CN117093943A - Power consumption monitoring and early warning method and device - Google Patents
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Abstract
The embodiment of the invention discloses a power consumption monitoring and early warning method and device, comprising the following steps: responding to a data modeling instruction to acquire historical electricity utilization data of a user, generating an electricity utilization distribution curve based on the historical electricity utilization data, acquiring real-time electricity utilization data of a target object, and comparing whether the real-time electricity utilization data exceeds the range of the electricity utilization distribution curve; and calculating the numerical value of the real-time electricity consumption data exceeding the electricity consumption distribution curve range, and generating early warning information when the numerical value exceeds a set threshold value. In the embodiment, because the whole historical electricity utilization conditions of a plurality of users are fully considered, a certain target object is intelligently compared with the whole conditions, real-time electricity utilization data are collected, the electricity utilization condition of the current time period can be timely monitored and analyzed, and early warning can be timely carried out when abnormality exists.
Description
Technical Field
The invention relates to the technical field of electricity larceny prevention, in particular to a power consumption monitoring and early warning method and device.
Background
At present, losses caused by a series of fraudulent electricity utilization behaviors such as electricity larceny and fraud of power distribution side power consumers are collectively called Non-Technical Loss (NTL). The normal operation of the power grid can be seriously influenced by the non-technical loss, the normal scheduling of the regional power grid is disturbed, and even safety accidents can be caused by the fact that users change the circuit privately. The current situation of anti-electricity-theft still depends on the theoretical line loss calculation value of the typical day to carry out comparison analysis with the actual management line loss value, and loss reduction measures are further proposed; the traditional line loss management mode has various defects such as time dissynchronism, data inaccuracy and the like, cannot reflect the actual line loss state, and cannot provide more accurate anti-electricity-stealing and loss reduction measures. Users with different power utilization levels are generally separated in the same power supply station area, and the power utilization characteristics of different users are different. At present, the countermeasure against electricity larceny is often limited by adding detection hardware to an ammeter terminal, so as to help judge whether the operation speed of the ammeter is changed through magnetic equipment and the like, and the electricity larceny behavior of a user cannot be early warned in time by means of digital intelligent analysis.
Disclosure of Invention
Aiming at the defects, the embodiment of the invention discloses a power consumption monitoring and early warning method and device, which can be used for intelligently monitoring power consumption behaviors and timely early warning the power stealing behaviors.
The first aspect of the embodiment of the invention discloses a power consumption monitoring and early warning method, which comprises the following steps:
responding to a data modeling instruction to obtain historical electricity consumption data of a user, and generating an electricity consumption distribution curve based on the historical electricity consumption data, wherein the electricity consumption distribution curve comprises relations between different time periods and electricity consumption;
collecting real-time electricity utilization data of a target object, and comparing whether the real-time electricity utilization data exceeds the electricity utilization distribution curve range;
and calculating the value of the real-time electricity consumption data exceeding the electricity consumption distribution curve range, and generating early warning information when the value exceeds a set threshold value.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, generating the electricity usage distribution curve based on the historical electricity usage data includes:
dividing 24 hours into different time periods, and dividing historical electricity consumption data in one year into historical electricity consumption data corresponding to four seasons of spring, summer, autumn and winter according to local climate factors;
respectively counting historical electricity consumption data of different time periods every day in four seasons to obtain a maximum electricity consumption threshold value and a minimum electricity consumption threshold value of different time periods every day in different seasons;
connecting the maximum power consumption thresholds of different time periods in different seasons to draw a first curve, and connecting the minimum power consumption thresholds of different time periods in different seasons to draw a second curve;
and drawing and generating a power consumption distribution curve based on the first curve and the second curve.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, drawing a first curve with maximum power consumption threshold connections of different time periods in different seasons and drawing a second curve with minimum power consumption threshold connections of different time periods in different seasons includes:
setting a first coefficient and a second coefficient, wherein the first coefficient is larger than 1, and the second coefficient is smaller than 1;
based on formula d max *a 1 Generating an upper power threshold for the different time periods, and based on formula d min *a 2 Generating a lower power consumption threshold for the different time periods, wherein d max Is the maximum electricity consumption threshold value of different time periods, d min Is the minimum electricity consumption threshold value of different time periods, a 1 Is a first coefficient, a 2 Is a second coefficient;
and drawing a first curve according to the upper limit connection of the power consumption threshold values of different time periods in different seasons, and drawing a second curve according to the lower limit connection of the power consumption threshold values of different time periods in different seasons.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, generating the electricity usage distribution curve based on the historical electricity usage data includes:
dividing 24 hours into different time periods, and dividing historical electricity consumption data in one year into historical electricity consumption data corresponding to four seasons of spring, summer, autumn and winter according to local climate factors;
