CN112821556B - Power detection control system and method - Google Patents
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Abstract
The invention provides an electric power detection control system and method, which are characterized in that electric power utilization data of each electric power branch of each user in a plurality of specific areas are collected and subjected to centralized analysis and comparison to obtain an electric power utilization behavior evaluation result of each specific area, a control method of each electric power branch of each user is determined according to the evaluation result, and a plurality of electric power branches of each user are directly controlled according to the determined control method. The embodiment of the invention can monitor the power utilization behaviors of each user in a specific area, such as an old cell or a parcel, and improve the problem of line faults caused by non-standard power utilization.
Description
Technical Field
The invention relates to the field of power detection, in particular to a power detection control system and a power detection control method.
Background
With the gradual development of the national urbanization process, more and more residential buildings are built, the electrification level matched with the residential buildings also rises with water, and however, more old districts or residential districts exist in the city. Along with the gradual improvement of the household electrification level, the load of electrical equipment in residents' homes is rapidly increased, the existing old community power distribution facilities cannot meet the reliability requirement, the old community has the problems of low planning and design standard, old electrical equipment, aging of a power transmission line, low per-household capacity configuration and the like to different degrees, and the convenience, the safety and the reliability of electricity utilization of the community residents are influenced to a certain degree. On the basis, the unsafe electricity utilization behaviors of residents often cause safety accidents or line faults and affect the daily life and even life safety of other residents in the same area, and the common unsafe electricity utilization behaviors comprise that a plurality of high-power electric appliances are used in one electricity utilization branch for a long time, temporary wires are arranged in the low-power electricity utilization branch in a pulling mode, wasted electricity is laid, and the like. At present, a measure capable of monitoring the power utilization behavior of an old cell or a parcel to reduce the occurrence probability of faults and accidents is lacked.
It should be noted that the above background is only used for assisting understanding of the technical logic of the technical solution, and is not taken as a basis for judging the prior art of the present application.
Disclosure of Invention
The invention aims to provide a power detection control system and a power detection control method, which are used for monitoring the power utilization behaviors of all users in old cells or districts and improving the problem of line faults caused by irregular power utilization.
In order to achieve the above object, an embodiment of the present invention is implemented as follows:
in a first aspect, the invention provides a power detection control system, which comprises a background server and a plurality of statistical servers, wherein the background server is in communication connection with each statistical server, each statistical server is in communication connection with intelligent distribution boxes of a plurality of users in a detection area, each intelligent distribution box is electrically connected with each power utilization branch in the power utilization area of the users, each intelligent distribution box comprises a switch, wherein,
the intelligent distribution box is configured to obtain power utilization data of each power utilization branch according to a preset period and send the power utilization data to the statistical server, wherein the power utilization data of each power utilization branch comprises a power utilization identifier and a power consumption amount corresponding to each power utilization branch and a unique identifier of a user;
the statistical server is configured to obtain power consumption data sent by each intelligent distribution box, package the power consumption data of all power consumption branches of each user according to a preset packaging mode according to a power consumption identifier, power consumption and a unique identifier of the user carried by the power consumption data to obtain a power consumption data packet of each user, and package all the power consumption data packets into statistical data packets to be sent to the background server;
the background server is configured to receive statistical data packets sent by each statistical server, extract power consumption data of power consumption branches in each statistical data packet according to power consumption identification and unique identification, classify the power consumption data according to a preset power classification method to obtain a power classification data table corresponding to each statistical data packet, calculate a weight value corresponding to each power classification data table according to a preset classification weight calculation method, judge whether the highest weight value in each power data table is higher than a preset lowest weight value, if the highest weight value is higher than the preset lowest weight value, determine the statistical data packet corresponding to the power data table with the highest weight value as a reference data packet, determine a reference weight according to the power consumption data in the reference data packet, determine a control method of each power consumption branch of each user according to the reference weight, package all control methods according to the power consumption identification and the unique identification, obtain a control method set corresponding to each statistical server, merge and send the control method set to the corresponding statistical server;
the statistical server is configured to receive the management and control method set, extract the management and control method corresponding to each user, and manage and control the power consumption behavior of the corresponding user according to the management and control method.
