A park-based intelligent power consumption data analysis and management system

Abstract

The present invention relates to the technical field of park power consumption management, and discloses an intelligent power consumption data analysis and management system based on a park. The system includes: a park information collection module for collecting the functional layout information of the park; a regional division module for dividing the park into a number of target areas according to the functional layout information of the park; a power consumption data collection module for regularly collecting the power consumption information data of each target area in the park; and a data analysis module for performing data analysis on the power consumption information data and generating an equipment supervision strategy based on the data analysis. The present invention can overcome the unified influence of factors such as the power consumption environment and production efficiency on the power consumption of each target area, and can timely discover the target area with abnormal changes in power consumption through analysis and perform targeted power consumption monitoring on the target area, thereby improving the robustness of park power consumption data analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of park electricity management, and particularly relates to an intelligent electricity data analysis and management system based on a park. Background Art

[0002] Electricity analysis and management is a comprehensive process aimed at achieving real-time monitoring, analysis, optimization, and safety management of electricity use through technical means and management measures. As an area that concentrates a large number of enterprises and personnel, the electricity analysis and management of a park plays an important role in improving operation efficiency, ensuring electricity safety, promoting energy conservation and emission reduction, and optimizing resource allocation.

[0003] Existing park management technologies can quickly understand the electricity consumption situation of a park by real-time monitoring of electricity consumption data in the park, including key indicators such as voltage, current, and power factor.

[0004] A park is usually divided into multiple areas according to its functional distribution, such as industrial areas, commercial areas, office areas, etc. Dispersed management of the electricity consumption of each area can improve the efficiency and accuracy of electricity data collection and management. However, the peak and valley of electricity consumption in each area of the park often have synchrony. This is mainly because the production and operation activities of each enterprise in the park usually have a certain regularity. For example, when a new project in the park is put into use or the production and operation scale of an enterprise expands, the overall electricity consumption will increase, and the electricity consumption of each area will also rise accordingly. Similarly, in seasonal changes, such as increased air-conditioning electricity consumption in summer and increased heating electricity consumption in winter, these seasonal changes will also be reflected in the electricity consumption of each area. The above-mentioned electricity consumption environment has a unified impact on the electricity consumption of each area. Therefore, the existing technology only analyzes the change range of the electricity consumption of each area separately, and it is difficult to timely discover the area where the electricity consumption changes abnormally.

[0005] However, the existing technology usually ignores the fact that the failure of electricity-consuming equipment will also cause changes in electricity consumption. When a large change in the electricity consumption data of the park is monitored, it is difficult to determine whether it is caused by the failure of the electricity-consuming equipment in the park. Therefore, timely response measures cannot be arranged according to the electricity consumption monitoring results. Summary of the Invention

[0006] The purpose of the present invention is to provide an intelligent electricity data analysis and management system based on a park to solve the above technical problems:

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] An intelligent electricity data analysis and management system based on a park, the system includes:

[0009] A park information collection module for collecting the functional layout information of the park;

[0010] An area division module, configured to divide the park into a number of target areas according to the functional layout information of the park;

[0011] An electricity data collection module, configured to regularly collect electricity consumption information data of each target area in the park;

[0012] An data analysis module, configured to perform data analysis on the electricity consumption information data and generate an equipment supervision strategy according to the data analysis; the process of performing data analysis on the electricity consumption information data includes: calculating and obtaining the difference between the current electricity consumption data of the target area and the historical average electricity consumption data of the corresponding target area, and marking the difference as the electricity consumption change coefficient, analyzing and obtaining the discreteness of the distribution of the electricity consumption change coefficients of each target area, and if the discreteness exceeds a preset standard, screening the target areas to be monitored according to the electricity consumption change coefficient and the number of electrical equipment of the target area.

[0013] As a further technical solution, the system further includes:

[0014] An electrical equipment management module, configured to execute the equipment supervision strategy and monitor the electrical equipment in the target areas to be monitored, including a collection terminal and an edge computing unit, where the collection terminal is configured to collect the status information parameters of each electrical equipment in the target area, and the edge computing unit is configured to perform a fault risk assessment on the relevant electrical equipment according to the status information parameters of the electrical equipment;

[0015] A communication module, configured to establish a communication connection between the electrical equipment management module and the cloud, and upload the fault risk assessment result data of the electrical equipment to the cloud;

[0016] The cloud, configured to store the fault risk assessment result data of the electrical equipment and the basic information parameters of the corresponding equipment;

[0017] An early warning module, including an early warning generation unit and a human-computer interaction unit, where the early warning generation unit is configured to generate an early warning prompt strategy according to the fault risk assessment result of the electrical equipment; the human-computer interaction unit is configured to execute the early warning prompt strategy.

