CN115578129B - Energy consumption abnormity early warning method and system based on energy Internet - Google Patents
Energy consumption abnormity early warning method and system based on energy Internet Download PDFInfo
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Abstract
The invention provides an energy consumption abnormity early warning method and system based on an energy internet, and relates to the technical field of regional energy management and control.
Description
Technical Field
The invention relates to the technical field of regional energy management and control, in particular to an energy consumption abnormity early warning method and system based on an energy internet.
Background
Because the difference of each regional development, make the region to the demand of diversified energy existence difference, consider energy system's uncertainty and ecological stability, need carry out more accurate, effectual management and control to the energy, regional energy internet is as the deep fusion product of energy system and information integration, including the transmission of the energy, conversion etc., can coordinate the management and control to the diversified energy in the region, in order to improve the management convenience, now, regard energy internet as main energy system, carry out the operation analysis of a plurality of energy networks, but because current analysis is comparatively wide range, mostly the macroscopic aspect, make analysis result adaptability insufficient, can't satisfy all-round energy and use.
In the prior art, when the consumption abnormity early warning of the energy internet is carried out, due to the fact that the whole energy system is not analyzed sufficiently, the analysis of the incidence relation among a plurality of energy networks is not careful, meanwhile, defects exist in the analysis and processing of energy data, the accuracy of an abnormity early warning result is insufficient, and the real-time effectiveness of the result cannot be guaranteed.
Disclosure of Invention
The application provides an energy consumption abnormity early warning method and system based on an energy internet, which are used for solving the technical problems that when the consumption abnormity early warning of the energy internet is carried out in the prior art, due to the fact that the whole energy system is not analyzed sufficiently, the analysis of the incidence relation among a plurality of energy networks is not careful, meanwhile, the analysis and the processing of energy data have flaws, the accuracy of an abnormity early warning result is not sufficient, and the real-time effectiveness of the result cannot be guaranteed.
In view of the above problems, the present application provides an energy consumption abnormality warning method and system based on an energy internet.
In a first aspect, the application provides an energy consumption abnormity early warning method based on an energy internet, the method comprising: connecting an energy operation control platform to obtain regional energy distribution equipment; modeling by using the regional energy distribution equipment to obtain an energy distribution module; performing module connection based on the energy flow direction of each module among the energy distribution modules to obtain an energy distribution topological structure; acquiring an interaction channel set according to the energy distribution topological structure; configuring an early warning threshold value set according to the interaction channel set, wherein the interaction channel set is in one-to-one correspondence with the early warning threshold value set; based on the energy data acquisition device, acquiring energy consumption data of each energy distribution module on the basis of the energy distribution topological structure to obtain an energy consumption data set; and carrying out abnormity identification on the energy consumption data set based on an energy abnormity early warning model generated by the early warning threshold value set, and outputting abnormity early warning information.
In a second aspect, the present application provides an energy consumption abnormity early warning system based on energy internet, the system comprising: the equipment acquisition module is used for connecting the energy operation control platform and acquiring regional energy distribution equipment; the distribution modeling module is used for modeling by the regional energy distribution equipment to obtain an energy distribution module; the structure acquisition module is used for carrying out module connection based on the energy flow direction of each module among the energy distribution modules to acquire an energy distribution topological structure; the channel acquisition module is used for acquiring an interaction channel set according to the energy distribution topological structure; the threshold configuration module is used for configuring an early warning threshold value set according to the interaction channel set, wherein the interaction channel set corresponds to the early warning threshold value set one by one; the data acquisition module is used for acquiring energy consumption data of each energy distribution module on the basis of the energy distribution topological structure based on the energy data acquisition device to obtain an energy consumption data set; and the information output module is used for carrying out abnormity identification on the energy consumption data set based on an energy abnormity early warning model generated by the early warning threshold value set and outputting abnormity early warning information.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
the embodiment of the application provides an energy consumption abnormity early warning method based on energy internet, which is characterized in that an energy operation management and control platform is connected to acquire regional energy distribution equipment, the regional energy distribution equipment is modeled to generate energy distribution modules, the modules are connected according to the energy flow direction of each module to acquire an energy distribution topological structure, and then an interaction channel set is acquired, and the interaction channel set is configured with an early warning threshold value set, wherein the interaction channel set corresponds to the early warning threshold value set one by one, based on an energy data acquisition device, energy consumption data acquisition is performed on each energy distribution module based on the energy distribution topological structure, an energy consumption data set is acquired, based on an energy abnormity early warning model generated by the early warning threshold value set, abnormity identification is performed on the energy consumption data set to output abnormity early warning information, the technical problem that when energy consumption abnormity early warning of the energy internet is performed in the prior art is solved, due to the insufficiency of analysis of an integral energy system, the analysis of the incidence relation among a plurality of energy networks is not careful, meanwhile, flaws exist in the analysis and processing of the abnormity result accuracy is insufficient, the real-time effectiveness of the energy internet is improved, and the analysis of the abnormity early warning process is optimized.
