CN117788046A - Power consumption monitoring and early warning method and device based on Internet of things - Google Patents
Power consumption monitoring and early warning method and device based on Internet of things Download PDFInfo
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Abstract
The embodiment of the invention discloses a power consumption monitoring and early warning method and device based on the Internet of things, and the method and device comprise the steps of generating power consumption standards of a target power consumption area in different time periods based on historical power consumption data; collecting electricity consumption data and detection data of a target electricity consumption area in real time, counting the electricity consumption of the target electricity consumption area at intervals of preset time length, and generating predicted electricity consumption in the current time period according to the electricity consumption; judging that the electricity consumption exceeds the electricity consumption standard according to the predicted electricity consumption, and generating alarm information; and monitoring whether the target electricity utilization area has electricity utilization faults currently according to the detection data, and acquiring fault information of each computing unit when the electricity utilization faults exist. The method and the device have the advantages that the method and the device can be used for predicting in advance, further can be used for extracting and taking targeted measures, intervene in advance to avoid exceeding of electricity consumption, monitor electricity consumption safety, detect whether electricity consumption faults exist in electricity consumption areas, start from more subdivided areas in the areas where the electricity consumption faults exist, and accordingly find out fault points to maintain more rapidly.
Description
Technical Field
The invention relates to the technical field of electricity consumption monitoring, in particular to an electricity consumption monitoring and early warning method and device based on the Internet of things.
Background
At present, the electric energy has the advantages of convenient use, simple transmission, cleanness, safety and the like, the proportion of the electric energy in national production and living energy sources is increased increasingly, and more than half of the electric energy sources in China are supplied in an electric energy form through improved electric energy transmission and distribution. The development of power systems has been an important component of national life. Statistics show that the electricity consumption of China is also increasing year by year along with the development of economy. Meanwhile, with the development of technology, the traditional power industry is changed to a highly intensive, highly knowledgeable and highly technically sophisticated direction, and a power grid becomes one of the largest and most complex machines in the world, so that users have higher requirements on the reliability, safety, economy and stability of a power system.
With the rapid development of economy, household appliances have been popularized to thousands of households, and more electric equipment is required to run for twenty-four hours in office buildings. In the report issued by the public security department every year, the electrical equipment is damaged and aged, and the like, so that the specific gravity of the fire is large, the state and people suffer property loss and personal injury, and serious electric power resource waste is caused by the fact that people walk and power is not timely cut off, so that the electricity utilization safety and the electricity consumption of the electricity utilization side are not monitored perfectly at present.
Disclosure of Invention
Aiming at the defects, the embodiment of the invention discloses a power consumption monitoring and early warning method and device based on the Internet of things, which can effectively monitor the power consumption condition of a monitored area.
The embodiment of the invention discloses an electricity consumption monitoring and early warning method based on the Internet of things, which comprises the following steps:
responding to a data collection instruction to collect historical electricity consumption data of a target electricity consumption area within a set period, and generating electricity consumption standards of the target electricity consumption area in different periods based on the historical electricity consumption data, wherein the electricity consumption standards of the target electricity consumption area in different periods comprise first electricity consumption standards of all computing units in the target electricity consumption area in different periods and second electricity consumption standards of different computing units in the target electricity consumption area in different periods;
collecting electricity consumption data and detection data of each calculation unit in a target electricity consumption area in real time, counting electricity consumption of each calculation unit in preset time length every preset time length according to the electricity consumption data and the detection data, calculating total electricity consumption of all calculation units according to the electricity consumption, and generating predicted electricity consumption in the current time period based on the total electricity consumption;
Judging whether the predicted electricity consumption exceeds a first electricity consumption standard, generating alarm information when the predicted electricity consumption exceeds the first electricity consumption standard, and monitoring whether the electricity consumption of each calculation unit in the preset time exceeds a corresponding second electricity consumption standard when the electricity consumption of the target electricity consumption area in the next preset time exceeds the first electricity consumption standard; when the predicted electricity consumption does not exceed the first electricity consumption standard, judging that the number of times that the target electricity consumption area continuously does not exceed the first electricity consumption standard within a preset time period is greater than the preset number of times, setting the electricity consumption monitoring number of times of the target electricity consumption area when the number of times is greater than the preset number of times, and monitoring the total electricity consumption of the target electricity consumption area in a set monitoring period based on the electricity consumption monitoring number of times;
and monitoring whether the target electricity utilization area has an electricity utilization fault currently according to the detection data, and acquiring fault information of each computing unit in the target electricity utilization area when the electricity utilization fault exists.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, generating, based on the historical electricity consumption data, electricity consumption standards of the target electricity consumption area in different periods includes:
acquiring a preset time period range, and classifying the historical electricity consumption data according to the time period range and different computing units;
Extracting first maximum data and first minimum data from historical electricity utilization data in each time period range respectively; and extracting second maximum data and second minimum data from the historical electricity consumption data within each time period range according to the division of each calculation unit;
obtaining a first threshold value according to the first maximum data multiplied by a first coefficient, obtaining a second threshold value according to the first minimum data multiplied by a second coefficient, and generating a first electric quantity standard of the period based on the second threshold value and the first threshold value;
and obtaining a third threshold value according to the second maximum data multiplied by the first coefficient, obtaining a fourth threshold value according to the second minimum data multiplied by the second coefficient, and generating a second electricity consumption standard of the period based on the fourth threshold value and the third threshold value.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, generating the predicted electricity consumption in the current period according to the electricity consumption includes:
the total electricity consumption of the target electricity consumption area counted each time is saved, and the total electricity consumption counted each time is added with the sum of all the total electricity consumption counted before to obtain the total current electricity consumption;
generating a power consumption increase track by the current total power consumption sum obtained after each statistics of the total power consumption;
And generating the predicted electricity consumption of each time node which is not counted in the current period according to the electricity consumption increasing track.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, determining whether the predicted power consumption exceeds the first power criterion includes:
comparing the predicted electricity consumption with a first electricity consumption standard, and judging whether the predicted electricity consumption is within the range of the first electricity consumption standard;
when the predicted electricity consumption is out of the range of the first electricity consumption standard, calculating a difference value of the predicted electricity consumption exceeding the range of the first electricity consumption standard;
and when the difference value is larger than the threshold value, judging that the predicted power consumption exceeds the first power standard.
