Multi-node energy analysis method, system, medium and equipment

Abstract

The invention provides a multi-node energy analysis method and system, a medium and equipment. The method comprises the steps that a model database is established based on energy consumption data of all electric equipment to generate a plurality of monitoring nodes; acquiring an actual energy consumption value based on the energy consumption data of the plurality of monitoring nodes; obtaining a threshold point of the actual energy consumption value and a standard consumption value prompt point to judge the energy use condition of the monitoring node; and analyzing an abnormal reason based on the energy use condition to form a visual data set. According to the multi-node energy analysis method and system, the medium and the equipment provided by the invention, a plurality of monitoring nodes can be redefined in a BI system in a data modeling manner, and energy consumption can be monitored in real time, so that the energy consumption degree can be accurately determined, and more energy-saving strategies can be directionally mined.

Description

Technical Field

[0001] The present application relates to the field of energy technology, and more particularly to an energy analysis method, system, medium and device for multi-node energy analysis. Background Art

[0002] The essence of business intelligence (BI) is a technology that effectively extracts information from data and discovers knowledge from information in a timely manner to provide support for decision-making. Business intelligence is usually understood as a tool that converts existing data in an enterprise into knowledge and helps the enterprise make wise business decisions. The data discussed here include orders, inventory, transaction accounts, customers and suppliers from the enterprise's business system, data from the industry and competitors of the enterprise, and various data from other external environments in which the enterprise is located. The business decisions that business intelligence can assist can be either operational, tactical or strategic. In order to convert data into knowledge, it is necessary to use technologies such as data warehouses, online analytical processing (OLAP) tools and data mining. Therefore, from a technical perspective, BI is the comprehensive application of technologies such as data warehouses, OLAP and data mining.

[0003] Existing energy analysis is still at the stage of monitoring and analyzing a single node. For multiple electrical devices, the monitoring and analysis efficiency is still not high enough, and the existing methods are difficult to obtain energy consumption within a certain period of time, and the timeliness is low. Therefore, for large enterprises, as the number of electrical devices continues to increase, how to use the BI system for energy consumption data analysis becomes particularly important. Summary of the invention

[0004] The purpose of this application is to provide a multi-node energy analysis method, system, medium and equipment to solve the technical problem that the existing technology cannot perform multi-node energy monitoring and analysis.

[0005] To achieve the above-mentioned purpose and other related purposes, the first aspect of the present application provides a multi-node energy analysis method, including establishing a model database based on the energy consumption data of each electrical equipment to generate multiple monitoring nodes; obtaining actual energy consumption values ​​based on the energy consumption data of multiple monitoring nodes; obtaining threshold points and standard consumption value prompt points of the actual energy consumption values ​​to determine the energy usage of the monitoring nodes; and analyzing abnormal causes based on the energy usage to form a visual data set.

[0006] In one embodiment of the first aspect, establishing a model database based on energy consumption data to generate multiple monitoring nodes includes: obtaining current energy consumption data characteristics based on the energy consumption data of each electrical device; projecting the current energy consumption data characteristics based on the feature analysis standard of the three-dimensional model and encrypting them to form a model database; and generating multiple monitoring nodes individually paired with each electrical device based on the model database.

[0007] In an embodiment of the first aspect, obtaining the actual energy consumption value based on the energy consumption data of multiple monitoring nodes includes: generating thermal energy information of each electrical device based on the energy consumption data; and obtaining the actual energy consumption value of the current device based on the thermal energy information and the total energy consumption of the current device.

[0008] In an embodiment of the first aspect, obtaining the threshold point of the actual energy consumption value and the standard consumption value prompt point to determine the energy usage of the monitoring node includes: if the threshold point of the actual energy consumption value is greater than the standard consumption value prompt point, determining the corresponding abnormal monitoring node; if the threshold point of the actual energy consumption value is not greater than the standard consumption value prompt point, determining the corresponding normal monitoring node; wherein, the standard consumption value prompt point corresponds to the total energy consumption of the current device.

[0009] In an embodiment of the first aspect, analyzing the abnormal cause based on the energy usage to form a visualization data set includes: forming an abnormal cause result set based on the energy activity trajectory of the abnormal monitoring node; performing data conversion on the abnormal cause result set and configuring parameters to form a visualization data set

[0010] In an embodiment of the first aspect, forming an abnormal cause result set based on the energy activity trajectory of the abnormal monitoring node includes: performing node tracking and node dimensionality reduction scanning on the historical energy activity trajectory of the abnormal monitoring node to establish a future energy activity trajectory change trend diagram.