Drawings
Fig. 1 is a schematic flow chart of an energy consumption abnormality early warning method based on an energy internet according to the present application;
fig. 2 is a schematic diagram illustrating a flow of acquiring an interaction channel set in an energy consumption abnormality early warning method based on an energy internet according to the present application;
fig. 3 is a schematic diagram illustrating a configuration flow of an early warning threshold set in an energy consumption abnormality early warning method based on an energy internet according to the present application;
fig. 4 is a schematic structural diagram of a system for early warning of energy consumption abnormality based on an energy internet.
Description of reference numerals: the device comprises an equipment acquisition module 11, a distribution modeling module 12, a structure acquisition module 13, a channel acquisition module 14, a threshold configuration module 15, a data acquisition module 16 and an information output module 17.
Detailed Description
The application provides an energy consumption abnormity early warning method and system based on an energy internet, regional energy distribution equipment is obtained to perform modeling to generate an energy distribution module, an energy distribution topological structure is built, then an interaction channel set is obtained and configured with an early warning threshold value set, an energy consumption data set is collected, an energy abnormity early warning model is generated based on the early warning threshold value set, abnormal early warning information is identified and output in data abnormity, and the method and system are used for solving the technical problems that in the prior art, when consumption abnormity early warning of the energy internet is performed, due to the fact that the whole energy system is not analyzed sufficiently, the incidence relation among a plurality of energy networks is not analyzed finely, meanwhile, defects exist in analysis and processing of energy data, the accuracy of an abnormal early warning result is not sufficient, and the real-time effectiveness of the result cannot be guaranteed.
Example one
As shown in fig. 1, the application provides an energy consumption abnormity early warning method based on energy internet, the method is applied to an energy internet management system, the system is in communication connection with an energy data acquisition device, and the method comprises the following steps:
step S100: connecting an energy operation control platform to obtain regional energy distribution equipment;
specifically, due to differences in development of various regions, requirements of the regions for diversified energy sources are different, the energy sources need to be controlled more accurately and effectively in consideration of uncertainty and ecological stability of an energy system, the energy consumption abnormity early warning method based on the energy internet is applied to the energy internet management system, the system is a system for comprehensive control of the diversified energy sources, the system is in communication connection with the energy data acquisition device, the energy data acquisition device is a device for acquiring real-time energy consumption data, the acquired data is used as source data for abnormity analysis and early warning, firstly, the energy operation control platform is connected, the energy operation control platform is a control platform for energy transmission and conversion, the energy application equipment in a control region is determined, the equipment type and the distribution position of the same energy source are determined, information integration is further performed to generate regional energy distribution equipment, and the acquisition of the regional energy distribution equipment provides a basic basis for subsequent energy distribution analysis.
Step S200: modeling by using the regional energy distribution equipment to obtain an energy distribution module;
step S300: performing module connection based on the energy flow direction of each module among the energy distribution modules to obtain an energy distribution topological structure;
specifically, the regional energy distribution equipment is classified, the corresponding energy distribution equipment is determined and identified based on the energy types, wherein the identification result corresponds to a plurality of equipment types, any type of energy distribution equipment is extracted for modeling, and the energy distribution module is generated.
Furthermore, a certain incidence relation exists between different energy sources, such as energy source replacement and energy source conversion, so that a certain energy flow exists between the constructed energy source distribution modules, for example, wind energy is converted into electric energy, and the like, and partial non-renewable energy sources can be replaced by energy source conversion, so that ecological balance is guaranteed on the basis of maintaining normal social operation, and comprehensive analysis of energy flow is performed on each energy source distribution module, wherein the flow incidence conditions of a plurality of energy source distribution modules, including unidirectional flow and bidirectional flow, may exist, and the energy source distribution modules are connected on the basis of the energy flow direction to form an energy source distribution topological structure, i.e., an integral network structure of energy source distribution, and the acquisition of the energy source distribution topological structure tamps the basis for subsequent energy source interactive analysis, so that the analysis efficiency can be effectively improved.