[0018] As a further technical solution, the process of collecting the electricity consumption information data of each target area in the park includes:

[0019] Install electricity meters electrically connected to each electrical equipment in the corresponding target area in each target area, and obtain the electricity consumption data of the target area through the electricity meters;

[0020] Transmit the electricity consumption data of each target area to the electricity data analysis module using a unified communication protocol.

[0021] As a further technical solution, the process of analyzing and obtaining the discreteness of the distribution of the electricity consumption change coefficients of each target area includes:

[0022] Calculate the electricity consumption difference evaluation coefficient of the park through the following formula ~ ; ;

[0023] ;

[0024] ;

[0025] ;

[0026] wherein, is the electricity consumption of the i-th target area; is the historical average electricity consumption of the i-th target area; is the number of target areas; is the preset proportionality coefficient corresponding to the i-th target area; is the electricity consumption change coefficient of the i-th target area;

[0027] Compare the electricity consumption difference evaluation coefficient with the preset difference threshold :

[0028] If , no equipment supervision strategy is generated;

[0029] If , the target areas to be monitored are screened according to the electricity consumption change coefficients of the target areas.

[0030] As a further technical solution, the process of screening the target areas to be monitored includes:

[0031] Calculate the electricity consumption anomaly risk coefficient of the target area through the formula ; ;

[0032] wherein, , are the preset first weight coefficients; is the electricity consumption change coefficient of the target area; is the number of electrical equipment in the corresponding target area;

[0033] Compare the electricity consumption anomaly risk value with the preset threshold :

[0034] If , the status information of the electrical equipment in the target area is not collected;

[0035] If , the status information of the electrical equipment in the target area is collected, and the edge computing unit evaluates the fault risk of the relevant electrical equipment according to the status information parameters of the electrical equipment.

[0036] As a further technical solution, the process of collecting the status information parameters of the electrical equipment includes: when the electrical equipment is under a preset working condition, the change data of the output power, operating noise volume, and average component temperature of the electrical equipment within a preset unit time period is collected. At the same time, the standard change curves of the output power, operating noise volume, and average component temperature of the electrical equipment are obtained correspondingly.

[0037] As a further technical solution, the process of evaluating the fault risk of the relevant electrical equipment includes:

[0038] By the formula Calculate and obtain the fault risk coefficient of the electrical equipment ;

[0039] Wherein, Is the preset second weight coefficient; Is the change value of the output power, operating noise volume, and average component temperature of the electrical equipment over time; Is the standard change curve of the output power, operating noise volume, and average component temperature of the electrical equipment; , Are the left and right endpoints of the preset unit time period respectively;

[0040] Compare the fault risk coefficient of the electrical equipment With the preset risk threshold :

[0041] If , it is determined that the electrical equipment is operating normally;

[0042] If , it is determined that the electrical equipment is operating abnormally, and a fault warning prompt signal for the corresponding electrical equipment is generated through the warning module and a warning is issued.

[0043] As a further technical solution, the system further includes:

[0044] A historical data update module for updating the historical average power consumption data of the target area. The process of updating the historical average power consumption data of the target area is as follows: if it is determined that there is an abnormally operating electrical equipment in the target area, the historical average power consumption data of the target area is not updated; otherwise, through the formula Calculate and obtain the updated historical average power consumption value , wherein, is the total number of times of collecting power consumption data for the target area.

[0045] Advantages of the present invention:

[0046] (1) By calculating the power consumption change coefficient between the current power consumption data of the target area and the historical average power consumption data of the corresponding target area, and then analyzing the discreteness of the distribution of the power consumption change coefficients of each target area, this analysis can overcome the unified influence of factors such as power consumption environment and production efficiency on the power consumption of each target area. Through the analysis, it is possible to timely discover the target area with abnormal power consumption changes and conduct targeted power consumption monitoring on this target area. Therefore, the robustness of the power consumption data analysis in the park is improved.

