CN117054736A - Power utilization detection method and device, electronic equipment and storage medium - Google Patents

Abstract

The embodiment of the invention discloses a power utilization detection method, a device, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring target power consumption information corresponding to a target user within a preset time length; determining a first electricity curve corresponding to a target user based on target electricity consumption information; and carrying out power utilization detection based on the target equipment information used by the target user and the first power curve, and determining a target power utilization detection result of the target user. According to the technical scheme provided by the embodiment of the invention, the automatic detection of the electricity consumption condition of the user can be realized without manual detection, so that the detection efficiency of the electricity consumption condition of the user is improved, and the accuracy of detecting the abnormal electricity consumption condition is improved.

Description

Power utilization detection method and device, electronic equipment and storage medium

Technical Field

Embodiments of the present invention relate to computer technologies, and in particular, to a power consumption detection method, apparatus, electronic device, and storage medium.

Background

Along with the acceleration construction of novel electric power system, in order to satisfy the safety access of special consumer such as distributed photovoltaic, energy storage equipment and charging stake, then need carry out the electricity consumption action to the consumer who uses traditional consumer and detect, carry out the electricity consumption action to the consumer who uses this kind of special consumer. Upon detecting the presence of excess capacity, overload, or other offending electrical activity by the user, the power supply personnel may alert or check the user.

At present, the electricity consumption behavior of each user is often detected in an artificial check mode, and on-site check is performed according to the artificial detection result, so that the user is warned or checked based on the on-site check result. However, in the manual detection mode, the judgment standards of everyone for illegal electricity consumption are not uniform, so that the detection result is inaccurate. Moreover, a large number of users exist in the power system, the efficiency of detecting the illegal power consumption behaviors of all the users in the power system in a manual detection mode is low, and especially the illegal power consumption behaviors of some large industrial users appear at night. It can be seen that there is a great need for a method for automatically detecting electricity usage.

Disclosure of Invention

The embodiment of the invention provides a power consumption detection method, a device, electronic equipment and a storage medium, which are used for realizing automatic detection of the power consumption condition of a user without manual detection, thereby improving the detection efficiency of the power consumption condition of the user and improving the detection accuracy of the abnormal power consumption condition.

In a first aspect, an embodiment of the present invention provides a power consumption detection method, including:

acquiring target power consumption information corresponding to a target user within a preset time length;

Determining a first electricity curve corresponding to the target user based on the target electricity consumption information;

and carrying out power utilization detection based on the target equipment information used by the target user and the first power curve, and determining a target power utilization detection result of the target user.

In a second aspect, an embodiment of the present invention provides an electricity usage detection device, including:

the target electricity consumption information acquisition module is used for acquiring target electricity consumption information corresponding to a target user in a preset time length;

the first electricity curve determining module is used for determining a first electricity curve corresponding to the target user based on the target electricity information;

and the target electricity utilization detection result determining module is used for carrying out electricity utilization detection based on the target equipment information used by the target user and the first electricity curve and determining a target electricity utilization detection result of the target user.

In a third aspect, an embodiment of the present invention provides an electronic device, including:

one or more processors;

a memory for storing one or more programs;

the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the power usage detection method as provided by any embodiment of the present invention.

In a fourth aspect, embodiments of the present invention provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the power usage detection method as provided by any of the embodiments of the present invention.

According to the technical scheme, the target electricity consumption information corresponding to the target user in the preset time period is obtained, so that the electricity consumption information of the user can be obtained in the user-defined time period for the specific user; based on the target electricity consumption information, determining a first electricity curve corresponding to the target user, so that the actual electricity consumption condition of the target user can be obtained, and normalized summary and visual display can be carried out on the actual electricity consumption condition of the target user in the form of the electricity consumption curve; and carrying out electricity utilization detection based on the target equipment information used by the target user and the first electricity curve, and determining a target electricity utilization detection result of the target user, so that the electricity utilization condition of the user can be automatically detected without manual detection, the detection efficiency of the electricity utilization condition of the user is further improved, the accuracy of detecting abnormal electricity utilization conditions is improved, and accurate basic detection data is further provided for electricity utilization management of an electricity utilization system.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent 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 flow chart of a power consumption detection method according to a first embodiment of the present invention;

fig. 2 is a flowchart of a power consumption detection method according to a second embodiment of the present invention;

