1 can be determined.

[0064] In one specific implementation, the sunrise time of the date is determined based on astronomical data; and the startup time of the target inverter on the date is determined based on the sunrise time.

[0065] Specifically, the cloud platform calculates the sunrise time for a given date based on the latitude and longitude of the power station where the target inverter is located, using astronomical formulas. Then, based on the sunrise time, it calculates the startup time of the target inverter on that date. For example, the sunrise time can be determined as the startup time of the target inverter, or the startup time can be a specified time interval after the sunrise time.

[0066] The historical running data in the same data group are arranged in chronological order, with a specified time interval between adjacent running data.

[0067] like Figure 3 As shown in (b), for each data group from N1 to N7, the historical operating data is arranged in chronological order, and there is a specified time interval t between each two adjacent operating data. For example, if the specified time interval is 5 minutes, it can be understood that the cycle for recording the operating data of the target inverter is 5 minutes.

[0068] The following embodiment provides a specific implementation method for updating the time information of historical running data in the data group corresponding to the startup time and the date: based on the startup time, update the time information of the historical running data that is first in the data group according to the time order; based on a specified time interval and the time information of the first-ranked historical running data, update the time information of the subsequent historical running data of the first-ranked historical running data in the data group.

[0069] like Figure 3 As shown in (b), Tm represents the start time of data group N7 on that date. The data groups during the network outage include N1 to N7, and T2 represents the start time of a certain date during the network outage. The start time of N7 is obtained by calculating the first product of the number of running data records in the data group where N7 is located and the specified time interval, and then calculating the difference between the second running data and the first product. The start times of N1 to N6 can be calculated using astronomical data. For N1 to N7, the time information of the first historical running data in the data group, sorted in chronological order, is updated according to the start time of the day of the network outage.

[0070] For example Figure 3 The time of the historical running data following the first ranked historical running data in the data groups N1 to N7 shown in (b) can be calculated based on the specified time interval t and the time information of the first ranked historical running data, and then the time information is updated.

[0071] In one specific implementation, the shutdown time of the target inverter on a given date is determined based on astronomical data; the updated time information of the historical operating data in the data group is checked to see if it matches the shutdown time; if they match, the historical operating data in the data group is determined to be valid data.

[0072] The cloud platform calculates the sunset time corresponding to the date based on the latitude and longitude of the power station where the target inverter is located and astronomical formulas. Then, based on the sunset time, it calculates the shutdown time of the target inverter on this date. The updated time information of the historical operating data in the data group is matched with the shutdown time to obtain the matching result. If the matching result indicates that the updated time information of the historical operating data in the data group matches the shutdown time, then the historical operating data in the data group is determined to be valid data.

[0073] Specifically, the updated time information of the last historical running data in the data group can be obtained. If the updated time information of the last historical running data is close to the shutdown time, the historical running data in the data group can be determined to be valid data.

[0074] Furthermore, the updated time information of the last sorted historical running data in the data group is obtained; if the time interval between the updated time information of the last sorted historical running data and the shutdown time is less than a specified interval threshold, the updated time information of the historical running data in the data group is determined to match the shutdown time; if the time interval between the updated time information of the last sorted historical running data and the shutdown time is greater than or equal to the specified interval threshold, the updated time information of the historical running data in the data group is determined not to match the shutdown time.

[0075] The specified interval threshold can be set according to actual needs.

[0076] Specifically, the cloud retrieves the updated time information of the last historical running data in each data group, and then matches this updated time information with the shutdown time. If the time interval between the two is less than a specified threshold, the matching result indicates that the updated time information of the historical running data in the data group matches the shutdown time; if the time interval is greater than or equal to the specified threshold, the matching result indicates that the updated time information of the historical running data in the data group does not match the shutdown time. If there is no match, the historical running data in the data group is determined to be invalid data.

[0077] If the time interval between the updated time of the last historical operating data and the shutdown time is less than the specified interval threshold, it means that the target inverter shut down at the shutdown time after generating the last historical operating data, and the historical operating data in this data group is reasonable and belongs to valid data.

[0078] If the time interval between the updated time of the last historical running data and the shutdown time is greater than the specified interval threshold, for example, if the specified interval threshold is 10 minutes, the updated time of the last historical running data is 18:05, the shutdown time is 20:00, and there is no historical running data between 18:05 and 20:00, it means that the historical running data of this data group is unreasonable and belongs to invalid data.