In a first aspect of the embodiment of the present invention, obtaining fault information of each computing unit in the target power consumption area includes:
dividing a target electricity utilization area into a plurality of calculation units;
and storing the electricity consumption data and the detection data of each computing unit in a classified manner, and generating fault information of each computing unit based on the detection data of the computing unit.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, generating fault information of each computing unit based on detection data of the computing unit includes:
The detection data of each unit is input into a preset fault detection model to output fault information, wherein the fault information comprises a fault result and a fault type.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the method further includes:
when no power failure exists, generating a numerical trend graph according to the sequence of the time nodes by using a plurality of detection data collected by different time nodes;
screening historical electricity data containing fault information from the collected historical electricity data as comparison data;
and generating a comparison value trend graph based on the comparison data according to the sequence of the time nodes, comparing the value trend graph with the comparison value trend graph, and generating fault early warning when the similarity of the two trend graphs exceeds a preset value.
The second aspect of the embodiment of the invention discloses an electricity consumption monitoring and early warning device based on the Internet of things, which comprises:
and a data collection module: the method comprises the steps of responding to a data collection instruction to collect historical electricity consumption data of a target electricity consumption area within a set period, and generating electricity consumption standards of the target electricity consumption area in different periods based on the historical electricity consumption data, wherein the electricity consumption standards of the target electricity consumption area in different periods comprise first electricity consumption standards of all computing units in the target electricity consumption area in different periods and second electricity consumption standards of different computing units in the target electricity consumption area in different periods;
And the electricity consumption prediction module is used for: the power consumption control method comprises the steps of collecting power consumption data and detection data of each calculation unit in a target power consumption area in real time, counting the power consumption of each calculation unit in preset time length every preset time length according to the power consumption data and the detection data, calculating the total power consumption of all calculation units according to the power consumption, and generating predicted power consumption in the current time period based on the total power consumption;
the electricity utilization alarming module is used for: the power utilization control method comprises the steps of judging whether the predicted power consumption exceeds a first power consumption standard, generating alarm information when the predicted power consumption exceeds the first power consumption standard, and monitoring whether the power consumption of each calculation unit exceeds a corresponding second power consumption standard in a preset time period when the power consumption of the target power utilization area exceeds the first power consumption standard in the next preset time period; when the predicted electricity consumption does not exceed the first electricity consumption standard, judging that the number of times that the target electricity consumption area continuously does not exceed the first electricity consumption standard within a preset time period is greater than the preset number of times, setting the electricity consumption monitoring number of times of the target electricity consumption area when the number of times is greater than the preset number of times, and monitoring the total electricity consumption of the target electricity consumption area in a set monitoring period based on the electricity consumption monitoring number of times;
And a fault detection module: and the system is used for monitoring whether the target electricity utilization area has electricity utilization faults currently according to the detection data, and acquiring fault information of each computing unit in the target electricity utilization area when the electricity utilization faults exist.
As an optional implementation manner, in the second aspect of the embodiment of the present invention, generating the electricity consumption standard of the target electricity consumption area in different periods based on the historical electricity consumption data includes:
acquiring a preset time period range, and classifying the historical electricity consumption data according to the time period range and different computing units;
extracting first maximum data and first minimum data from historical electricity utilization data in each time period range respectively; and extracting second maximum data and second minimum data from the historical electricity consumption data within each time period range according to the division of each calculation unit;
obtaining a first threshold value according to the first maximum data multiplied by a first coefficient, obtaining a second threshold value according to the first minimum data multiplied by a second coefficient, and generating a first electric quantity standard of the period based on the second threshold value and the first threshold value;
and obtaining a third threshold value according to the second maximum data multiplied by the first coefficient, obtaining a fourth threshold value according to the second minimum data multiplied by the second coefficient, and generating a second electricity consumption standard of the period based on the fourth threshold value and the third threshold value.