FIG. 3 is an exemplary graph of a first power curve for abnormal power usage in accordance with a second embodiment of the present invention;

fig. 4 is a schematic structural diagram of an electricity consumption detecting device according to a third embodiment of the present invention;

fig. 5 is a schematic structural diagram of an electronic device implementing the power consumption detection method according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, 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 but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Example 1

Fig. 1 is a flowchart of an electricity consumption detection method provided in an embodiment of the present invention, where the embodiment may be suitable for automatic detection of electricity consumption conditions of various users connected in a power system, and especially suitable for automatic detection of electricity consumption conditions for large industrial users, where the method may be performed by an electricity consumption detection device, where the electricity consumption detection device may be implemented in a form of hardware and/or software, and where the electricity consumption detection device may be configured in an electronic device. As shown in fig. 1, the method includes:

s110, acquiring target power consumption information corresponding to a target user within a preset time period.

The preset duration may refer to a duration preset by a worker in the power system based on a service requirement. For example, in order to detect the electricity consumption behavior or electricity consumption condition of each user in the power system in the night electricity rate preference period, the preset time period may be set to an 8-hour time period from 0 a.m. to 8 a.m.. Or the preset time period can be set to be 24 hours from 0 a.m. to 0 a.m. in the next day in order to realize the electricity consumption behavior or electricity consumption condition of each user in the power system in each period of the whole day. The user may refer to a user accessing the power system for electricity. The target user may refer to a user to be subjected to the electricity usage behavior detection. For example, the target user may be, but is not limited to, a large industrial user or a charging pile management user. The target electricity consumption information may refer to electricity consumption information corresponding to each moment of a target user stored or recorded in a basic database in the power system. For example, the electricity usage may be, but is not limited to, current, voltage, active power, reactive power, and power factor. The basic database can refer to the original data collected by the metering automation system in the power system, and the database with complete information is formed after processing.

Specifically, after the preset duration is reached, the target electricity consumption information corresponding to the target user in the preset duration can be acquired at one time. And the information acquisition instruction can be issued before the preset time length starts, so that the target power utilization information corresponding to the target user at each preset time in the preset time length can be acquired in real time when the preset time length starts. Meanwhile, when the service requirement is changed, the preset time length can be correspondingly adjusted to obtain effective target electricity consumption.

Illustratively, the determination of the complete underlying database includes: carrying out data cleaning and screening based on the original data acquired by the metering automation system in the power system, and determining a reflux library; and extracting target reflow data corresponding to the target user from the reflow library to generate a complete basic database.

The raw data may refer to the current, voltage, and power factor collected, among others. A reflow library may refer to a database that stores processed data. For example, the reflow library may refer to a database formed by cleaning and screening raw data collected by a metering automation system in a power system. The target reflow data may include target electricity usage information.

Specifically, based on the original data collected by the metering automation system in the power system, the original data is cleaned by utilizing the data cleaning function of the Python, the cleaned data missing values are filled by utilizing the pandas library and the numpy library in the Python, the repeated values are deleted, and the processing such as the adjustment of the standardized data format is completed. And the processed data are subjected to operations such as screening, sorting, grouping and the like to determine a reflow library. And determining and extracting target reflow data corresponding to the target user from the reflow library by adopting a crawler technology, determining a basic database by utilizing the target reflow data, and judging the integrity of data in the basic database based on a preset integrity condition so as to obtain the complete basic database.

S120, determining a first electricity curve corresponding to the target user based on the target electricity consumption information.

The electricity consumption curve may be a characteristic electricity consumption curve capable of reflecting electricity consumption conditions. The first electricity curve may refer to a characteristic electricity curve that reflects actual electricity usage by the target user. The characteristic electricity usage curve may refer to a curve that characterizes a correspondence between a certain electricity usage characteristic and time.

Specifically, a feature representing the electricity consumption situation of the user is determined based on the target electricity consumption information, and a first electricity curve corresponding to the target user is determined based on a corresponding relation between the feature and each moment in a preset duration.