[0079] For example, if the last historical operating data was updated at 18:05 and the shutdown time was 16:00, the target inverter should not generate any operating data between 16:00 and 18:05. However, the historical operating data for this time period still exists, indicating that the historical operating data of this data group is unreasonable and is invalid.

[0080] In one approach, a first inverter that is within a specified distance range from the target inverter is identified; wherein, during the period when the target inverter is offline, the first inverter is connected to the network; the start-up time of the first inverter on a given date is obtained, and the start-up time of the target inverter on a given date is updated based on the start-up time of the first inverter on that date.

[0081] The first inverter is typically located closer to the target inverter. The first inverter can usually be located at a power station adjacent to the power station where the target inverter is located.

[0082] The controller in the cloud typically stores the address information of multiple inverters, such as latitude and longitude information; it can identify the first inverter that meets the specified distance range from the target inverter among the adjacent power stations of the power station where the target inverter is located; the specified distance range can be 100 meters, etc.

[0083] The first inverter connects to the network and uploads operational data during the target inverter's network outage period. It obtains the start time of the data set corresponding to the date, and then updates the target inverter's start time on that date based on the first inverter's start time. For example, the first inverter's start time on that date can be used as the target inverter's start time, or the target inverter's start time can be obtained by shortening or lengthening the first inverter's start time based on the latitude and longitude of the two inverters.

[0084] In another approach, the geographic information of the target inverter is obtained; based on the geographic information, the start-up time of the target inverter on the specified date is updated.

[0085] Geographic information can include weather conditions at the location of the target inverter.

[0086] The cloud-based controller can obtain the geographical information of the target inverter. After calculating the sunrise time for the date using astronomical data and taking into account factors such as weather, it updates the startup time of the target inverter for that date. For example, in rainy weather, the startup time needs to be postponed.

[0087] In one embodiment, such as Figure 4 As shown below, the steps for the target inverter to process operating data are described in detail.

[0088] Step S401: The target inverter is started, and the initial time information in the target inverter is obtained;

[0089] Step S402: Establish a communication connection with the controller in the cloud;

[0090] Step S403: Determine whether the connection is successful. If the connection is successful, proceed to step S404; if the connection is unsuccessful, proceed to step S409.

[0091] Step S404: The target inverter obtains the real-time time from the controller in the cloud.

[0092] Step S405: The target inverter uploads the historical operating data stored during the network outage;

[0093] Step S406: Determine whether the time interval t2 since the last upload is greater than the interval threshold T2. If it is greater than the time threshold T2, proceed to step S407; if it is less than or equal to the time threshold T2, proceed to step S408.

[0094] Step S407: The target inverter uploads real-time operating data and returns to step S406 for a loop; End.

[0095] Step S408: Determine if the time synchronization has been reached. If yes, proceed to step S404; otherwise, proceed to step S405. For example, it can be preset to synchronize time every two hours. In this case, a two-hour countdown can be set in the target inverter. After the countdown ends, the time synchronization is reached. End.

[0096] Step S409: Determine whether the time interval t1 for storing the target inverter's operating data is greater than the interval threshold T1. If yes, proceed to step S410; otherwise, proceed to step S402.

[0097] In step S410, the target inverter stores the operating data and returns to step S409 for a loop.

[0098] In one embodiment, such as Figure 5 As shown below, the steps for updating historical running data by the controller in the cloud after performing step S405 are described in detail below.

[0099] Step S501: The controller in the cloud acquires historical operating data;

[0100] Step S502: Divide the data into groups according to the timestamp feature algorithm. The timestamp feature algorithm can extract abnormal time information carried in the historical running data. Based on the year, month and day in the abnormal time information, the historical running data is divided. The running data in the same data group belongs to the same date.

[0101] Step S503: Determine whether the historical operation data is valid. If it is valid, proceed to step S504; if it is invalid, proceed to step S509. Specifically, the validity of the historical operation data can be determined based on the number of dates during the network outage and the number of data groups. For example, if the number of dates during the network outage is equal to the number of data groups, the historical operation data can be determined to be valid.