[0047] (2) The present invention provides an intelligent power consumption data analysis and management system based on the park. First, the park is divided into multiple target areas according to the functional layout of the park, which is convenient for individual monitoring and management of each target area to improve management efficiency. Through the monitoring and analysis of the power consumption information of each target area, the target areas with abnormal power consumption are screened out, and the fault risk assessment and investigation of the power consumption equipment in this area are carried out. Therefore, through the analysis of the power consumption data in the park, not only can the power consumption trend in the park be revealed, but also the abnormal power consumption equipment can be identified, which is convenient for arranging the maintenance measures for the corresponding power consumption equipment in a timely manner. Description of the Drawings

[0048] The present invention will be further described below with reference to the accompanying drawings.

[0049] Figure 1 is the content summary block diagram of the intelligent power consumption data analysis and management system based on the park in the present invention. Detailed Embodiments

[0050] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0051] Please refer to Figure 1 as shown, an intelligent power consumption data analysis and management system based on the park, the system includes:

[0052] The park information collection module is used to collect the functional layout information of the park. The area division module is used to divide the park into several target areas according to the functional layout information of the park. Specifically, according to the functional layout of the park, the areas with similar electricity consumption characteristics are divided into the same electricity consumption area. For example, the production area, office area, dormitory area, etc. are divided into different electricity consumption target areas respectively. In addition, it is also considered to divide according to the load density and power supply reliability of each area. The load density is the electricity consumption load per unit area. Areas with high load density may require more power supply and a more complex power grid structure. The power supply reliability is to determine the power supply reliability level of each area according to the operation requirements of the park.

[0053] The electricity consumption data collection module is used to regularly collect the electricity consumption information data of each target area in the park. Specifically, independent electricity meters can be installed in each area, and the electricity consumption change data on the electricity meters can be obtained regularly.

[0054] The data analysis module is used to perform data analysis on the electricity consumption information data and generate an equipment supervision strategy according to the data analysis. Specifically, the process of performing data analysis on the electricity consumption information data includes: calculating the difference between the current electricity consumption data of the target area and the historical average electricity consumption data of the corresponding target area, and marking the difference as the electricity consumption change coefficient, analyzing the discreteness of the distribution of the electricity consumption change coefficients of each target area. If the discreteness exceeds the preset standard, the target areas to be monitored are screened according to the electricity consumption change coefficients and the number of electrical equipment in the target areas. Through the above analysis, the unified influence of factors such as the electricity consumption environment and production efficiency on the electricity consumption of each target area can be overcome, the target areas with abnormal electricity consumption can be discovered in time, and targeted electricity consumption monitoring can be carried out on this area. The robustness and efficiency of the park electricity consumption data analysis are improved. That is, a sudden change in the electricity consumption of a certain target area does not mean that there is abnormal electricity consumption in this area, but only when the change in the electricity consumption of the target area is significantly different from that of other areas does it reflect the possibility of abnormal electricity consumption in this area.

[0055] Through the above technical solution, this embodiment provides an intelligent electricity consumption data analysis and management system based on the park. First, the park is divided into multiple target areas according to the functional layout of the park, which is convenient for individual monitoring and management of each target area to improve management efficiency.

[0056] The system also includes:

[0057] The electrical equipment management module is used to execute the equipment supervision strategy, including a collection terminal and an edge computing unit. The collection terminal is used to collect the status information parameters of each electrical equipment in the target area, and the edge computing unit is used to perform a fault risk assessment on the relevant electrical equipment according to the status information parameters of the electrical equipment.

[0058] A communication module, which is used to establish a communication link between the power consumption equipment management module and the cloud, and upload the fault risk evaluation result data of the power consumption equipment to the cloud, so as to facilitate maintenance personnel to call the data in time during the repair of faulty power consumption equipment;

[0059] The cloud, which is used to store the fault risk evaluation result data of the power consumption equipment and the basic information parameters of the corresponding equipment. The basic information parameters specifically include the spare quantity of the power consumption equipment, the equipment year, etc., providing favorable data for the maintenance and analysis process of the faulty equipment.

