Electric energy quality operation data management operation and maintenance system based on cloud collaboration

Abstract

The invention discloses an electric energy quality operation data management operation and maintenance system based on cloud collaboration, and relates to the technical field of cloud collaboration, and the system comprises a data collection module which collects the number, position, peak power consumption and transmission data of terminals in real time, processes the data through a central calculation module to obtain abnormal parameters and a lag model after preprocessing, analyzes the transmission state according to the abnormal parameters and the lag model, and stores the data; if yes, whether power failure occurs or not is analyzed, and if power failure occurs, an alarm module is called. The central calculation processing module constructs a lagging model, couples parameters to quantitatively evaluate a transmission state, triggers an adjacent-end intelligent calculation algorithm to shunt data when a threshold value is exceeded, relieves bandwidth pressure, distinguishes transmission delay and power failure, avoids misjudgment, and reduces resource waste. Millimeter-level positioning of a power failure area is realized in combination with terminal three-dimensional coordinates, and cloud data are associated to provide one-stop information support.

Description

Technical Field

[0001] The present invention relates to the field of cloud collaboration technology, and specifically to a power quality operation data management and maintenance system based on cloud collaboration. Background Art

[0002] The cloud collaborates and integrates electricity consumption data from multiple sources, and through real-time collection of external data such as information from smart meters, distribution terminals and other equipment, it achieves efficient transmission, unified storage and in-depth analysis of electricity consumption data. At the same time, it supports cross-regional collaboration among multiple departments, quickly locates and diagnoses power outages, helps power companies optimize resource allocation and improve power supply reliability, and provides users with accurate energy-saving suggestions to achieve intelligent and refined energy management.

[0003] For example, Chinese patent publication number: CN117096910A provides a distributed photovoltaic optimization scheduling method and system based on a cloud-edge collaborative mechanism, which establishes a day-ahead scheduling model for consumer photovoltaic and electric vehicle loads that considers the two objectives of total electricity cost and photovoltaic consumption, and uses a non-dominated sorting genetic algorithm to solve the model, and a satisfaction evaluation method to select the optimal compromise solution; further, based on the cloud-side collaborative mechanism, the above technology can be deployed in intelligent sensing terminal devices, and shared with household electricity loads, electric vehicle loads, and other households through intelligent terminal sensing devices, so that the terminal devices execute the downlink computing, storage, and resource management strategies of the cloud station to meet the allocation of resources required for the task, realize power sharing, improve the operating economy of the power grid, and reduce energy consumption and electricity costs. The cloud-edge collaborative distributed photovoltaic optimization scheduling strategy proposed in the present invention is conducive to improving the economic benefits of users' electricity use, promoting the consumption of clean energy, and has broad application prospects.

[0004] However, the above solution does not take into account that during peak electricity consumption periods, the power load increases dramatically, causing the amount of electricity consumption data collected by terminal devices to grow exponentially. At this time, if the cloud collaboration mechanism faces problems such as network bandwidth bottlenecks and insufficient server computing power, data transmission will easily be stuck, resulting in the terminal data being unable to be uploaded to the cloud in a timely manner. Because the cloud fails to receive the data on time, it mistakenly judges the transmission delay as a power outage for the user, thereby triggering unnecessary fault repair processes and causing waste of manpower and material resources. Summary of the Invention

[0005] Technical problems solved In response to the shortcomings of the existing technology, the present invention provides a power quality operation data management and maintenance system based on cloud collaboration, which solves the problem that data transmission jams during peak power consumption periods can easily lead to the cloud misjudging power outages, triggering ineffective emergency repairs and wasting resources.

[0006] Technical Solution To achieve the above objectives, the present invention is implemented through the following technical solutions: a power quality operation data management and operation and maintenance system based on cloud collaboration, comprising the following specific modules: a data acquisition module: starts real-time terminal data collection, the terminal data including the number of terminals, the physical location of the terminals, the peak power consumption data of each terminal, and the terminal power consumption information transmission data; a data preprocessing module: preprocesses the terminal data; a central computing and processing module: comprehensively processes the preprocessed terminal data to obtain peak power consumption abnormality parameters and power transmission abnormality parameters, comprehensively processes the peak power consumption abnormality parameters and the power transmission abnormality parameters to obtain a power information transmission jam model, analyzes the terminal power information transmission jam situation according to the power information transmission jam model, if the transmission jam is analyzed, it is adjusted through the neighboring intelligent calculation algorithm, and returns to the data acquisition module until it is analyzed that the transmission is normal, if the transmission is analyzed to be normal, then continue to analyze whether a terminal is out of power based on the terminal power consumption information transmission data, if the power outage is analyzed, call the alarm module and end the detection, if the power outage is analyzed, return to the real-time acquisition module; the alarm module: alarms a terminal for power outage.