As an optional implementation manner, in a second aspect of the embodiment of the present invention, generating, according to the power consumption, a predicted power consumption in the current period includes:
storing the electricity consumption of the target electricity consumption area counted each time, and adding the sum of the electricity consumption counted each time and all the electricity consumption counted before to obtain the total amount of the current electricity consumption;
generating a power consumption increase track by the current power consumption sum obtained after each statistics of the power consumption;
and generating the predicted electricity consumption of each time node which is not counted in the current period according to the electricity consumption increasing track.
In a second aspect of the embodiment of the present invention, determining whether the predicted power consumption exceeds the first power consumption standard includes:
comparing the predicted electricity consumption with a first electricity consumption standard, and judging whether the predicted electricity consumption is within the range of the first electricity consumption standard;
when the predicted electricity consumption is out of the range of the first electricity consumption standard, calculating a difference value of the predicted electricity consumption exceeding the range of the first electricity consumption standard;
and when the difference value is larger than the threshold value, judging that the predicted power consumption exceeds the first power standard.
In a second aspect of the embodiment of the present invention, obtaining fault information of each computing unit in the target power consumption area includes:
Dividing a target electricity utilization area into a plurality of calculation units;
and storing the electricity consumption data and the detection data of each computing unit in a classified manner, and generating fault information of each computing unit based on the detection data of the computing unit.
As an optional implementation manner, in the second aspect of the embodiment of the present invention, generating fault information of each computing unit based on detection data of the computing unit includes:
the detection data of each unit is input into a preset fault detection model to output fault information, wherein the fault information comprises a fault result and a fault type.
As an optional implementation manner, in the second aspect of the embodiment of the present invention, the method further includes:
when no power failure exists, generating a numerical trend graph according to the sequence of the time nodes by using a plurality of detection data collected by different time nodes;
screening historical electricity data containing fault information from the collected historical electricity data as comparison data;
and generating a comparison value trend graph based on the comparison data according to the sequence of the time nodes, comparing the value trend graph with the comparison value trend graph, and generating fault early warning when the similarity of the two trend graphs exceeds a preset value.
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 codes stored in the memory to execute the electricity utilization monitoring and early warning method based on the Internet of things disclosed in the first aspect of the embodiment of the invention.
The fourth aspect of the embodiment of the invention discloses a computer readable storage medium storing a computer program, wherein the computer program enables a computer to execute the electricity consumption monitoring and early warning method based on the internet of things disclosed in the first aspect of the embodiment of the 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 target electricity consumption area are collected, so that two electricity consumption standards under different time periods are generated as comparison references, one is the second electricity consumption standard corresponding to each calculation unit respectively, the other is the first electricity consumption standard corresponding to all calculation units of the target electricity consumption area, when the electricity consumption data collected in real time generate the predicted electricity consumption, the predicted electricity consumption is compared with the first electricity consumption standard, when the two continuous monitoring exceeds the first electricity consumption standard, each calculation unit is further monitored to be compared with the second electricity consumption standard, the prediction in advance can be achieved, the targeted measure can be extracted and taken, the electricity consumption exceeding standard is avoided through the intervention in advance, when the number of times of continuously monitoring the target electricity consumption area not exceeding the first electricity consumption standard is larger than the preset number of times, the sampling detection is carried out in the monitoring period according to the set electricity consumption monitoring number of times, the monitoring pressure can be reduced, meanwhile, the embodiment also monitors the electricity consumption safety, detects whether the electricity consumption fault exists in the electricity consumption area, and the area is more rapidly subdivided from the area with the fault, and the fault is more rapidly found out.
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 an electricity consumption monitoring and early warning method based on the internet of things, which is disclosed by the embodiment of the invention;
fig. 2 is a schematic flow chart of another electricity consumption monitoring and early warning method based on the internet of things, which is disclosed in the embodiment of the invention;
fig. 3 is a schematic flow chart of another electricity consumption monitoring and early warning method based on the internet of things, which is disclosed by the embodiment of the invention;
fig. 4 is a schematic structural diagram of an electricity consumption monitoring and early warning device based on the internet of things, which is provided by the embodiment of the 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 based on the Internet of things, wherein in the embodiment, historical power consumption data of a target power consumption area are collected, so that two power consumption standards under different time periods are generated as comparison references, one of the two power consumption standards is respectively corresponding to each calculation unit, the other is a total first power consumption standard of all calculation units of the target power consumption area, when the power consumption data collected in real time generate predicted power consumption, the predicted power consumption is compared with the first power consumption standard, when the two continuous monitoring exceeds the first power consumption standard, each calculation unit is further monitored to be compared with the second power consumption standard, the purpose of predicting in advance, further the purpose of taking targeted measures can be extracted, the purpose of avoiding power consumption exceeding is intervened in advance, when the frequency of continuously monitoring the target power consumption area is not more than the first power consumption standard, the pressure is reduced, the power consumption is monitored in the monitoring period according to the set power consumption monitoring frequency, meanwhile, the embodiment is also used for monitoring safety, whether the power consumption area is more rapidly monitored, and a fault point is more rapidly found out, and the fault is more rapidly found and the fault is more rapidly maintained in the power consumption area.