[0011] In an embodiment of the first aspect, the configuration parameters include an extraction amount, an extraction frequency, an extraction range, and an extraction object.

[0012] The second aspect of the present application provides a multi-node energy analysis system, characterized in that it includes a generation module for establishing a model database based on the energy consumption data of each electrical device to generate multiple monitoring nodes; a monitoring module for obtaining actual energy consumption values ​​based on the energy consumption data of multiple monitoring nodes; a judgment module for obtaining threshold points and standard consumption value prompt points of the actual energy consumption values ​​to judge the energy usage of the monitoring nodes; and an analysis module for analyzing abnormal causes based on the energy usage to form a visual data set.

[0013] The third aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the multi-node energy analysis method described in the first aspect of the present application.

[0014] The fourth aspect of the present application provides an electronic device, comprising: a memory storing a computer program; a processor communicatively connected to the memory, and executing the multi-node energy analysis method described in the first aspect of the present application when calling the computer program.

[0015] As described above, the multi-node energy analysis method, system, medium and equipment provided in the embodiments of the present application have the following beneficial effects: through feature collection under data modeling, the energy consumption within a certain period of time can be obtained in a timely manner with high timeliness, and by establishing multiple monitoring nodes, monitoring and analysis stages under multiple monitoring nodes can be generated. For multiple electrical equipment, the monitoring and analysis efficiency is significantly improved, and energy consumption can be monitored in real time, so that the degree of energy consumption can be accurately determined, and more energy-saving strategies can be explored in a targeted manner, which has certain market promotion prospects and practical application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Shown is a flow chart of a multi-node energy analysis method in an embodiment of the present application.

[0017] Figure 2 Shown is a flow chart of a multi-node energy analysis method in an embodiment of the present application.

[0018] Figure 3 Shown is a flow chart of a multi-node energy analysis method in an embodiment of the present application.

[0019] Figure 4 Shown is a flow chart of a multi-node energy analysis method in an embodiment of the present application.

[0020] Figure 5 Shown is a structural schematic diagram of a multi-node energy analysis system in an embodiment of the present application.

[0021] Figure 6 Shown is a schematic diagram of the structure of an electronic device in an embodiment of the present application.

[0022] Component number description

[0023] 20 Generate Module

[0024] 30 Monitoring module

[0025] 40 Judgment module

[0026] 50 Analysis Modules

[0027] 90 Electronic equipment

[0028] 901 Memory

[0029] 902 processor

[0030] 903 Display

[0031] Steps S1 to S4

[0032] Steps S11 to S13

[0033] Steps S21 to S22

[0034] Steps S41 to S42 DETAILED DESCRIPTION

[0035] The following describes the embodiments of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0036] It should be noted that the diagrams provided in the following embodiments are only schematic illustrations of the basic concept of the present application. The diagrams only show the components related to the present application rather than the number, shape and size of the components in actual implementation. The type, quantity and proportion of each component in actual implementation can be changed at will, and the component layout type may also be more complicated. In addition, in this article, relational terms such as "first", "second", etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0037] The present application provides a multi-node energy analysis method, system, medium and equipment that can be used on a BI system, redefine multiple monitoring nodes in a data modeling manner, can monitor energy consumption in real time, and can also obtain energy consumption within a certain period of time, so as to accurately determine the degree of energy use and dig out more energy-saving strategies in a targeted manner.

[0038] Next, the multi-node energy analysis method, system, medium and device provided by the present application will be described by way of specific embodiments and drawings.

[0039] like Figure 1 As shown, in one embodiment, the multi-node energy analysis method of the present application includes steps S1 to S4:

[0040] S1: A model database is established based on the energy consumption data of each electrical device to generate multiple monitoring nodes.

[0041] Specifically, Figure 2 As shown, step S1 includes steps S11 to S13:

[0042] S11: Acquire current energy consumption data characteristics based on the energy consumption data of each electrical device.

[0043] Specifically, the energy consumption data of each electrical device under the current energy data acquisition instrument is collected, the acquired energy consumption data is cleaned and sorted, and then low-pass filtered to finally obtain the current energy consumption data characteristics.

[0044] S12: Projecting the current energy consumption data features based on the feature analysis standard of the three-dimensional model and encrypting them to form a model database.

[0045] Specifically, in one embodiment, the blank three-dimensional model of the BI system is labeled and classified according to the current energy consumption data characteristics, and the current energy consumption data characteristics are projected onto the pre-labeled and divided areas according to the feature analysis standards in the original three-dimensional model library. After the target coordinate system is selected, the current coordinate system is encrypted to form a model database.

