A power consumption safety monitoring method based on daily power consumption characteristics

Abstract

The application discloses a kind of based on daily power consumption characteristics electric safety monitoring method, it is related to power protection technical field, consider the seasonal characteristics S c , high-power electrical appliances proportion H ratio , daily average power consumption D avg And voltage fluctuation rate V and multiple influence factors such as calculation of the power consumption risk assessment value R of different families, compared with early warning threshold Y1 And dangerous threshold Y2 It is compared with three intervals to monitor family, and corresponding safety measures are taken to the power consumption risk assessment value R in higher interval power consumption family, and can optimize the allocation of monitoring resources under limited monitoring resources, for the power consumption of high risk, increase monitoring frequency, ensure power consumption safety, and for the power consumption of small, reduce monitoring frequency, save resources, for power consumption safety monitoring method more scientific and reasonable power consumption safety monitoring distribution strategy is formulated, improve the monitoring efficiency of power consumption safety monitoring.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power protection, in particular to a power safety monitoring method based on daily power consumption characteristics. BACKGROUND

[0002] At present, the power supply bureau can only increase the monitoring frequency of power consumption safety for households with more power consumption when monitoring the power consumption safety of households, ignoring the influence of voltage fluctuation frequency, the proportion of high-power electrical appliances in households and different seasons on power consumption safety. In order to ensure the safe power consumption of households, the above problems also need to be considered in the monitoring frequency of household power consumption safety. Moreover, when the power supply bureau monitors that the voltage load of household power consumption is too high, it will directly take the protection measure of tripping. For residential areas where multiple households share one power meter, direct tripping will simultaneously affect the power consumption of multiple households, which is not conducive to use. In view of the above problems, the present application provides a power safety monitoring method based on daily power consumption characteristics. SUMMARY

[0003] The present application aims to provide a power safety monitoring method based on daily power consumption characteristics, which solves the problems raised in the background art.

[0004] To achieve the above-mentioned purpose, the present application provides the following technical solution: a power safety monitoring method based on daily power consumption characteristics, the method comprising the following steps:

[0005] Information data collection, specifically including:

[0006] Obtaining the load value P at the monitoring time point, the total impedance Z in the household power distribution system and the total number of faults of the power consumption system in the past year in the power consumption monitoring system of the power supply bureau power grid;

[0007] Data preprocessing, transmitting the collected load value P at the monitoring time point and the total impedance Z in the household power distribution system to the data processing module for decoding preprocessing to obtain the important parameters of the monitoring frequency F and the power consumption risk assessment value R; m

[0008] The power safety monitoring method specifically includes:

[0009] Substituting the parameter values obtained after decoding 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 , which are two important parameters affecting the power consumption risk assessment value R;

[0010] Then, the calculated voltage fluctuation frequency V and daily average power consumption D avg ​The values are substituted into the power consumption risk assessment value calculation unit to calculate the power consumption risk assessment value R;

[0011] The calculated power consumption risk assessment value R is recorded and stored in the database, the early warning threshold Y1 of the power consumption risk assessment value is set to 0.6, the dangerous threshold Y2 of the power consumption risk assessment value is set to 0.8, and the software system comprehensive score value H is compared with the early warning threshold Y1 and the dangerous threshold Y2;

[0012] The power consumption family with the power consumption risk assessment value R less than Y1 is classified into interval one, and the power consumption of the family in the interval one represents the safe power consumption range;

[0013] The power consumption family with the power consumption risk assessment value R greater than Y1 and less than Y2 is classified into interval two, and the power consumption safety in the interval two represents the alert range, the power supply bureau will reduce the output voltage of the family, the reduced output voltage directly affects the power consumption of the family, and directly reflects the dimming of the light, reminding the power consumption family that the total voltage load of the electrical appliances used is too large;

[0014] The power consumption family with the power consumption risk assessment value R greater than the dangerous threshold Y2 is classified into interval three, and the power supply bureau will directly suspend the power transmission to the power consumption family in the interval three to avoid power accidents caused by excessive power consumption load;

[0015] Feedback and adjustment, specifically including:

[0016] The parameter value obtained after decoding is substituted into the monitoring frequency adjustment formula to calculate the different monitoring frequencies F of different power consumption families per day m times, according to different power consumption situations of different families, the power consumption safety monitoring times per day are changed, and more suitable resource allocation is made for power consumption safety monitoring of different families.