Further, the control method for determining each electricity utilization branch of each user according to the reference weight comprises the following steps:
calculating Jacard similarity coefficients of the statistical data packets and the reference data packets respectively to obtain similarity values of the statistical data packets and the reference data packets, and sequencing the similarity values according to the similarity values, wherein data in the statistical data packets are presented in a multi-dimensional vector form;
distributing an adjusting coefficient for each statistical data packet according to the similarity value and a preset distribution method; according to the sorting sequence of the statistical data packets, carrying out weight calculation on the electricity utilization data of each electricity utilization branch in the statistical data packets according to a preset branch electricity utilization weight calculation method to obtain branch weights, and calculating the branch weights and the distributed adjustment coefficients to obtain corrected branch weights;
and determining a control method of each power utilization branch circuit according to the difference value between the corrected branch circuit weight and the reference weight of each power utilization branch circuit.
Further, the control method comprises the steps of adjusting the electricity prices of the corresponding electricity utilization branches and controlling the on-off of the switch of the intelligent distribution box, specifically, determining the corresponding control method according to the range where the difference value is located, adjusting the electricity prices of the electricity utilization branches corresponding to the difference value to a preset electricity price when the difference value is located in the first range, and performing on-off control on the electricity utilization branches corresponding to the difference value according to a preset on-off time period when the difference value is located in the second range.
Further, intelligent power distribution box still is configured to gather each power consumption branch road's power consumption and send to statistics server, and statistics server calculates the power consumption expense according to each power consumption branch road's power consumption and the price of electricity that matches.
Further, calculating the weight value corresponding to each power classification data table according to a preset classification weight calculation method includes:
each power classification data table comprises a plurality of power classifications and power utilization data corresponding to the power classifications, the power utilization data comprise power utilization times, power utilization maintaining time and power consumption, each power classification is matched with a weight calculation ratio in advance according to power attributes, classification weight values corresponding to the power classifications are obtained through calculation of the power utilization data and the weight calculation ratio, and the classification weight values are added to obtain the weight values.
Further, determining the benchmark weight from the electricity usage data in the reference data packet comprises:
and inputting the electricity utilization data in the reference data packet into a pre-established convolutional neural network, identifying and calculating the electricity utilization data in the reference data packet based on the convolutional neural network, and outputting a benchmark weight corresponding to the electricity utilization data in the reference data packet, wherein the electricity utilization data in the reference data packet is presented in a multi-dimensional vector form.
In a second aspect, an embodiment of the present invention provides a power detection control method, where the method is applied to a background server, the background server is in communication connection with multiple statistical servers, each statistical server is in communication connection with multiple intelligent distribution boxes of users in a detection area, each intelligent distribution box is electrically connected to each power utilization branch in a power utilization area of a user, each intelligent distribution box includes a switch, and the method includes:
receiving a statistical data packet sent by each statistical server, wherein the statistical data packet acquires power utilization data sent by each intelligent distribution box for the statistical servers, the power utilization data are acquired by the intelligent distribution boxes according to a preset period, the power utilization data of each power utilization branch comprise a power utilization identifier and a power consumption corresponding to each power utilization branch and a unique identifier of a user according to the power utilization identifier, the power consumption and the unique identifier of the user carried by the power utilization data, the statistical servers pack the power utilization data of all the power utilization branches of each user according to a preset packing mode to obtain power utilization data packets of each user, and pack all the power utilization data packets to obtain statistical data packets;
extracting the power utilization data of the power utilization branch in each statistical data packet according to the power utilization identification and the unique identification;
classifying the power utilization data according to a preset power classification method to obtain a power classification data table corresponding to each statistical data packet;
calculating the weight value corresponding to each power classification data table according to a preset classification weight calculation method;
judging whether the highest weighted value in each power data table is higher than a preset lowest weighted value or not, and if so, determining a statistical data packet corresponding to the power data table with the highest weighted value as a reference data packet;
determining a benchmark weight according to the electricity utilization data in the reference data packet;
determining a control method of each electricity utilization branch of each user according to the reference weight;
and packaging all the control methods according to the power utilization identification and the unique identification to obtain a control method set corresponding to each statistical server and sending the control method set to the corresponding statistical server so that the statistical server can extract the control method corresponding to each user according to the control method set, and manage and control the power utilization behavior of the corresponding user according to the control method.
