A power gateway data processing method

Abstract

This invention provides a power gateway data processing method, which specifically includes: setting a data acquisition cycle and a data upload cycle for the power gateway; during the data acquisition cycle, the power gateway polls its subordinate sub-devices to collect real-time electrical data and transmits the real-time electrical data to the power gateway's control module; the control module classifies the real-time electrical data, matches corresponding data filtering algorithms according to the electrical data type, and performs data filtering and cleaning on the corresponding real-time electrical data based on the matched data filtering methods; during the data upload cycle, the control module uploads the most recently filtered real-time electrical data to the cloud platform. This invention enables the power gateway to perform data filtering and cleaning by matching corresponding data filtering algorithms after receiving real-time electrical data from subordinate sub-devices, ensuring the reliability of the real-time electrical data uploaded by the power gateway from subordinate sub-devices.

Description

Technical Field

[0001] This invention relates to the field of power gateway technology, and in particular to a power gateway data processing method. Background Technology

[0002] During the operation of a power system, due to its large scale, it is necessary to remotely acquire the operating data of the power equipment in order to monitor its working status. However, since different power devices use different communication protocols, a power gateway is required to transmit the operating data of the power equipment.

[0003] Power gateways need to connect to various types of power devices, but after receiving data from these devices, they do not filter or verify the data uploaded by the devices. This can easily lead to erroneous data being sent to the cloud platform, compromising the accuracy of the cloud platform's assessment of the line's operational status. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a power gateway data processing method. After receiving real-time electrical data from subordinate sub-devices, the power gateway matches the corresponding data filtering algorithm to perform data filtering and cleaning. This solves the problems that existing power gateways cannot filter and identify the data of power devices, easily send erroneous data uploaded by power devices to the cloud platform, and cannot guarantee the accuracy of line operation status judgment. This invention ensures the credibility of the real-time electrical data of subordinate sub-devices uploaded by the power gateway.

[0005] The objective of this invention is achieved through the following technical solution:

[0006] A power gateway data processing method, comprising:

[0007] Set the data acquisition cycle and data upload cycle for the power gateway;

[0008] During the data acquisition cycle, the power gateway polls its subordinate sub-devices to collect real-time electrical data and transmits the real-time electrical data to the power gateway's control module.

[0009] The control module classifies real-time electrical data, matches the corresponding data filtering algorithm according to the type of electrical data, and performs data filtering and cleaning on the corresponding real-time electrical data based on the matched data filtering method.

[0010] During the data upload cycle, the control module uploads the most recently filtered real-time electrical data to the cloud platform.

[0011] After matching the corresponding data filtering algorithm according to the electrical data type, the subordinate sub-devices corresponding to each type of electrical data are determined, and the historical data filtering pass rate and historical alarm information of the subordinate sub-devices corresponding to each type of electrical data are retrieved. Based on the historical data filtering pass rate and historical alarm information, the filtering threshold of the matching data filtering algorithm is adjusted.

[0012] Furthermore, when the power gateway polls its subordinate sub-devices to collect real-time electrical data, it also obtains the device identifier of the subordinate sub-devices and marks the collected real-time electrical data according to the device identifier. When determining the subordinate sub-device corresponding to each type of electrical data, the device identifier is determined by retrieving the mark of the real-time electrical data corresponding to each type of electrical data, and the subordinate sub-device to which it belongs is determined according to the device identifier.

[0013] Furthermore, the electrical data types include line voltage and current data, real-time line power data, temperature data, frequency data, and line power data.

[0014] Furthermore, the specific data filtering algorithm for the line voltage and current data is as follows: Determine the subordinate sub-equipment corresponding to the line voltage and current data; determine if the subordinate sub-equipment is a three-phase device; if the subordinate sub-equipment is not a three-phase device, extract the B-phase voltage and current data or the C-phase voltage and current data from the line voltage and current data; determine if the read B-phase voltage and current data or C-phase voltage and current data is greater than zero; if the B-phase voltage and current data or the C-phase voltage and current data is greater than zero, then the line voltage and current data is determined to be abnormal data, the line voltage and current data is filtered, and the filtering count is increased by one. If the subordinate sub-equipment is a three-phase device, or if the subordinate sub-equipment is not a three-phase device and the B-phase voltage and current data and the C-phase voltage and current data are less than or equal to... If the value is zero, the voltage and current limits of the subordinate sub-device are extracted, and the line voltage and current limits are used as the filtering threshold for the line voltage and current data. The line voltage and current data are compared with the filtering threshold. If the line voltage and current data is greater than the filtering threshold, it is determined whether the gateway has simultaneously collected the corresponding alarm information. If the corresponding alarm information is collected, the line voltage and current data is determined to be normal data. If the corresponding alarm information is not collected, the line voltage and current data is determined to be abnormal data, the line voltage and current data is filtered, and the filtering count is increased by one. Each time the filtering count is increased, the current filtering count is compared with the preset filtering threshold. When the filtering count exceeds the preset filtering threshold, the power gateway sends a data error alarm to the cloud platform.