[0017] Optionally, the power consumption safety monitoring method adopts an information data collection module, a data preprocessing module, a calculation processing module, and a data storage module.

[0018] Optionally, 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.

[0019] Optionally, the voltage fluctuation frequency algorithm unit is as follows:

[0020] ;

[0021] Wherein:

[0022] V represents the voltage fluctuation frequency;

[0023] △P represents the voltage load instantaneous change amount;

[0024] P prev represents the average load of household electricity;

[0025] Z represents the total impedance of the power grid;

[0026] E represents the power supply regulation rate;

[0027] α is the voltage fluctuation adjustment factor.

[0028] Optionally, the daily average electricity consumption algorithm unit is as follows:

[0029] ;

[0030] wherein:

[0031] D avg represents the daily average electricity consumption, in degree;

[0032] D i represents the electricity consumption of the i-th day;

[0033] n is the total number of days in the monitoring time range.

[0034] Optionally, the electricity risk assessment value algorithm unit is as follows:

[0035] ;

[0036] wherein:

[0037] R represents the electricity risk assessment value;

[0038] V represents the voltage fluctuation rate;

[0039] H ratio represents the electricity consumption proportion of high-power electrical appliances;

[0040] D avg represents the daily average electricity consumption;

[0041] H f represents the historical failure rate;

[0042] S c represents the seasonal characteristic coefficient; indicates the influence degree of the current season on the electricity safety risk; the specific algorithm formula is as follows:

[0043] ;

[0044] wherein:

[0045] Q s is the total electricity consumption of the current quarter;

[0046] Q a is the total electricity consumption of the year;

[0047] β is an adjustment factor.

[0048] Optionally, the monitoring frequency adjustment formula in the monitoring frequency algorithm unit is as follows:

[0049]

[0050] Wherein:

[0051] F m represents the adjusted daily monitoring frequency;

[0052] F base represents the basic daily monitoring frequency; usually twice an interval, 12 times a day;

[0053] T max represents the power consumption in the hour with the most power consumption in a day;

[0054] T min represents the power consumption in the hour with the least power consumption in a day.

[0055] Optionally, the early warning threshold Y1 of the power consumption risk assessment value is set to 0.6, and the dangerous threshold Y2 of the power consumption risk assessment value is set to 0.8.

[0056] Compared with the prior art, the present application has the following beneficial effects:

[0057] Firstly, the present application forms the core architecture of the power consumption safety monitoring method based on daily power consumption characteristics through the mutual cooperation of the four algorithm units, and in the power consumption safety monitoring, the power consumption risk assessment value R of different families is calculated by comprehensively considering the seasonal characteristics S c , the high-power appliance proportion H ratio , the daily average power consumption D avg and the voltage fluctuation rate V and other influencing factors, fully reflecting the actual situation and potential risks of family power consumption, and according to the comparison of the different power consumption risk assessment value R calculated for each family with the early warning threshold Y1 and the dangerous threshold Y2, the monitoring families are divided into three intervals, so as to accurately judge the power consumption safety of each power consumption family, and take corresponding safety measures for the power consumption family with high power consumption risk assessment value R, which will not affect other power consumption families in the residential area when taking safety measures such as power failure or reducing output voltage, ensuring the pertinence and effectiveness of power consumption safety monitoring.

