Power utilization safety monitoring method based on daily power utilization characteristics

Abstract

The invention discloses an electricity utilization safety monitoring method based on daily electricity utilization characteristics, relates to the technical field of electricity utilization protection, and comprehensively considers a plurality of influence factors such as seasonal characteristics Sc, high-power electric appliance proportion Hratio, daily average electricity consumption Davg and voltage fluctuation ratio V in household electricity utilization to calculate electricity utilization risk assessment values R of different families. According to the method, the power utilization risk assessment value R is calculated and compared with an early warning threshold value Y1 and a danger threshold value Y2, a monitoring family is divided into three intervals, corresponding safety measures are taken for the power utilization family with the power utilization risk assessment value R in the high interval, distribution of monitoring resources can be optimized under limited monitoring resources, the monitoring frequency is increased for the power utilization family with large power consumption and high risk, and the safety of the power utilization family is improved. And for electricity utilization families with small electricity consumption and low electricity utilization risk, the monitoring frequency is reduced, resources are saved, a more scientific and reasonable electricity utilization safety monitoring distribution strategy is formulated for the electricity utilization safety monitoring method, and the monitoring efficiency of electricity utilization safety monitoring is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electricity protection, and in particular to a method for monitoring electricity safety based on daily electricity consumption characteristics. Background Art

[0002] At present, when monitoring household electricity safety, the power supply bureau can only increase the monitoring frequency of electricity safety for households with higher electricity consumption based on the electricity consumption of different households, but ignores that the voltage fluctuation frequency, the proportion of electricity consumption of high-power electrical appliances in the household, and the different electricity consumption seasons will also affect electricity safety. In order to ensure the safe use of electricity in households, the above problems also need to be considered in the monitoring frequency of household electricity safety. And currently, when the power supply bureau detects that the voltage load of household electricity is too high, it will directly take the protective measure of tripping. For residential areas where multiple households share one meter, direct tripping will affect the electricity consumption of multiple households at the same time, which is not conducive to use. In response to the above problems, the present invention provides a method for monitoring electricity safety based on daily electricity consumption characteristics. Summary of the invention

[0003] The purpose of the present invention is to provide a method for monitoring electricity safety based on daily electricity usage characteristics to solve the problems raised in the above-mentioned background technology.

[0004] To achieve the above object, the present invention provides the following technical solution: a method for monitoring electricity safety based on daily electricity consumption characteristics, the method comprising the following steps: Information data collection, including: Obtain the load value P at the monitoring time point, the total impedance Z in the household power distribution system, and the total number of power system failures in the past year from the power consumption monitoring system of the power supply bureau; Data preprocessing: the load value P collected at the monitoring time point and the total impedance Z in the household power distribution system are transmitted to the data processing module for decoding preprocessing to obtain the number of monitoring times F. m And the important parameters of the electricity risk assessment value R; The electricity safety monitoring method specifically includes: Substitute the decoded parameter values ​​into the voltage fluctuation frequency algorithm unit and the daily average power consumption algorithm unit to calculate the voltage fluctuation frequency V and the daily average power consumption D avg , two parameters that have an important impact on the electricity risk assessment value R; Next, the calculated voltage fluctuation frequency V and daily average power consumption D avg Substitute them together into the electricity risk assessment value algorithm unit to calculate the electricity risk assessment value R; Afterwards, the calculated power consumption risk assessment value R is recorded and stored in the database, the warning threshold value Y1 of the power consumption risk assessment value is set to 0.6, the danger threshold value Y2 of the power consumption risk assessment value is set to 0.8, and the comprehensive score value H of the software system is compared with the warning threshold value Y1 and the danger threshold value Y2; The households with the risk assessment value of electricity consumption R less than Y1 are classified into interval 1. The household electricity consumption in interval 1 is within the safe electricity consumption range; Households with a power risk assessment value R greater than Y1 and less than Y2 are classified into interval 2. The power safety in interval 2 is within the warning range. The power supply bureau will reduce the output voltage of the household. The reduced output voltage directly affects the household's power consumption and is directly reflected in the dimming of the lights, reminding the household that the total voltage load of the electrical appliances used is too large. The households with a power consumption risk assessment value R greater than the danger threshold Y2 are classified into interval 3. The power supply bureau will directly suspend power supply to households in interval 3 to avoid power accidents caused by excessive power load. Feedback and adjustments, including: Substitute the decoded parameter value into the monitoring frequency adjustment formula to calculate the different monitoring times F for different electricity-consuming households per day. m Times, according to the different electricity usage situations of different households, change the number of daily electricity safety monitoring times, and make more appropriate resource allocation for electricity safety monitoring of different households.