[0015] Furthermore, the data filtering algorithm corresponding to the real-time power data of the line is as follows: Based on the real-time power data of the line, the power factor is obtained. It is determined whether the power factor is greater than 1. If the power factor is greater than 1, the real-time power data of the line is considered abnormal, and the real-time power data of the line is filtered, with an additional filtering iteration. If the power factor is less than or equal to 1, the subordinate sub-equipment corresponding to the real-time power data of the line is identified. It is determined whether the subordinate sub-equipment is a three-phase device. If the subordinate sub-equipment is not a three-phase device, the B-phase power or C-phase power in the real-time power data of the line is extracted. It is determined whether the B-phase power or C-phase power is greater than zero. If the B-phase power or C-phase power is greater than zero, the real-time power data of the line is considered abnormal, and the real-time power data of the line is filtered, with an additional filtering iteration. If the subordinate equipment is a three-phase device, or if the subordinate sub-equipment is not a three-phase device and the B-phase power is less than or equal to zero and the C-phase power is less than or equal to zero, the corresponding line voltage and current data are retrieved and processed. The system calculates the actual power of the line and the error between the actual power and the real-time power data. If the error exceeds the filtering threshold for the real-time power data, the real-time power data is considered abnormal, filtered, and the filtering count is increased by one. If the error does not exceed the filtering threshold, the system reads the power limit of the subordinate sub-devices and compares the real-time power data with the power limit. Simultaneously, it checks whether the gateway has collected the corresponding alarm information. If the real-time power data is less than the power limit and no corresponding alarm information is collected, the real-time power data is considered normal. Otherwise, the real-time power data is considered abnormal, filtered, and the filtering count is increased by one. Each time the filtering count is increased, it is compared with a preset filtering threshold. When the filtering count exceeds the preset threshold, the power gateway sends a data error alarm to the cloud platform.

[0016] Furthermore, the specific data filtering algorithm for the temperature data is as follows: Determine the subordinate sub-device corresponding to the temperature data; determine if the subordinate sub-device is a three-phase device; if the subordinate sub-device is not a three-phase device, extract the B-phase temperature data or C-phase temperature data from the temperature data; if the B-phase temperature data or C-phase temperature data is greater than zero, determine that the temperature data is abnormal, filter the temperature data, and increase the filtering count by one; if the subordinate sub-device is a three-phase device, or if the subordinate sub-device is not a three-phase device and the B-phase temperature data and C-phase temperature data are less than or equal to zero, read the temperature limit value of the subordinate sub-device and set the temperature limit... The value serves as the filtering threshold for temperature data. If the temperature data is less than or equal to the temperature limit, it is considered normal. If the temperature data is greater than the temperature limit, it is checked whether the gateway has simultaneously collected the corresponding alarm information. If the corresponding alarm information is collected, the temperature data is considered normal. If the corresponding alarm information is not collected, the temperature data is considered abnormal, and the filtering count is increased by one. Each time the filtering count is increased, the current filtering count is compared with the preset filtering threshold. When the filtering count exceeds the preset filtering threshold, the power gateway sends a data error alarm to the cloud platform.

[0017] Furthermore, the specific data filtering algorithm for frequency data is as follows: calculate the frequency information error of the frequency data, and compare the frequency information error with the frequency data filtering threshold. If the frequency information error is less than the filtering threshold, the frequency information is judged to be normal data. If the frequency information error is greater than or equal to the filtering threshold, the frequency information is judged to be abnormal data, the frequency data is filtered, and the filtering count is increased by one. Each time the filtering count is increased, the current filtering count is compared with the preset filtering threshold. When the filtering count exceeds the preset filtering threshold, the power gateway sends a data error alarm to the cloud platform.