Step S400: acquiring an interaction channel set according to the energy distribution topological structure;
specifically, the energy distribution modules are connected in an associated manner based on energy flow to generate the energy distribution topological structure, the energy distribution modules are constituent nodes of the topological structure, connection relation analysis is performed on the topological nodes, based on a one-way connection relation, namely only energy one-way flow exists between any two nodes, a one-way interaction channel is constructed between the nodes based on the one-way connection relation, direction identification is performed based on the energy flow direction, based on a two-way connection relation, namely two-way flow exchange of energy exists between any two nodes, the energy interaction ratio of the two-way interaction channel is determined according to the actual situation, a two-way interaction channel is constructed between the corresponding nodes, further, integrated identification is performed on the one-way interaction channel and the two-way interaction channel covered in the energy topological structure, the interaction channel set is obtained, and the obtaining of the interaction channel set provides a basic basis for subsequent interaction analysis between energy networks.
Further, as shown in fig. 2, the step S400 of obtaining the interaction channel set according to the energy distribution topology further includes:
step S410: analyzing the unidirectional connection relation among all topological nodes in the energy distribution topological structure to obtain a unidirectional interaction channel set; and
step S420: analyzing the bidirectional connection relation among all topological nodes in the energy distribution topological structure to obtain a bidirectional interaction channel set;
step S430: and outputting the interaction channel set based on the unidirectional interaction channel set and the bidirectional interaction channel set.
Specifically, the energy distribution topological structure is generated by performing correlation analysis on the energy flow directions among the energy distribution modules, wherein a plurality of topological nodes included in the energy distribution topological structure express a plurality of energy distribution modules, namely a plurality of single energy distribution networks, such as a power network, a natural gas network, a petroleum network and the like, unidirectional connection relation analysis is performed on the topological nodes, namely unidirectional flow of energy only exists between any two topological nodes, a corresponding unidirectional interaction channel is determined, and then the unidirectional interaction channel is subjected to direction identification based on the energy flow direction to generate the unidirectional interaction channel set; similarly, the bidirectional connection relationship between the topological nodes is analyzed, that is, bidirectional flow of energy exists between any two topological nodes, an interaction channel is constructed between the nodes as a bidirectional interaction channel, a plurality of existing bidirectional interaction channels are incorporated into the bidirectional interaction channel set, and then the unidirectional interaction channel set and the bidirectional interaction channel set are integrated to generate the interaction channel set.
Step S500: configuring an early warning threshold value set according to the interaction channel set, wherein the interaction channel set is in one-to-one correspondence with the early warning threshold value set;
specifically, the unidirectional interaction channel set and the bidirectional interaction channel set are extracted based on the interaction channel set, a preset time interval is obtained, historical energy consumption data of unidirectional energy modules connected with the unidirectional interaction channel set are acquired based on the preset time interval, comprehensive evaluation is performed by combining corresponding module attribute information, a unidirectional energy early warning threshold value is generated, historical energy consumption data and historical energy interaction data of bidirectional energy modules connected with the bidirectional interaction channel set are acquired in a similar manner, comprehensive evaluation is performed by combining corresponding module attribute information, a bidirectional energy early warning threshold value is generated, further corresponding identification is performed on the energy early warning threshold value and the corresponding energy module, the early warning threshold value set is generated, the interaction channel set corresponds to the early warning threshold value set one by one, the early warning set is a data evaluation standard for energy interaction, and reference is provided for subsequent real-time energy consumption data abnormity judgment.
Further, as shown in fig. 3, the configuring an early warning threshold value set according to the interaction channel set further includes, in step S500 of the present application:
step S510: configuring a unidirectional energy early warning threshold value by analyzing the energy attribute of the nodes of the unidirectional interaction channel set; and
step S520: performing energy attribute analysis according to the nodes of the bidirectional interaction channel set, and configuring a bidirectional energy early warning threshold;
step S530: and configuring the early warning threshold value set based on the unidirectional energy early warning threshold value and the bidirectional energy early warning threshold value.