[0005] Optionally, the electricity safety monitoring method is operated using an information data collection module, a data preprocessing module, a calculation processing module and a data storage module.

[0006] Optionally, the calculation and processing module includes a voltage fluctuation frequency algorithm unit, a daily average power consumption algorithm unit, a power consumption risk assessment value algorithm unit and a monitoring frequency algorithm unit.

[0007] Optionally, the voltage fluctuation frequency algorithm unit is as follows: ;

[0008] in: V represents the voltage fluctuation frequency; △P represents the instantaneous change of voltage load; P prev Represents the average load of household electricity; Z represents the total impedance of the grid; E represents the power regulation rate; α is the voltage fluctuation adjustment factor.

[0009] Optionally, the daily average power consumption algorithm unit is as follows: ;

[0010] in: D avg Represents the average daily electricity consumption, in degrees; D i represents the electricity consumption on the i-th day; n is the total number of days in the monitoring time range.

[0011] Optionally, the electricity risk assessment value algorithm unit is as follows: ;

[0012] in: R represents the risk assessment value of electricity use; V represents the voltage fluctuation rate; H ratio Represents the proportion of electricity used by high-power electrical appliances; D avg represents the average daily electricity consumption; H f represents the historical failure rate; S c Represents the seasonal characteristic coefficient; indicates the degree of influence of the current season on the power safety risk; the specific algorithm formula is as follows: ;

[0013] in: Q s is the total electricity consumption in the current quarter; Q a is the total electricity consumption for a year; β is an adjustment factor.

[0014] Optionally, the monitoring frequency adjustment formula in the monitoring frequency algorithm unit is as follows: ;

[0015] in: F m represents the adjusted number of monitoring times per day; F base Represents the number of basic monitoring times per day; usually once every two hours, 12 times a day; T max Represents the electricity consumption in the hour with the highest electricity consumption in a day; T min Represents the electricity consumption during the hour with the least electricity consumption in a day.

[0016] Optionally, the warning threshold value Y1 of the electricity consumption risk assessment value is set to 0.6, and the danger threshold value Y2 of the electricity consumption risk assessment value is set to 0.8.

[0017] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention cooperates with four groups of algorithm units to form the core framework of the power safety monitoring method based on daily power consumption characteristics. In the power safety monitoring, the seasonal characteristics S of household power consumption are comprehensively considered. c 、The proportion of high-power electrical appliances ratio , daily average electricity consumption D avg The electricity risk assessment value R of different households is calculated based on multiple influencing factors such as the voltage fluctuation rate V, which comprehensively reflects the actual situation and potential risks of household electricity consumption. The different electricity risk assessment values ​​R calculated for each household are compared with the warning threshold Y1 and the danger threshold Y2, and the monitored households are divided into three intervals, so as to accurately judge the electricity safety of each household, and take corresponding safety measures for households with higher electricity risk assessment values ​​R. When taking safety measures such as cutting off power or reducing output voltage, it will not affect other households in the residential area, thereby ensuring the pertinence and effectiveness of electricity safety monitoring.