[0007] Furthermore, the specific method for obtaining the electrical information transmission jam model is: ;in, Indicates the transmission jam model of power consumption information. Indicates peak power consumption abnormal parameters, Indicates abnormal parameters of power transmission, Represents a positive real number.

[0008] Furthermore, the specific method for obtaining the peak power consumption abnormality parameters is as follows: set the standard power consumption, the peak power consumption data of each terminal includes the power consumption at different times, and perform a comprehensive calculation based on the power consumption at different times and the standard power consumption to obtain the peak power consumption of a single terminal, and sum up the peak power consumption of a single terminal according to the number of terminals to obtain the peak power consumption abnormality parameters.

[0009] Furthermore, the specific method for obtaining the peak power consumption of the single terminal is as follows: perform peak power consumption analysis on the power consumption at different times and the standard power consumption to obtain the peak power consumption within a certain time period, and perform a comprehensive calculation of the peak power consumption within a certain time period based on the time series of the peak time period to obtain the peak power consumption of the single terminal.

[0010] Furthermore, the specific method of obtaining the peak power consumption in a certain time period is as follows: the power consumption at different times is compared with the standard power consumption in sequence. If the power consumption at different times is greater than the standard power consumption, the time when the peak power consumption is detected is recorded to obtain time, and so on, we get time... At that moment, if the power consumption at different moments is less than or equal to the standard power consumption, the moment when the normal power consumption is detected is recorded to obtain Moment, from Time to The moment before The time period between the times is recorded as the peak time period, and the power consumption at different times is compared with the standard power consumption in turn, and this cycle is repeated.

[0011] Furthermore, the specific method for obtaining the power transmission abnormality parameters is as follows: the power consumption information transmission data of each terminal includes the actual data transmission volume per unit time, the actual total amount of data received by the cloud, and the actual interruption time of receiving data. The standard data transmission volume per unit time, the standard total amount of data received by the cloud, and the standard interruption time of receiving data are set. The power transmission abnormality parameters are obtained by comprehensive calculation through the actual data transmission volume per unit time, the actual total amount of data received by the cloud, the actual interruption time of receiving data, the standard data transmission volume per unit time, the standard total amount of data received by the cloud, and the standard interruption time of receiving data.

[0012] Furthermore, the specific method of analyzing the terminal power consumption information transmission jamming situation based on the power consumption information transmission jamming model is: setting the jamming threshold through historical experiments, and comparing the power consumption information transmission jamming model with the jamming threshold. If the power consumption information transmission jamming model is greater than the jamming threshold, it indicates that the transmission is jammed. If the power consumption information transmission jamming model is less than or equal to the jamming threshold, it indicates that the transmission is normal.

[0013] Furthermore, the specific method of adjusting by the neighboring terminal intelligent calculation algorithm is as follows: the physical position of the terminal is converted into a three-dimensional coordinate, and the terminal that is transmitting data is recorded as ,set up The terminal range threshold is based on The area of ​​the circle with the dot is used to make the calculation standard of terminals in different directions consistent. The terminals within this threshold are all represented The nearby terminal is denoted as ,express The terminal range threshold is within Terminal, yes Perform quantity statistics and obtain The number of nearby terminals, based on The number of nearby terminals is calculated for each and The distance between the terminals is obtained by the distance between the terminals, and the distance between the terminals is sorted in ascending order by the sorting algorithm. and The minimum distance, according to and The minimum distance will be The unsent part of the terminal data is sent to the Nearest terminal ,pass Will The unsent terminal data continues to be transmitted to the cloud.

[0014] Furthermore, the specific method of obtaining the distance between the terminals is as follows: ;in, Indicates the distance between terminals, express of coordinate, express of coordinate, express of coordinate, express of coordinate, express of coordinate, express of coordinate.