Example 1
Referring to fig. 1, fig. 1 is a schematic flow chart of an electricity consumption monitoring and early warning method based on the internet of things 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 based on the internet of things comprises the following steps:
101. and responding to the data collection instruction, collecting historical electricity consumption data of the target electricity consumption area within a set period, and generating electricity consumption standards of the target electricity consumption area in different periods based on the historical electricity consumption data, wherein the electricity consumption standards of the target electricity consumption area in different periods comprise first electricity consumption standards of all computing units in the target electricity consumption area in different periods and second electricity consumption standards of different computing units in the target electricity consumption area in different periods.
In an embodiment, different areas are monitored by dividing the power consumption area, and each monitored area is a target power consumption area. The target electricity utilization area may be a village, a residential district, or a building. The historical electricity consumption data is the electricity consumption data of the target electricity consumption region in a certain past time period. The electricity usage data includes electricity usage.
In the embodiment, the target electricity consumption area is formed by a plurality of calculation units, and the calculation units are one unit for independently counting electricity consumption conditions in the target electricity consumption area, and the embodiment counts the total electricity consumption of all calculation units and also counts the electricity consumption corresponding to each calculation unit respectively. The first power criterion is thus generated for all computing units, each corresponding to the second power criterion.
102. And collecting electricity consumption data and detection data of each calculation unit in the target electricity consumption area in real time, counting the electricity consumption of each calculation unit in the preset time period at intervals of the preset time period according to the electricity consumption data and the detection data, calculating the total electricity consumption of all calculation units according to the electricity consumption, and generating the predicted electricity consumption in the current time period based on the total electricity consumption.
Wherein the electricity consumption data includes electricity consumption amount, and the detection data includes current data, voltage data, and the like. In an embodiment, the preset duration may be one day, may be three days, may be one week, and so on. Illustratively, the predetermined period of time is one week, i.e., the total power usage for the week is counted once a week. And each period is, for example, one month, the electricity consumption of the whole month can be predicted according to the electricity consumption statistics of the previous weeks.
103. Judging whether the predicted electricity consumption exceeds a first electricity consumption standard, generating alarm information when the predicted electricity consumption exceeds the first electricity consumption standard, and monitoring whether the electricity consumption of each calculation unit in the preset time exceeds a corresponding second electricity consumption standard when the total electricity consumption of the target electricity consumption area in the next preset time exceeds the first electricity consumption standard; when the predicted electricity consumption does not exceed the first electricity consumption standard, judging that the number of times that the target electricity consumption area continuously does not exceed the first electricity consumption standard within a preset time period is larger than the preset number of times, setting the electricity consumption monitoring number of times of the target electricity consumption area when the number of times is larger than the preset number of times, and monitoring the total electricity consumption of the target electricity consumption area in a set monitoring period based on the electricity consumption monitoring number of times.
When the electricity consumption exceeds the electricity consumption standard, alarm information is generated in advance, so that effective early warning can be realized, and targeted measures are taken in advance to avoid exceeding the actual electricity consumption.
In the step, firstly, whether the predicted electricity consumption exceeds the first electricity consumption standard is detected from the electricity consumption condition of the whole area of the target electricity consumption area, when the predicted electricity consumption exceeds the first electricity consumption standard, whether the total electricity consumption condition in the next preset time period exceeds the first electricity consumption standard is continuously monitored, if the total electricity consumption condition exceeds the first electricity consumption standard, each calculation unit of the target electricity consumption area is further monitored, the electricity consumption condition can be monitored from a smaller angle, early warning can be carried out, and prediction and improvement can be carried out from a specific calculation unit, so that the follow-up actual exceeding standard is avoided.
104. And monitoring whether the target electricity utilization area has an electricity utilization fault currently according to the detection data, and acquiring fault information of each computing unit in the target electricity utilization area when the electricity utilization fault exists.
The embodiment also monitors the electricity utilization safety, judges whether the electricity utilization fault exists in the target electricity utilization area by collecting detection data, and further acquires the fault information of each computing unit if the electricity utilization fault exists, so that the fault of which computing unit is determined, and the maintenance can be more quickly assisted. The calculation unit is a statistical unit further divided in the target electricity consumption area, for example, when the target electricity consumption area is a building, the calculation unit may be a building, and may be each household.
Fig. 2 shows a flowchart of another electricity consumption monitoring and early warning method based on the internet of things, which is disclosed in the embodiment of the invention, as shown in fig. 2, and includes:
201. collecting historical electricity utilization data of a target electricity utilization area, acquiring a preset time period range, and classifying the historical electricity utilization data according to the time period range; maximum data and minimum data are extracted from the historical electricity usage data within each period range, respectively. The maximum data comprises first maximum data and second maximum data, and the minimum data comprises first minimum data and second minimum data. Specifically, first maximum data and first minimum data are respectively extracted from historical electricity utilization data in each period range; and extracting second maximum data and second minimum data from the historical electricity consumption data within each period range according to division by each calculation unit.