[0018] Furthermore, the specific data filtering algorithm for the line power consumption data is as follows: Extract the line power consumption data that passed the previous filtering, and compare the current line power consumption data with the previously filtered data. If the current line power consumption data is less than the previously filtered data, it is determined to be abnormal data, and the power gateway sends a data error alarm to the cloud platform. If the current line power consumption data is greater than or equal to the previously filtered data, it is stored. After judging abnormal data for all line power consumption data of the day, the line power consumption data for the day is obtained using the least squares method based on all filtered line power consumption data for the day. The dataset is used to filter out time points with anomalies based on the SRE value of each line's power consumption data in the dataset. One of the time points with anomalies is selected, and the line power consumption data of the previous time point is obtained. The power consumption increment in the time period from the previous time point to the current time point is calculated, and the real-time power data of the line in this time period is extracted. Power consumption simulation calculation is performed based on the real-time power data of the line, and the error between the power consumption simulation calculation value and the power consumption increment is calculated. If the error exceeds the filtering threshold, the power consumption data of the time point and its corresponding line is deleted from the dataset, and the power gateway sends a data error alarm to the cloud platform. If the error does not exceed the filtering threshold, the power consumption data of the time point and its line is retained.

[0019] The beneficial effects of this invention are:

[0020] 1. It can filter and clean real-time electrical data uploaded by subordinate devices through the power gateway, ensuring the reliability of the real-time electrical data. Furthermore, it can match the corresponding data filtering algorithm based on the type of electrical data, thereby simultaneously achieving filtering and cleaning of multiple types of electrical data, resulting in higher efficiency in data filtering and cleaning.

[0021] 2. After determining the data filtering algorithm, the filtering threshold of the data filtering algorithm is also adjusted based on the historical data filtering pass rate and historical alarm information of the subordinate sub-devices. The historical data filtering pass rate and historical alarm information can reflect the data reporting errors of the subordinate sub-devices. Based on the data upload error situation, the filtering threshold is adjusted to improve the filtering requirements of real-time electrical data and ensure the credibility of real-time electrical data uploaded to the cloud platform. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of a process of the present invention;

[0023] Figure 2 This is a flowchart of a data filtering algorithm corresponding to line voltage and current data according to an embodiment of the present invention;

[0024] Figure 3This is a flowchart of a data filtering algorithm corresponding to real-time power data of a line according to an embodiment of the present invention;

[0025] Figure 4 This is a flowchart of a data filtering algorithm corresponding to temperature data according to an embodiment of the present invention;

[0026] Figure 5 This is a flowchart of a data filtering algorithm corresponding to frequency data according to an embodiment of the present invention;

[0027] Figure 6 This is a flowchart of a data filtering algorithm corresponding to line power data according to an embodiment of the present invention. Detailed Implementation

[0028] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0029] Example:

[0030] A power gateway data processing method, such as Figure 1 As shown, it includes:

[0031] Set the data acquisition cycle and data upload cycle for the power gateway;

[0032] During the data acquisition cycle, the power gateway polls its subordinate sub-devices to collect real-time electrical data and transmits the real-time electrical data to the power gateway's control module.

[0033] The control module classifies real-time electrical data, matches the corresponding data filtering algorithm according to the type of electrical data, and performs data filtering and cleaning on the corresponding real-time electrical data based on the matched data filtering method.

[0034] During the data upload cycle, the control module uploads the most recently filtered real-time electrical data to the cloud platform.

[0035] After matching the corresponding data filtering algorithm according to the electrical data type, the subordinate sub-devices corresponding to each type of electrical data are determined, and the historical data filtering pass rate and historical alarm information of the subordinate sub-devices corresponding to each type of electrical data are retrieved. Based on the historical data filtering pass rate and historical alarm information, the filtering threshold of the matching data filtering algorithm is adjusted.

[0036] The historical alarm information includes the number of data error alarms from subordinate sub-devices, the alarm time of each data error alarm, and the alarm frequency of data error alarms. The historical data filtering pass rate includes the data filtering pass rate within each data acquisition cycle. When obtaining the data filtering pass rate, the amount of real-time electrical data that was filtered out within each data acquisition cycle is determined, and this amount is compared with the amount of real-time electrical data acquired within the data acquisition cycle to determine the data filtering pass rate.