Further, the control method for determining each electricity utilization branch of each user according to the reference weight comprises the following steps:
calculating Jacard similarity coefficients of the statistical data packets and the reference data packets respectively to obtain similarity values of the statistical data packets and the reference data packets, and sequencing the similarity values according to the similarity values, wherein data in the statistical data packets are presented in a multi-dimensional vector form;
distributing an adjusting coefficient for each statistical data packet according to the similarity value and a preset distribution method; according to the sorting sequence of the statistical data packets, carrying out weight calculation on the electricity utilization data of each electricity utilization branch in the statistical data packets according to a preset branch electricity utilization weight calculation method to obtain branch weights, and calculating the branch weights and the distributed adjustment coefficients to obtain corrected branch weights;
the control method comprises the steps of adjusting the electricity price of the corresponding electricity utilization branch and controlling the on-off of a switch of the intelligent distribution box, concretely, the corresponding control method is determined according to the range where the difference value is located, when the difference value is located in a first range, the electricity price of the electricity utilization branch corresponding to the difference value is adjusted to be a preset electricity price, and when the difference value is located in a second range, the on-off control is carried out on the electricity utilization branch corresponding to the difference value according to a preset on-off time period.
Further, calculating the weight value corresponding to each power classification data table according to a preset classification weight calculation method includes:
each power classification data table comprises a plurality of power classifications and power utilization data corresponding to the power classifications, the power utilization data comprise power utilization times, power utilization maintaining time and power consumption, each power classification is matched with a weight calculation ratio in advance according to power attributes, classification weight values corresponding to the power classifications are obtained through calculation of the power utilization data and the weight calculation ratio, and the classification weight values are added to obtain the weight values.
Further, determining the benchmark weight from the electricity usage data in the reference data packet comprises:
inputting the power consumption data in the reference data packet into a pre-established convolutional neural network, identifying and calculating the power consumption data in the reference data packet based on the convolutional neural network, and outputting a reference weight corresponding to the power consumption data in the reference data packet, wherein the power consumption data in the reference data packet is presented in a multi-dimensional vector form.
The embodiment of the invention provides a power detection control system and a power detection control method, which are used for acquiring power utilization data of each power utilization branch of each user in a plurality of specific areas, carrying out centralized analysis and comparison to obtain power utilization behavior evaluation results of each specific area, determining a control method of each power utilization branch of each user according to the evaluation results, and directly controlling a plurality of power utilization branches of each user according to the determined control method. The embodiment of the invention can monitor the power utilization behaviors of each user in a specific area, such as an old cell or a parcel, and improve the problem of line faults caused by non-standard power utilization.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic system architecture diagram of a power detection control system according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of a background server according to an embodiment of the present invention.
Fig. 3 is a flowchart of a power detection control method according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of functional modules of a power detection control apparatus according to an embodiment of the present invention.
Icon:
a background server-10; a power monitoring and controlling device-11; a receiving module-111; an extraction module-112; a classification module-113; a computing module-114; a judgment module-115; weight determination module-116; a management and control method generation module-117; a packing module-118; a sending module-119; a memory-12; a processor-13; a communication unit-14; a statistics server-20; an intelligent distribution box-30; the electrical branch-40 is used.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Referring to fig. 1, a schematic diagram of a system architecture of a power detection control system 100 according to an embodiment of the present invention is shown, where the power detection control system 100 includes a background server 10 and a plurality of statistical servers 20, the background server 10 is in communication connection with each statistical server 20, and each statistical server 20 is in communication connection with a plurality of smart distribution boxes 30 of users in a detection area. The smart distribution box 30 is electrically connected to each of the power utilization branches 40 in the power utilization area of the user, and the smart distribution box 30 includes a switch.
In this embodiment, the detection area is an old cell or a living area that needs to be monitored, each old cell or living area is configured with one statistical server 20, and the line aging degrees of the cells or areas monitored by the statistical servers 20 are similar and have a basis for mutual reference.
In order to implement effective supervision, each user of the old cell in this embodiment is installed with an intelligent distribution box 30, and the intelligent distribution box 30 can identify the power consumption attribute of each power consumption branch 40 in the user room, optionally, the identification may be based on an existing line architecture, intelligent identification, or after manual statistics, pre-store the usage of each power consumption branch 40. Intelligent distribution box 30 can carry out switching control to each power consumption branch road 40 to and gather each power consumption branch road 40's power consumption data, and what understand easily, this intelligent distribution box 30's realization principle is prior art, and existing intelligent house block terminal can foretell function, and this embodiment is not repeated.