[0018] 2. The present invention determines different monitoring frequencies for different households based on the actual situation of household electricity consumption and potential risks, so that different monitoring frequencies F for different households can be calculated through the monitoring frequency adjustment formula under limited monitoring resources. m , optimize the allocation of monitoring resources. For households with high electricity consumption and high risks, increase the monitoring frequency to ensure electricity safety. For households with low electricity consumption and low electricity risks, appropriately reduce the monitoring frequency to save resources. It can formulate a more scientific and reasonable electricity safety monitoring allocation strategy for electricity safety monitoring methods to improve the monitoring efficiency of electricity safety monitoring and reduce monitoring costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flow chart of a method for monitoring electricity safety based on daily electricity consumption characteristics; Figure 2 The figure is a schematic diagram of the overall structure of an electricity safety monitoring method based on daily electricity consumption characteristics. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0021] Example 1: Please refer to Figure 1 and Figure 2The present invention provides a technical solution: a method for monitoring power safety based on daily power consumption characteristics, the method comprising the following steps: Information data collection, including: Obtain the load value P at the monitoring time point, the total impedance Z in the household power distribution system, and the total number of power system failures in the past year from the power consumption monitoring system of the power supply bureau; Data preprocessing: the load value P collected at the monitoring time point and the total impedance Z in the household power distribution system are transmitted to the data processing module for decoding preprocessing to obtain the number of monitoring times F. m And the important parameters of the electricity risk assessment value R; The electricity safety monitoring method specifically includes: Substitute the decoded parameter values ​​into the voltage fluctuation frequency algorithm unit and the daily average power consumption algorithm unit to calculate the voltage fluctuation frequency V and the daily average power consumption D avg , two parameters that have an important impact on the electricity risk assessment value R; Next, the calculated voltage fluctuation frequency V and daily average power consumption D avg Substitute them together into the electricity risk assessment value algorithm unit to calculate the electricity risk assessment value R; Afterwards, the calculated power consumption risk assessment value R is recorded and stored in the database, the warning threshold value Y1 of the power consumption risk assessment value is set to 0.6, the danger threshold value Y2 of the power consumption risk assessment value is set to 0.8, and the comprehensive score value H of the software system is compared with the warning threshold value Y1 and the danger threshold value Y2; The households with the risk assessment value of electricity consumption R less than Y1 are classified into interval 1. The household electricity consumption in interval 1 is within the safe electricity consumption range; Households with a power risk assessment value R greater than Y1 and less than Y2 are classified into interval 2. The power safety in interval 2 is within the warning range. The power supply bureau will reduce the output voltage of the household. The reduced output voltage directly affects the household's power consumption and is directly reflected in the dimming of the lights, reminding the household that the total voltage load of the electrical appliances used is too large. The households with a power consumption risk assessment value R greater than the danger threshold Y2 are classified into interval 3. The power supply bureau will directly suspend power supply to households in interval 3 to avoid power accidents caused by excessive power load. Feedback and adjustment: Substitute the decoded parameter value into the monitoring frequency adjustment formula to calculate the different monitoring times F for different electricity-consuming households per day. m Times, according to the different electricity usage situations of different households, change the number of daily electricity safety monitoring times, and make more appropriate resource allocation for electricity safety monitoring of different households.

[0022] The electricity safety monitoring method adopts an information data collection module, a data preprocessing module, a calculation processing module and a data storage module to operate.

[0023] In this embodiment: The present invention cooperates with each other through four groups of algorithm units to form the core architecture of the power safety monitoring method based on daily power consumption characteristics. The voltage fluctuation frequency V and the daily average power consumption D calculated by the voltage fluctuation frequency algorithm unit and the daily average power consumption algorithm unit are avg Substitute them together into the electricity risk assessment value algorithm unit to calculate the electricity risk assessment value R; The risk assessment value of electricity consumption R comprehensively considers the seasonal characteristics S of household electricity consumption. c 、The proportion of high-power electrical appliances ratio , daily average electricity consumption D avg As well as multiple influencing factors such as voltage fluctuation rate V, it fully reflects the actual situation and potential risks of household electricity consumption. According to the different electricity consumption risk assessment values ​​R calculated for each household, the monitored households are divided into three intervals: Households with an electricity risk assessment value R less than Y1 are classified into interval 1. Household electricity use in interval 1 is within the safe electricity use range; Households with a power risk assessment value R greater than Y1 and less than Y2 are classified into interval 2. The power safety in interval 2 is within the warning range. The power supply bureau will reduce the output voltage of the household to remind the household that the total voltage load of the electrical appliances used is too large. Households with a power consumption risk assessment value R greater than the danger threshold Y2 are classified into interval 3. The power supply bureau will suspend power supply to households in interval 3 to avoid power accidents caused by excessive power load. In summary, through the different electricity risk assessment values ​​R calculated for each household, the power supply bureau can accurately judge the electricity safety of each household and take corresponding safety measures for households with higher electricity risk assessment values ​​R. When taking safety measures such as cutting off power or reducing output voltage, it will not affect other households in the residential area, ensuring the pertinence and effectiveness of electricity safety monitoring.