[0037] When the amount of real-time electrical data filtered out exceeds the expected value, the power gateway will determine that there is a problem with the reported data of the subordinate sub-device and issue an alarm. Therefore, historical alarm information and historical data filtering pass rate can reflect the probability of the subordinate sub-device reporting data errors.

[0038] For subordinate sub-devices with a high number of data error alarms and a low historical data filtering pass rate, the time period with a high probability of data error alarms is determined based on the alarm time of each data error alarm. The filtering threshold is then adjusted for the determined time period with a high probability of data error alarms. By adjusting the filtering threshold, the range of normal data is narrowed, and the data filtering requirements of the subordinate sub-device during that time period are improved.

[0039] For other subordinate sub-devices, the default filtering threshold is used directly.

[0040] When the power gateway polls its subordinate sub-devices to collect real-time electrical data, it also obtains the device identifier of the subordinate sub-devices and marks the collected real-time electrical data according to the device identifier. When determining the subordinate sub-device corresponding to each type of electrical data, the device identifier is determined by retrieving the mark of the real-time electrical data corresponding to each type of electrical data, and the subordinate sub-device to which it belongs is determined according to the device identifier.

[0041] Due to the large scale of the power system, the power gateway will connect to multiple subordinate sub-devices of the same type at the same time. In order to ensure the accuracy of data filtering and to ensure that subsequent data error alarms can be associated with subordinate sub-devices, real-time electrical data is marked by device identifiers, which can accurately determine the corresponding subordinate sub-device of the real-time electrical data.

[0042] The electrical data types include line voltage and current data, real-time line power data, temperature data, frequency data, and line power data.

[0043] like Figure 2As shown, the specific data filtering algorithm for line voltage and current data is as follows: First, determine the subordinate sub-devices corresponding to the line voltage and current data. Then, determine if the subordinate sub-device is a three-phase device. If the subordinate sub-device is not a three-phase device, extract the B-phase voltage and current data or the C-phase voltage and current data from the line voltage and current data. Next, determine if the read B-phase voltage and current data or C-phase voltage and current data is greater than zero. If the B-phase voltage and current data or the C-phase voltage and current data is greater than zero, then the line voltage and current data is considered abnormal. Filter the line voltage and current data and increase the filtering count by one. If the subordinate sub-device is a three-phase device, or if the subordinate sub-device is not a three-phase device and the B-phase voltage and current data and the C-phase voltage and current data are less than or equal to zero, then extract the voltage and current limit value for that subordinate sub-device. If the voltage and current limit value for that subordinate sub-device cannot be extracted, then the default value is used directly. The line voltage and current limits are used as the filtering threshold for line voltage and current data. The line voltage and current data are compared with the filtering threshold. If the line voltage and current data is greater than the filtering threshold, it is determined whether the gateway has collected the corresponding alarm information at the same time. If the corresponding alarm information is collected, the line voltage and current data is determined to be normal data. If the corresponding alarm information is not collected, the line voltage and current data is determined to be abnormal data, the line voltage and current data is filtered, and the filtering count is increased by one.

[0044] like Figure 3As shown, the data filtering algorithm corresponding to the real-time power data of the line is as follows: Based on the real-time power data of the line, obtain the power factor and determine if the power factor is greater than 1. If the power factor is greater than 1, the real-time power data of the line is determined to be abnormal, and the real-time power data of the line is filtered and the filtering count is increased by one. If the power factor is less than or equal to 1, determine the subordinate sub-devices corresponding to the real-time power data of the line, and determine if the subordinate sub-devices are three-phase devices. If the subordinate sub-devices are not three-phase devices, extract the B-phase power or C-phase power from the real-time power data of the line, and determine if the B-phase power or C-phase power is greater than zero. If the B-phase power or C-phase power is greater than zero, the real-time power data of the line is determined to be abnormal, and the real-time power data of the line is filtered and the filtering count is increased by one. If the subordinate device is a three-phase device, or if the subordinate sub-device is not a three-phase device and the B-phase power is less than or equal to zero and the C-phase power is less than or equal to zero, then retrieve the corresponding line voltage. The current data is used to calculate the actual power of the line. The error between the actual power and the real-time power data is calculated. If the error exceeds the filtering threshold of the real-time power data (5% in this embodiment), the real-time power data is considered abnormal, filtered, and the filtering count is increased by one. If the error does not exceed the filtering threshold, the power limit of the subordinate sub-device is read. If the subordinate sub-device does not specify a power limit, the default value is directly used, and the real-time power data is compared with the power limit. At the same time, it is determined whether the gateway has collected the corresponding alarm information. If the real-time power data is less than the power limit and no corresponding alarm information is collected, the real-time power data is considered normal. Otherwise, the real-time power data is considered abnormal, filtered, and the filtering count is increased by one.