[0046] Specifically, the implementation method of encrypting the current coordinate system includes: digital encryption.

[0047] Specifically, before digital encryption, a specific encryption algorithm is set and loaded into the control device.

[0048] S13: Generate a plurality of monitoring nodes individually paired with each of the electrical devices based on the model database.

[0049] Specifically, for example, monitoring node a corresponds to monitoring device Y1, which supplies electrical equipment X1 and X2. After actual investigation and research, the attributes of the monitoring node are redefined by data accumulation in data modeling, so that each monitoring node and each electrical equipment can be paired individually, and finally an energy consumption visualization panel is formed under the data modeling, so as to better monitor the energy consumption of electrical equipment individually and realize precise energy use.

[0050] S2: Obtaining actual energy consumption values ​​based on energy consumption data of the plurality of monitoring nodes.

[0051] Specifically, according to the collected energy consumption data characteristics, the operating power and energy consumption parameters of the current electrical equipment are obtained, and then the actual energy consumption value in the current period is determined.

[0052] Specifically, the energy consumption parameters include the specific heat, initial temperature value and final temperature value of the current electrical equipment.

[0053] Specifically, after data modeling is implemented in step S1, in step S2, the numerical values ​​corresponding to the operating power and energy consumption parameters of the current electrical equipment are input into the model database to obtain the actual energy consumption value of the electrical equipment in the current period.

[0054] Specifically, Figure 3 As shown, step S2 includes step S21 and step S22:

[0055] S21: Generate thermal energy information of each electrical device based on the energy consumption data.

[0056] Specifically, the thermal energy information of each electrical device is generated based on the energy consumption parameters.

[0057] Specifically, assuming that the thermal energy information of the electrical equipment is Q, then:

[0058] Q=c·m·(t1-t0)

[0059] Wherein, c is the specific heat of the electrical equipment, m is the mass, t1 is the final temperature value of the electrical equipment, and t0 is the initial temperature value of the electrical equipment.

[0060] S22: Acquire the actual energy consumption value of the current device based on the thermal energy information and the total energy consumption of the current device.

[0061] Specifically, for each monitoring node, the working current and working voltage of the corresponding electrical equipment when it is operating normally are obtained. After preprocessing the working current and working voltage, the actual power of the current electrical equipment is calculated based on the power factor, that is, the total energy consumption of the current equipment Q a .

[0062] Afterwards, the actual energy consumption value of the current device is calculated based on the thermal energy information and the total energy consumption of the current device.

[0063] Specifically, actual energy consumption value = total energy consumption value - thermal energy information. That is, let the actual energy consumption value be Q c , then:

[0064] Q c =Q a -Q

[0065] S3: Obtain the threshold value of the actual energy consumption value and the prompt point of the standard consumption value to determine the energy usage of the monitoring node.

[0066] Specifically, in one embodiment, a threshold point under the actual energy consumption value of the current device is established in the BI system configuration table, and a standard consumption value prompt point corresponding to the total energy consumption of the current device is established to determine the energy usage of the monitoring node.

[0067] It should be noted that the standard consumption value prompt point corresponds to the total energy consumption when the current equipment is working normally.

[0068] Specifically, if the threshold value of the actual energy consumption value is greater than the standard consumption value prompt point, the corresponding abnormal monitoring node is judged, an alarm signal is generated, and a remote alarm is performed through wireless transmission.

[0069] Specifically, if the threshold point of the actual energy consumption value is not greater than the standard consumption value prompt point, the corresponding normal monitoring node is judged and no alarm signal is generated at this time.

[0070] S4: Analyze abnormal causes based on the energy usage to form a visualization data set.

[0071] Specifically, Figure 4 As shown, step S4 includes step S41 and step S42:

[0072] S41: forming an abnormal cause result set based on the energy activity trajectory of the abnormal monitoring node.

[0073] Specifically, node tracking and node dimension reduction scanning are performed on the energy activity trajectories of abnormal monitoring nodes.

[0074] Specifically, the abnormal monitoring nodes are diagnosed individually, and the historical energy activity trajectories under the abnormal monitoring nodes are checked, and the next activity trend and activity range of the energy activity trajectory source are analyzed to establish a changing trend diagram of the future energy activity trajectory.

[0075] S42: Performing data conversion on the abnormal cause result set and configuring parameters to form a visual data set.

[0076] Specifically, data conversion is performed on the abnormal cause result set, and after configuring parameters, a visual data set is generated and transmitted to a memory.