[0015] Furthermore, the specific method of continuing to analyze whether a terminal has a power outage based on the terminal power consumption information transmission data is: setting a power outage time threshold through historical experiments, and comparing the difference between the total amount of standard data received by the cloud and the total amount of actual data received by the cloud with the power outage time threshold; if the difference between the total amount of standard data received by the cloud and the total amount of actual data received by the cloud is greater than the power outage time threshold, it indicates a power outage; if the difference between the total amount of standard data received by the cloud and the total amount of actual data received by the cloud is less than or equal to the power outage time threshold, it indicates that there is no power outage.

[0016] Beneficial effects Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: 1. The power consumption information transmission jam model constructed through the central computing and processing module performs logarithmic coupling on the peak power consumption anomaly parameters and the power consumption transmission anomaly parameters to quantitatively evaluate the network transmission status. When the model calculation value exceeds the jam threshold set by historical experiments, the system automatically triggers the neighboring intelligent calculation algorithm to divert the unsent data of the jammed terminal to the nearest neighboring terminal in the three-dimensional coordinate system. The data is then relayed through the neighboring terminals to alleviate bandwidth pressure. This mechanism effectively distinguishes transmission delays from actual power outage scenarios, avoids the cloud from misjudging power outages due to data reception delays, and reduces the waste of human and material resources.

[0017] 2. The alarm module integrates multiple early warning methods such as sound and light alarms, SMS push notifications, and platform pop-up windows. Combined with the terminal's three-dimensional physical coordinates obtained by GPS, it achieves millimeter-level positioning of the power outage area. At the same time, the module automatically links the power grid topology map, user information, and historical fault records in the cloud database, providing the operation and maintenance team with one-stop information support for "power outage location - impact range - disposal plan."

[0018] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This invention: A flow chart of a power quality operation data management and maintenance method based on cloud collaboration.

[0020] Figure 2 This is the present invention: a structural diagram of a power quality operation data management and maintenance system based on cloud collaboration. DETAILED DESCRIPTION

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0022] It should be noted that, in this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include," "comprise," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0023] Example 1: like Figure 1-Figure 2 As shown, the embodiment of the present invention provides a power quality operation data management and maintenance system based on cloud collaboration, which includes the following specific modules: Data collection module: Starts collecting terminal data in real time. Terminal refers to equipment such as distribution cabinets or distribution boxes that collect user electricity consumption. Terminal data includes the number of terminals, the physical location of the terminals obtained by GPS, the peak power consumption data of each terminal obtained by the voltage sensor, and the power consumption information transmission data of each terminal obtained by the network traffic monitor.

[0024] Data preprocessing module: Encrypts terminal data to prevent it from being stolen or tampered with during transmission to the cloud.

[0025] Central computing and processing module: Standardizes encrypted terminal data to eliminate dimensional differences in terminal data, converts values ​​of different orders of magnitude into a unified range, and performs comprehensive calculations to obtain peak power consumption anomaly parameters and power transmission anomaly parameters. Normalization is performed on these parameters to further eliminate dimensional differences between them, and comprehensive calculations are performed to obtain a power information transmission jam model. The terminal power consumption information transmission jamming situation is analyzed according to the power consumption information transmission jamming model. If the analysis shows that the transmission is jammed, it is adjusted through the neighboring intelligent calculation algorithm and returns to the data acquisition module until it is analyzed that the transmission is normal. If the analysis shows that the transmission is normal, the terminal continues to analyze whether a terminal has a power outage based on the terminal power consumption information transmission data. If the analysis shows that there is a power outage, the alarm module is called and the detection ends. If the analysis shows that there is no power outage, it returns to the real-time acquisition module.

[0026] Alarm module: By integrating multiple early warning methods such as sound and light alarms, SMS push, platform pop-up windows, etc., accurate power outage location information and fault type prompts can be sent to operation and maintenance personnel, power dispatching centers and relevant management departments in real time.