[0045] like Figure 4As shown, the specific data filtering algorithm for the temperature data is as follows: First, determine the subordinate sub-device corresponding to the temperature data. Then, determine if the subordinate sub-device is a three-phase device. If the subordinate sub-device is not a three-phase device, extract either the B-phase temperature data or the C-phase temperature data from the temperature data. If either the B-phase temperature data or the C-phase temperature data is greater than zero, then the temperature data is considered abnormal, and the data is filtered, with an additional filtering iteration. If the subordinate sub-device is a three-phase device, or if the subordinate sub-device is not a three-phase device and both the B-phase and C-phase temperature data are less than or equal to zero, then read... Similarly, if the temperature limit of a subordinate sub-device cannot be read, the default value is used directly, and the temperature limit is used as the filtering threshold for temperature data. If the temperature data is less than or equal to the temperature limit, the temperature data is considered normal. If the temperature data is greater than the temperature limit, it is determined whether the gateway has collected the corresponding alarm information. If the corresponding alarm information is collected, the temperature data is considered normal. If the corresponding alarm information is not collected, the temperature data is considered abnormal, the temperature data is filtered, and the filtering count is increased by one.

[0046] like Figure 5 As shown, the specific data filtering algorithm for the frequency data is as follows: calculate the frequency information error of the frequency data, and compare the frequency information error with the frequency data filtering threshold. In this embodiment, the frequency data filtering threshold is set to ±1Hz. If the frequency information error is less than the filtering threshold, the frequency information is determined to be normal data; if the frequency information error is greater than or equal to the filtering threshold, the frequency information is determined to be abnormal data, the frequency data is filtered, and the filtering count is increased by one.

[0047] like Figure 6As shown, the specific data filtering algorithm for line power data is as follows: Extract the line power data that passed the previous filtering. If the previously filtered line power data cannot be collected, determine that the current data is the first collected line power data, and default the line power data for comparison to 0. Compare the current line power data with the previously filtered line power data. If the current line power data is less than the previously filtered line power data, it is determined to be abnormal data, and the power gateway sends a data error alarm to the cloud platform. If the current line power data is greater than or equal to the previously filtered line power data, the current line power data is stored. After performing abnormal data judgment on all line power data for the day, based on all available data for the day... The filtered line power consumption data is used to obtain the daily line power consumption data dataset using the least squares method. Based on the SRE value of each line power consumption data in the dataset, time points with anomalies are filtered out. One of the time points with anomalies is selected, and the line power consumption data of the previous time point is obtained. The power consumption increment in the time period from the previous time point to the current time point is calculated, and the real-time power data of the line in this time period is extracted. Power consumption simulation calculation is performed based on the real-time power data of the line, and the error between the power consumption simulation calculation value and the power consumption increment is calculated. If the error exceeds the filtering threshold, the time point and its corresponding line power consumption data are deleted from the dataset, and the power gateway sends a data error alarm to the cloud platform. If the error does not exceed the filtering threshold, the time point and its line power consumption data are retained.

[0048] When the data upload cycle is reached, the most recently filtered and stored line power data will be extracted and uploaded, and previously filtered line power data will not be replaced.

[0049] The SRE value is an evaluation index of the power generation growth rate, which is obtained by calculating the growth rate of power generation data for each line compared to the power generation data at the previous time point.

[0050] After the dataset is filtered, the daily electricity consumption data can be obtained. At the end of each day, the power gateway will upload the daily electricity consumption data dataset to the cloud platform, and the cloud platform will perform electricity consumption data trend analysis based on the daily electricity consumption data.