[0024] It is worth noting that the present invention can also determine different monitoring frequencies for different households according to the actual situation and potential risks of household electricity consumption. Under limited monitoring resources, the monitoring frequency F is calculated by the monitoring frequency adjustment formula in the monitoring frequency algorithm unit. m , optimize the allocation of monitoring resources. For households with high electricity consumption and high risks, increase the monitoring frequency to ensure electricity safety, and for households with low electricity consumption and low electricity risks, appropriately reduce the monitoring frequency to save resources; That is, a more scientific and reasonable electricity safety monitoring allocation strategy can be formulated for electricity safety monitoring methods to improve the monitoring efficiency of electricity safety monitoring and reduce monitoring costs.

[0025] Embodiment 2: The calculation processing module includes a voltage fluctuation frequency algorithm unit, a daily average power consumption algorithm unit, a power consumption risk assessment value algorithm unit and a monitoring frequency algorithm unit.

[0026] See also Figure 1 to Figure 2 , the voltage fluctuation frequency algorithm unit is as follows: ;

[0027] in: V represents the voltage fluctuation frequency; △P represents the absolute value of the instantaneous change in voltage load; it is obtained by calculating the difference between the grid load at two adjacent monitoring time points. Since the load may increase or decrease, the absolute value is taken to represent the magnitude of the load change; P prev Represents the average load of household electricity consumption. The load data is obtained from the load monitoring system of the power grid. Z represents the total impedance of the power grid; it is the total impedance of the household power distribution system, which is obtained through the power consumption monitoring system of the power grid in the power supply bureau. The value of Z will change according to the different household appliances installed in each family, that is, the more household appliances there are in the family, the larger the value of Z will be; E represents the power regulation rate; it is calculated by (rated output voltage - no-load output voltage) / rated output voltage × 100%, where: The rated output voltage of household electricity is usually 220 volts. The no-load output voltage is the voltage output when the appliance is not in use, that is, when the load is 0. It is obtained through the power consumption monitoring system of the power grid in the power supply bureau. Similarly, the value of the no-load output voltage will also change depending on the different household appliances installed in each family. α is the voltage fluctuation adjustment factor, and its value will be adjusted automatically as the power safety monitoring is carried out.

[0028] “ "This part represents the relative amplitude of load change in the formula calculation. This ratio reflects the degree of fluctuation of household electricity load at a certain moment relative to its average level. The larger the value, the greater the amplitude of load change, that is, the household electricity load has experienced a large increase or decrease in a short period of time. This value will have a positive impact on the calculation of voltage fluctuation frequency V; “ "This part in the formula calculation represents the response capability of the household power distribution system, i.e. the household power grid, to load changes. Specifically: Divide the total grid impedance Z by the power regulation rate E. The larger the ratio, the weaker the household power distribution system's ability to respond to load changes, which will make the voltage fluctuation frequency V larger. Conversely, the smaller the ratio, the stronger the grid's ability to respond, and the smaller the voltage fluctuation frequency V.