respectively counting historical electricity consumption data of different time periods every day in four seasons to obtain a maximum electricity consumption threshold value and a minimum electricity consumption threshold value of different time periods every day in different seasons;
acquiring historical electricity utilization data of other local users, and generating electricity utilization distribution ranges of different time periods every day in four seasons based on the historical electricity utilization data of the other users;
comparing whether the maximum electricity consumption threshold value and the minimum electricity consumption threshold value are in an electricity consumption distribution range, if so, generating an electricity consumption distribution curve based on the maximum electricity consumption threshold value and the minimum electricity consumption threshold value in different time periods, otherwise, correcting the maximum electricity consumption threshold value and the minimum electricity consumption threshold value based on the electricity consumption distribution range, and generating the electricity consumption distribution curve based on the corrected maximum electricity consumption threshold value and the minimum electricity consumption threshold value.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, correcting the maximum electricity consumption threshold and the minimum electricity consumption threshold based on the electricity consumption distribution range includes:
acquiring a distribution maximum value and a distribution minimum value in a power utilization distribution range in different time periods of different seasons;
and acquiring an intermediate value between the distribution maximum value and the maximum electricity consumption threshold as a corrected maximum electricity consumption threshold, and acquiring an intermediate value between the distribution minimum value and the minimum electricity consumption threshold as a corrected minimum electricity consumption threshold.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, generating the early warning information when the value exceeds the set threshold value includes:
when the value exceeds a first set threshold value and does not exceed a second set threshold value, acquiring historical electricity consumption information of a target object, generating a credit level of the target object based on the historical electricity consumption information, generating early warning information when the credit level of the target object is lower than a set standard, continuously monitoring whether real-time electricity consumption data of the target object in the next time period exceeds an electricity consumption distribution curve or not when the credit level of the target object is higher than the set standard, and generating early warning information when the real-time electricity consumption data of the next time period exceeds the electricity consumption distribution curve;
and when the value exceeds a second set threshold, directly generating early warning information.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the method further includes:
and continuously monitoring the real-time electricity utilization data of the target object, and marking the target object as an electricity stealing risk object when the real-time electricity utilization data of the target object exceeds the electricity utilization distribution curve range in the same time period of exceeding the electricity utilization distribution curve range on the next day and the current day.
The second aspect of the embodiment of the invention discloses a power consumption monitoring and early warning device, which is characterized by comprising:
a history curve generation module: responding to a data modeling instruction to obtain historical electricity consumption data of a user, and generating an electricity consumption distribution curve based on the historical electricity consumption data, wherein the electricity consumption distribution curve comprises relations between different time periods and electricity consumption;
the real-time electricity acquisition module is as follows: collecting real-time electricity utilization data of a target object, and comparing whether the real-time electricity utilization data exceeds the electricity utilization distribution curve range;
the early warning information generation module: and the method is used for calculating the numerical value of the real-time electricity consumption data exceeding the electricity consumption distribution curve range, and generating early warning information when the numerical value exceeds a set threshold value.
As an alternative implementation manner, in the second aspect of the embodiment of the present invention, generating a power consumption distribution curve based on the historical power consumption data includes:
dividing 24 hours into different time periods, and dividing historical electricity consumption data in one year into historical electricity consumption data corresponding to four seasons of spring, summer, autumn and winter according to local climate factors;
respectively counting historical electricity consumption data of different time periods every day in four seasons to obtain a maximum electricity consumption threshold value and a minimum electricity consumption threshold value of different time periods every day in different seasons;
connecting the maximum power consumption thresholds of different time periods in different seasons to draw a first curve, and connecting the minimum power consumption thresholds of different time periods in different seasons to draw a second curve;
and drawing and generating a power consumption distribution curve based on the first curve and the second curve.
As an optional implementation manner, in the second aspect of the embodiment of the present invention, the drawing the first curve with the maximum power consumption threshold connection of different time periods in different seasons and the drawing the second curve with the minimum power consumption threshold connection of different time periods in different seasons includes:
setting a first coefficient and a second coefficient, wherein the first coefficient is larger than 1, and the second coefficient is smaller than 1;
based on formula d max *a 1 Generating an upper power threshold for the different time periods, and based on formula d min *a 2 Generating a lower power consumption threshold for the different time periods, wherein d max Is the maximum electricity consumption threshold value of different time periods, d min Is the minimum electricity consumption threshold value of different time periods, a 1 Is a first coefficient, a 2 Is a second coefficient;
and drawing a first curve according to the upper limit connection of the power consumption threshold values of different time periods in different seasons, and drawing a second curve according to the lower limit connection of the power consumption threshold values of different time periods in different seasons.