Specifically, the method includes performing node association analysis on an energy distribution topological structure to generate the interaction channel set, extracting the unidirectional interaction channel set, performing energy attribute analysis respectively, judging whether the unidirectional interaction channel set belongs to renewable energy or non-renewable energy, configuring unidirectional energy early warning thresholds for each interaction channel in the unidirectional interaction channel set based on the generated interaction channel set, namely performing early warning thresholds for energy application not reaching standards, including energy quantity and energy utilization rate, when the energy is non-renewable energy, strictly controlling energy flow, maximizing energy utilization as much as possible, avoiding energy exhaustion and influencing ecology, such as petroleum, coal mines and the like, and similarly, extracting the bidirectional interaction channel set, when bidirectional interaction of energy exists, performing evaluation based on multiple dimensions to determine whether the energy of each bidirectional interaction channel belongs to renewable energy, performing multi-attribute analysis on energy utilization rate, energy conversion rate and the like, configuring corresponding energy early warning thresholds for each bidirectional interaction channel respectively, performing data early warning on interaction channel interaction data, wherein the bidirectional interaction channel set is determined based on accuracy of configuring thresholds respectively to improve data analysis evaluation, performing multi-attribute analysis on the energy thresholds, and performing further performing bidirectional energy early warning threshold integration analysis on the bidirectional interaction data sets, and generating the bidirectional interaction data early warning thresholds, and performing further performing bidirectional interaction data analysis on the bidirectional interaction data sets.
Further, the step S510 of configuring the unidirectional energy early warning threshold by performing energy attribute analysis on the nodes of the unidirectional interaction channel set further includes:
step S511: acquiring energy attribute information of each unidirectional energy module and historical energy consumption data of each unidirectional energy module according to the unidirectional interaction channel set;
step S512: inputting the energy attribute information of each unidirectional energy module into a unidirectional energy attribute analysis module, wherein the energy analysis indexes of the unidirectional energy attribute analysis module comprise energy value rate and energy conversion rate;
step S513: and outputting the unidirectional energy early warning threshold value by taking the energy value rate and the energy conversion rate as input variables and taking historical energy consumption data of each unidirectional energy module as input quantification.
Specifically, the unidirectional interaction channel set is called, energy attribute information corresponding to energy modules connected with each unidirectional interaction channel, such as that petroleum belongs to non-renewable energy, wind energy belongs to renewable energy and the like, is determined, a preset time interval is set, historical energy consumption data of each unidirectional energy module is acquired based on the preset time interval, furthermore, the energy value rate and the energy conversion rate are used as analysis indexes, a multi-level index interval is determined, the unidirectional energy attribute analysis module is constructed based on the multi-level index interval, the energy attribute information of each unidirectional energy module is input into the unidirectional energy attribute analysis module to ensure objectivity and overall fairness of module analysis results, wherein indexes corresponding to different energy attributes require high requirements, for example, the indexes of non-renewable energy, the module analysis results, namely the energy utilization rate and the energy conversion rate are used as input variables, the acquired historical energy consumption data of each unidirectional energy module are used as input quantification, the unidirectional energy early warning threshold is output through comprehensive evaluation analysis of input parameters, illustratively, a differential fitness function or a parameter evaluation model can be constructed, and the unidirectional energy early warning threshold is analyzed through one-by one-way interaction channel set, wherein the unidirectional energy module historical energy consumption data corresponds to one-by one.
Further, said analyzing the energy attribute according to the node of the bidirectional interaction channel set, and configuring the bidirectional energy early warning threshold, step S520 of the present application further includes:
step S521: acquiring energy attribute information of each bidirectional energy module according to the bidirectional interaction channel set; and
step S522: historical energy consumption data of each bidirectional energy module and historical energy interaction data of each bidirectional energy module;
step S523: inputting the energy attribute information of each bidirectional energy module into a bidirectional energy attribute analysis module, wherein the energy analysis indexes of the bidirectional energy attribute analysis module comprise energy value rate, energy conversion rate and energy interaction rate;
step S524: and outputting the bidirectional energy early warning threshold value by taking the energy value rate, the energy conversion rate and the energy interaction rate as input variables, and taking the historical energy consumption data of each bidirectional energy module and the historical energy interaction data of each bidirectional energy module as input quantitives.
Specifically, the bidirectional interaction channel set is called based on the interaction channel set, energy attribute information corresponding to the energy modules connected with the bidirectional interaction channel is determined, namely whether the energy belongs to renewable energy or not, and data acquisition is further performed on each bidirectional energy module based on the preset time interval, wherein the data acquisition includes historical energy consumption data and historical energy interaction data of each bidirectional energy module, and the data are actual energy use data and have real-time effectiveness.