The power detection control method provided by the embodiment of the invention is applied to the background server, the background server is used for communicating with the statistical server, processing data uploaded by the statistical server, issuing control instructions and the like, and it can be understood that the background server 10 comprises a communication unit for realizing communication connection with each statistical server 20.
Referring to fig. 2, it is a schematic diagram of a background server, where the background server 10 includes a power detection control device 11, a memory 12, a processor 13, and a communication unit 14. The memory 12, processor 13 and communication unit 14 are electrically connected to each other directly or indirectly to enable data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The power detection control device 11 includes a plurality of software functional modules which may be stored in the form of software or firmware (firmware) in the memory 12 or solidified in an Operating System (OS) of the background server 10. The processor 13 is used for executing executable modules stored in the memory 12, such as software functional modules and computer programs included in the power detection control device 11.
The Memory 12 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Read Only Memory (EPROM), an electrically Erasable Read Only Memory (EEPROM), and the like. The memory 12 is used for storing a program, and the processor 13 executes the program after receiving an execution instruction. The communication unit 14 is configured to establish a communication connection between the backend server and the statistics server 20 via a network, and is configured to receive and transmit data via the network.
The processor 13 may be an integrated circuit chip having signal processing capabilities. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP)), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Referring to fig. 3, a flowchart of a power detection control method provided in this embodiment is shown, where the method includes the following steps:
in step S1, the statistical data packets transmitted by the statistical servers 20 are received.
In this embodiment, intelligent power distribution box 30 acquires the power consumption data of each power consumption branch road 40 according to the preset cycle to with power consumption data transmission to statistics server 20, wherein, the power consumption data of each power consumption branch road 40 includes the power consumption sign and the power consumption that each power consumption branch road 40 corresponds and user's unique sign.
The time length of the preset period is determined according to the line aging degree of the old cell, and the higher the aging degree is, the shorter the time length of the preset period is. The power utilization identifier corresponding to each power utilization branch 40 is used for representing the power utilization attributes of the power utilization branch 40, such as kitchen power utilization, bathroom power utilization, air conditioner sockets and the like. The unique identification of the user is used to characterize the identity of the user. The information is also set in the statistical server 20, so that the electricity consumption data, the electricity consumption branch 40 and the user can be conveniently corresponded.
The statistical server 20 obtains the electricity consumption data sent by each intelligent distribution box 30, packages the electricity consumption data of all electricity consumption branches 40 of each user according to a preset packaging mode according to the electricity consumption identification carried by the electricity consumption data, the electricity consumption amount and the unique identification of the user to obtain an electricity consumption data packet of each user, and packages all the electricity consumption data packets into statistical data packets to be sent to the background server 10. The data size of the electricity consumption data received by the statistics server 20 is huge, and the data is convenient to package through various identifiers in the data.
And S2, extracting the power utilization data of the power utilization branch 40 in each statistical data packet according to the power utilization identification and the unique identification.
And S3, classifying the power utilization data according to a preset power classification method to obtain a power classification data table corresponding to each statistical data packet.
In this embodiment, the preset power classification method is used to classify the power consumption property of the power consumption data so as to reflect the overall power consumption behavior of the old community corresponding to the statistics server 20, and the classification is divided according to the power consumption attributes of each power consumption branch 40, such as domestic power consumption, kitchen and toilet power consumption, and power consumption of high-power electric appliances. It can be understood that the background server 10 stores in advance rules for classifying and dividing various types of power consumption data, so as to divide each type of power consumption data into corresponding classifications, and after classifying and filling the corresponding power consumption data, remember the power classification data table of each statistical data packet, where the power classification data table reflects the overall power consumption condition of the cell or slice area corresponding to the corresponding statistical server 20.
And S4, calculating the weight value corresponding to each power classification data table according to a preset classification weight calculation method.