As an alternative implementation manner, in the second aspect of the embodiment of the present invention, generating a power consumption distribution curve based on the historical power consumption data includes:
dividing 24 hours into different time periods, and dividing historical electricity consumption data in one year into historical electricity consumption data corresponding to four seasons of spring, summer, autumn and winter according to local climate factors;
respectively counting historical electricity consumption data of different time periods every day in four seasons to obtain a maximum electricity consumption threshold value and a minimum electricity consumption threshold value of different time periods every day in different seasons;
acquiring historical electricity utilization data of other local users, and generating electricity utilization distribution ranges of different time periods every day in four seasons based on the historical electricity utilization data of the other users;
comparing whether the maximum electricity consumption threshold value and the minimum electricity consumption threshold value are in an electricity consumption distribution range, if so, generating an electricity consumption distribution curve based on the maximum electricity consumption threshold value and the minimum electricity consumption threshold value in different time periods, otherwise, correcting the maximum electricity consumption threshold value and the minimum electricity consumption threshold value based on the electricity consumption distribution range, and generating the electricity consumption distribution curve based on the corrected maximum electricity consumption threshold value and the minimum electricity consumption threshold value.
As an alternative implementation manner, in the second aspect of the embodiment of the present invention, correcting the maximum electricity usage threshold value and the minimum electricity usage threshold value based on the electricity usage distribution range includes:
acquiring a distribution maximum value and a distribution minimum value in a power utilization distribution range in different time periods of different seasons;
and acquiring an intermediate value between the distribution maximum value and the maximum electricity consumption threshold as a corrected maximum electricity consumption threshold, and acquiring an intermediate value between the distribution minimum value and the minimum electricity consumption threshold as a corrected minimum electricity consumption threshold.
In a second aspect of the embodiment of the present invention, the generating the early warning information when the value exceeds the set threshold includes:
when the value exceeds a first set threshold value and does not exceed a second set threshold value, acquiring historical electricity consumption information of a target object, generating a credit level of the target object based on the historical electricity consumption information, generating early warning information when the credit level of the target object is lower than a set standard, continuously monitoring whether real-time electricity consumption data of the target object in the next time period exceeds an electricity consumption distribution curve or not when the credit level of the target object is higher than the set standard, and generating early warning information when the real-time electricity consumption data of the next time period exceeds the electricity consumption distribution curve;
and when the value exceeds a second set threshold, directly generating early warning information.
As an optional implementation manner, in the second aspect of the embodiment of the present invention, the method further includes:
and continuously monitoring the real-time electricity utilization data of the target object, and marking the target object as an electricity stealing risk object when the real-time electricity utilization data of the target object exceeds the electricity utilization distribution curve range in the same time period of exceeding the electricity utilization distribution curve range on the next day and the current day.
A third aspect of an embodiment of the present invention discloses an electronic device, including: a memory storing executable program code; a processor coupled to the memory; the processor invokes the executable program code stored in the memory to execute the electricity consumption monitoring and early warning method disclosed in the first aspect of the embodiment of the invention.
A fourth aspect of the embodiment of the present invention discloses a computer-readable storage medium storing a computer program, where the computer program causes a computer to execute the electricity consumption monitoring and early warning method disclosed in the first aspect of the embodiment of the present invention.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
according to the embodiment of the invention, the historical electricity consumption data of the users are obtained, so that the relation between different time periods and the electricity consumption is generated, then whether the real-time electricity consumption data of the target object exceeds the electricity consumption distribution curve is compared, whether early warning information is generated is determined according to the size of the exceeding electricity consumption distribution curve, and because the whole historical electricity consumption conditions of a plurality of users are fully considered, the intelligent comparison of a certain target object and the whole condition is carried out, the real-time electricity consumption data is collected, the monitoring analysis can be carried out on the electricity consumption condition of the current time period in time, and the early warning can be carried out in time when the abnormality exists.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a power consumption monitoring and early warning method disclosed in the embodiment of the invention;
FIG. 2 is a schematic flow chart of another method for monitoring and pre-warning power consumption according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of another method for monitoring and pre-warning power consumption according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a power consumption monitoring and early warning device according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that the terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present invention are used for distinguishing between different objects and not necessarily for describing a particular sequential or chronological order. The terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
The embodiment of the invention discloses a power consumption monitoring and early warning method, a device, electronic equipment and a storage medium, wherein in the embodiment, by acquiring historical power consumption data of users, the relation between different time periods and power consumption is further generated, then whether the real-time power consumption data of a target object exceeds a power consumption distribution curve is compared, whether early warning information is generated is further determined according to the size of the exceeding power consumption distribution curve, and because the whole historical power consumption conditions of a plurality of users are fully considered, intelligent comparison is carried out on a certain target object and the whole condition, the real-time power consumption data are acquired, the monitoring and analysis can be carried out on the power consumption condition of the current time period in time, and early warning can be carried out in time when the power consumption condition is abnormal.