[0029] In summary, the voltage fluctuation rate V calculated by the voltage fluctuation frequency algorithm unit, as an important indicator of electricity risk assessment, can directly reflect the response capability of the household power distribution system to load changes and the degree of voltage fluctuation. By real-time monitoring and calculation of the voltage fluctuation rate V, the safety status of household electricity consumption can be accurately assessed, potential voltage instability problems can be discovered in time, and strong data support can be provided for electricity safety monitoring.

[0030] Based on the calculation results of the voltage fluctuation rate V, the power supply bureau can assign staff to visit households with higher voltage fluctuation rates to formulate more scientific and reasonable electricity safety strategies, such as adding voltage stabilizing equipment, optimizing electricity use plans and other measures to reduce the impact of voltage fluctuations on household electrical equipment and improve the safety of electricity use.

[0031] See also Figure 1 to Figure 2 , the daily average electricity consumption algorithm unit is as follows:

[0032] in: D avg Represents the average daily electricity consumption, in degrees; D i represents the electricity consumption on the i-th day; n is the total number of days in the monitoring time range.

[0033] The daily average power consumption D calculated by the daily average power consumption algorithm unit avg On the one hand, it is the most direct parameter to measure the risk assessment value of household electricity consumption. On the other hand, it can also help the power supply bureau's electricity consumption monitoring system to identify the daily electricity consumption characteristics of different households, such as by comparing different D avg The value can reveal the user's daily electricity consumption characteristics. This identification helps the monitoring system to more accurately predict the user's electricity consumption trends, thereby providing users with more personalized electricity consumption recommendations and safety warnings.

[0034] See also Figure 1 to Figure 2 , the daily average power consumption algorithm unit is as follows: The electricity risk assessment value algorithm unit is as follows: ;

[0035] in: R represents the electricity risk assessment value; it is used to indicate the safety risk level of the current electricity system.

[0036] V represents the voltage fluctuation rate; H ratio Represents the proportion of high-power electrical appliances, which indicates the ratio of the power consumption of high-power electrical appliances to the total power consumption. Electrical appliances that use more than 220 volts AC and more than 1200W are defined as high-power electrical appliances. D avg represents the average daily electricity consumption; H f represents the historical failure rate, which indicates the frequency of power system failures in the past year. It is obtained by obtaining the number of power failures in the past year from the failure information of the power monitoring system of the power grid in the power supply bureau and dividing it by 100. S c Represents the seasonal characteristic coefficient, indicating the impact of the current season on the power safety risk; the specific algorithm formula is as follows: ;

[0037] in: Q s is the total electricity consumption in the current quarter; Q a is the total electricity consumption for a year; β is an adjustment factor used to further adjust the electricity consumption according to seasonal characteristics. It will adjust itself as the electricity safety monitoring is carried out to reflect the relative changes in electricity consumption in different seasons. For example, in the summer and winter when electricity consumption is high, β will increase according to the electricity safety monitoring, while in the spring and autumn when electricity consumption is low, β will decrease according to the electricity safety monitoring. The warning threshold value Y1 of the electricity consumption risk assessment value is set to 0.6, and the danger threshold value Y2 of the electricity consumption risk assessment value is set to 0.8.

[0038] In the calculation formula of the electricity risk assessment value R: The proportion of electricity consumption of high-power electrical appliances ratio And the average daily electricity consumption D avg The size of will directly affect the calculation of the power consumption risk assessment value R. The average power consumption on that day is D avg Or the proportion of electricity used by high-power electrical appliances H ratio When it is higher, the electricity risk assessment value R will also increase accordingly; Section characteristic coefficient S c It reflects the impact of different seasons on electricity demand. For example, in summer, due to high temperatures, the electricity consumption of refrigeration equipment such as air conditioners will increase significantly; in winter, due to low temperatures, the electricity consumption of heating equipment such as heaters will also increase. In the calculation formula, the change of seasonal characteristic coefficient will also have a direct impact on the electricity risk assessment value R. That is, in the peak season of electricity consumption, the seasonal characteristic coefficient S c The higher the power consumption risk assessment value R is, the higher the power consumption risk assessment value R will be. c In summer or winter when the value is higher, the increase in peak electricity consumption during household electricity consumption increases the load on the power grid.