[0058] Secondly, the present application determines different monitoring frequencies for different families according to the actual situation and potential risks of family power consumption, so as to calculate the different monitoring frequencies F m ​, the allocation of monitoring resources is optimized, for the high-risk high-power consumption family, increase the monitoring frequency, ensure the safety of electricity, and for the low-risk low-power consumption family, appropriately reduce the monitoring frequency, save resources, and make more scientific and reasonable power safety monitoring allocation strategy for the power safety monitoring method, improve the monitoring efficiency of power safety monitoring, and reduce the monitoring cost. BRIEF DESCRIPTION OF DRAWINGS

[0059] Figure 1 A flowchart of a power safety monitoring method based on daily power consumption characteristics;

[0060] Figure 2 A schematic diagram of the overall structure of a power safety monitoring method based on daily power consumption characteristics. DETAILED DESCRIPTION

[0061] The technical solutions in the embodiments of the present application will be described in detail below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0062] Embodiment one: please refer to Figure 1 and Figure 2 The present application provides a technical solution: a power safety monitoring method based on daily power consumption characteristics, the method comprising the following steps:

[0063] Information data collection, specifically including:

[0064] Obtain the load value P of the monitoring time point, the total impedance Z in the household power distribution system and the total number of faults in the power system in the past year in the power supply bureau power grid monitoring system;

[0065] Data preprocessing, the collected load value P and total impedance Z in the household power distribution system are transmitted to the data processing module for decoding preprocessing, and the important parameters affecting the monitoring frequency F m and the power risk assessment value R are obtained;

[0066] The power safety monitoring method specifically includes:

[0067] The parameter values obtained after decoding are substituted 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 important to the power risk assessment value R;

[0068] Then, the calculated voltage fluctuation frequency V and daily average power consumption Davg together into the power consumption risk assessment value algorithm unit, and a power consumption risk assessment value R is calculated;

[0069] Afterwards, the calculated power consumption risk assessment value R is recorded and stored in a database, a warning threshold Y1 of the power consumption risk assessment value is set as 0.6, a danger threshold Y2 of the power consumption risk assessment value is set as 0.8, and the software system comprehensive score value H is compared with the warning threshold Y1 and the danger threshold Y2;

[0070] The power consumption family with the power consumption risk assessment value R less than Y1 is classified into interval one, and the power consumption of the family in the interval one is represented in the safe power consumption range;

[0071] The power consumption family with the power consumption risk assessment value R greater than Y1 and less than Y2 is classified into interval two, and the power consumption safety in the interval two is represented in the alert range, and the power supply bureau will reduce the output voltage of the family, the reduced output voltage directly affects the power consumption of the family, and directly reflects the light darkening, reminding the total voltage load of the electrical appliances used by the power consumption family is too large;

[0072] The power consumption family with the power consumption risk assessment value R greater than the danger threshold Y2 is classified into interval three, and the power supply bureau will directly suspend the power transmission to the power consumption family in the interval three, to avoid the power accidents caused by the too large power consumption load;

[0073] Feedback and adjustment, the parameter values obtained after decoding are substituted into the monitoring frequency adjustment formula, and the different monitoring frequencies F of different power consumption families per day are calculated m times, according to the different power consumption conditions of different families, the power consumption safety monitoring times per day are changed, and more suitable resource allocation is made for the power consumption safety monitoring of different families.

[0074] The power consumption safety monitoring method adopts an information data collection module, a data preprocessing module, a calculation processing module and a data storage module.

[0075] In the embodiment, the present application jointly constitutes the core architecture of the power consumption safety monitoring method based on the daily power consumption characteristics through the mutual cooperation of the four algorithm units, and the voltage fluctuation frequency V and the daily average power consumption D avg calculated by the voltage fluctuation frequency algorithm unit and the daily average power consumption algorithm unit are together substituted into the power consumption risk assessment value algorithm unit to obtain the power consumption risk assessment value R;

[0076] The power consumption risk assessment value R comprehensively considers the seasonal characteristics S c , the high-power electrical appliance proportion H ratio , and the daily average power consumption D avgand the voltage fluctuation rate V multiple influencing factors, fully reflect the actual situation and potential risk of household electricity, according to the different electricity risk assessment value R calculated for each household, the monitoring family is divided into three intervals:

[0077] The electricity risk assessment value R is less than Y1, and the electricity of the electricity family is classified into interval one, and the household electricity in the interval one represents the safe electricity range;

[0078] The electricity risk assessment value R is greater than Y1 and less than Y2, and the electricity of the electricity family is classified into interval two, and the electricity safety in the interval two is in the warning range, and the power supply bureau will reduce the output voltage of the family, reminding the total voltage load of the electric appliance used by the electricity family;

[0079] The electricity risk assessment value R is greater than the danger threshold Y2, and the electricity of the electricity family is classified into interval three, and the power supply bureau will suspend the power transmission to the electricity family in the interval three, to avoid the power accident caused by the excessive electricity load;

[0080] In summary, through the different electricity risk assessment value R calculated for each household, the power supply bureau can accurately judge the electricity safety of each electricity family, and take corresponding safety measures for the electricity family with high electricity risk assessment value R, and when taking safety measures such as power failure or reducing output voltage, other electricity families in the residential area will not be affected, ensuring the pertinence and effectiveness of the electricity safety monitoring.

[0081] It is worth noting that the present application can also determine the different monitoring frequencies of different families through the actual situation and potential risk of household electricity, and through the monitoring frequency adjustment formula in the monitoring frequency algorithm unit, the monitoring frequency F m is calculated, the distribution of monitoring resources is optimized, the monitoring frequency of the electricity family with large electricity consumption and high risk is increased to ensure the electricity safety, and the monitoring frequency of the electricity family with small electricity consumption and low electricity risk is appropriately reduced to save resources;

[0082] That is, a more scientific and reasonable electricity safety monitoring distribution strategy can be made for the electricity safety monitoring method, so as to improve the monitoring efficiency of the electricity safety monitoring and reduce the monitoring cost.

[0083] Embodiment two: the calculation processing module comprises a voltage fluctuation frequency algorithm unit, a daily average electricity consumption algorithm unit, an electricity risk assessment value algorithm unit and a monitoring frequency algorithm unit.

[0084] Please refer to Figures 1 to 2 , the voltage fluctuation frequency algorithm unit is as follows:

[0085] ;

[0086] Among them:

[0087] V represents the voltage fluctuation frequency;

[0088] △P represents the absolute value of the instantaneous change of the voltage load, which is obtained by calculating the difference between the adjacent two monitoring time points of the grid load. Since the load may increase or decrease, the absolute value is taken to represent the amplitude of the load change;

[0089] P prev represents the average load of household electricity, and the load data is obtained from the load monitoring system of the power grid;

[0090] Z represents the total impedance of the power grid; it is the total impedance of the household power distribution system, which is obtained from the load monitoring system of the power grid in the power supply bureau. According to the different household appliances installed in each household, the value of Z will change, that is, the more household appliances in the household, the larger the value of Z;

[0091] E represents the power adjustment rate; it is calculated by (rated output voltage-no load output voltage) / rated output voltage × 100%, wherein:

[0092] The rated output voltage of household electricity is usually 220 volts, and the no-load output voltage is the voltage output when no appliances are used, that is, the load is 0. It is obtained from the load monitoring system of the power grid in the power supply bureau. Similarly, according to the different household appliances installed in each household, the value of the no-load output voltage will also change;

[0093] α is the voltage fluctuation adjustment factor, which will be self-adjusted with the progress of the electricity safety monitoring.

[0094] This part represents the relative amplitude of the load change in the formula calculation. This ratio reflects the degree of fluctuation of the household electricity load at a certain moment relative to its average level. The larger the value, the greater the amplitude of the load change, that is, the household electricity load experiences a large increase or decrease in a short period of time. This value will have a positive effect on the calculation of the voltage fluctuation frequency V;

[0095] This part in the formula calculation represents the response ability of the household power distribution system, that is, the household power grid to the load change. Specifically:

[0096] The larger the ratio obtained by dividing the total impedance of the power grid Z by the power adjustment rate E, the weaker the response ability of the household power distribution system to the load change, which will make the voltage fluctuation frequency V larger; on the contrary, the smaller the ratio, the stronger the response ability of the power grid, and the smaller the voltage fluctuation frequency V.