Example 1
Referring to fig. 1, fig. 1 is a flow chart of a power consumption monitoring and early warning method according to an embodiment of the invention. The execution main body of the method described in the embodiment of the invention is an execution main body composed of software or/and hardware, and the execution main body can receive related information in a wired or/and wireless mode and can send a certain instruction. Of course, it may also have certain processing and storage functions. The execution body may control a plurality of devices, such as a remote physical server or cloud server and related software, or may be a local host or server and related software that performs related operations on a device that is located somewhere, etc. In some scenarios, multiple storage devices may also be controlled, which may be located in the same location or in different locations than the devices. As shown in fig. 1, the electricity consumption monitoring and early warning method includes the following steps:
101. and responding to the data modeling instruction to acquire historical electricity consumption data of the user, and generating an electricity consumption distribution curve based on the historical electricity consumption data, wherein the electricity consumption distribution curve comprises relations between different time periods and electricity consumption.
In this step, the user refers to a power consumption unit in a certain administrative division area, and the power consumption unit may be a person, an enterprise, or the like. Acquiring historical electricity data of users generally refers to acquiring the historical electricity data of a plurality of users in a region so as to enlarge sample capacity and increase accuracy of the data. The power consumption distribution curve expresses the power consumption corresponding to different time periods, for example, one year is divided into four seasons, each day in each season is divided into different time periods, the maximum power consumption and the minimum power consumption of each time period are counted respectively, the power consumption distribution interval corresponding to the time period is generated according to the maximum power consumption and the minimum power consumption, the maximum power consumption of each time period is connected to form a maximum power consumption distribution curve, the minimum power consumption of each time period is connected to form a minimum power consumption distribution curve, and then the power consumption distribution curve is formed according to the combination of the maximum power consumption distribution curve and the minimum power consumption distribution curve.
102. And collecting real-time electricity utilization data of the target object, and comparing whether the real-time electricity utilization data exceeds the electricity utilization distribution curve range.
In an embodiment, the target object refers to an object that is currently being monitored for data analysis in a certain administrative area, and may be one of the individuals of the user in step 101 or may be one of the enterprises. In practice, many users can be monitored synchronously, but since each user is predicted by separate data analysis, the target objects are used in the embodiment to distinguish. The real-time electricity consumption data refers to the electricity consumption parameters of the monitoring user in the current time period, including how much the electricity meter turns. The unit of the real-time electricity consumption data is the same as the unit of the electricity consumption distribution curve, so that comparison is convenient. In the application, since the electricity stealing behavior is pre-warned, whether the real-time electricity consumption data exceeds the electricity consumption distribution curve range or not is specific, whether the corresponding real-time electricity consumption data is lower than the electricity consumption distribution curve range or not is judged, and when the electricity consumption is lower than an electricity consumption threshold value, the abnormal electricity consumption is indicated.
103. And calculating the value of the real-time electricity consumption data exceeding the electricity consumption distribution curve range, and generating early warning information when the value exceeds a set threshold value.
And (3) specifically analyzing the quantity of the real-time electricity consumption data exceeding the electricity consumption distribution curve range under the condition that the target object exceeds the electricity consumption distribution curve range, and calculating the exceeding value, for example, the real-time electricity consumption in the current time period is a, the electricity consumption in the electricity consumption distribution curve corresponding to the time period is b, and calculating the difference value of a-b as the exceeding value.
In another example, fig. 2 further illustrates another power consumption monitoring and early warning method, as shown in fig. 2, including:
201. historical electricity usage data for the user is obtained in response to the data modeling instructions.
202. The 24 hours are divided into different time periods, and the historical electricity consumption data in one year is divided into historical electricity consumption data corresponding to four seasons of spring, summer, autumn and winter according to local climate factors.