The time interval range of the embodiment is that the starting time point and the ending time point of one time interval, and the historical electricity consumption data are arranged in a cabinet mode according to the time interval, so that the data corresponding to the maximum electricity consumption amount and the minimum electricity consumption amount of the historical electricity consumption data corresponding to each time interval can be counted.
202. Obtaining a first threshold value according to the first maximum data multiplied by a first coefficient, obtaining a second threshold value according to the first minimum data multiplied by a second coefficient, generating a first electricity consumption standard of the period based on the second threshold value and the first threshold value, obtaining a third threshold value according to the second maximum data multiplied by the first coefficient, obtaining a fourth threshold value according to the second minimum data multiplied by the second coefficient, and generating a second electricity consumption standard of the period based on the fourth threshold value and the third threshold value.
In an embodiment, the first coefficient is greater than 1 and the second coefficient is less than 1.
203. And collecting electricity consumption data and detection data of each calculation unit in the target electricity consumption area in real time, and counting the electricity consumption of each calculation unit in the preset time length at intervals according to the electricity consumption data and the detection data.
204. And storing the total electricity consumption of the target electricity consumption area counted each time, and adding the total electricity consumption counted each time and the sum of all the total electricity consumption counted before to obtain the total current electricity consumption.
For example, the total power consumption corresponding to a certain period is counted three times currently, namely a1, a2 and a3 respectively, when a2 is counted, the total current power consumption is calculated as a1+a2, and when a3 is counted, the total current power consumption is calculated as a1+a2+a3.
205. And generating a power consumption increase track by the current total power consumption sum obtained after counting the total power consumption each time.
206. And generating the predicted electricity consumption of each time node which is not counted in the current period according to the electricity consumption increasing track.
207. Judging whether the predicted electricity consumption exceeds an electricity consumption standard, and generating alarm information when the predicted electricity consumption exceeds the electricity consumption standard.
In the step, specifically, the predicted electricity consumption is compared with a first electricity consumption standard, and whether the predicted electricity consumption is within the range of the first electricity consumption standard is judged; when the predicted electricity consumption is out of the range of the first electricity consumption standard, calculating a difference value of the predicted electricity consumption exceeding the range of the first electricity consumption standard; and when the difference value is larger than the threshold value, judging that the predicted power consumption exceeds the first power standard.
208. And monitoring whether the target electricity utilization area has an electricity utilization fault currently according to the detection data, and acquiring fault information of each computing unit in the target electricity utilization area when the electricity utilization fault exists.
Specifically, dividing a target electricity utilization area into a plurality of calculation units; and storing the electricity consumption data and the detection data of each computing unit in a classified manner, and generating fault information of each computing unit based on the detection data of the computing unit. Further, generating fault information of each computing unit based on the detection data of the computing unit includes: the detection data of each unit is input into a preset fault detection model to output fault information, wherein the fault information comprises a fault result and a fault type.
Fig. 3 shows a flowchart of another electricity consumption monitoring and early warning method based on the internet of things, which is disclosed in the embodiment of the invention, and as shown in fig. 3, the electricity consumption monitoring and early warning method based on the internet of things comprises:
301. and responding to the data collection instruction to collect historical electricity consumption data of the target electricity consumption area within a set period, and generating electricity consumption standards of the target electricity consumption area in different periods based on the historical electricity consumption data, wherein the electricity consumption standards of the target electricity consumption area in different periods comprise first electricity consumption standards of all computing units in the target electricity consumption area in different periods and second electricity consumption standards of different computing units in the target electricity consumption area in different periods.
302. And collecting electricity consumption data and detection data of each calculation unit in the target electricity consumption area in real time, counting the electricity consumption of each calculation unit in the preset time period at intervals of the preset time period according to the electricity consumption data and the detection data, calculating the total electricity consumption of all calculation units according to the electricity consumption, and generating the predicted electricity consumption in the current time period based on the total electricity consumption.
303. Judging whether the predicted electricity consumption exceeds a first electricity consumption standard, generating alarm information when the predicted electricity consumption exceeds the first electricity consumption standard, and monitoring whether the electricity consumption of each calculation unit in the preset time exceeds a corresponding second electricity consumption standard when the total electricity consumption of the target electricity consumption area in the next preset time exceeds the first electricity consumption standard; when the predicted electricity consumption does not exceed the first electricity consumption standard, judging that the number of times that the target electricity consumption area continuously does not exceed the first electricity consumption standard within a preset time period is larger than the preset number of times, setting the electricity consumption monitoring number of times of the target electricity consumption area when the number of times is larger than the preset number of times, and monitoring the total electricity consumption of the target electricity consumption area in a set monitoring period based on the electricity consumption monitoring number of times.
304. And monitoring whether the target electricity utilization area has an electricity utilization fault currently according to the detection data, and dividing the target electricity utilization area into a plurality of calculation units when the electricity utilization fault exists.
305. And storing the electricity consumption data and the detection data of each computing unit in a classified manner, and generating fault information of each computing unit based on the detection data of the computing unit.
Specifically, the detection data of each unit is input into a preset fault detection model to output fault information, wherein the fault information comprises a fault result and a fault type.