Further, the energy value rate, the energy conversion rate and the energy interaction rate are used as analysis indexes, multi-level index intervals are respectively determined, the bidirectional energy attribute analysis module, namely an auxiliary tool for performing index analysis on energy attributes is constructed on the basis of the analysis indexes, energy attribute information of each bidirectional energy module is input into the bidirectional energy attribute analysis module, the energy value rate, the energy conversion rate and the energy interaction rate corresponding to each bidirectional energy module are determined through index analysis, index data and the bidirectional energy module are correspondingly identified, the energy value rate, the energy conversion rate and the energy interaction rate are further used as input variables, historical energy consumption data of each bidirectional energy module and historical energy interaction data of each bidirectional energy module are used as input quantities, early warning thresholds of the energy consumption data and the energy interaction data are respectively determined, threshold analysis of each bidirectional energy module is respectively performed, the early warning thresholds and the bidirectional energy module are correspondingly identified, the bidirectional energy early warning thresholds are generated, the judgment standards are respectively set for performing abnormal energy operation interaction based on each bidirectional energy module, and the effective judgment and the judgment efficiency can be guaranteed.
Step S600: based on the energy data acquisition device, acquiring energy consumption data of each energy distribution module on the basis of the energy distribution topological structure to obtain an energy consumption data set;
step S700: and carrying out abnormity identification on the energy consumption data set based on an energy abnormity early warning model generated by the early warning threshold value set, and outputting abnormity early warning information.
Specifically, the energy data acquisition device is a device for acquiring energy consumption data and energy interaction data of the energy modules, traverses the energy distribution topological structure, acquires the energy consumption data of the unidirectional energy modules based on the energy data acquisition device, acquires the energy consumption data and the energy interaction data of the bidirectional energy modules, correspondingly identifies the acquired energy data and the energy modules, and generates the energy consumption data set.
Further, the energy anomaly early warning model is constructed based on machine learning calculation, the early warning threshold value set is input into the energy anomaly early warning model for model improvement and optimization, historical energy consumption data is used as sample data, the sample data is divided into a training set and a verification set, the training set and the verification set are input into the energy anomaly early warning model, model training and verification are performed to enable the output accuracy of the model to reach a preset standard, the constructed energy anomaly early warning model is generated, the energy anomaly early warning model is a multi-level network layer and comprises a data identification layer, a data analysis layer and an early warning output layer, the data analysis layer comprises two analysis modules, data analysis and judgment are respectively performed on the unidirectional energy module and the bidirectional energy module, the energy consumption data set is input into the energy anomaly early warning model, multi-level hierarchical data identification and analysis are performed to determine anomaly early warning information, the anomaly early warning information is output based on the early warning output layer, and data anomaly analysis is performed through the construction model, so that the accuracy and the objective early warning information can be effectively guaranteed.
Further, said performing anomaly identification on the energy consumption data set, and outputting anomaly early warning information, step S700 of the present application further includes:
step S710: classifying the energy consumption data sets to obtain a consumption data set of a unidirectional energy module and a consumption data set of a bidirectional energy module;
step S720: judging whether the consumption data set of the unidirectional energy module is in the unidirectional energy early warning threshold value or not, and if not, acquiring N unidirectional energy modules in abnormal states;
step S730: judging whether the consumption data set of the bidirectional energy module is in the bidirectional energy early warning threshold value or not, and if not, acquiring M bidirectional energy modules in abnormal states;
step S740: and generating the abnormity early warning information by the N unidirectional energy modules and the M bidirectional energy modules.
Specifically, the energy consumption data set is input into the energy abnormity early warning model, the abnormity early warning model comprises the data identification layer, the data analysis layer and the early warning output layer, the data identification and classification are carried out on the input energy consumption data set based on the data identification layer, the consumption data set of the unidirectional energy module and the consumption data set of the bidirectional energy module are generated, the classification result is further transmitted to the data analysis layer, the data analysis layer comprises a unidirectional analysis module and a bidirectional analysis module, the consumption data of the unidirectional energy module are input into the unidirectional analysis module, the consumption data are matched and corresponding to the unidirectional energy early warning threshold value, threshold value comparison is carried out to judge whether the data are in the corresponding unidirectional energy early warning threshold value, if the data are in the corresponding unidirectional energy early warning threshold value, the data are normal, namely the corresponding unidirectional energy module is in a normal operation state, if the data are not in a normal operation state, the unidirectional energy module corresponding to the abnormity data are taken as the N unidirectional energy modules in an abnormal state.
Similarly, the consumption data of the bidirectional energy module is input into the bidirectional analysis module, the consumption data is matched with the bidirectional energy early warning threshold value correspondingly, threshold value comparison is carried out based on a matching result, whether the consumption data are in the corresponding bidirectional energy early warning threshold value or not is judged, if not, the bidirectional energy module corresponding to the consumption data is in an abnormal operation state, M bidirectional energy modules in an abnormal state are obtained, the N unidirectional energy modules and the M bidirectional energy modules are further input into the early warning output layer, abnormal early warning information is generated and output, and the abnormal early warning information is matched with the real-time state of the energy modules and has real-time effectiveness.