The four seasons are divided according to the weather reasons of different areas, so that the reasonable power consumption of different time periods can be met. For example, in the southern areas, more electricity is usually used in summer and less in winter.
203. And respectively counting historical electricity consumption data of different time periods every day in four seasons, and obtaining a maximum electricity consumption threshold and a minimum electricity consumption threshold of different time periods every day in different seasons.
204. And drawing a first curve by connecting the maximum power consumption thresholds of different time periods in different seasons, and drawing a second curve by connecting the minimum power consumption thresholds of different time periods in different seasons.
Specifically, a first coefficient and a second coefficient are set, wherein the first coefficient is larger than 1, and the second coefficient is smaller than 1; based on formula d max *a 1 Generating an upper power threshold for the different time periods, and based on formula d min *a 2 Generating a lower power consumption threshold for the different time periods, wherein d max Is the maximum electricity consumption threshold value of different time periods, d min Is the minimum electricity consumption threshold value of different time periods, a 1 Is a first coefficient, a 2 Is a second coefficient; and drawing a first curve according to the upper limit connection of the power consumption threshold values of different time periods in different seasons, and drawing a second curve according to the lower limit connection of the power consumption threshold values of different time periods in different seasons.
205. And drawing and generating an electricity consumption distribution curve based on the first curve and the second curve, wherein the electricity consumption distribution curve comprises the relation between different time periods and electricity consumption.
206. And collecting real-time electricity utilization data of the target object, and comparing whether the real-time electricity utilization data exceeds the electricity utilization distribution curve range.
207. And calculating the value of the real-time electricity consumption data exceeding the electricity consumption distribution curve range, and generating early warning information when the value exceeds a set threshold value.
In another example, fig. 3 further illustrates another power consumption monitoring and early warning method, as shown in fig. 3, including:
301. historical electricity usage data for the user is obtained in response to the data modeling instructions.
302. The 24 hours are divided into different time periods, and the historical electricity consumption data in one year is divided into historical electricity consumption data corresponding to four seasons of spring, summer, autumn and winter according to local climate factors.
303. And respectively counting historical electricity consumption data of different time periods every day in four seasons, and obtaining a maximum electricity consumption threshold and a minimum electricity consumption threshold of different time periods every day in different seasons.
304. And acquiring historical electricity utilization data of other local users, and generating electricity utilization distribution ranges of different time periods every day in four seasons based on the historical electricity utilization data of the other users.
305. Comparing whether the maximum electricity consumption threshold value and the minimum electricity consumption threshold value are in an electricity consumption distribution range, if so, generating an electricity consumption distribution curve based on the maximum electricity consumption threshold value and the minimum electricity consumption threshold value in different time periods, otherwise, correcting the maximum electricity consumption threshold value and the minimum electricity consumption threshold value based on the electricity consumption distribution range, and generating an electricity consumption distribution curve based on the corrected maximum electricity consumption threshold value and the minimum electricity consumption threshold value, wherein the electricity consumption distribution curve comprises the relation between different time periods and electricity consumption.
The step of correcting the maximum electricity consumption threshold and the minimum electricity consumption threshold based on the electricity consumption distribution range comprises the following steps: acquiring a distribution maximum value and a distribution minimum value in a power utilization distribution range in different time periods of different seasons; and acquiring an intermediate value between the distribution maximum value and the maximum electricity consumption threshold as a corrected maximum electricity consumption threshold, and acquiring an intermediate value between the distribution minimum value and the minimum electricity consumption threshold as a corrected minimum electricity consumption threshold.
306. And collecting real-time electricity utilization data of the target object, and comparing whether the real-time electricity utilization data exceeds the electricity utilization distribution curve range.
307. And calculating the value of the real-time electricity consumption data exceeding the electricity consumption distribution curve range, and generating early warning information when the value exceeds a set threshold value.
In the step, when the numerical value exceeds a first set threshold and does not exceed a second set threshold, historical electricity consumption information of a target object is obtained, credit grade of the target object is generated based on the historical electricity consumption information, early warning information is generated when the credit grade of the target object is lower than a set standard, when the credit grade of the target object is higher than the set standard, whether real-time electricity consumption data of the target object in the next time period exceeds an electricity consumption distribution curve is continuously monitored, and early warning information is generated when the real-time electricity consumption data of the next time period exceeds the electricity consumption distribution curve; and when the value exceeds a second set threshold, directly generating early warning information.
308. And continuously monitoring the real-time electricity utilization data of the target object, and marking the target object as an electricity stealing risk object when the real-time electricity utilization data of the target object exceeds the electricity utilization distribution curve range in the same time period of exceeding the electricity utilization distribution curve range on the next day and the current day.