In the present embodiment, each power classification data table includes a plurality of power classifications and power consumption data corresponding to the power classifications, where the power consumption data includes the number of times of power consumption, power consumption maintaining time, and power consumption, and each power classification is pre-matched with a weight calculation ratio according to power attributes. The weight ratio depends on the importance of evaluating the safety factor, for example, the weight calculation ratio of the power classification corresponding to the power consumption data of the high-power branch 40 is larger, and the weight calculation ratio of the power classification corresponding to the power consumption data of the weak-power branch such as a toilet is smaller. And calculating the power consumption data and the weight calculation ratio to obtain a classification weight value corresponding to each power classification, and adding the classification weight values to obtain the weight value. The weight value can reflect the quality of the electricity consumption behavior, and the higher the weight value is, the better the electricity consumption behavior of the residents of the community or the parcel is on the whole.
And S5, judging whether the highest weight value in each power data table is higher than a preset lowest weight value or not, and if so, executing the step S6.
In this embodiment, the preset lowest weight value is used to evaluate whether the weight value meets the lowest standard, so as to prevent the power utilization behavior of the cell or parcel with the best power utilization behavior among multiple cells or parcels from being still the non-advocated power utilization behavior.
And S6, determining the statistical data packet corresponding to the power data table with the highest weight value as a reference data packet.
And if the weight values of the power data tables corresponding to all the cells or the districts are lower than the preset lowest weight value, no longer determining any statistical data packet as a reference data packet, and automatically matching the reference data packet in the previous period as the reference data packet in the current period.
And S7, determining a reference weight according to the electricity utilization data in the reference data packet.
In this embodiment, the electricity consumption data in the reference data packet is presented in the form of a multidimensional vector, and the basis weight is determined by inputting the electricity consumption data in the reference data packet into a pre-established convolutional neural network, performing identification calculation on the electricity consumption data in the reference data packet based on the convolutional neural network, and outputting the basis weight corresponding to the electricity consumption data in the reference data packet.
And S8, determining a control method of each electricity utilization branch 40 of each user according to the reference weight.
Specifically, the step of determining the control method of each power utilization branch 40 of each user in this embodiment is:
and calculating Jacard similarity coefficients of the statistical data packets and the reference data packets respectively to obtain similarity values of the statistical data packets and the reference data packets, and sequencing according to the similarity values, wherein data in the statistical data packets are presented in a multi-dimensional vector mode.
And distributing an adjusting coefficient for each statistical data packet according to the similarity value and a preset distribution method.
The higher the similarity value is, the closer the approximation degree of the electricity utilization behaviors represented by the statistical data packet and the reference data packet is, the better the electricity utilization behaviors are, and the higher the distributed adjustment coefficient is.
And according to the sequencing sequence of the statistical data packets, sequentially carrying out weight calculation on the power consumption data of each power consumption branch 40 in the statistical data packets according to a preset branch power consumption weight calculation method to obtain branch weights, and calculating the branch weights and the distributed adjustment coefficients to obtain corrected branch weights. The branch electricity utilization weight is calculated by combining the properties of the corresponding electricity utilization branches 40 and the electricity consumption, specifically, corresponding weight factors can be matched for the electricity utilization branches 40 with different properties, and the branch weight is obtained by multiplying the weight factor of each electricity utilization branch 40 by the electricity consumption, so that the branch weight is easy to understand and is smaller as the electricity consumption is higher. Because the overall electricity utilization behaviors of each cell or district are different, the cell or district having good electricity utilization behaviors overall has the branch weight of each electricity utilization branch 40 of the user therein can be adjusted upwards, and the final corrected branch weight is obtained by correcting the adjustment coefficient.
And determining a control method of each electricity utilization branch 40 according to the difference value between the corrected branch weight and the reference weight of each electricity utilization branch 40.
The control method may include adjusting the electricity prices of the corresponding electricity utilization branches 40 and controlling the on-off of the switch of the intelligent distribution box 30, specifically, determining the corresponding control method according to the range where the difference value is located, adjusting the electricity prices of the electricity utilization branches 40 corresponding to the difference value to a preset electricity price when the difference value is located in a first range, and performing on-off control on the electricity utilization branches 40 corresponding to the difference value according to a preset on-off time period when the difference value is located in a second range. In this embodiment, specific numerical values of the first range and the second range are not limited, and it should be noted that the first range and the second range do not have an intersection, and a maximum value of the first range is smaller than a minimum value of the second range. For the electricity utilization branch 40 corresponding to the difference value in the first range, the safety of the electricity utilization behavior of the user on the electricity utilization branch 40 is weak, but the danger degree is not high, a certain restriction needs to be performed, in order to restrict the user from reducing the power consumption of the power utilization branch 40, the power utilization price of the power utilization branch 40 can be increased, and the use of the power utilization equipment on the power utilization branch 40 by the user can be reduced. Under this control method, intelligent power distribution box 30 still gathers each power consumption branch road 40's power consumption and sends to statistics server 20, and statistics server 20 calculates user's power consumption expense according to each power consumption branch road 40's power consumption and the price of electricity that matches.