In this embodiment, if there are multiple features that can represent the electricity consumption situation of the user, a first electricity curve corresponding to each feature may be determined, and subsequent electricity detection is performed for each electricity curve. Or based on each first electricity curve and a pre-trained target electric equipment prediction model, comprehensively determining the type and the number of target equipment actually used by a target user in a preset time period. Wherein the target device type comprises an abnormal device type. The target device number contains an abnormal device number. When a user accesses a power system, the type of equipment to be used and the number of equipment corresponding to each type of equipment need to be actively provided. I.e. pre-provisioning the device type and number of devices. The abnormal device type is a device type which is not previously reported to obtain a use permission and which is privately accessed to the power system by a user and is used by being electrified. The number of abnormal devices may refer to the number of devices corresponding to each abnormal device type. The device does not pre-report to obtain the use permission, but the user privately accesses the power system and electrifies the use behavior, so that the super-capacity power utilization or the overload power utilization can be caused, and the privately connected power utilization behavior is illegal power utilization behavior.

It should be noted that, the target electric equipment prediction model may determine the type of target equipment and the number of target equipment actually used by the target user within a preset duration by using the pre-calibrated standard equipment power consumption curves and the first power consumption curves. The standard equipment power consumption curve may refer to a single equipment power consumption curve corresponding to each type of electric equipment calibrated in advance. The library of preset standard curves may be determined using the individual standard device power curves.

And S130, performing power utilization detection based on the target equipment information used by the target user and the first power curve, and determining a target power utilization detection result of the target user.

The target device information may refer to a backup device type corresponding to a device that obtains a use license and the number of backup devices corresponding to each backup device type in advance when the target user accesses the power system. The target electricity utilization detection result can represent whether the target user has illegal electricity utilization behaviors. The devices used by the target users can be, but are not limited to, energy storage devices, photovoltaic power generation devices, charging devices, industrial production devices and other electric devices needing to be brought into the safety supervision of the power grid.

Specifically, the target device information and the first electricity curve can be input into a target electric equipment prediction model to perform electricity utilization detection. In the target electric equipment prediction model, the target equipment information is utilized to determine that the corresponding second electric utilization curve is respectively determined when the target user uses each type of equipment with each quantity. For example, if the target user pre-reports 2 lathes and 1 charging pile of the same model, the second electricity consumption curve corresponding to the use of 1 lathe, the second electricity consumption curve corresponding to the use of 1 charging pile, the second electricity consumption curve corresponding to the use of 1 lathe and 1 charging pile, and the second electricity consumption curve corresponding to the use of 2 lathes and 1 charging pile may be determined. And detecting electricity utilization by utilizing each determined second electricity utilization curve and first electricity utilization curve. If the similarity between the first electricity curve and a certain second electricity curve is larger than a preset similarity threshold, determining that the target user does not have illegal electricity utilization behaviors, and determining the type of equipment actually used by the target user and the number of equipment corresponding to each type of equipment based on the second electricity curve. If the similarity between the first electricity curve and all the second electricity curves is smaller than or equal to a preset similarity threshold, determining that the target user has illegal electricity utilization behaviors, and determining the type of equipment (including abnormal equipment types) actually used by the target user and the number of equipment (including abnormal equipment numbers) corresponding to each equipment type based on the first electricity curve and each standard equipment electricity curve.

According to the technical scheme, the target electricity consumption information corresponding to the target user in the preset time period is obtained, so that the electricity consumption information of the user can be obtained in the user-defined time period for the specific user; determining a first electricity curve corresponding to the target user based on the target electricity information, so that the actual electricity consumption situation of the target user can be obtained, and normalized summary and visual display can be carried out on the actual electricity consumption situation of the target user in the form of the electricity consumption curve; and carrying out electricity utilization detection based on the target equipment information used by the target user and the first electricity curve, and determining a target electricity utilization detection result of the target user, so that the electricity utilization condition of the user can be automatically detected without manual detection, the detection efficiency of the electricity utilization condition of the user is further improved, the accuracy of detecting abnormal electricity utilization conditions is improved, and accurate basic detection data is further provided for electricity utilization management of an electricity utilization system.

Based on the above technical solution, S120 may include: determining the target power corresponding to each moment based on the target current and the target voltage corresponding to each moment in the preset time; and determining a first power curve corresponding to the target user based on each target power.

The first electrical profile may be, but is not limited to, a current profile, a voltage profile, a power profile, or a load profile. In the electricity utilization detection interface, a curve format corresponding to the first electricity curve can be selected from curve examples displayed in a drop-down menu in the interface. Specifically, taking a power curve as an example, multiplying a target current and a target voltage corresponding to each moment in a preset time period, determining a target power corresponding to each moment in the preset time period, generating a power-time curve with an abscissa as increasing time based on a corresponding relation between each target power and the moment, and determining the curve as a first power curve corresponding to a target user.