Example two
Referring to fig. 4, fig. 4 is a schematic structural diagram of a power consumption monitoring and early warning device according to an embodiment of the invention. As shown in fig. 4, the electricity consumption monitoring and early warning device may include: the system comprises a history curve generation module 401, a real-time electricity utilization acquisition module 402 and an early warning information generation module 403, wherein the history curve generation module 401: responding to a data modeling instruction to obtain historical electricity consumption data of a user, and generating an electricity consumption distribution curve based on the historical electricity consumption data, wherein the electricity consumption distribution curve comprises relations between different time periods and electricity consumption; real-time electricity acquisition module 402: collecting real-time electricity utilization data of a target object, and comparing whether the real-time electricity utilization data exceeds the electricity utilization distribution curve range; the early warning information generation module 403: and the method is used for calculating the numerical value of the real-time electricity consumption data exceeding the electricity consumption distribution curve range, and generating early warning information when the numerical value exceeds a set threshold value.
In the history curve generating module 401, the 24 hours are divided into different time periods, and the history electricity consumption data in one year is divided into the history electricity consumption data corresponding to four seasons of spring, summer, autumn and winter according to local climate factors; respectively counting historical electricity consumption data of different time periods every day in four seasons to obtain a maximum electricity consumption threshold value and a minimum electricity consumption threshold value of different time periods every day in different seasons; connecting the maximum power consumption thresholds of different time periods in different seasons to draw a first curve, and connecting the minimum power consumption thresholds of different time periods in different seasons to draw a second curve; and drawing and generating a power consumption distribution curve based on the first curve and the second curve.
In the foregoing, the drawing of the first curve by connecting the maximum power consumption threshold values of different time periods in different seasons and the drawing of the second curve by connecting the minimum power consumption threshold values of different time periods in different seasons includes: setting a first coefficient and a second coefficient, wherein the first coefficient is larger than 1, and the second coefficient is larger than the first coefficientThe coefficient is less than 1; based on formula d max *a 1 Generating an upper power threshold for the different time periods, and based on formula d min *a 2 Generating a lower power consumption threshold for the different time periods, wherein d max Is the maximum electricity consumption threshold value of different time periods, d min Is the minimum electricity consumption threshold value of different time periods, a 1 Is a first coefficient, a 2 Is a second coefficient; and drawing a first curve according to the upper limit connection of the power consumption threshold values of different time periods in different seasons, and drawing a second curve according to the lower limit connection of the power consumption threshold values of different time periods in different seasons.
In another example of the history curve generation module 401, the 24 hours may be divided into different time periods, and the historical electricity consumption data in one year may be divided into the historical electricity consumption data corresponding to four seasons of spring, summer, autumn and winter according to the local climate factors; respectively counting historical electricity consumption data of different time periods every day in four seasons to obtain a maximum electricity consumption threshold value and a minimum electricity consumption threshold value of different time periods every day in different seasons; acquiring historical electricity utilization data of other local users, and generating electricity utilization distribution ranges of different time periods every day in four seasons based on the historical electricity utilization data of the other users; comparing whether the maximum electricity consumption threshold value and the minimum electricity consumption threshold value are in an electricity consumption distribution range, if so, generating an electricity consumption distribution curve based on the maximum electricity consumption threshold value and the minimum electricity consumption threshold value in different time periods, otherwise, correcting the maximum electricity consumption threshold value and the minimum electricity consumption threshold value based on the electricity consumption distribution range, and generating the electricity consumption distribution curve based on the corrected maximum electricity consumption threshold value and the minimum electricity consumption threshold value.
In the above, the correcting the maximum electricity consumption threshold and the minimum electricity consumption threshold based on the electricity consumption distribution range includes: acquiring a distribution maximum value and a distribution minimum value in a power utilization distribution range in different time periods of different seasons; and acquiring an intermediate value between the distribution maximum value and the maximum electricity consumption threshold as a corrected maximum electricity consumption threshold, and acquiring an intermediate value between the distribution minimum value and the minimum electricity consumption threshold as a corrected minimum electricity consumption threshold.
In the early warning information generating module 403, when the value exceeds a first set threshold and does not exceed a second set threshold, historical electricity consumption information of the target object is obtained, a credit level of the target object is generated based on the historical electricity consumption information, and when the credit level of the target object is lower than a set standard, early warning information is generated, and when the credit level of the target object is higher than the set standard, whether real-time electricity consumption data of the target object in the next time period exceeds an electricity consumption distribution curve is continuously monitored, and when the real-time electricity consumption data of the next time period exceeds the electricity consumption distribution curve, early warning information is generated; and when the value exceeds a second set threshold, directly generating early warning information.