[0102] Step S504: Obtain astronomical data and calculate the sunrise and sunset times corresponding to the date;

[0103] Step S505: Calculate the start-up time of the target inverter;

[0104] Step S506: Calibrate the start-up time of the target inverter based on weather factors;

[0105] Step S507: Recalibrate the start-up time of the target inverter based on the start-up time of the first inverter of the adjacent latitude and longitude power station;

[0106] Step S508: Update the time information of historical running data; specifically, the time information of the first historical running data in the data group, sorted by time order, can be updated according to the start time, and then the time information of the subsequent historical running data of the first historical running data in the data group can be updated in combination with the specified time interval.

[0107] This embodiment solves the problem that, without increasing costs or affecting the overall service life of the product, the historical operating data of devices such as micro-reversers, which is the periodic operating data stored during the period when the connection between the micro-reverser or monitoring device and the router network is interrupted, can only be correctly stored and displayed for one day or not stored and displayed at all, in monitoring scenarios where there is no power failure to maintain the clock.

[0108] This embodiment uses a cloud-based controller to obtain the timestamps of online equipment data from adjacent power plants or convert latitude and longitude to micro-reverse start-up timestamps, and calibrates historical data timestamps, thereby improving the accuracy of displaying historical data without time synchronization after micro-reverse transmission.

[0109] This embodiment further optimizes the data segmentation for determining micro-inverters during daytime power outages based on historical data of the day's weather conditions and cumulative power generation trends.

[0110] See Figure 6 The diagram shows a schematic of an inverter operation data processing device; the device includes:

[0111] The historical operation data acquisition module 61 is used to acquire the historical operation data of the target inverter; wherein, the historical operation data is the operation data generated by the target inverter during the grid outage, and the historical operation data carries abnormal time information; the abnormal time information is uncalibrated time information; the data group division module is used to divide the historical operation data into at least one data group based on the abnormal time information; wherein, the operation data in the same data group belongs to the same date;

[0112] The start-up time determination module 62 is used to acquire the astronomical data corresponding to the date and, based on the astronomical data, determine the start-up time of the target inverter on the date.

[0113] The time information update module 63 is used to update the time information of historical running data in the data group corresponding to the start time.

[0114] The aforementioned inverter operation data processing device acquires historical operation data of the target inverter. This historical operation data is generated during grid outages and carries abnormal time information; the abnormal time information is uncalibrated time information. Based on the abnormal time information, the historical operation data is divided into at least one data group; the operation data within the same data group belongs to the same date. The device acquires the astronomical data corresponding to the date, and based on the astronomical data, determines the start-up time of the target inverter on that date. Based on the start-up time, the time information of the historical operation data in the data group corresponding to that date is updated. In this method, the start-up time of the inverter on that date is determined based on the astronomical data corresponding to the same date, and then the time information of the historical operation data in the data group is updated based on the start-up time. This method can accurately determine the time information carried in the operation data during the inverter grid outage, ensuring that the operation data accurately reflects the operating status of the photovoltaic modules.

[0115] The aforementioned device further includes an operation data acquisition module, used to: acquire first operation data and second operation data of the target inverter; wherein, the first operation data is the last operation data received by the target inverter before the start of the grid outage period; the second operation data is the first operation data received by the target inverter after the end of the grid outage period; the first operation data and the second operation data carry normal time information; the normal time information is calibrated time information; based on the first operation data and the second operation data, determine the number of dates during the grid outage period; if the number of dates matches the number of data groups, determine that the historical operation data is valid.

[0116] The aforementioned device also includes a mismatch module, used to determine that the historical operating data is invalid if the number of dates does not match the number of data groups; to stop the execution of the steps of acquiring the astronomical data corresponding to the date, determining the start-up time of the target inverter on the date based on the astronomical data, and updating the time information of the historical operating data in the data group corresponding to the date based on the start-up time.

[0117] The aforementioned device further includes a date information determination module, used to determine the date information corresponding to the data group based on the first operating data and / or the second operating data.

[0118] The aforementioned startup time determination module is also used to determine the sunrise time of a date based on astronomical data; and to determine the startup time of the target inverter on a date based on the sunrise time.

[0119] The historical running data in the same data group are arranged in chronological order, and there is a specified time interval between adjacent running data. The time information update module is also used to update the time information of the first historical running data in the data group based on the start time; and to update the time information of the subsequent historical running data of the first historical running data in the data group based on the specified time interval and the time information of the first historical running data.