306. And when no power failure exists, generating a numerical trend graph according to the sequence of the time nodes by using a plurality of detection data collected by different time nodes.
307. And screening the historical electricity data containing fault information from the collected historical electricity data as comparison data.
308. And generating a comparison value trend graph based on the comparison data according to the sequence of the time nodes, comparing the value trend graph with the comparison value trend graph, and generating fault early warning when the similarity of the two trend graphs exceeds a preset value.
The embodiment compares the generated numerical trend graphs under the condition that no faults exist so as to predict whether the faults exist, early warning is carried out in advance when faults are possible in the near future, preparation measures are prepared in advance to avoid faults, and the faults can be solved more rapidly in time.
Example two
Referring to fig. 4, fig. 4 is a schematic structural diagram of an electricity consumption monitoring and early warning device based on the internet of things according to an embodiment of the present invention. As shown in fig. 4, the electricity consumption monitoring and early warning device based on the internet of things may include: a data collection module 401, a power consumption prediction module 402, a power consumption warning module 403 and a fault detection module 404. Wherein the data collection module 401: the method comprises the steps of responding to a data collection instruction to collect historical electricity consumption data of a target electricity consumption area within a set period, and generating electricity consumption standards of the target electricity consumption area in different periods based on the historical electricity consumption data, wherein the electricity consumption standards of the target electricity consumption area in different periods comprise first electricity consumption standards of all computing units in the target electricity consumption area in different periods and second electricity consumption standards of different computing units in the target electricity consumption area in different periods; electricity consumption prediction module 402: the power consumption control method comprises the steps of collecting power consumption data and detection data of each calculation unit in a target power consumption area in real time, counting the power consumption of each calculation unit in preset time length every preset time length according to the power consumption data and the detection data, calculating the total power consumption of all calculation units according to the power consumption, and generating predicted power consumption in the current time period based on the total power consumption; electricity usage alert module 403: the method comprises the steps of judging whether the predicted electricity consumption exceeds a first electricity consumption standard, generating alarm information when the predicted electricity consumption exceeds the first electricity consumption standard, and monitoring whether the electricity consumption of each calculation unit in the preset time exceeds a corresponding second electricity consumption standard when the total electricity consumption of the target electricity consumption area in the next preset time exceeds the first electricity consumption standard; when the predicted electricity consumption does not exceed the first electricity consumption standard, judging that the number of times that the target electricity consumption area continuously does not exceed the first electricity consumption standard within a preset time period is greater than the preset number of times, setting the electricity consumption monitoring number of times of the target electricity consumption area when the number of times is greater than the preset number of times, and monitoring the total electricity consumption of the target electricity consumption area in a set monitoring period based on the electricity consumption monitoring number of times; fault detection module 404: and the system is used for monitoring whether the target electricity utilization area has electricity utilization faults currently according to the detection data, and acquiring fault information of each computing unit in the target electricity utilization area when the electricity utilization faults exist.
In the data collection module 401, a preset time period range is obtained, and the historical electricity consumption data are classified according to the time period range and different calculation units; extracting first maximum data and first minimum data from historical electricity utilization data in each time period range respectively; and extracting second maximum data and second minimum data from the historical electricity consumption data within each time period range according to the division of each calculation unit; obtaining a first threshold value according to the first maximum data multiplied by a first coefficient, obtaining a second threshold value according to the first minimum data multiplied by a second coefficient, and generating a first electric quantity standard of the period based on the second threshold value and the first threshold value; and obtaining a third threshold value according to the second maximum data multiplied by the first coefficient, obtaining a fourth threshold value according to the second minimum data multiplied by the second coefficient, and generating a second electricity consumption standard of the period based on the fourth threshold value and the third threshold value.
The electricity consumption prediction module 402 generates predicted electricity consumption in the current period according to the electricity consumption, including: the total electricity consumption of the target electricity consumption area counted each time is saved, and the total electricity consumption counted each time is added with the sum of all the total electricity consumption counted before to obtain the total current electricity consumption; generating a power consumption increase track by the current total power consumption sum obtained after each statistics of the total power consumption; and generating the predicted electricity consumption of each time node which is not counted in the current period according to the electricity consumption increasing track.
In the electricity usage alert module 403, determining whether the predicted electricity usage exceeds the first electricity usage criteria includes: comparing the predicted electricity consumption with a first electricity consumption standard, and judging whether the predicted electricity consumption is within the range of the first electricity consumption standard; when the predicted electricity consumption is out of the range of the first electricity consumption standard, calculating a difference value of the predicted electricity consumption exceeding the range of the first electricity consumption standard; and when the difference value is larger than the threshold value, judging that the predicted power consumption exceeds the first power standard.
In the fault detection module 404, obtaining fault information of each computing unit in the target power consumption area includes: dividing a target electricity utilization area into a plurality of calculation units; and storing the electricity consumption data and the detection data of each computing unit in a classified manner, and generating fault information of each computing unit based on the detection data of the computing unit. Further, the detection data of each unit is input into a preset fault detection model to output fault information, wherein the fault information comprises a fault result and a fault type.