Illustratively, taking the load curve as an example, "determining the first power curve corresponding to the target user based on the respective target powers" may include: determining a target coefficient between the power and the load of the target user based on target equipment information used by the target user, and determining a target load corresponding to each moment based on the target power and the target coefficient corresponding to each moment; and determining a first electricity curve corresponding to the target user based on each target load.

Based on the technical scheme, the method further comprises the following steps: if the target electricity utilization detection result is an abnormal result, determining the type and the number of the abnormal devices used by the target user in an abnormal time period based on the first electricity utilization curve, the second electricity utilization curve and the electricity utilization curves of all the standard devices in the preset standard curve library.

The second electricity consumption curve may refer to an electricity consumption curve generated when all devices of the target user combine together. The abnormal period may refer to a preset detection period in which the user power consumption abnormality is detected. The preset detection time period may be a power consumption detection time period for the target user determined according to a service requirement or a device pre-reported by the target user. For example, for large industrial users, power utilization detection is performed for a night power utilization preferential period, so that personalized power utilization detection can be performed for different users.

Specifically, if the target electricity utilization detection result is an abnormal result, determining a second electricity utilization curve with highest similarity to the first electricity utilization curve based on the first electricity utilization curve and the second electricity utilization curve, and determining equipment types (including abnormal equipment types) corresponding to all equipment used by the target user in an abnormal time period and equipment numbers (including abnormal equipment numbers) corresponding to each equipment type based on the second electricity utilization curve and each standard equipment electricity utilization curve in a preset standard curve library. If the target electricity utilization detection result is a normal result, determining the device types (excluding the abnormal device types) and the device numbers (excluding the abnormal device numbers) corresponding to all the devices used by the target user in the preset detection time period based on the first electricity utilization curve and each standard device electricity utilization curve in the preset standard curve library

Example two

Fig. 2 is a flowchart of a power consumption detection method according to a second embodiment of the present invention, and the process of determining the target power consumption detection result of the target user through power consumption detection is described in detail on the basis of the foregoing embodiment. Wherein the explanation of the same or corresponding terms as those of the above embodiments is not repeated herein. As shown in fig. 2, the method includes:

s210, acquiring target power consumption information corresponding to a target user in a preset time period.

S220, determining a first electricity curve corresponding to the target user based on the target electricity consumption information.

S230, determining a target device power utilization curve corresponding to each target device based on the target device type of each target device used by the target user.

The power consumption curve of the target device may be a power consumption curve corresponding to a single target device. The target device power consumption curves corresponding to two target devices of the same type may be the same. Specifically, a standard equipment power consumption curve successfully matched with the target equipment type of each target equipment is determined from the standard equipment power consumption curves of the preset standard curve library, and a target equipment power consumption curve corresponding to each target equipment is determined.

S240, determining a second electricity utilization curve based on the number of target devices corresponding to each type of device and the electricity utilization curve of each target device.

Specifically, by using the number of target devices corresponding to each type of device and the power consumption curves of the respective target devices, a second power consumption curve corresponding to the usage combination of the plurality of devices can be determined, so that all the usage conditions of the devices corresponding to the target users are considered and determined.

S250, determining a target electricity utilization detection result of the target user based on the first electricity utilization curve and the second electricity utilization curve.

Specifically, the electricity behavior detection, that is, the electricity detection, of the target user can be performed based on the first electricity curve and the second electricity curve, and the target electricity detection result of the target user is determined. For example, the charging pile power on the market is 7kW, and the collected charging rated current is 31A. Then, for the relation between the current and the time of the charging pile, the electricity utilization behavior of the charging pile user in a preset detection time period can be analyzed, and a target electricity utilization detection result corresponding to the user is determined. The second electricity usage profile was 31A at full day time (0 to 24 points). And if the current of the first power curve is about 31A in the whole day, determining that the target power utilization detection result of the target user is normal power utilization. FIG. 3 shows an exemplary graph of a first electrical curve for abnormal electricity usage. Referring to fig. 3, if the current is about 10A in the period from 12 to 8 a in the night (valley electricity price), it indicates that the current collected in the period from 12 to 8 a in the night has too large deviation from the current during normal charging, and it is determined that the target electricity detection result of the target user is abnormal electricity.