[0039] The voltage fluctuation rate V calculated by the voltage fluctuation frequency algorithm unit can directly reflect the response capability of the household power distribution system to load changes and the degree of voltage fluctuation. As an important indicator for calculating the power risk assessment value R, the size of the V value will have a positive impact on the power risk assessment value R.

[0040] Historical failure rate H f : Indicates the frequency of power failures that occurred in the past period of time. The level of historical failure rate can reflect the stability and safety of the power environment. The historical failure rate H f The increase in the value will also increase the electricity risk assessment value R, because for areas or households with a high historical failure rate, their electricity environment may have potential safety hazards, so a higher electricity risk assessment value R is needed to provide early warning of electricity safety.

[0041] The electricity risk assessment values ​​R calculated for different households are recorded and stored in the database, and compared with the warning threshold Y1 and the danger threshold Y2; The households with the risk assessment value of electricity consumption R less than Y1 are classified into interval 1. The household electricity consumption in interval 1 is within the safe electricity consumption range; Households with a power risk assessment value R greater than Y1 and less than Y2 are classified into interval 2. The power safety in interval 2 is within the warning range. The power supply bureau will reduce the output voltage of the household. The reduced output voltage directly affects the household's power consumption and is directly reflected in the dimming of the lights, reminding the household that the total voltage load of the electrical appliances used is too large. Electricity users whose electricity risk assessment value R is greater than the danger threshold Y2 will be classified into interval three. The power supply bureau will directly suspend power supply to electricity users in interval three to avoid power accidents caused by excessive electricity load.

[0042] In summary, through the different electricity risk assessment values ​​R calculated for each household, the power supply bureau can accurately judge the electricity safety of each household and take corresponding safety measures for households with higher electricity risk assessment values ​​R. When taking safety measures such as cutting off power or reducing output voltage, it will not affect other households in the residential area, ensuring the pertinence and effectiveness of electricity safety monitoring.

[0043] See also Figure 1 to Figure 2 , the monitoring frequency adjustment formula in the monitoring frequency algorithm unit is as follows: ;

[0044] in: F m represents the adjusted number of monitoring times per day; F base Represents the number of basic monitoring times per day; the basic monitoring frequency is once every two hours, 12 times a day; T max Represents the electricity consumption in the hour with the highest electricity consumption in a day; T min Represents the electricity consumption during the hour with the least electricity consumption in a day; At the monitoring frequency F m The calculation formula comprehensively considers seasonal characteristics, the proportion of high-power electrical appliances, the average daily power consumption, and the voltage fluctuation rate to fully reflect the actual situation and potential risks of household electricity consumption. The monitoring frequency F is calculated m , can optimize the allocation of monitoring resources. For households with high electricity consumption and high risks, the monitoring frequency can be increased to ensure electricity safety. For households with low electricity consumption and low risks, the monitoring frequency can be appropriately reduced to save resources. It can also formulate a more scientific and reasonable electricity safety monitoring allocation strategy for electricity safety monitoring methods to improve the monitoring efficiency of electricity safety monitoring and reduce monitoring costs.

[0045] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for monitoring electricity safety based on daily electricity consumption characteristics, characterized in that: The method comprises the following steps: Information data collection; The electricity safety monitoring method specifically includes: Substitute the decoded parameter values ​​into the voltage fluctuation frequency algorithm unit and the daily average power consumption algorithm unit to calculate the voltage fluctuation frequency V and the daily average power consumption D avg , two parameters that have an important impact on the electricity risk assessment value R; Next, the calculated voltage fluctuation frequency V and daily average power consumption D avg Substitute them together into the electricity risk assessment value algorithm unit to calculate the electricity risk assessment value R; Afterwards, the calculated power consumption risk assessment value R is recorded and stored in the database, the warning threshold value Y1 of the power consumption risk assessment value is set to 0.6, the danger threshold value Y2 of the power consumption risk assessment value is set to 0.8, and the comprehensive score value H of the software system is compared with the warning threshold value Y1 and the danger threshold value Y2; The households with the risk assessment value of electricity consumption R less than Y1 are classified into interval 1. The household electricity consumption in interval 1 is within the safe electricity consumption range; Households with a power risk assessment value R greater than Y1 and less than Y2 are classified into interval 2. The power safety in interval 2 is within the warning range. The power supply bureau will reduce the output voltage of the household. The reduced output voltage directly affects the household's power consumption and is directly reflected in the dimming of the lights, reminding the household that the total voltage load of the electrical appliances used is too large. The households with a power consumption risk assessment value R greater than the danger threshold Y2 are classified into interval 3. The power supply bureau will directly suspend power supply to households in interval 3 to avoid power accidents caused by excessive power load. Finally, provide feedback and make adjustments.