[0051] Each time the number of filters is increased, the current number of filters is compared with the preset filtering threshold. When the number of filters for a type of power data exceeds the preset filtering threshold, the power gateway sends a data error alarm to the cloud platform.

[0052] In this embodiment, a preset filtering threshold of 3 times is set. When the number of filtering times exceeds 3, the power gateway issues a data error alarm and resets the number of filtering times to zero, waiting for the next data collection cycle to re-filter the data.

[0053] The power gateway specifically collects real-time electrical data from its subordinate devices via a RS-485 communication module. Furthermore, the data processing method for this power gateway is built using a Linux system. Linux is a multi-tasking operating system, allowing data processing to be performed simultaneously on multiple devices, saving time and ensuring the real-time nature of the electrical data.

[0054] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any way. Other variations and modifications are possible without departing from the technical solutions described in the claims.

Claims

1. A power gateway data processing method, characterized in that, include: Set the data acquisition cycle and data upload cycle for the power gateway; During the data acquisition cycle, the power gateway polls its subordinate sub-devices to collect real-time electrical data and transmits the real-time electrical data to the power gateway's control module. The control module classifies real-time electrical data, matches the corresponding data filtering algorithm according to the type of electrical data, and performs data filtering and cleaning on the corresponding real-time electrical data based on the matched data filtering method. During the data upload cycle, the control module uploads the most recently filtered real-time electrical data to the cloud platform; After matching the corresponding data filtering algorithm according to the electrical data type, the subordinate sub-devices corresponding to each type of electrical data are determined, and the historical data filtering pass rate and historical alarm information of the subordinate sub-devices corresponding to each type of electrical data are retrieved. Based on the historical data filtering pass rate and historical alarm information, the filtering threshold of the matching data filtering algorithm is adjusted. The electrical data types include line voltage and current data, real-time line power data, temperature data, frequency data, and line power data; The specific data filtering algorithm for real-time power data of the line is as follows: Based on the real-time power data, obtain the power factor and determine if the power factor is greater than 1. If the power factor is greater than 1, the real-time power data is considered abnormal, and the data is filtered with an additional filtering iteration. If the power factor is less than or equal to 1, determine the corresponding subordinate sub-equipment and whether it is a three-phase device. If the subordinate sub-equipment is not a three-phase device, extract the B-phase power or C-phase power from the real-time power data and determine if it is greater than zero. If the B-phase power or C-phase power is greater than zero, the real-time power data is considered abnormal, and the data is filtered with an additional filtering iteration. If the subordinate device is a three-phase device, or if the subordinate sub-equipment is not a three-phase device and both the B-phase power and C-phase power are less than or equal to zero, then retrieve the corresponding line voltage and current data for line analysis. Actual power calculation involves determining the error between the actual power of the line and the real-time power data. If the error exceeds the filtering threshold for the real-time power data, the real-time power data is considered abnormal, filtered, and the filtering count is increased by one. If the error does not exceed the filtering threshold, the power limit of the subordinate sub-device is read, and the real-time power data is compared with the power limit. Simultaneously, it is determined whether the gateway has collected the corresponding alarm information. If the real-time power data is less than the power limit and no corresponding alarm information is collected, the real-time power data is considered normal. Otherwise, the real-time power data is considered abnormal, filtered, and the filtering count is increased by one. Each time the filtering count is increased, the current filtering count is compared with a preset filtering threshold. When the filtering count exceeds the preset filtering threshold, the power gateway sends a data error alarm to the cloud platform.

2. The power gateway data processing method according to claim 1, characterized in that, When the power gateway polls its subordinate sub-devices to collect real-time electrical data, it also obtains the device identifier of the subordinate sub-devices and marks the collected real-time electrical data according to the device identifier. When determining the subordinate sub-device corresponding to each type of electrical data, the device identifier is determined by retrieving the mark of the real-time electrical data corresponding to each type of electrical data, and the subordinate sub-device to which it belongs is determined according to the device identifier.