To the power consumption branch road 40 that the difference value that is in the second scope value corresponds, the power consumption action security of user on this power consumption branch road 40 is extremely poor, and degree of danger is high, needs to intervene in time, can the disconnection power supply of this power consumption branch road 40 of direct control, prevents that danger from taking place.
And S9, packaging all the control methods according to the electricity utilization identification and the unique identification to obtain a control method set corresponding to each statistical server 20 and sending the control method set to the corresponding statistical server 20.
The statistical server 20 extracts the control method corresponding to each user according to the control method set, and manages and controls the power consumption behavior of the corresponding user according to the control method.
It can be understood that, in the power detection control system and method provided in the embodiments of the present invention, power consumption data of each power consumption branch 40 of each user in a plurality of specific areas is collected, and is subjected to centralized analysis and comparison to obtain a power consumption behavior evaluation result in each specific area, a control method of each power consumption branch 40 of each user is determined according to the evaluation result, and the plurality of power consumption branches 40 of each user are directly controlled according to the determined control method. The embodiment of the invention can monitor the power utilization behaviors of each user in a specific area, such as an old cell or a parcel, and improve the problem of line faults caused by non-standard power utilization.
Referring to fig. 4, an embodiment of the present invention provides a power detection control apparatus 21 for performing the steps S1 to S9, where the power detection control apparatus 21 includes:
a receiving module 111, configured to receive the statistics data packet sent by each statistics server 20. The receiving module 111 is configured to perform step S1.
And the extracting module 112 is configured to extract the power utilization data of the power utilization branch 40 in each statistical data packet according to the power utilization identifier and the unique identifier. The extraction module 112 is configured to perform step S2.
The classification module 113 is configured to classify the power consumption data according to a preset power classification method, so as to obtain a power classification data table corresponding to each statistical data packet. The classification module 113 is configured to perform step S3.
And a calculation module 114 for completing various calculation steps. The calculation module 114 is used for executing step S4.
And a judging module 115 for executing various judging logics. The judging module 115 is used for executing the step S5.
A weight determining module 116, configured to complete determination of each weight, and configured to perform steps S6 and S7.
And a control method generation module 117, configured to determine a control method for each electricity utilization branch 40 of each user according to the reference weight. For executing step S8.
And a packing module 118, configured to pack all the management and control methods according to the power consumption identifier and the unique identifier, so as to obtain a management and control method set corresponding to each statistics server 20.
A sending module 119, configured to send the management and control method set to the corresponding statistics server 20. The packing module 118 and the sending module 119 are configured to jointly perform step S9.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes. It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.
It should be understood that, for technical terms which are not noun explanations in the above-mentioned contents, a person skilled in the art can deduce and unambiguously determine the meaning of the present invention from the above-mentioned disclosure, for example, for some values, coefficients, weights and other terms, a person skilled in the art can deduce and determine from the logical relationship between the above and the below, the value range of these values can be selected according to the actual situation, for example, 0 to 1, for example, 1 to 10, for example, 50 to 100, but not limited thereto, and a person skilled in the art can unambiguously determine some preset, reference, predetermined, set and target technical features/technical terms according to the above-mentioned disclosure. For some technical characteristic terms which are not explained, the technical solution can be clearly and completely implemented by those skilled in the art by reasonably and unambiguously deriving the technical solution based on the logical relations in the previous and following paragraphs. The foregoing will therefore be clear and complete to those skilled in the art. It should be understood that the process of deriving and analyzing technical terms, which are not explained, by those skilled in the art based on the above disclosure is based on the contents described in the present application, and thus the above contents are not an inventive judgment of the overall scheme.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Claims (10)
1. An electric power detection control system is characterized by comprising a background server and a plurality of statistical servers, wherein the background server is in communication connection with each statistical server, each statistical server is in communication connection with intelligent distribution boxes of a plurality of users in a detection area, each intelligent distribution box is electrically connected with each power utilization branch in the power utilization areas of the users, each intelligent distribution box comprises a switch, wherein,
the intelligent distribution box is configured to obtain power consumption data of each power consumption branch according to a preset period and send the power consumption data to the statistical server, wherein the power consumption data of each power consumption branch comprises a power consumption identifier and a power consumption amount corresponding to each power consumption branch and the unique identifier of the user;