[0027] The specific method for obtaining the power consumption information transmission jam model is as follows: ; in, Indicates the transmission jam model of power consumption information, reflecting whether the transmission of user power consumption information is jammed. Indicates the peak power consumption abnormality parameter, and is greater than zero, reflecting whether the peak power consumption is abnormal. Indicates the abnormal parameters of power transmission, reflecting whether the power transmission is abnormal. Represents a positive real number. When the power transmission abnormality parameter is less than zero, Make corrections.

[0028] The specific method for obtaining peak power consumption abnormality parameters is as follows: Set standard power consumption, which is not peak power consumption. Each terminal's peak power consumption data includes power consumption at different times. Combine the power consumption at different times with the standard power consumption to obtain the peak power consumption of each terminal. Based on the number of terminals, sum the peak power consumption of each terminal to obtain the peak power consumption anomaly parameter, accurately quantifying the degree to which peak power consumption deviates from the normal state. ; in, Indicates peak power consumption abnormal parameters, Indicates the number of terminals, Indicates the The peak power consumption of a single terminal in a terminal.

[0029] The specific method for obtaining the peak power consumption of a single terminal is as follows: Perform peak power consumption analysis on the power consumption at different times and the standard power consumption to obtain the peak power consumption within a certain time period. That is, the power consumption at different times within a certain time period is all peak power consumption. This time period is recorded as the peak time period. Based on the time series of the peak time period, the peak power consumption within a certain time period is comprehensively calculated to obtain the peak power consumption of a single terminal. ; in, Represents the peak power consumption of a single terminal and is a continuous variable. Time to The time is the peak period. Peak electricity consumption during a certain time period.

[0030] The specific method for obtaining the peak power consumption within a certain period of time is as follows: The power consumption at different times is compared with the standard power consumption in turn. If the power consumption at different times is greater than the standard power consumption, it means that the power consumption at this time is peak power consumption, and the time when the peak power consumption is detected is recorded to obtain time, and so on, we get time... The peak power consumption in a certain time period is continuous. The power consumption change process at different times is accurately calculated by definite integral, and its cumulative effect in the peak time period is revealed. If the power consumption at different times is less than or equal to the standard power consumption, it means that the power consumption at this time is normal power consumption, and the time when the normal power consumption is detected is recorded to obtain At this moment, it is no longer the peak power consumption, so Time to The moment before The time period between the times is recorded as the peak time period, because If the electricity consumption at the time is not the peak electricity consumption, the electricity consumption at different times will be compared with the standard electricity consumption in turn, and the cycle will continue.

[0031] The specific method for obtaining power transmission abnormal parameters is as follows: The power consumption information transmission data of each terminal includes the actual data transmission volume per unit time, the actual total amount of data received by the cloud, and the actual interruption time of receiving data, wherein the interruption time of receiving data is the period of time when no data is received between the time when the cloud receives the last data and the time when the cloud receives the next data. The standard data transmission volume per unit time, the standard total amount of data received by the cloud, and the standard interruption time of receiving data are set. The power consumption transmission abnormality parameter is obtained by performing a comprehensive calculation based on the actual data transmission volume per unit time, the actual total amount of data received by the cloud, the actual interruption time of receiving data, the standard data transmission volume per unit time, the standard total amount of data received by the cloud, and the standard interruption time of receiving data; ; in, Indicates abnormal parameters of power transmission, Indicates the actual data transmission volume per unit time. It indicates the standard data transmission rate per unit time. The greater the difference between the actual data transmission rate per unit time and the standard data transmission rate per unit time, the more congested the network is, and the lower the transmission efficiency is. Indicates the actual total amount of data received by the cloud. Indicates the total amount of standard data received by the cloud. The greater the difference between the total amount of standard data received by the cloud and the actual amount of data received by the cloud, the less data the cloud receives, and thus the lower the transmission efficiency. Indicates the actual interruption time of receiving data. Indicates the standard interval for receiving data. The larger the difference between the actual interval for receiving data and the standard interval for receiving data, the lower the transmission efficiency.

[0032] The specific method for analyzing the jamming of terminal power consumption information transmission based on the power consumption information transmission jamming model is as follows: The jamming threshold is set through historical experiments, and the jamming model of power consumption information transmission is compared with the jamming threshold. If the jamming model of power consumption information transmission is greater than the jamming threshold, it indicates that the transmission is jammed. If the jamming model of power consumption information transmission is less than or equal to the jamming threshold, it indicates that the transmission is normal.