Further, step S740 of the present application further includes:
step S741: judging whether the N unidirectional energy modules and the M bidirectional energy modules are abnormally overlapped or not, and if the N unidirectional energy modules and the M bidirectional energy modules are abnormally overlapped, acquiring an identification instruction;
step S742: and according to the identification instruction, identifying and outputting the energy modules with the abnormal overlapping modules.
Specifically, energy consumption data is evaluated and judged, an energy module corresponding to abnormal data is determined, the N unidirectional energy modules and the M bidirectional energy modules are obtained, whether abnormal coincidence exists between the N unidirectional energy modules and the M bidirectional energy channels is further judged, when abnormal coincidence does not exist, early warning information is normally generated and output, when abnormal coincidence exists, the modules are multiple abnormal modules, multiple early warning of the same energy module is avoided, early warning complexity is reduced, adjustment of the early warning information can be completed to achieve single output, early warning orderliness is improved on the basis of not influencing early warning results, identification instructions are generated, the energy modules with abnormal overlapping are identified based on the identification instructions, rapid identification and distinguishing are conveniently conducted, and then associated abnormal data integration is conducted to generate abnormal early warning information to be output.
Example two
Based on the same inventive concept as the energy consumption abnormity early warning method based on the energy internet in the foregoing embodiment, as shown in fig. 4, the application provides an energy consumption abnormity early warning system based on the energy internet, the system includes:
the equipment acquisition module 11 is used for connecting an energy operation control platform to acquire regional energy distribution equipment;
the distribution modeling module 12, the distribution modeling module 12 is configured to model the regional energy distribution equipment to obtain an energy distribution module;
the structure acquisition module 13 is configured to perform module connection based on the energy flow direction of each module between the energy distribution modules, and acquire an energy distribution topology structure;
a channel obtaining module 14, where the channel obtaining module 14 is configured to obtain an interaction channel set according to the energy distribution topology;
a threshold configuration module 15, where the threshold configuration module 15 is configured to configure an early warning threshold set according to the interaction channel set, where the interaction channel set corresponds to the early warning threshold set one to one;
the data acquisition module 16 is used for acquiring energy consumption data of each energy distribution module based on the energy data acquisition device and based on the energy distribution topological structure to obtain an energy consumption data set;
and the information output module 17 is used for performing anomaly identification on the energy consumption data set based on an energy anomaly early warning model generated by the early warning threshold value set and outputting anomaly early warning information.
Further, the system further comprises:
the unidirectional interaction channel acquisition module is used for analyzing unidirectional connection relations among all topological nodes in the energy distribution topological structure to acquire a unidirectional interaction channel set; and
the bidirectional interaction channel acquisition module is used for analyzing the bidirectional connection relationship among all topological nodes in the energy distribution topological structure to acquire a bidirectional interaction channel set;
and the interactive channel acquisition module is used for outputting the interactive channel set based on the unidirectional interactive channel set and the bidirectional interactive channel set.
Further, the system further comprises:
the unidirectional early warning threshold configuration module is used for configuring a unidirectional energy early warning threshold by performing energy attribute analysis on the nodes of the unidirectional interaction channel set; and
the bidirectional early warning threshold configuration module is used for carrying out energy attribute analysis according to the nodes of the bidirectional interaction channel set and configuring a bidirectional energy early warning threshold;
and the early warning threshold configuration module is used for configuring the early warning threshold set based on the unidirectional energy early warning threshold and the bidirectional energy early warning threshold.
Further, the system further comprises:
the information acquisition module is used for acquiring the energy attribute information of each unidirectional energy module and historical energy consumption data of each unidirectional energy module according to the unidirectional interaction channel set;
the unidirectional information input module is used for inputting the energy attribute information of each unidirectional energy module into the unidirectional energy attribute analysis module, wherein the energy analysis indexes of the unidirectional energy attribute analysis module comprise energy value rate and energy conversion rate;
and the unidirectional threshold output module is used for outputting the unidirectional energy early warning threshold by taking the energy value rate and the energy conversion rate as input variables and taking historical energy consumption data of each unidirectional energy module as input quantification.