the statistical server is configured to obtain power consumption data sent by each intelligent distribution box, package the power consumption data of all power consumption branches of each user according to a preset packaging mode according to a power consumption identification, power consumption and the unique identification of the user, wherein the power consumption identification, the power consumption and the unique identification are carried by the power consumption data, obtain power consumption data packets of each user, package all the power consumption data packets into statistical data packets, and send the statistical data packets to the background server;
the background server is configured to receive the statistical data packets sent by the statistical servers, extract the power consumption data of the power consumption branches in each statistical data packet according to the power consumption identification and the unique identification, classify the power consumption data according to a preset power classification method to obtain a power classification data table corresponding to each statistical data packet, calculate a weight value corresponding to each power classification data table according to a preset classification weight calculation method, judge whether the highest weight value in each power classification data table is higher than a preset lowest weight value, determine the statistical data packet corresponding to the power classification data table with the highest weight value as a reference data packet if the highest weight value is higher than the preset lowest weight value, determine a reference weight according to the power consumption data in the reference data packet, determine a control method of each power consumption branch of each user according to the reference weight, package all the control methods according to the power consumption identification and the unique identification to obtain a control method set corresponding to each statistical server, and send the control method set corresponding to each statistical server to the corresponding statistical server;
the statistical server is configured to receive the management and control method set, extract a management and control method corresponding to each user, and manage and control electricity utilization behaviors of the corresponding users according to the management and control method.
2. The power detection control system according to claim 1, wherein the method for determining the control of each power branch of each user according to the reference weight comprises:
calculating Jacard similarity coefficients of the statistical data packets and the reference data packets respectively to obtain similarity values of the statistical data packets and the reference data packets, and sequencing according to the similarity values, wherein data in the statistical data packets are presented in a multi-dimensional vector mode;
distributing an adjusting coefficient for each statistical data packet according to the similarity value and a preset distribution method; according to the sorting sequence of the statistical data packets, carrying out weight calculation on the electricity utilization data of each electricity utilization branch in the statistical data packets according to a preset branch electricity utilization weight calculation method to obtain branch weights, and calculating the branch weights and the distributed adjustment coefficients to obtain corrected branch weights;
and determining a control method of each power utilization branch according to the difference value between the corrected branch weight and the reference weight of each power utilization branch.
3. The power detection control system according to claim 2, wherein the control method includes adjusting the electricity prices of the corresponding power utilization branches and controlling the on/off of switches of the intelligent distribution box, specifically, the control method is determined according to a range in which the difference value is located, when the difference value is located in a first range, the electricity prices of the power utilization branches corresponding to the difference value are adjusted to a preset electricity price, and when the difference value is located in a second range, the power utilization branches corresponding to the difference value are controlled to be on/off according to a preset on/off time period.
4. The power detection control system of claim 3, wherein the intelligent distribution box is further configured to collect the power consumption of each power utilization branch and send the power consumption to the statistical server, and the statistical server calculates the power consumption cost according to the power consumption of each power utilization branch and the matched power price.
5. The power detection control system according to any one of claims 1 to 4, wherein the calculating the weight value corresponding to each power classification data table according to a preset classification weight calculation method includes:
each electric power classification data table comprises a plurality of electric power classifications and electric power data corresponding to the electric power classifications, the electric power data comprise electricity utilization times, electricity utilization maintaining time and electricity utilization amount, each electric power classification is matched with a weight calculation ratio in advance according to electric power attributes, classification weight values corresponding to the electric power classifications are obtained through calculation of the electric power data and the weight calculation ratio, and the classification weight values are added to obtain the weight values.
6. The power detection control system of claim 5, wherein said determining a benchmark weight from the power usage data in the reference data packet comprises:
inputting the electricity utilization data in the reference data packet into a pre-constructed convolutional neural network, identifying and calculating the electricity utilization data in the reference data packet based on the convolutional neural network, and outputting a reference weight corresponding to the electricity utilization data in the reference data packet, wherein the electricity utilization data in the reference data packet is presented in a multi-dimensional vector form.