[0120] The aforementioned device also includes a shutdown time determination module, used to determine the shutdown time of the target inverter on a given date based on astronomical data; to determine whether the updated time information of the historical operating data in the data group matches the shutdown time; and if they match, to determine that the historical operating data in the data group is valid data.

[0121] The aforementioned shutdown time determination module is also used to obtain the updated time information of the last sorted historical running data in the data group; if the time interval between the updated time information of the last sorted historical running data and the shutdown time is less than a specified interval threshold, the updated time information of the historical running data in the data group is determined to match the shutdown time; if the time interval between the updated time information of the last sorted historical running data and the shutdown time is greater than or equal to the specified interval threshold, the updated time information of the historical running data in the data group is determined not to match the shutdown time.

[0122] The aforementioned device also includes an invalid data determination module, used to determine that historical running data in the data group is invalid data if there is a mismatch.

[0123] The aforementioned device further includes a first startup time update module, used to determine a first inverter that meets a specified distance range from the target inverter; wherein, during the period when the target inverter is offline, the first inverter is connected to the network; the startup time of the first inverter on a certain date is obtained, and the startup time of the target inverter on a certain date is updated based on the startup time of the first inverter on that date.

[0124] The aforementioned device also includes a second startup time update module, used to acquire the geographic information of the target inverter; and based on the geographic information, update the startup time of the target inverter on a given date.

[0125] This embodiment also provides an electronic device, including a processor and a memory. The memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the above-described method for processing inverter operating data.

[0126] See Figure 7 As shown, the electronic device includes a processor 100 and a memory 101. The memory 101 stores computer-executable instructions that can be executed by the processor 100. The processor 100 executes the computer-executable instructions to implement the above-described method for processing inverter operating data.

[0127] Furthermore, Figure 7 The electronic device shown also includes a bus 102 and a communication interface 103, with the processor 100, the communication interface 103 and the memory 101 connected via the bus 102.

[0128] It should be noted that the electronic device in this embodiment does not include a clock circuit.

[0129] This clock circuit is typically implemented using an RTC (Real-Time Clock) circuit, a clock chip, or similar means. It provides accurate real-time time, and even when the electronic device loses power, it can continue to operate normally on battery power, ensuring the device's time remains accurate.

[0130] In this embodiment, the electronic device does not include a clock circuit. When the electronic device loses power, it cannot continue to run time. When the electronic device is powered on and connected to the network, it can obtain accurate time through the network.

[0131] The memory 101 may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 103 (which can be wired or wireless), such as the Internet, wide area network, local area network, or metropolitan area network. The bus 102 may be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 7 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0132] The processor 100 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of the processor 100 or by instructions in software form. The processor 100 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a readily available storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 101, and the processor 100 reads the information from memory 101 and, in conjunction with its hardware, completes the steps of the method described in the foregoing embodiments.

[0133] This embodiment also provides a computer-readable storage medium storing computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions cause the processor to implement the above-described method for processing inverter operating data.

[0134] The inverter operation data processing method, apparatus, and electronic device computer program product provided in this application embodiment include a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the preceding method embodiments. For specific implementation, please refer to the method embodiments, which will not be repeated here.

[0135] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system and apparatus described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0136] Furthermore, in the description of the embodiments of this application, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0137] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0138] In the description of this application, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0139] Finally, it should be noted that the above embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the technical scope disclosed in this application. Such modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be determined by the protection scope of the claims.

Claims

1. A method for processing inverter operating data, characterized in that, The method includes: Obtain historical operating data of the target inverter; wherein, the historical operating data is the operating data generated by the target inverter during the grid outage, and the historical operating data carries abnormal time information; the abnormal time information is uncalibrated time information; Based on the abnormal time information, the historical operation data is divided into at least one data group; wherein, the operation data in the same data group belongs to the same date; Obtain the astronomical data corresponding to the date, and based on the astronomical data, determine the start-up time of the target inverter on the date; Based on the startup time, update the time information of the historical running data in the data group corresponding to the date.