3. The power gateway data processing method according to claim 2, characterized in that, The specific data filtering algorithm for line voltage and current data is as follows: Identify the subordinate sub-equipment corresponding to the line voltage and current data; determine if the subordinate sub-equipment is a three-phase device. If the subordinate sub-equipment is not a three-phase device, extract the B-phase voltage and current data or the C-phase voltage and current data from the line voltage and current data; determine if the read B-phase voltage and current data or C-phase voltage and current data is greater than zero. If the B-phase voltage and current data or the C-phase voltage and current data is greater than zero, then the line voltage and current data is determined to be abnormal data, filtered, and the filtering count is increased by one. If the subordinate sub-equipment is a three-phase device, or the subordinate sub-equipment... If the device is not a three-phase device and the voltage and current data of phase B and phase C are less than or equal to zero, then the voltage and current limits of the subordinate sub-device are extracted, and the line voltage and current limits are used as the filtering threshold for the line voltage and current data. The line voltage and current data are compared with the filtering threshold. If the line voltage and current data is greater than the filtering threshold, then it is determined whether the gateway has collected the corresponding alarm information at the same time. If the corresponding alarm information is collected, then the line voltage and current data is determined to be normal data. If the corresponding alarm information is not collected, then the line voltage and current data is determined to be abnormal data, the line voltage and current data is filtered, and the filtering count is increased by one. Each time the number of filters is increased, the current number of filters is compared with the preset filtering threshold. When the number of filters exceeds the preset filtering threshold, the power gateway sends a data error alarm to the cloud platform.

4. The power gateway data processing method according to claim 2, characterized in that, The specific data filtering algorithm for temperature data is as follows: First, determine the subordinate sub-device corresponding to the temperature data. Then, determine if the subordinate sub-device is a three-phase device. If it is not a three-phase device, extract either the B-phase or C-phase temperature data from the temperature data. If either the B-phase or C-phase temperature data is greater than zero, the temperature data is considered abnormal, filtered, and the filtering count is increased. If the subordinate sub-device is a three-phase device, or if it is not a three-phase device but both the B-phase and C-phase temperature data are less than or equal to zero, read the temperature limit value of the subordinate sub-device and set the temperature limit value as... The temperature data is set as a filtering threshold. If the temperature data is less than or equal to the temperature limit, it is considered normal. If the temperature data is greater than the temperature limit, it is checked whether the gateway has simultaneously collected the corresponding alarm information. If the corresponding alarm information is collected, the temperature data is considered normal. If the corresponding alarm information is not collected, the temperature data is considered abnormal, and the temperature data is filtered and the filtering count is increased by one. Each time the filtering count is increased, the current filtering count is compared with the preset filtering threshold. When the filtering count exceeds the preset filtering threshold, the power gateway sends a data error alarm to the cloud platform.

5. The power gateway data processing method according to claim 1, characterized in that, The specific data filtering algorithm for frequency data is as follows: calculate the frequency information error of the frequency data, and compare the frequency information error with the frequency data filtering threshold. If the frequency information error is less than the filtering threshold, the frequency information is judged to be normal data. If the frequency information error is greater than or equal to the filtering threshold, the frequency information is judged to be abnormal data, the frequency data is filtered, and the filtering count is increased by one. Each time the filtering count is increased, the current filtering count is compared with the preset filtering threshold. When the filtering count exceeds the preset filtering threshold, the power gateway sends a data error alarm to the cloud platform.

6. The power gateway data processing method according to claim 1, characterized in that, The specific data filtering algorithm for line power consumption data is as follows: Extract the line power consumption data that passed the previous filtering, and compare the current line power consumption data with the previously filtered data. If the current line power consumption data is less than the previously filtered data, it is considered abnormal, and the power gateway sends a data error alarm to the cloud platform. If the current line power consumption data is greater than or equal to the previously filtered data, it is stored. After judging abnormal data for all line power consumption data for the day, based on all the filtered line power consumption data for the day, the least squares method is used to obtain the total line power consumption data for the day. The system collects data and filters out time points with anomalies based on the SRE values ​​of each line's power consumption data in the dataset. It selects one of these time points with anomalies and obtains the line's power consumption data from the previous time point. It calculates the power consumption increment during the time period from the previous time point to this time point and extracts the line's real-time power data during this time period. It then performs power consumption simulation calculations based on the line's real-time power data and calculates the error between the simulated power consumption value and the power consumption increment. If the error exceeds the filtering threshold, the time point and its corresponding line's power consumption data are deleted from the dataset, and the power gateway sends a data error alarm to the cloud platform. If the error does not exceed the filtering threshold, the time point and its line's power consumption data are retained.

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