[0097] ​​In summary, the voltage fluctuation rate V calculated by the voltage fluctuation frequency algorithm unit serves as an important indicator of the power consumption risk assessment value, which can directly reflect the response ability of the household power distribution system to load changes and the degree of voltage fluctuation. By monitoring and calculating the voltage fluctuation rate V in real time, the safety status of household power consumption can be accurately assessed, and potential voltage instability problems can be discovered in a timely manner, providing strong data support for power consumption safety monitoring.

[0098] According to the calculation result of the voltage fluctuation rate V, the power supply bureau can assign staff to visit households with high voltage fluctuation rates to develop more scientific and reasonable power consumption safety strategies, such as increasing voltage stabilizing equipment, optimizing power consumption plans, etc., to reduce the impact of voltage fluctuations on household power consumption equipment and improve the safety of power consumption.

[0099] Please refer to Figures 1 to 2 , the daily average power consumption algorithm unit is as follows:

[0100]

[0101] Where:

[0102] D avg represents the daily average power consumption, unit: degree;

[0103] D i represents the power consumption of the i-th day;

[0104] n is the total number of days in the monitoring time range.

[0105] The daily average power consumption D avg calculated by the daily average power consumption algorithm unit, on the one hand, serves as a parameter that can most directly measure the household power consumption risk assessment value, and on the other hand, can help the power consumption monitoring system of the power supply bureau to identify the daily power consumption characteristics of different power consumption households. For example, by comparing different D avg values in different time periods (such as weekdays and weekends), the user's daily power consumption characteristics can be revealed. This identification helps the monitoring system more accurately predict the user's power consumption trend, thereby providing more personalized power consumption recommendations and safety warnings for users.

[0106] Please refer to Figures 1 to 2 , the daily average power consumption algorithm unit is as follows:

[0107] The power consumption risk assessment value algorithm unit is as follows:

[0108] ;

[0109] Where:

[0110] R represents the power consumption risk assessment value; used to represent the safety risk level of the current power consumption system.

[0111] V represents the voltage fluctuation rate;

[0112] H ratio represents the proportion of high-power electrical appliances, indicating the ratio of the power consumption of high-power electrical appliances to the total power consumption, and defines the use of electrical appliances with more than 220 volts of alternating current and more than 1200W as high-power electrical appliances;

[0113] D avg represents the daily average power consumption;

[0114] H f represents the historical failure rate, indicating the frequency of power system failures in the past year, and is obtained by dividing the number of power failures in the past year obtained from the failure information of the power grid monitoring system in the power supply bureau by 100;

[0115] S c represents the seasonal characteristic coefficient, indicating the influence of the current season on the power safety risk; the specific algorithm formula is as follows:

[0116] ;

[0117] wherein:

[0118] Q s is the total power consumption of the current quarter;

[0119] Q a is the total power consumption of the year;

[0120] β is an adjustment factor for further adjusting the power consumption according to the seasonal characteristics, which will be adjusted automatically according to the power safety monitoring to reflect the relative changes of power consumption in different seasons, for example, in summer and winter with high power consumption, β will increase according to the power safety monitoring, while in spring and autumn with lower power consumption, β will decrease according to the power safety monitoring;

[0121] The warning threshold Y1 of the power risk assessment value is set to 0.6, and the danger threshold Y2 of the power risk assessment value is set to 0.8.