Further, the system further comprises:
the attribute information acquisition module is used for acquiring the energy attribute information of each bidirectional energy module according to the bidirectional interaction channel set; and
the historical data acquisition module is used for acquiring historical energy consumption data of each bidirectional energy module and historical energy interaction data of each bidirectional energy module;
the bidirectional energy source attribute analysis module is used for analyzing the energy source attribute information of each bidirectional energy source module according to the energy source value rate, the energy source conversion rate and the energy source interaction rate;
and the bidirectional threshold output module is used for outputting the bidirectional energy early warning threshold by taking the energy value rate, the energy conversion rate and the energy interaction rate as input variables, taking historical energy consumption data of each bidirectional energy module and historical energy interaction data of each bidirectional energy module as input quantities.
Further, the system further comprises:
the data classification module is used for classifying the energy consumption data set to obtain a consumption data set of the unidirectional energy module and a consumption data set of the bidirectional energy module;
the unidirectional data judgment module is used for judging whether the consumption data set of the unidirectional energy module is within the unidirectional energy early warning threshold value or not, and if not, acquiring N unidirectional energy modules in abnormal states;
the bidirectional data judgment module is used for judging whether the consumption data set of the bidirectional energy module is in the bidirectional energy early warning threshold value or not, and if not, acquiring M bidirectional energy modules in abnormal states;
and the early warning information generation module is used for generating the abnormal early warning information by using the N unidirectional energy modules and the M bidirectional energy modules.
Further, the system further comprises:
the instruction acquisition module is used for judging whether the N unidirectional energy modules and the M bidirectional energy modules are abnormally overlapped or not, and acquiring an identification instruction if the abnormal overlapping modules exist;
and the module identification module is used for identifying and outputting the energy module with the abnormal overlapping module according to the identification instruction.
In the present specification, through the foregoing detailed description of the energy consumption abnormality early-warning method based on the energy internet, those skilled in the art can clearly know that, in the present embodiment, the energy consumption abnormality early-warning method and system based on the energy internet are provided.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (4)
1. An energy consumption abnormity early warning method based on an energy internet is characterized in that the method is applied to an energy internet management system, the system is in communication connection with an energy data acquisition device, and the method comprises the following steps:
connecting an energy operation control platform to obtain regional energy distribution equipment;
modeling by using the regional energy distribution equipment to obtain an energy distribution module;
performing module connection based on the energy flow direction of each module among the energy distribution modules to obtain an energy distribution topological structure;
acquiring an interaction channel set according to the energy distribution topological structure;
analyzing the unidirectional connection relation among all topological nodes in the energy distribution topological structure to obtain a unidirectional interaction channel set; and
analyzing the bidirectional connection relation among all topological nodes in the energy distribution topological structure to obtain a bidirectional interaction channel set;
outputting the interaction channel set based on the unidirectional interaction channel set and the bidirectional interaction channel set;
configuring an early warning threshold value set according to the interaction channel set, wherein the interaction channel set is in one-to-one correspondence with the early warning threshold value set;
configuring a unidirectional energy early warning threshold value by analyzing the energy attribute of the nodes of the unidirectional interaction channel set;
acquiring energy attribute information of each unidirectional energy module and historical energy consumption data of each unidirectional energy module according to the unidirectional interaction channel set;
inputting the energy attribute information of each unidirectional energy module into a unidirectional energy attribute analysis module, wherein the energy analysis indexes of the unidirectional energy attribute analysis module comprise energy value rate and energy conversion rate;
taking the energy value rate and the energy conversion rate as input variables, taking historical energy consumption data of each unidirectional energy module as input quantification, and outputting the unidirectional energy early warning threshold;
performing energy attribute analysis according to the nodes of the bidirectional interaction channel set, and configuring a bidirectional energy early warning threshold;
acquiring energy attribute information of each bidirectional energy module according to the bidirectional interaction channel set; and
historical energy consumption data of each bidirectional energy module and historical energy interaction data of each bidirectional energy module;
inputting the energy attribute information of each bidirectional energy module into a bidirectional energy attribute analysis module, wherein the energy analysis indexes of the bidirectional energy attribute analysis module comprise an energy value rate, an energy conversion rate and an energy interaction rate;
taking the energy value rate, the energy conversion rate and the energy interaction rate as input variables, taking historical energy consumption data of each bidirectional energy module and historical energy interaction data of each bidirectional energy module as input quantitives, and outputting the bidirectional energy early warning threshold;
configuring the early warning threshold value set based on the unidirectional energy early warning threshold value and the bidirectional energy early warning threshold value;
based on the energy data acquisition device, acquiring energy consumption data of each energy distribution module on the basis of the energy distribution topological structure to obtain an energy consumption data set;
and carrying out abnormity identification on the energy consumption data set based on an energy abnormity early warning model generated by the early warning threshold value set, and outputting abnormity early warning information.