[0033] Example 2 differs from Example 1 in that: The specific method of adjustment through the neighbor intelligent calculation algorithm is as follows: Convert the terminal's physical location into three-dimensional coordinates, which include coordinate, Coordinates and Coordinates, because the terminal physical location is GPS longitude and latitude coordinates, the terminal that is transmitting data is recorded as , Indicates the coordinates of this terminal, set The terminal range threshold is based on The area of ​​the circle with the dot is used to make the calculation standard of terminals in different directions consistent. The terminals within this threshold are all represented The nearby terminal is denoted as , express The terminal range threshold is within The coordinates of the terminal, Perform quantity statistics and obtain The number of nearby terminals, based on The number of nearby terminals is calculated for each and The distance between the terminals is obtained by the distance between the terminals, and the distance between the terminals is sorted in ascending order by a sorting algorithm. For example, by using a bubble sorting algorithm, by comparing and exchanging the distances between adjacent terminals, the distance between the largest terminals is gradually moved to the end of the array, and finally the sorting from small to large is achieved. and The minimum distance is and The minimum distance will be The unsent part of the terminal data is sent to the Nearest terminal ,pass Will The unsent terminal data continues to be transmitted to the cloud to improve transmission efficiency, avoiding There will be a jam during the transmission process, and this algorithm can also avoid Power outage in the area caused The terminal data transmission is interrupted, causing the cloud to receive The terminal data failed.

[0034] The specific method for obtaining the distance between terminals is as follows: ; in, Indicates the distance between terminals, express of coordinate, express of coordinate, express of coordinate, express of coordinate, express of coordinate, express of coordinate.

[0035] The specific method of analyzing whether a terminal has a power outage based on the terminal power consumption information transmission data is as follows: A power outage time threshold is set through historical experiments, which represents the upper limit of the difference between the total amount of standard data received by the cloud and the total amount of actual data received by the cloud. The difference between the total amount of standard data received by the cloud and the total amount of actual data received by the cloud is compared with the power outage time threshold. If the difference between the total amount of standard data received by the cloud and the total amount of actual data received by the cloud is greater than the power outage time threshold, it indicates a power outage. If the difference between the total amount of standard data received by the cloud and the total amount of actual data received by the cloud is less than or equal to the power outage time threshold, it indicates that there is no power outage.

[0036] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to the specific embodiments described. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A cloud-based collaborative power quality operation data management and maintenance system, characterized by: Includes the following specific modules: Data collection module: starts collecting terminal data in real time, including the number of terminals, physical location of terminals, peak power consumption data of each terminal, and terminal power consumption information transmission data; Data preprocessing module: preprocess terminal data; Central computing and processing module: Comprehensively process the pre-processed terminal data to obtain peak power consumption anomaly parameters and power transmission anomaly parameters. Comprehensively process the peak power consumption anomaly parameters and power transmission anomaly parameters to obtain a power information transmission jam model. Analyze the terminal power information transmission jam situation based on the power information transmission jam model. If the analysis shows that the transmission is jammed, adjust it through the neighboring intelligent calculation algorithm and return to the data acquisition module until it is analyzed that the transmission is normal. If the analysis shows that the transmission is normal, continue to analyze whether a terminal has a power outage based on the terminal power information transmission data. If the analysis shows that the power outage is, call the alarm module and end the detection. If the analysis shows that there is no power outage, return to the real-time acquisition module. Alarm module: issues an alarm when a terminal loses power.

2. The cloud-based collaborative power quality operation data management and maintenance system according to claim 1, characterized in that: The specific method for obtaining the electrical information transmission jam model is as follows: ； in, Indicates the transmission jam model of power consumption information. Indicates peak power consumption abnormal parameters, Indicates abnormal parameters of power transmission, Represents a positive real number.

3. The cloud-based collaborative power quality operation data management and maintenance system according to claim 2, characterized in that: The specific method of obtaining the peak power consumption abnormality parameters is as follows: Set the standard power consumption. The peak power consumption data of each terminal includes the power consumption at different times. The power consumption at different times is comprehensively calculated with the standard power consumption to obtain the peak power consumption of a single terminal. The peak power consumption of a single terminal is summed up according to the number of terminals to obtain the peak power consumption abnormality parameters.