[0122] In the calculation formula of the power risk assessment value R:

[0123] the power consumption proportion H of high-power electrical appliances ratio and the daily average power consumption D avg will directly affect the calculation of the power risk assessment value R, when the daily average power consumption D avg or the power consumption proportion H of high-power electrical appliances ratio is high, the power risk assessment value R will also increase accordingly;

[0124] the seasonal characteristic coefficient S cReflects the influence of different seasons on electricity demand, for example, in summer due to high temperature, air conditioning and other refrigeration equipment electricity consumption will increase significantly; winter due to low temperature, heating and other heating equipment electricity consumption will also increase, in the calculation formula, the change of seasonal characteristic coefficient will directly affect the electricity risk assessment value R;

[0125] That is, in the peak season of electricity, the seasonal characteristic coefficient S c is higher, the electricity risk assessment value R will also increase, to represent in the summer or winter, the increase of the family electricity grid load in the peak time of electricity. c

[0126] The voltage fluctuation rate V calculated by the voltage fluctuation frequency algorithm unit can directly reflect the response ability of the household power distribution system to load change and the degree of voltage fluctuation, as an important indicator for calculating the electricity risk assessment value R, the value of V will have a positive effect on the electricity risk assessment value R.

[0127] The historical failure rate H f : indicates the frequency of electricity failure in the past period of time, the stability and safety of the electricity environment can be reflected by the historical failure rate, the increase of the historical failure rate H f value will also increase the electricity risk assessment value R, because for the area or family with high historical failure rate, there may be potential safety hazards in the electricity environment, so a higher electricity risk assessment value R is needed to warn the electricity safety.

[0128] The electricity risk assessment value R calculated for different families is recorded and stored in the database, and compared with the warning threshold Y1 and the danger threshold Y2;

[0129] The electricity risk assessment value R less than Y1 of the electricity family is classified to interval one, the electricity of the family in interval one represents in the safe electricity range;

[0130] The electricity risk assessment value R greater than Y1 and less than Y2 of the electricity family is classified to interval two, the electricity safety in interval two represents in the warning range, the power supply bureau will reduce the output voltage of the family, the reduced output voltage directly affects the electricity of the family, and directly reflects the light darkening, reminding the total voltage load of the electrical appliances used by the electricity family is too large;

[0131] The electricity risk assessment value R greater than the danger threshold Y2 of the electricity family is classified to interval three, the power supply bureau will directly suspend the power transmission to the electricity family in interval three, to avoid the power accident caused by the too large electricity load.

[0132] ​In summary, by calculating the different electricity risk assessment values R of each household, the power supply bureau can accurately judge the electricity safety of each household, and take corresponding safety measures for the household with a higher electricity risk assessment value R, without affecting other households in the residential area when taking safety measures such as power failure or reducing output voltage, ensuring the pertinence and effectiveness of electricity safety monitoring.

[0133] Please refer to Figures 1 to 2 The monitoring frequency adjustment formula in the monitoring frequency algorithm unit is as follows:

[0134] ;

[0135] Wherein:

[0136] F m represents the adjusted daily monitoring frequency;

[0137] F base represents the basic monitoring frequency per day; the basic monitoring frequency is twice an interval, 12 times a day;

[0138] T max represents the electricity consumption in the hour with the largest electricity consumption in a day;

[0139] T min represents the electricity consumption in the hour with the smallest electricity consumption in a day;

[0140] In the calculation formula of the monitoring frequency F m , the seasonal characteristics, the proportion of high-power electrical appliances, the daily average electricity consumption, and the voltage fluctuation rate are comprehensively considered to fully reflect the actual situation and potential risks of household electricity consumption. The monitoring frequency F m obtained by calculation can optimize the allocation of monitoring resources, increase the monitoring frequency for households with high electricity consumption and high risk, and ensure electricity safety, and appropriately reduce the monitoring frequency for households with low electricity consumption and low electricity risk to save resources. A more scientific and reasonable electricity safety monitoring distribution strategy can be developed for the electricity safety monitoring method to improve the monitoring efficiency of electricity safety monitoring and reduce the monitoring cost.