The embodiment can also comprise a fault early warning module which is used for generating a numerical trend graph according to the sequence of the time nodes by using a plurality of detection data collected by different time nodes when no power failure exists; screening historical electricity data containing fault information from the collected historical electricity data as comparison data; and generating a comparison value trend graph based on the comparison data according to the sequence of the time nodes, comparing the value trend graph with the comparison value trend graph, and generating fault early warning when the similarity of the two trend graphs exceeds a preset value.
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 part or all of the steps in the electricity consumption monitoring and early warning method based on the internet of things in the first embodiment.
The embodiment of the invention discloses a computer readable storage medium which stores a computer program, wherein the computer program enables a computer to execute part or all of the steps in an electricity consumption monitoring and early warning method based on the Internet of things 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 based on the Internet of things 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 enabled to execute part or all of the steps in the electricity consumption monitoring and early warning method based on the Internet of things 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, device, electronic equipment and storage medium based on the Internet of things 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 embodiment 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 early warning method based on thing networking which characterized in that includes:
responding to a data collection instruction to collect historical electricity consumption data of a target electricity consumption area within a set period, and generating electricity consumption standards of the target electricity consumption area in different periods based on the historical electricity consumption data, wherein the electricity consumption standards of the target electricity consumption area in different periods comprise first electricity consumption standards of all computing units in the target electricity consumption area in different periods and second electricity consumption standards of different computing units in the target electricity consumption area in different periods;
collecting electricity consumption data and detection data of each calculation unit in a target electricity consumption area in real time, counting electricity consumption of each calculation unit in preset time length every preset time length according to the electricity consumption data and the detection data, calculating total electricity consumption of all calculation units according to the electricity consumption, and generating predicted electricity consumption in the current time period based on the total electricity consumption;
Judging whether the predicted electricity consumption exceeds a first electricity consumption standard, generating alarm information when the predicted electricity consumption exceeds the first electricity consumption standard, and monitoring whether the electricity consumption of each calculation unit in the preset time exceeds a corresponding second electricity consumption standard when the total electricity consumption of the target electricity consumption area in the next preset time exceeds the first electricity consumption standard; when the predicted electricity consumption does not exceed the first electricity consumption standard, judging that the number of times that the target electricity consumption area continuously does not exceed the first electricity consumption standard within a preset time period is greater than the preset number of times, setting the electricity consumption monitoring number of times of the target electricity consumption area when the number of times is greater than the preset number of times, and monitoring the total electricity consumption of the target electricity consumption area in a set monitoring period based on the electricity consumption monitoring number of times;
and monitoring whether the target electricity utilization area has an electricity utilization fault currently according to the detection data, and acquiring fault information of each computing unit in the target electricity utilization area when the electricity utilization fault exists.
2. The electricity consumption monitoring and early warning method according to claim 1, wherein generating electricity consumption standards of the target electricity consumption area in different periods based on the historical electricity consumption data comprises:
acquiring a preset time period range, and classifying the historical electricity consumption data according to the time period range and different computing units;
Extracting first maximum data and first minimum data from historical electricity utilization data in each time period range respectively; and extracting second maximum data and second minimum data from the historical electricity consumption data within each time period range according to the division of each calculation unit;
obtaining a first threshold value according to the first maximum data multiplied by a first coefficient, obtaining a second threshold value according to the first minimum data multiplied by a second coefficient, and generating a first electric quantity standard of the period based on the second threshold value and the first threshold value;
and obtaining a third threshold value according to the second maximum data multiplied by the first coefficient, obtaining a fourth threshold value according to the second minimum data multiplied by the second coefficient, and generating a second electricity consumption standard of the period based on the fourth threshold value and the third threshold value.
3. The electricity consumption monitoring and early warning method according to claim 1, wherein generating the predicted electricity consumption in the present time period according to the total electricity consumption includes:
the total electricity consumption of the target electricity consumption area counted each time is saved, and the total electricity consumption counted each time is added with the sum of all the total electricity consumption counted before to obtain the total current electricity consumption;
generating a power consumption increase track by the current total power consumption sum obtained after each statistics of the total power consumption;
And generating the predicted electricity consumption of each time node which is not counted in the current period according to the electricity consumption increasing track.
4. The electricity consumption monitoring and early warning method according to claim 3, wherein determining whether the predicted electricity consumption exceeds the first electricity consumption standard comprises:
comparing the predicted electricity consumption with a first electricity consumption standard, and judging whether the predicted electricity consumption is within the range of the first electricity consumption standard;
when the predicted electricity consumption is out of the range of the first electricity consumption standard, calculating a difference value of the predicted electricity consumption exceeding the range of the first electricity consumption standard;
and when the difference value is larger than the threshold value, judging that the predicted power consumption exceeds the first power standard.
5. The electricity consumption monitoring and early warning method according to claim 1, wherein acquiring fault information of each computing unit in the target electricity consumption area includes:
dividing a target electricity utilization area into a plurality of calculation units;
and storing the electricity consumption data and the detection data of each computing unit in a classified manner, and generating fault information of each computing unit based on the detection data of the computing unit.