4. The cloud-based collaborative power quality operation data management and maintenance system according to claim 3, characterized in that: The specific method for obtaining the peak power consumption of a single terminal is as follows: The peak power consumption at different times is analyzed against the standard power consumption to obtain the peak power consumption within a certain time period. The peak power consumption within a certain time period is comprehensively calculated based on the time series of the peak time period to obtain the peak power consumption of a single terminal.

5. The cloud-based collaborative power quality operation data management and maintenance system according to claim 4, characterized in that: The specific method for obtaining the peak power consumption within a certain time period is as follows: The power consumption at different times is compared with the standard power consumption in turn. If the power consumption at different times is greater than the standard power consumption, the time when the peak power consumption is detected is recorded to obtain time, and so on, we get time... At that moment, if the power consumption at different moments is less than or equal to the standard power consumption, the moment when the normal power consumption is detected is recorded to obtain Moment, from Time to The moment before The time period between the times is recorded as the peak time period, and the power consumption at different times is compared with the standard power consumption in turn, and this cycle is repeated.

6. The cloud-based collaborative power quality operation data management and maintenance system according to claim 2, characterized in that: The specific method for obtaining the power transmission abnormality parameter is as follows: The electricity consumption information transmission data of each terminal includes the actual data transmission volume per unit time, the actual total amount of data received by the cloud, and the actual interruption time of receiving data. The standard data transmission volume per unit time, the standard total amount of data received by the cloud, and the standard interruption time of receiving data are set. The actual data transmission volume per unit time, the actual total amount of data received by the cloud, the actual interruption time of receiving data, the standard data transmission volume per unit time, the standard total amount of data received by the cloud, and the standard interruption time of receiving data are comprehensively calculated to obtain the electricity consumption transmission abnormality parameters.

7. The cloud-based collaborative power quality operation data management and maintenance system according to claim 1, characterized in that: The specific method of analyzing the jamming of terminal power consumption information transmission according to the power consumption information transmission jamming model is as follows: The jamming threshold is set through historical experiments, and the jamming model of power consumption information transmission is compared with the jamming threshold. If the jamming model of power consumption information transmission is greater than the jamming threshold, it indicates that the transmission is jammed. If the jamming model of power consumption information transmission is less than or equal to the jamming threshold, it indicates that the transmission is normal.

8. The cloud-based collaborative power quality operation data management and maintenance system according to claim 1, characterized in that: The specific method of adjusting by the neighboring intelligent calculation algorithm is as follows: The physical position of the terminal is converted into three-dimensional coordinates, and the terminal that is transmitting data is recorded as ,set up The terminal range threshold is based on The area of ​​the circle with the dot is used to make the calculation standard of terminals in different directions consistent. The terminals within this threshold are all represented The nearby terminal is denoted as ,express The terminal range threshold is within Terminal, yes Perform quantity statistics and obtain The number of nearby terminals, based on The number of nearby terminals is calculated for each and The distance between the terminals is obtained by the distance between the terminals, and the distance between the terminals is sorted in ascending order by the sorting algorithm. and The minimum distance, according to and The minimum distance will be The unsent part of the terminal data is sent to the Nearest terminal ,pass Will The unsent terminal data continues to be transmitted to the cloud.

9. The cloud-based collaborative power quality operation data management and maintenance system according to claim 8, characterized in that: The specific method of obtaining the distance between the terminals is as follows: ； in, Indicates the distance between terminals, express of coordinate, express of coordinate, express of coordinate, express of coordinate, express of coordinate, express of coordinate.

10. The cloud-based collaborative power quality operation data management and maintenance system according to claim 6, characterized in that: The specific method of continuing to analyze whether a terminal has a power outage based on the terminal power consumption information transmission data is as follows: A power outage time threshold is set through historical experiments, and the difference between the total amount of standard data received by the cloud and the total amount of actual data received by the cloud is compared with the power outage time threshold. If the difference between the total amount of standard data received by the cloud and the total amount of actual data received by the cloud is greater than the power outage time threshold, it indicates a power outage. If the difference between the total amount of standard data received by the cloud and the total amount of actual data received by the cloud is less than or equal to the power outage time threshold, it indicates that there is no power outage.

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