2. The method according to claim 1, characterized in that, After dividing the historical operational data into at least one data group based on the abnormal time information, the method further includes: Acquire first and second operating data of the target inverter; wherein, the first operating data is the last operating data received by the target inverter before the start of the grid outage period; the second operating data is the first operating data received by the target inverter after the end of the grid outage period; the first and second operating data carry normal time information; the normal time information is calibrated time information; Based on the first operating data and the second operating data, determine the number of days during the network outage period; If the number of dates matches the number of groups in the data set, the historical running data is deemed valid.

3. The method according to claim 2, characterized in that, The method further includes: If the number of dates does not match the number of data groups, the historical operation data is determined to be invalid. The steps of obtaining astronomical data corresponding to the date, determining the start-up time of the target inverter on the date based on the astronomical data, and updating the time information of historical operating data in the data group corresponding to the date based on the start-up time are stopped.

4. The method according to claim 2, characterized in that, After the steps of acquiring the first operating data and the second operating data of the target inverter, the method further includes: Based on the first running data and / or the second running data, determine the date information corresponding to the data group.

5. The method according to claim 1, characterized in that, The step of determining the start-up time of the target inverter on the date based on the astronomical data includes: Based on the astronomical data, determine the sunrise time for the given date; Based on the sunrise time, the start-up time of the target inverter on that date is determined.

6. The method according to claim 1, characterized in that, Historical running data within the same data group are arranged in chronological order, with a specified time interval between adjacent running data. The step of updating the time information of historical running data in the data group corresponding to the date based on the startup time includes: Based on the startup time, update the time information of the historical running data that is first in the data group according to the time order; Based on the specified time interval and the time information of the first-ranked historical running data, update the time information of the subsequent historical running data of the first-ranked historical running data in the data group.

7. The method according to claim 1, characterized in that, After updating the time information of historical running data in the data group corresponding to the date based on the startup time, the method further includes: Based on the astronomical data, the shutdown time of the target inverter on the specified date is determined; Determine whether the updated time information of the historical running data in the data group matches the shutdown time; If a match is found, the historical running data in the data group is determined to be valid data.

8. The method according to claim 7, characterized in that, The step of determining whether the updated time information of the historical running data in the data group matches the shutdown time includes: Obtain the updated time information of the last sorted historical running data in the data group; If the time interval between the updated time information of the last sorted historical running data and the shutdown time is less than a specified interval threshold, the updated time information of the historical running data in the data group is determined to match the shutdown time. If the time interval between the updated time information of the last historical running data in the sorted data and the shutdown time is greater than or equal to a specified interval threshold, it is determined that the updated time information of the historical running data in the data group does not match the shutdown time.

9. The method according to claim 7, characterized in that, The method further includes: If there is a mismatch, the historical running data in the data group is determined to be invalid data.

10. The method according to claim 1, characterized in that, Following the step of determining the start-up time of the target inverter on the date based on the astronomical data, the method further includes: A first inverter that is within a specified distance range from the target inverter is identified; wherein, during the grid outage of the target inverter, the first inverter is connected to the network. Obtain the start-up time of the first inverter on the specified date, and update the start-up time of the target inverter on the specified date based on the start-up time of the first inverter on the specified date.

11. The method according to claim 1, characterized in that, Following the step of determining the start-up time of the target inverter on the date based on the astronomical data, the method further includes: Obtain the geographical information of the target inverter; Based on the geographic information, update the start-up time of the target inverter on the specified date.

12. A device for processing inverter operating data, characterized in that, The device includes: The historical operation data acquisition module is used to acquire the historical operation data of the target inverter; wherein, the historical operation data is the operation data generated by the target inverter during the grid outage, and the historical operation data carries abnormal time information; the abnormal time information is uncalibrated time information; The data group partitioning module is used to divide the historical running data into at least one data group based on the abnormal time information; wherein the running data in the same data group belongs to the same date; The start-up time determination module is used to acquire astronomical data corresponding to the date, and determine the start-up time of the target inverter on the date based on the astronomical data; The time information update module is used to update the time information of the historical running data in the data group corresponding to the date based on the start time.

13. An electronic device, characterized in that, The device includes a processor and a memory, the memory storing computer-executable instructions that can be executed by the processor, the processor executing the computer-executable instructions to implement the inverter operating data processing method according to any one of claims 1-11.

14. The electronic device according to claim 13, characterized in that, The electronic device does not include a clock circuit.

15. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when invoked and executed by a processor, cause the processor to implement the inverter operating data processing method according to any one of claims 1-11.

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