[0060] The warning module includes a warning generation unit and a human-computer interaction unit. The warning generation unit is used to generate a warning prompt strategy according to the fault risk evaluation result of the power consumption equipment; the human-computer interaction unit is used to execute the warning prompt strategy. The human-computer interaction unit specifically includes the handheld terminal (such as a mobile phone) of relevant staff or a unified display terminal (such as a monitor set up in the park management department).

[0061] Through the above technical solutions, this embodiment provides other contents of the system, including: a communication module, a cloud, and a warning module. It realizes the storage and call of the power consumption data analysis result information, providing warning prompts and data support for the management decision-making of park management personnel.

[0062] The process of collecting the power consumption information data of each target area in the park includes:

[0063] Install electric energy meters electrically connected to each power consumption equipment in each target area respectively, and obtain the power consumption data of the target area through the electric energy meters;

[0064] Transmit the power consumption data of each target area to the power consumption data analysis module by using a unified communication protocol. Through the unified protocol, the power consumption data can be transmitted to the power consumption data analysis module in real time and accurately, ensuring the timeliness of power grid monitoring, dispatching and other work.

[0065] Through the above technical solutions, the process of collecting the power consumption information data of each target area in the park is provided. The power consumption data of each target area is obtained through independently set electric energy meters, and then the power consumption data of each target area is transmitted to the power consumption data analysis module by using a unified communication protocol.

[0066] The process of analyzing and obtaining the discreteness of the distribution of the power consumption change coefficients of each target area includes:

[0067] Through the following formula ~ Calculate and obtain the power consumption difference evaluation coefficient of the park ;

[0068] ;

[0069] ;

[0070] ;

[0071] Among them, is the electricity consumption of the i-th target area; is the historical average electricity consumption of the i-th target area; is the number of target areas; is the preset proportionality coefficient corresponding to the i-th target area; is the electricity consumption change coefficient of the i-th target area;

[0072] Compare the electricity consumption difference evaluation coefficient with the preset difference threshold :

[0073] If , no equipment supervision strategy is generated;

[0074] If , the target areas to be monitored are screened according to the electricity consumption change coefficient of the target areas.

[0075] Through the above technical solution, this embodiment provides a process for data analysis of the electricity consumption information data. Specifically, first, through the formulas , , calculate and obtain the electricity consumption difference evaluation coefficient of the park. As can be seen from the formula, this coefficient not only reflects the difference between the electricity consumption information of the target area and its historical electricity consumption information, but also reflects the change in the electricity consumption connection between different areas. Compare the electricity consumption difference evaluation coefficient with the preset difference threshold : Considering the unified influence of environmental factors, production efficiency and other factors on the electricity consumption of each target area, there is a certain correlation in the electricity consumption changes of each area. When , it indicates that the difference in the electricity consumption changes of each area is small, and no equipment supervision strategy is generated; when , it indicates that the difference in the electricity consumption changes of each area is large. Therefore, the target areas to be monitored are screened according to the electricity consumption change coefficient of the target areas, and then the failure risks of the electrical equipment in the target areas to be monitored are analyzed. It should be noted that in the above formulas, is the electricity consumption of the i-th target area; is the historical average electricity consumption of the i-th target area, which is obtained by adding up the historical electricity consumption and dividing by the number of electricity consumption collection times. is the number of target areas; is the preset proportionality coefficient corresponding to the i-th target area, which is specifically related to the characteristics of the device itself and can be obtained according to empirical data. is the coefficient of change in electricity consumption of the i-th target area.

[0076] The process of screening the target areas to be monitored includes:

[0077] By the formula Calculate and obtain the risk coefficient of abnormal electricity consumption in the target area ;

[0078] Among them, , is the preset first weight coefficient; is the coefficient of change in electricity consumption of the target area; is the number of electrical equipment in the corresponding target area;

[0079] Compare the abnormal electricity consumption risk value with the preset threshold :

[0080] If , then do not collect the status information of the electrical equipment in the target area;

[0081] If , then collect the status information of the electrical equipment in the target area, and evaluate the fault risk of the relevant electrical equipment by the edge computing unit according to the status information parameters of the electrical equipment.