Embodiments may also include a power theft risk tagging module configured to continuously monitor real-time power usage data of the target object, and tag the target object as a power theft risk object when the real-time power usage data of the target object exceeds the power usage profile range for the same period of time that the target object exceeds the power usage profile range on the next day and the current day.
Example III
Referring to fig. 5, fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the invention. The electronic device may be a computer, a server, or the like, and of course, may also be an intelligent device such as a mobile phone, a tablet computer, a monitor terminal, or the like, and an image acquisition device having a processing function. As shown in fig. 5, the electronic device may include:
a memory 501 in which executable program codes are stored;
a processor 502 coupled to the memory 501;
the processor 502 invokes executable program codes stored in the memory 501 to execute some or all of the steps in the electricity consumption monitoring and early warning method in the first embodiment.
The embodiment of the invention discloses a computer readable storage medium storing a computer program, wherein the computer program enables a computer to execute part or all of the steps in the electricity consumption monitoring and early warning method in the first embodiment.
The embodiment of the invention also discloses a computer program product, wherein when the computer program product runs on a computer, the computer is caused to execute part or all of the steps in the electricity consumption monitoring and early warning method in the first embodiment.
The embodiment of the invention also discloses an application release platform, wherein the application release platform is used for releasing a computer program product, and when the computer program product runs on a computer, the computer is caused to execute part or all of the steps in the electricity consumption monitoring and early warning method in the first embodiment.
In various embodiments of the present invention, it should be understood that the size of the sequence numbers of the processes does not mean that the execution sequence of the processes is necessarily sequential, and the execution sequence of the processes should be determined by the functions and internal logic thereof, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer-accessible memory. Based on this understanding, the technical solution of the present invention, or a part contributing to the prior art or all or part of the technical solution, may be embodied in the form of a software product stored in a memory, comprising several requests for a computer device (which may be a personal computer, a server or a network device, etc., in particular may be a processor in a computer device) to execute some or all of the steps of the method according to the embodiments of the present invention.
In the embodiments provided herein, it should be understood that "B corresponding to a" means that B is associated with a, from which B can be determined. It should also be understood that determining B from a does not mean determining B from a alone, but may also determine B from a and/or other information.
Those of ordinary skill in the art will appreciate that some or all of the steps of the various methods of the described embodiments may be implemented by hardware associated with a program that may be stored in a computer-readable storage medium, including Read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), erasable programmable Read-Only Memory (Erasable Programmable Read-Only Memory, EPROM), one-time programmable Read-Only Memory (OTPROM), electrically erasable programmable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM), or other optical disk Memory, magnetic disk Memory, tape Memory, or any other medium capable of being used to carry or store data that is readable by a computer.
The power consumption monitoring and early warning method, the device, the electronic equipment and the storage medium disclosed by the embodiment of the invention are described in detail, and specific examples are applied to the description of the principle and the implementation mode of the invention, and the description of the above embodiments is only used for helping to understand the method and the core idea of the invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.
Claims (10)
1. The utility model provides a power consumption monitoring and early warning method which is characterized in that the method comprises the following steps:
responding to a data modeling instruction to obtain historical electricity consumption data of a user, and generating an electricity consumption distribution curve based on the historical electricity consumption data, wherein the electricity consumption distribution curve comprises relations between different time periods and electricity consumption;
collecting real-time electricity utilization data of a target object, and comparing whether the real-time electricity utilization data exceeds the electricity utilization distribution curve range;
and calculating the value of the real-time electricity consumption data exceeding the electricity consumption distribution curve range, and generating early warning information when the value exceeds a set threshold value.
2. The electricity usage monitoring and early warning method according to claim 1, wherein generating an electricity usage profile based on the historical electricity usage data comprises:
dividing 24 hours into different time periods, and dividing historical electricity consumption data in one year into historical electricity consumption data corresponding to four seasons of spring, summer, autumn and winter according to local climate factors;
respectively counting historical electricity consumption data of different time periods every day in four seasons to obtain a maximum electricity consumption threshold value and a minimum electricity consumption threshold value of different time periods every day in different seasons;
connecting the maximum power consumption thresholds of different time periods in different seasons to draw a first curve, and connecting the minimum power consumption thresholds of different time periods in different seasons to draw a second curve;
and drawing and generating a power consumption distribution curve based on the first curve and the second curve.