According to the technical scheme, the target equipment power utilization curve corresponding to each target equipment is determined based on the type of the target equipment of each target equipment used by a target user, so that the target equipment power utilization curve corresponding to the target equipment pre-reported by the target user can be determined from the pre-calibrated standard equipment power utilization curves; based on the number of the target devices corresponding to each type of device and the power utilization curves of the target devices, a second power utilization curve corresponding to each type of device combination power utilization of a target user can be more comprehensively determined; and determining a target electricity utilization detection result of the target user based on the first electricity utilization curve and the second electricity utilization curve, so that the electricity utilization condition of the user can be automatically detected without manual detection, the detection efficiency of the electricity utilization condition of the user is improved, the detection accuracy of the abnormal electricity utilization condition is improved, and accurate basic detection data is further provided for electricity utilization management of an electricity utilization system.

Based on the above technical solution, S230 may include: matching the target equipment type of each target equipment used by the target user with each standard equipment type in a preset standard curve library; and determining the target equipment power utilization curve corresponding to each target equipment from the pre-calibrated standard equipment power utilization curves.

If the power consumption curves of the standard devices in the preset standard curve library are power-time curves, the power-time curves can be converted into current-time curves through i=p/Ucos phi. i denotes current, p denotes power, U denotes voltage, cos Φ denotes power factor. The device type may be used as a unique identification for matching. The method has the advantages that the target equipment power consumption curve corresponding to the target equipment used by the target user can be accurately and quickly determined from the preset standard curve library storing a large number of standard equipment power consumption curves.

Based on the above technical solution, S240 may include: based on the number of target devices corresponding to each type of device, performing curve superposition on the target device power consumption curve corresponding to each type of device, and determining at least one candidate device power consumption curve corresponding to each type of device; and carrying out curve superposition on the candidate equipment power utilization curves corresponding to each type of equipment, and determining at least one second power utilization curve corresponding to the target user.

The candidate equipment power consumption curve may refer to the equipment power consumption curve determined by sequentially overlapping the number of the equipment. For example, the candidate equipment power consumption curve may refer to a power consumption curve corresponding to one machine tool, a power consumption curve corresponding to two machine tools together, or a power consumption curve corresponding to a plurality of machine tools together.

Specifically, based on the number of target devices corresponding to each type of device, the target device power consumption curves corresponding to each type of device are sequentially subjected to curve superposition from few to many, and at least one candidate device power consumption curve corresponding to each type of device is determined. For example, if the number of target devices corresponding to the type a machine tool is 6, 7 candidate device power curves are corresponding. The 7 candidate equipment power consumption curves respectively correspond to 0 machine tools, 1 machine tool, 2 machine tools, 3 machine tools, 4 machine tools, 5 machine tools and 6 machine tools for power consumption. And superposing the ordinate values corresponding to the same moment in the candidate equipment power utilization curves corresponding to each type of equipment to generate a new superposed curve, namely a second power utilization curve. Along the above example, if the number of target devices corresponding to the type a machine tool is 6 and the number of target devices corresponding to the type B charging pile is 1, 14 second electricity utilization curves corresponding to the target user can be determined.

Based on the above technical solution, S250 may include: determining a third electricity curve most similar to the first electricity curve based on each second electricity curve; determining a target similarity between the first electricity curve and the third electricity curve in a preset detection time period based on the first electricity curve, the third electricity curve and the preset detection time period; and determining a target electricity utilization detection result of the target user based on the target similarity and a preset electricity utilization abnormal condition.

The preset power consumption abnormal condition may be that a preset similarity threshold is met. For example, taking current detection in a preset detection period as an example, if the current fluctuation deviation between the first electricity curve and the third electricity curve is ±10%, determining that the target similarity between the first electricity curve and the third electricity curve in the preset detection period is 90%, and prompting a positive deviation or a negative deviation. For another example: a large industrial user contracts for capacity 800kVA and charges basic electricity according to the capacity. And in a preset detection time period, if the power curve of the user continuously reaches 1500kVA, prompting positive deviation, wherein the similarity is 10%. And comparing the determined similarity with a preset similarity threshold (80%), and determining that the target similarity of the target user in a preset detection time period does not meet a preset electricity consumption abnormal condition, wherein the user is suspected of having the excessive electricity consumption behavior, so that the target electricity consumption detection result of the target user is determined to be an abnormal result.