7. A power detection control method is applied to a background server, the background server is in communication connection with a plurality of statistical servers, each statistical server is in communication connection with intelligent distribution boxes of a plurality of users in a detection area, each intelligent distribution box is electrically connected with each power utilization branch in the power utilization areas of the users, each intelligent distribution box comprises a switch, and the method comprises the following steps:
receiving a statistical data packet sent by each statistical server, wherein the statistical data packet is power consumption data sent by each intelligent distribution box acquired by the statistical server, the power consumption data is power consumption data of each power consumption branch acquired by the intelligent distribution box according to a preset period, the power consumption data of each power consumption branch comprises a power consumption identification and a power consumption amount corresponding to each power consumption branch and a unique identification of a user according to the power consumption identification, the power consumption amount and the unique identification of the user carried by the power consumption data, the statistical server packs the power consumption data of all the power consumption branches of each user according to a preset packing mode to obtain the power consumption data packet of each user, and packs all the power consumption data packets to obtain the statistical data packet;
extracting the electricity utilization data of the electricity utilization branch in each statistical data packet according to the electricity utilization identification and the unique identification;
classifying the electricity utilization data according to a preset electricity classification method to obtain an electricity classification data table corresponding to each statistical data packet;
calculating the weight value corresponding to each power classification data table according to a preset classification weight calculation method;
judging whether the highest weighted value in each power classification data table is higher than a preset lowest weighted value or not, and if so, determining a statistical data packet corresponding to the power classification data table with the highest weighted value as a reference data packet;
determining a benchmark weight according to the electricity utilization data in the reference data packet;
determining a control method of each electricity utilization branch of each user according to the reference weight;
and packaging all the control methods according to the power utilization identification and the unique identification to obtain a control method set corresponding to each statistical server and sending the control method set to the corresponding statistical server so that the statistical server can extract the control method corresponding to each user according to the control method set and manage and control the power utilization behavior of the corresponding user according to the control method.
8. The power detection control method according to claim 7, wherein the method of determining the control of each power branch of each user according to the reference weight includes:
calculating Jacard similarity coefficients of the statistical data packets and the reference data packets respectively to obtain similarity values of the statistical data packets and the reference data packets, and sequencing according to the similarity values, wherein data in the statistical data packets are presented in a multi-dimensional vector mode;
distributing an adjusting coefficient for each statistical data packet according to the similarity value and a preset distribution method; according to the sorting sequence of the statistical data packets, carrying out weight calculation on the electricity utilization data of each electricity utilization branch in the statistical data packets according to a preset branch electricity utilization weight calculation method to obtain branch weights, and calculating the branch weights and the distributed adjustment coefficients to obtain corrected branch weights;
the control method of each power utilization branch is determined according to the difference value between the corrected branch weight of each power utilization branch and the reference weight, the control method comprises the steps of adjusting the electricity price of the corresponding power utilization branch and controlling the on-off of the switch of the intelligent distribution box, specifically, the corresponding control method is determined according to the range where the difference value is located, when the difference value is located in the first range, the electricity price of the power utilization branch corresponding to the difference value is adjusted to be a preset electricity price, and when the difference value is located in the second range, the on-off control of the power utilization branch corresponding to the difference value is performed according to a preset on-off time period.
9. The power detection control method according to claim 7 or 8, wherein the calculating the weight value corresponding to each power classification data table according to a preset classification weight calculation method includes:
each electric power classification data table comprises a plurality of electric power classifications and electric power data corresponding to the electric power classifications, the electric power data comprise electricity utilization times, electricity utilization maintaining time and electricity utilization amount, each electric power classification is matched with a weight calculation ratio in advance according to electric power attributes, classification weight values corresponding to the electric power classifications are obtained through calculation of the electric power data and the weight calculation ratio, and the classification weight values are added to obtain the weight values.
10. The power detection control method of claim 8, wherein the determining a reference weight from the power usage data in the reference data packet comprises:
inputting the electricity utilization data in the reference data packet into a pre-constructed convolutional neural network, identifying and calculating the electricity utilization data in the reference data packet based on the convolutional neural network, and outputting a reference weight corresponding to the electricity utilization data in the reference data packet, wherein the electricity utilization data in the reference data packet is presented in a multi-dimensional vector form.
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