2. The method of claim 1, wherein said identifying anomalies in said energy consumption data set and outputting anomaly warning information comprises:
classifying the energy consumption data sets to obtain a consumption data set of a unidirectional energy module and a consumption data set of a bidirectional energy module;
judging whether the consumption data set of the unidirectional energy module is within the unidirectional energy early warning threshold value, and if not, acquiring N unidirectional energy modules in abnormal states;
judging whether the consumption data set of the bidirectional energy module is in the bidirectional energy early warning threshold value or not, and if not, acquiring M bidirectional energy modules in abnormal states;
and generating the abnormal early warning information by the N unidirectional energy modules and the M bidirectional energy modules.
3. The method of claim 2, wherein the method further comprises:
judging whether the N unidirectional energy modules and the M bidirectional energy modules are abnormally overlapped or not, and if the N unidirectional energy modules and the M bidirectional energy modules are abnormally overlapped, acquiring an identification instruction;
and according to the identification instruction, identifying and outputting the energy modules with the abnormal overlapping modules.
4. The utility model provides an energy consumption abnormity early warning system based on energy internet, which is characterized in that, the system and energy data acquisition device communication connection, the system includes:
the equipment acquisition module is used for connecting the energy operation control platform and acquiring regional energy distribution equipment;
the distribution modeling module is used for modeling by the regional energy distribution equipment to obtain an energy distribution module;
the structure acquisition module is used for carrying out module connection based on the energy flow direction of each module among the energy distribution modules to acquire an energy distribution topological structure;
the channel acquisition module is used for acquiring an interaction channel set according to the energy distribution topological structure;
the unidirectional interaction channel acquisition module is used for analyzing unidirectional connection relations among all topological nodes in the energy distribution topological structure to acquire a unidirectional interaction channel set; and
the bidirectional interaction channel acquisition module is used for analyzing the bidirectional connection relationship among all topological nodes in the energy distribution topological structure to acquire a bidirectional interaction channel set;
the interactive channel acquisition module is used for outputting the interactive channel set based on the unidirectional interactive channel set and the bidirectional interactive channel set;
a threshold configuration module, configured to configure an early warning threshold value set according to the interaction channel set, where the interaction channel set corresponds to the early warning threshold value set one to one;
the unidirectional early warning threshold configuration module is used for configuring a unidirectional energy early warning threshold by analyzing the energy attribute of the nodes of the unidirectional interaction channel set;
the information acquisition module is used for acquiring the energy attribute information of each unidirectional energy module and historical energy consumption data of each unidirectional energy module according to the unidirectional interaction channel set;
the unidirectional information input module is used for inputting the energy attribute information of each unidirectional energy module into the unidirectional energy attribute analysis module, wherein the energy analysis indexes of the unidirectional energy attribute analysis module comprise energy value rate and energy conversion rate;
the unidirectional threshold output module is used for outputting the unidirectional energy early warning threshold by taking the energy value rate and the energy conversion rate as input variables and taking historical energy consumption data of each unidirectional energy module as input quantitives;
the bidirectional early warning threshold configuration module is used for analyzing the energy attribute according to the nodes of the bidirectional interaction channel set and configuring a bidirectional energy early warning threshold;
the attribute information acquisition module is used for acquiring the energy attribute information of each bidirectional energy module according to the bidirectional interaction channel set; and
the historical data acquisition module is used for acquiring historical energy consumption data of each bidirectional energy module and historical energy interaction data of each bidirectional energy module;
the bidirectional energy source attribute analysis module is used for analyzing the energy source attribute information of each bidirectional energy source module according to the energy source value rate, the energy source conversion rate and the energy source interaction rate;
the bidirectional threshold output module is used for outputting the bidirectional energy early warning threshold by taking the energy value rate, the energy conversion rate and the energy interaction rate as input variables, and taking historical energy consumption data of each bidirectional energy module and historical energy interaction data of each bidirectional energy module as input quantities;
an early warning threshold configuration module, configured to configure the set of early warning thresholds based on the unidirectional energy early warning threshold and the bidirectional energy early warning threshold; the data acquisition module is used for acquiring energy consumption data of each energy distribution module on the basis of the energy distribution topological structure based on the energy data acquisition device to obtain an energy consumption data set;
and the information output module is used for carrying out abnormity identification on the energy consumption data set based on an energy abnormity early warning model generated by the early warning threshold value set and outputting abnormity early warning information.
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