In the above embodiment, the steps of determining the first electricity curve corresponding to the target user based on the target electricity information, and determining the target electricity detection result of the target user based on the target equipment information used by the target user and the first electricity curve may be performed by using a trained network model, so as to further improve the detection efficiency of the electricity consumption situation of the user and the accuracy of detecting the abnormal electricity consumption situation. The network model may employ neural network automatic learning methods. When the network model is trained, training data can be divided according to user types, and the normal electricity utilization curve of each type of user is utilized to determine the electricity utilization curve corresponding to the type of user, so that the network model is trained based on the determined electricity utilization curve corresponding to the type of user. And calculating the loss function value of the output result similarity and the detection result of the network model based on the preset label, adjusting parameters in the network model based on the determined loss function value, and finally realizing the training of the network model. The method can also determine the similarity between the power utilization curve corresponding to each feature and the actual power utilization curve of the target user by using the trained network model, and determine the target power utilization detection result of the target user based on the similarity result corresponding to each feature, thereby further improving the comprehensiveness of power utilization detection and the accuracy of the target power utilization detection result.

The following is an embodiment of an electrical power consumption detection apparatus provided by the embodiment of the present invention, which belongs to the same inventive concept as the electrical power consumption detection method of the above embodiments, and details of the electrical power consumption detection apparatus embodiment that are not described in detail may refer to the electrical power consumption detection method embodiment.

Example III

Fig. 4 is a schematic structural diagram of an electrical detection device according to a third embodiment of the present invention. As shown in fig. 4, the apparatus includes: the target electricity usage information acquisition module 410, the first electricity curve determination module 420, and the target electricity usage detection result determination module 430.

The target electricity consumption information acquisition module 410 is configured to acquire target electricity consumption information corresponding to a target user within a preset duration; the first electricity curve determining module 420 is configured to determine a first electricity curve corresponding to the target user based on the target electricity consumption; the target electricity utilization detection result determining module 430 is configured to perform electricity utilization detection based on the target device information used by the target user and the first electricity curve, and determine a target electricity utilization detection result of the target user.

According to the technical scheme, the target electricity consumption information corresponding to the target user in the preset time period is obtained, so that the electricity consumption information of the user can be obtained in the user-defined time period for the specific user; determining a first electricity curve corresponding to the target user based on the target electricity information, so that the actual electricity consumption situation of the target user can be obtained, and normalized summary and visual display can be carried out on the actual electricity consumption situation of the target user in the form of the electricity consumption curve; and carrying out electricity utilization detection based on the target equipment information used by the target user and the first electricity curve, and determining a target electricity utilization detection result of the target user, so that the electricity utilization condition of the user can be automatically detected without manual detection, the detection efficiency of the electricity utilization condition of the user is further improved, the accuracy of detecting abnormal electricity utilization conditions is improved, and accurate basic detection data is further provided for electricity utilization management of an electricity utilization system.

Optionally, the first electrical curve determination module 420 is specifically configured to: determining the target power corresponding to each moment based on the target current and the target voltage corresponding to each moment in the preset time; and determining a first power curve corresponding to the target user based on each target power.

Optionally, the target electricity usage detection result determination module 430 may include:

the target equipment power utilization curve determining submodule is used for determining a target equipment power utilization curve corresponding to each target equipment based on the type of the target equipment of each target equipment used by a target user;

the second electricity utilization curve determining submodule is used for determining a second electricity utilization curve based on the number of target devices corresponding to each type of device and the electricity utilization curve of each target device;

and the target electricity utilization detection result determining sub-module is used for determining the target electricity utilization detection result of the target user based on the first electricity utilization curve and the second electricity utilization curve.

Optionally, the target device power consumption curve determination submodule is specifically configured to: matching the target equipment type of each target equipment used by the target user with each standard equipment type in a preset standard curve library; and determining the target equipment power utilization curve corresponding to each target equipment from the pre-calibrated standard equipment power utilization curves.

Optionally, the second power usage curve determination submodule is specifically configured to: based on the number of target devices corresponding to each type of device, performing curve superposition on the target device power consumption curve corresponding to each type of device, and determining at least one candidate device power consumption curve corresponding to each type of device; and carrying out curve superposition on the candidate equipment power utilization curves corresponding to each type of equipment, and determining at least one second power utilization curve corresponding to the target user.