[0082] Through the above technical solution, this embodiment provides a process for screening the target areas to be monitored. Specifically, first, calculate and obtain the risk coefficient of abnormal electricity consumption in the target area by . It can be seen from the formula that the abnormal risk coefficient is related to the number of electrical equipment in the target area. The more the number, the more uncontrollable factors, and the greater the probability that the change in electricity consumption is caused by equipment failure. Then compare the abnormal electricity consumption risk value with the preset threshold : If , it means that the abnormal electricity consumption risk in the target area is small, and do not collect the status information of the electrical equipment in the target area; if , it means that the abnormal electricity consumption risk in the target area is large. Therefore, collect the status information of the electrical equipment in the target area, and evaluate the fault risk of the relevant electrical equipment by the edge computing unit according to the status information parameters of the electrical equipment.

[0083] The process of collecting the status information parameters of the electrical equipment includes: when the electrical equipment is under a preset working condition, collecting the change data of the output power, operating noise volume, and average component temperature of the electrical equipment within a preset unit time period. At the same time, correspondingly obtaining the standard change curves of the output power, operating noise volume, and average component temperature of the electrical equipment.

[0084] Through the above technical solution, this embodiment provides the process of collecting the status information parameters of the electrical equipment. Specifically, when the electrical equipment is under a preset working condition, collecting the change data of the output power, operating noise volume, and average component temperature of the electrical equipment within a preset unit time period. At the same time, correspondingly obtaining the standard change curves of the output power, operating noise volume, and average component temperature of the electrical equipment. It should be noted that each standard change curve is obtained according to a normal equipment under the same preset working condition as above.

[0085] The process of evaluating the failure risk of the relevant electrical equipment includes:

[0086] By the formula Calculate and obtain the failure risk coefficient of the electrical equipment ;

[0087] Wherein, Is the preset second weight coefficient; Are the change values of the output power, operating noise volume, and average component temperature of the electrical equipment over time. Specifically, for example: Is the change value of the output power of the electrical equipment over time, Is the change value of the operating noise volume of the electrical equipment over time, Is the change value of the average component temperature of the electrical equipment over time. Are the standard change curves of the output power, operating noise volume, and average component temperature of the electrical equipment, ~ The corresponding relationship with the output power, operating noise volume, and average component temperature is the same as the above explanation of , and will not be elaborated here; , Are the left and right endpoints of the preset unit time period respectively;

[0088] Compare the failure risk coefficient Of the electrical equipment with the preset risk threshold :

[0089] If , then it is judged that the electrical equipment is operating normally;

[0090] If , then it is judged that the electrical equipment is operating abnormally, and a failure warning prompt signal corresponding to the electrical equipment is generated through the warning module and a warning is issued.

[0091] Through the above technical solution, this embodiment provides a process for evaluating the fault risk of relevant electrical equipment, that is, first through the formula Calculate and obtain the fault risk coefficient of the electrical equipment , and then compare the fault risk coefficient of the electrical equipment with the preset risk threshold : If , it indicates that the fault risk of the electrical equipment is relatively small, so it is judged that the electrical equipment is operating normally; if , it indicates that the fault risk of the electrical equipment is relatively large, so it is judged that the electrical equipment is operating abnormally, and a fault warning prompt signal corresponding to the electrical equipment is generated through the warning module and a warning is issued. The warning content specifically includes the equipment name and the location information of the equipment in the park.

[0092] The system further includes:

[0093] A historical data update module, which is used to update the historical average power consumption data of the target area. The process of updating the historical average power consumption data of the target area is as follows: If it is judged that there is an abnormally operating electrical equipment in the target area, the historical average power consumption data of the target area will not be updated; otherwise, through the formula Calculate and obtain the updated historical average power consumption value , where is the total number of times the power consumption data of the target area is collected. Through the above technical solution, this embodiment provides a specific method for updating the historical average power consumption data of the target area.

[0094] The above has described an embodiment of the present invention in detail, but the content described is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the present invention application shall still fall within the scope covered by the patent of the present invention.