2. The method for monitoring electricity safety based on daily electricity consumption characteristics according to claim 1, characterized in that: The information data collection specifically includes: Obtain the load value P at the monitoring time point, the total impedance Z in the household power distribution system, and the total number of power system failures in the past year from the power consumption monitoring system of the power supply bureau; Data preprocessing: the load value P collected at the monitoring time point and the total impedance Z in the household power distribution system are transmitted to the data processing module for decoding preprocessing to obtain the number of monitoring times F. m And the important parameters of the electricity risk assessment value R; The feedback and adjustments specifically include: Substitute the decoded parameter value into the monitoring frequency adjustment formula to calculate the different monitoring times F for different electricity-consuming households per day. m Times, according to the different electricity usage situations of different households, change the number of daily electricity safety monitoring times, and make more appropriate resource allocation for electricity safety monitoring of different households.

3. The method for monitoring electricity safety based on daily electricity consumption characteristics according to claim 2, characterized in that: The electricity safety monitoring method is operated by using an information data collection module, a data preprocessing module, a calculation processing module and a data storage module.

4. The method for monitoring electricity safety based on daily electricity consumption characteristics according to claim 3 is characterized in that: The calculation and processing module includes a voltage fluctuation frequency algorithm unit, a daily average power consumption algorithm unit, a power consumption risk assessment value algorithm unit and a monitoring frequency algorithm unit.

5. The method for monitoring electricity safety based on daily electricity consumption characteristics according to claim 4 is characterized in that: The voltage fluctuation frequency algorithm unit is as follows: ； in: V represents the voltage fluctuation frequency; △P represents the instantaneous change of voltage load; P prev Represents the average load of household electricity; Z represents the total impedance of the power grid; E represents the power regulation rate; α is the voltage fluctuation adjustment factor.

6. The method for monitoring electricity safety based on daily electricity consumption characteristics according to claim 5, characterized in that: The daily average power consumption algorithm unit is as follows: ； in: D avg Represents the average daily electricity consumption, in degrees; D i represents the electricity consumption on the i-th day; n is the total number of days in the monitoring time range.

7. The method for monitoring electricity safety based on daily electricity consumption characteristics according to claim 6, characterized in that: The electricity risk assessment value algorithm unit is as follows: ； in: R represents the risk assessment value of electricity use; V represents the voltage fluctuation rate; H ratio Represents the proportion of electricity used by high-power electrical appliances; D avg represents the average daily electricity consumption; H f represents the historical failure rate; S c Represents the seasonal characteristic coefficient; indicates the degree of influence of the current season on the power safety risk; the specific algorithm formula is as follows: ； in: Q s is the total electricity consumption in the current quarter; Q a is the total electricity consumption for a year; β is an adjustment factor.

8. The Fmax software product information management system based on big data according to claim 6 is characterized by: The monitoring frequency adjustment formula in the monitoring frequency algorithm unit is as follows: ； in: F m represents the adjusted number of monitoring times per day; F base Represents the number of basic monitoring times per day; usually once every two hours, 12 times a day; T max Represents the electricity consumption in the hour with the highest electricity consumption in a day; T min Represents the electricity consumption during the hour with the least electricity consumption in a day.

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