Optionally, the target electricity utilization detection result determining submodule is specifically configured to: determining a third electricity curve most similar to the first electricity curve based on each second electricity curve; determining a target similarity between the first electricity curve and the third electricity curve in a preset detection time period based on the first electricity curve, the third electricity curve and the preset detection time period; and determining a target electricity utilization detection result of the target user based on the target similarity and a preset electricity utilization abnormal condition.

Optionally, the method further comprises:

the abnormal equipment determining module is used for determining the type and the number of the abnormal equipment used by the target user in the abnormal time period based on the first power utilization curve, the second power utilization curve and the power utilization curves of the standard equipment in the preset standard curve library if the target power utilization detection result is an abnormal result.

The electricity consumption detection device provided by the embodiment of the invention can execute the electricity consumption detection method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the electricity consumption detection method.

It should be noted that, in the above embodiment of power consumption detection, each unit and module included are only divided according to the functional logic, but not limited to the above division, so long as the corresponding functions can be implemented; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.

Example IV

Fig. 5 shows a schematic diagram of the structure of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.

As shown in fig. 5, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.

Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.

The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the power detection method.

In some embodiments, the power usage detection method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the power usage detection method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the power usage detection method in any other suitable way (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.

The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.

The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.

Claims (10)

1. An electricity usage detection method, comprising:

acquiring target power consumption information corresponding to a target user within a preset time length;

determining a first electricity curve corresponding to the target user based on the target electricity consumption information;

and carrying out power utilization detection based on the target equipment information used by the target user and the first power curve, and determining a target power utilization detection result of the target user.

2. The method of claim 1, wherein the determining a first power curve corresponding to the target user based on the target power consumption information comprises:

Determining the target power corresponding to each moment based on the target current and the target voltage corresponding to each moment in the preset time;

and determining a first electricity curve corresponding to the target user based on each target power.

3. The method of claim 1, wherein the determining the target power usage detection result of the target user based on the target device information used by the target user and the first power curve comprises:

determining a target equipment power utilization curve corresponding to each target equipment based on the target equipment type of each target equipment used by the target user;

determining a second electricity utilization curve based on the number of target devices corresponding to each type of device and the electricity utilization curve of each target device;

and determining a target electricity utilization detection result of the target user based on the first electricity utilization curve and the second electricity utilization curve.

4. The method of claim 3, wherein the determining a target device power up profile for each target device based on the target device type for each target device used by the target user comprises:

matching the target equipment type of each target equipment used by the target user with each standard equipment type in a preset standard curve library;

And determining the target equipment power utilization curve corresponding to each target equipment from the pre-calibrated standard equipment power utilization curves.

5. The method of claim 3, wherein determining a second power usage profile based on the number of target devices for each type of device and the respective target device power usage profile comprises:

based on the number of target devices corresponding to each type of device, performing curve superposition on the target device power consumption curve corresponding to each type of device, and determining at least one candidate device power consumption curve corresponding to each type of device;

and carrying out curve superposition on the candidate equipment power utilization curves corresponding to each type of equipment, and determining at least one second power utilization curve corresponding to the target user.

6. The method of claim 3, wherein the determining the target power usage detection result of the target user based on the first power usage curve and the second power usage curve comprises:

determining a third electricity curve most similar to the first electricity curve based on each second electricity curve;

determining target similarity between the first electricity curve and the third electricity curve in a preset detection time period based on the first electricity curve, the third electricity curve and the preset detection time period;

And determining a target electricity utilization detection result of the target user based on the target similarity and a preset electricity utilization abnormal condition.

7. The method according to claim 1, wherein the method further comprises:

if the target electricity utilization detection result is an abnormal result, determining the type and the number of the abnormal devices used by the target user in an abnormal time period based on the first electricity utilization curve, the second electricity utilization curve and the electricity utilization curves of all the standard devices in the preset standard curve library.

8. An electricity usage detection device, comprising:

the target electricity consumption information acquisition module is used for acquiring target electricity consumption information corresponding to a target user in a preset time length;

the first electricity curve determining module is used for determining a first electricity curve corresponding to the target user based on the target electricity information;

and the target electricity utilization detection result determining module is used for carrying out electricity utilization detection based on the target equipment information used by the target user and the first electricity curve and determining a target electricity utilization detection result of the target user.

9. An electronic device, the electronic device comprising:

one or more processors;

a memory for storing one or more programs;

When executed by the one or more processors, causes the one or more processors to implement the power usage detection method of any of claims 1-7.

10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the electricity usage detection method according to any one of claims 1-7.