Claims

1. An intelligent power consumption data analysis and management system based on a park, characterized in that: The system comprises: Park information collection module, used to collect functional layout information of the park; The area division module is used to divide the park into several target areas according to the functional layout information of the park; The electricity consumption data collection module is used to regularly collect electricity consumption information data of each target area in the park; A data analysis module is used to perform data analysis on the power consumption information data and generate an equipment supervision strategy based on the data analysis; the process of performing data analysis on the power consumption information data includes: calculating the difference between the current power consumption data of the target area and the historical average power consumption data of the corresponding target area, marking the difference as the power consumption change coefficient, analyzing and obtaining the discreteness of the distribution of the power consumption change coefficient of each target area, and if the discreteness exceeds a preset standard, screening the target area to be monitored according to the power consumption change coefficient and the number of power-consuming equipment in the target area; The system further comprises: An electric equipment management module, which is used to execute the equipment supervision strategy and monitor the electric equipment in the target area to be monitored, and includes a collection terminal and an edge computing unit. The collection terminal is used to collect status information parameters of each electric equipment in the target area, and the edge computing unit is used to perform fault risk assessment on the relevant electric equipment according to the status information parameters of the electric equipment; A communication module, used to establish a communication connection between the power consumption equipment management module and the cloud, and upload the fault risk assessment result data of the power consumption equipment to the cloud; The cloud is used to store the fault risk assessment result data of electrical equipment and the basic information parameters of the corresponding equipment; The early warning module includes an early warning generation unit and a human-computer interaction unit, wherein the early warning generation unit is used to generate an early warning prompt strategy according to the failure risk assessment result of the electric equipment; and the human-computer interaction unit is used to execute the early warning prompt strategy; The process of collecting electricity consumption information data for each target area in the park includes: Installing electric energy meters electrically connected to the electric devices in the corresponding target areas in each target area, and obtaining the electric energy consumption data of the target area through the electric energy meters; A unified communication protocol is used to transmit the power consumption data of each target area to the power consumption data analysis module; The process of analyzing and obtaining the discreteness of the distribution of the coefficient of variation of electricity consumption in each target area includes: Through the following formula ~ Calculate the power consumption difference evaluation coefficient of the park ; ； ； ； in, is the power consumption of the i-th target area; is the historical average electricity consumption of the i-th target area; is the number of target areas; is the preset proportional coefficient corresponding to the i-th target area; is the power consumption variation coefficient of the i-th target area; The electricity consumption difference evaluation coefficient Difference from preset threshold To compare: like , then no device supervision policy is generated; like , then select the target area to be monitored according to the power consumption change coefficient of the target area; The process of selecting target areas for monitoring includes: By formula Calculate the power consumption abnormality risk factor of the target area ; in, , is a preset first weight coefficient; is the coefficient of change of electricity consumption in the target area; is the number of electrical equipment in the corresponding target area; The abnormal risk value of electricity consumption With preset threshold Make a comparison: like , then the status information of the electrical equipment in the target area will not be collected; like , then collect the status information of the electrical equipment in the target area, and use the edge computing unit to evaluate the fault risk of the relevant electrical equipment according to the status information parameters of the electrical equipment; The process of collecting the status information parameters of the electrical equipment includes: when the electrical equipment is under a preset working condition, collecting the change data of the output power, operating noise volume and average temperature of the components of the electrical equipment within a preset unit time period, and at the same time, obtaining the standard change curve of the output power, operating noise volume and average temperature of the components of the electrical equipment; The process of conducting failure risk assessment on relevant electrical equipment includes: By formula Calculate the failure risk factor of electrical equipment ; in, is a preset second weight coefficient; The output power, operating noise volume and average component temperature of the electrical equipment change over time; It is the standard variation curve of the output power, operating noise volume and average temperature of components of electrical equipment; , They are the left and right endpoints of the preset unit time period respectively; The failure risk factor of the electrical equipment With preset risk threshold To compare: like , it is judged that the electrical equipment is operating normally; like , it is judged that the electrical equipment is operating abnormally, and a fault warning prompt signal for the electrical equipment is generated through the early warning module and an early warning is issued.

2. According to claim 1, the intelligent power consumption data analysis and management system based on the park is characterized in that: The system further comprises: The historical data update module is used to update the historical average power consumption data of the target area. The process of updating the historical average power consumption data of the target area is as follows: if it is determined that there are abnormal power consumption devices in the target area, the historical average power consumption data of the target area will not be updated; otherwise, the historical average power consumption data of the target area will be updated through the formula Calculate and obtain the updated historical average power consumption value ,in, The total number of times the electricity consumption data of the target area is collected.

Images