6. The electricity consumption monitoring and early warning method according to claim 5, wherein generating fault information of each computing unit based on detection data of the computing unit includes:
The detection data of each unit is input into a preset fault detection model to output fault information, wherein the fault information comprises a fault result and a fault type.
7. The electricity consumption monitoring and early warning method according to claim 1, further comprising:
when no power failure exists, generating a numerical trend graph according to the sequence of the time nodes by using a plurality of detection data collected by different time nodes;
screening historical electricity data containing fault information from the collected historical electricity data as comparison data;
and generating a comparison value trend graph based on the comparison data according to the sequence of the time nodes, comparing the value trend graph with the comparison value trend graph, and generating fault early warning when the similarity of the two trend graphs exceeds a preset value.
8. Power consumption monitoring early warning device based on thing networking, its characterized in that includes:
and a data collection module: the method comprises the steps of responding to a data collection instruction to collect historical electricity consumption data of a target electricity consumption area within a set period, and generating electricity consumption standards of the target electricity consumption area in different periods based on the historical electricity consumption data, wherein the electricity consumption standards of the target electricity consumption area in different periods comprise first electricity consumption standards of all computing units in the target electricity consumption area in different periods and second electricity consumption standards of different computing units in the target electricity consumption area in different periods;
And the electricity consumption prediction module is used for: the power consumption control method comprises the steps of collecting power consumption data and detection data of each calculation unit in a target power consumption area in real time, counting the power consumption of each calculation unit in preset time length every preset time length according to the power consumption data and the detection data, calculating the total power consumption of all calculation units according to the power consumption, and generating predicted power consumption in the current time period based on the total power consumption;
the electricity utilization alarming module is used for: the power utilization control method comprises the steps of judging whether the predicted power consumption exceeds a first power consumption standard, generating alarm information when the predicted power consumption exceeds the first power consumption standard, and monitoring whether the power consumption of each calculation unit exceeds a corresponding second power consumption standard in a preset time period when the power consumption of the target power utilization area exceeds the first power consumption standard in the next preset time period; when the predicted electricity consumption does not exceed the first electricity consumption standard, judging that the number of times that the target electricity consumption area continuously does not exceed the first electricity consumption standard within a preset time period is greater than the preset number of times, setting the electricity consumption monitoring number of times of the target electricity consumption area when the number of times is greater than the preset number of times, and monitoring the total electricity consumption of the target electricity consumption area in a set monitoring period based on the electricity consumption monitoring number of times;
And a fault detection module: and the system is used for monitoring whether the target electricity utilization area has electricity utilization faults currently according to the detection data, and acquiring fault information of each computing unit in the target electricity utilization area when the electricity utilization faults exist.
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 executing the electricity usage monitoring and early warning method based on the internet of things 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 usage monitoring and early warning method based on the internet of things according to any one of claims 1 to 7.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018232937A1 (en) * | 2017-06-23 | 2018-12-27 | 深圳市盛路物联通讯技术有限公司 | Electric power cable fault monitoring method and apparatus |
| CN114816917A (en) * | 2022-04-24 | 2022-07-29 | 京东科技信息技术有限公司 | Monitoring data processing method, device, equipment and storage medium |
| CN117039850A (en) * | 2023-07-12 | 2023-11-10 | 湖北华中电力科技开发有限责任公司 | Abnormal electricity consumption analysis method and system based on space-time ground feature characteristics |
| CN117036104A (en) * | 2023-10-08 | 2023-11-10 | 北京前景无忧电子科技股份有限公司 | Intelligent electricity utilization method and system based on electric power Internet of things |
| CN117093943A (en) * | 2023-08-23 | 2023-11-21 | 广东电网有限责任公司佛山供电局 | Power consumption monitoring and early warning method and device |
| CN117147958A (en) * | 2023-08-23 | 2023-12-01 | 广东电网有限责任公司佛山供电局 | Method and device for discriminating electricity larceny based on real-time electricity utilization monitoring |
-
2024
- 2024-01-25 CN CN202410110285.8A patent/CN117788046A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018232937A1 (en) * | 2017-06-23 | 2018-12-27 | 深圳市盛路物联通讯技术有限公司 | Electric power cable fault monitoring method and apparatus |
| CN114816917A (en) * | 2022-04-24 | 2022-07-29 | 京东科技信息技术有限公司 | Monitoring data processing method, device, equipment and storage medium |
| CN117039850A (en) * | 2023-07-12 | 2023-11-10 | 湖北华中电力科技开发有限责任公司 | Abnormal electricity consumption analysis method and system based on space-time ground feature characteristics |
| CN117093943A (en) * | 2023-08-23 | 2023-11-21 | 广东电网有限责任公司佛山供电局 | Power consumption monitoring and early warning method and device |
| CN117147958A (en) * | 2023-08-23 | 2023-12-01 | 广东电网有限责任公司佛山供电局 | Method and device for discriminating electricity larceny based on real-time electricity utilization monitoring |
| CN117036104A (en) * | 2023-10-08 | 2023-11-10 | 北京前景无忧电子科技股份有限公司 | Intelligent electricity utilization method and system based on electric power Internet of things |
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