[0141] Although embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A power consumption safety monitoring method based on daily power consumption characteristics, characterized in that: The method comprises the following steps: information data collection; The power consumption safety monitoring method specifically comprises: The parameter value obtained after decoding is substituted 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 important influence on the power consumption risk assessment value R; Next, the calculated voltage fluctuation frequency V and the daily average power consumption D avg are input into the power consumption risk assessment value algorithm unit together, and the power consumption risk assessment value R is calculated. Then, the calculated power consumption risk assessment value R is recorded and stored in a database, the early warning threshold Y1 of the power consumption risk assessment value is set to 0.6, the dangerous threshold Y2 of the power consumption risk assessment value is set to 0.8, and the software system comprehensive score value H is compared with the early warning threshold Y1 and the dangerous threshold Y2; The power consumption household with the power consumption risk assessment value R less than Y1 is classified into interval one, and the power consumption of the household in the interval one indicates that the power consumption is within the safe power consumption range; The power consumption household with the power consumption risk assessment value R greater than Y1 and less than Y2 is classified into interval two, and the power consumption safety in the interval two indicates that the power consumption is within the alert range, the output voltage of the power supply bureau is reduced, the reduced output voltage directly affects the power consumption of the household, and the total voltage load of the electrical appliances used by the power consumption household is directly reflected in the dimming of the light, reminding the power consumption household that the total voltage load of the electrical appliances is too large; The power consumption household with the power consumption risk assessment value R greater than the dangerous threshold Y2 is classified into interval three, and the power supply bureau directly suspends the power supply to the power consumption household in the interval three to avoid power accidents caused by excessive power consumption load; Finally, feedback and adjustment are performed; The power consumption safety monitoring method comprises an information data collection module, a data preprocessing module, a calculation processing module, and a data storage module; The calculation processing module comprises 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; The voltage fluctuation frequency algorithm unit is as follows: ； Wherein: V represents the voltage fluctuation frequency; △P represents the voltage load instantaneous change amount; P prev representing the average load of the household electricity; Z represents the total impedance of the power grid; E represents the power source adjustment rate; α is the voltage fluctuation adjustment factor; The daily average power consumption algorithm unit is as follows: ； Wherein: D avg Represent the daily average electricity consumption, units of degrees; D i represents the power consumption on the i-th day; n is the total number of days in the monitoring time range; The power consumption risk assessment value algorithm unit is as follows: ； Wherein: R represents the power consumption risk assessment value; V represents the voltage fluctuation rate; H ratio The power consumption ratio representing a large-power electrical appliance; D avg represent the daily average power consumption; H f Representative historical failure rate; S c Representative seasonal characteristic coefficient; indicates the degree of influence of the current season on the safety risk of electricity use.

2. The method for monitoring the safety of electricity use based on daily electricity use characteristics according to claim 1, characterized in that: The information data collection specifically comprises: The load value P at the monitoring time point, the total impedance Z in the household power distribution system, and the total number of times of power system failures in the past year are obtained in the power consumption monitoring system of the power supply bureau power grid; 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 influence monitoring frequency F m and the important parameters of the power consumption risk assessment value R; The feedback and adjustment specifically comprise: The parameter value obtained after decoding is substituted into the monitoring frequency adjustment formula, and the different monitoring times F of different families per day are calculated m times, according to the different power consumption of different families, the power consumption safety monitoring times per day are changed, and more suitable resource allocation is performed on the power consumption safety monitoring of different families.

3. The power consumption safety monitoring method based on daily power consumption characteristics according to claim 1, characterized in that: S c The specific algorithm formula is as follows: ； Wherein: Q s is the total electricity consumption of the current quarter; Q a is the total electricity consumption for the year; β is an adjustment factor.

4. The method for monitoring the safety of electricity use based on daily electricity use characteristics according to claim 1, characterized in that: The monitoring frequency adjustment formula in the monitoring frequency algorithm unit is as follows: ; Wherein: F m represents the adjusted number of monitoring times per day; F base represents the number of basal monitoring per day; once for two time intervals, 12 times a day; T max represents the power consumption in the hour with the most power consumption in a day; T min represents the power consumption in the hour with the least power consumption in a day.

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