3. The power consumption monitoring and early warning method according to claim 2, wherein the drawing of the first curve by connecting the maximum power consumption threshold values of different time periods in different seasons and the drawing of the second curve by connecting the minimum power consumption threshold values of different time periods in different seasons includes:
setting a first coefficient and a second coefficient, wherein the first coefficient is larger than 1, and the second coefficient is smaller than 1;
based on formula d max *a 1 Generating an upper power threshold for the different time periods, and based on formula d min *a 2 Generating a lower power consumption threshold for the different time periods, wherein d max Is the maximum electricity consumption threshold value of different time periods, d min Is the minimum electricity consumption threshold value of different time periods, a 1 Is a first coefficient, a 2 Is a second coefficient;
and drawing a first curve according to the upper limit connection of the power consumption threshold values of different time periods in different seasons, and drawing a second curve according to the lower limit connection of the power consumption threshold values of different time periods in different seasons.
4. The electricity usage monitoring and early warning method according to claim 1, wherein generating an electricity usage profile based on the historical electricity usage data comprises:
dividing 24 hours into different time periods, and dividing historical electricity consumption data in one year into historical electricity consumption data corresponding to four seasons of spring, summer, autumn and winter according to local climate factors;
respectively counting historical electricity consumption data of different time periods every day in four seasons to obtain a maximum electricity consumption threshold value and a minimum electricity consumption threshold value of different time periods every day in different seasons;
acquiring historical electricity utilization data of other local users, and generating electricity utilization distribution ranges of different time periods every day in four seasons based on the historical electricity utilization data of the other users;
comparing whether the maximum electricity consumption threshold value and the minimum electricity consumption threshold value are in an electricity consumption distribution range, if so, generating an electricity consumption distribution curve based on the maximum electricity consumption threshold value and the minimum electricity consumption threshold value in different time periods, otherwise, correcting the maximum electricity consumption threshold value and the minimum electricity consumption threshold value based on the electricity consumption distribution range, and generating the electricity consumption distribution curve based on the corrected maximum electricity consumption threshold value and the minimum electricity consumption threshold value.
5. The electricity consumption monitoring and early warning method according to claim 4, wherein correcting the maximum electricity consumption threshold and the minimum electricity consumption threshold based on the electricity consumption distribution range includes:
acquiring a distribution maximum value and a distribution minimum value in a power utilization distribution range in different time periods of different seasons;
and acquiring an intermediate value between the distribution maximum value and the maximum electricity consumption threshold as a corrected maximum electricity consumption threshold, and acquiring an intermediate value between the distribution minimum value and the minimum electricity consumption threshold as a corrected minimum electricity consumption threshold.
6. The electricity consumption monitoring and early warning method according to claim 1, wherein generating early warning information when the value exceeds a set threshold value includes:
when the value exceeds a first set threshold value and does not exceed a second set threshold value, acquiring historical electricity consumption information of a target object, generating a credit level of the target object based on the historical electricity consumption information, generating early warning information when the credit level of the target object is lower than a set standard, continuously monitoring whether real-time electricity consumption data of the target object in the next time period exceeds an electricity consumption distribution curve or not when the credit level of the target object is higher than the set standard, and generating early warning information when the real-time electricity consumption data of the next time period exceeds the electricity consumption distribution curve;
and when the value exceeds a second set threshold, directly generating early warning information.
7. The electricity consumption monitoring and early warning method according to claim 1, further comprising:
and continuously monitoring the real-time electricity utilization data of the target object, and marking the target object as an electricity stealing risk object when the real-time electricity utilization data of the target object exceeds the electricity utilization distribution curve range in the same time period of exceeding the electricity utilization distribution curve range on the next day and the current day.
8. The utility model provides a power consumption monitoring early warning device which characterized in that includes:
a history curve generation module: responding to a data modeling instruction to obtain historical electricity consumption data of a user, and generating an electricity consumption distribution curve based on the historical electricity consumption data, wherein the electricity consumption distribution curve comprises relations between different time periods and electricity consumption;
the real-time electricity acquisition module is as follows: collecting real-time electricity utilization data of a target object, and comparing whether the real-time electricity utilization data exceeds the electricity utilization distribution curve range;
the early warning information generation module: and the method is used for calculating the numerical value of the real-time electricity consumption data exceeding the electricity consumption distribution curve range, and generating early warning information when the numerical value exceeds a set threshold value.
9. An electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor invokes the executable program code stored in the memory for performing the electricity usage monitoring and early warning method of any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute the electricity consumption monitoring and early warning method according to any one of claims 1 to 7.
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