[0077] Specifically, the abnormal cause result set is converted into the real energy consumption data information of the current electrical equipment. After configuring the parameters, a visual data set is generated, displayed on the energy consumption data panel, and transmitted to the storage device. In this way, the energy consumption of each electrical equipment corresponding to multiple monitoring nodes can be monitored in real time, accurate energy use can be achieved, and more energy-saving strategies can be explored in a targeted manner.

[0078] Specifically, the configuration parameters include energy extraction amount, energy extraction frequency, energy extraction range, and energy extraction object.

[0079] like Figure 5 As shown, the present application also provides a multi-node energy analysis system, including a generation module 20 and a monitoring module 30 , a judgment module 40 and an analysis module 50 .

[0080] The generation module 20 is used to establish a model database based on the energy consumption data of each electrical device to generate multiple monitoring nodes.

[0081] The monitoring module 30 is used to obtain the actual energy consumption value based on the energy consumption data of the plurality of monitoring nodes;

[0082] The judgment module 40 is used to obtain the threshold value of the actual energy consumption value and the prompt point of the standard consumption value to judge the energy usage of the monitoring node;

[0083] The analysis module 50 is used to analyze abnormal causes based on the energy usage to form a visual data set.

[0084] Specifically, in one embodiment, the generation module 20 obtains the energy consumption data of each electrical device, and obtains the current energy consumption data characteristics after removing impurities, sorting, and low-pass filtering. Then, the generation module 20 projects the current energy consumption data characteristics based on the characteristic analysis standard of the three-dimensional model and encrypts them to form a model database, and generates a plurality of monitoring nodes that are individually paired with each electrical device. The monitoring module 30 generates thermal energy information based on the energy consumption data, and obtains the actual energy consumption value of the current device based on the thermal energy information and the total energy consumption of the current device.

[0085] At this time, the judgment module 40 will judge the energy usage of the electrical equipment corresponding to the monitoring node. If the threshold point of the actual energy consumption value is greater than the standard consumption value prompt point, the corresponding abnormal monitoring node is judged, and an alarm signal is generated at this time, and a remote alarm is made through wireless transmission; if the threshold point of the actual energy consumption value is not greater than the standard consumption value prompt point, the corresponding normal monitoring node is judged, and no alarm signal is generated at this time.

[0086] Among them, for the abnormal monitoring nodes, the analysis module 50 will perform node tracking and node dimension reduction scanning on the energy activity trajectory of the abnormal monitoring nodes.

[0087] Specifically, the analysis module 50 performs a separate diagnosis on the abnormal monitoring node, checks the historical activity trajectory of the energy activity trajectory source under the abnormal monitoring node, and analyzes the next activity trend and activity range of the energy activity trajectory source, thereby establishing a change trend diagram of the future energy activity trajectory. At the same time, the analysis module 50 performs data conversion on the abnormal cause result set, generates a visual data set after configuring parameters, and transmits it to the memory.

[0088] It should be noted that the configuration parameters include energy extraction amount, energy extraction frequency, energy extraction range and energy extraction object.

[0089] The present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the multi-node energy analysis method provided in the embodiment of the present application is implemented.

[0090] In the present application, any combination of one or more storage media may be used. The storage medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a RAM, a ROM, an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or device.

[0091] The present application also provides an electronic device. Figure 6 The diagram is a schematic diagram of the structure of an electronic device 90 in one embodiment of the present application. Figure 6 As shown, in this embodiment, the electronic device 90 includes a memory 901 and a processor 902 .

[0092] The memory 901 is used to store computer programs; preferably, the memory 901 includes: ROM, RAM, disk, USB flash drive, memory card or CD-ROM and other media that can store program codes.

[0093] Specifically, the memory 901 may include a computer system readable medium in the form of a volatile memory, such as a random access memory (RAM) and / or a cache memory. The electronic device 90 may further include other removable / non-removable, volatile / non-volatile computer system storage media. The memory 901 may include at least one program product, which has a set (e.g., at least one) of program modules, which are configured to perform the functions of the various embodiments of the present application.

[0094] The processor 902 is connected to the memory 901 and is used to execute the computer program stored in the memory 901 so that the electronic device 90 executes the multi-node energy analysis method provided in the embodiment of the present application.

[0095] Preferably, the processor 902 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0096] Preferably, the electronic device 90 in this embodiment may further include a display 903. The display 903 is communicatively connected with the memory 901 and the processor 902, and is used to display a GUI interaction interface related to the multi-node energy analysis method.

[0097] The protection scope of the multi-node energy analysis method described in the present application is not limited to the execution order of the steps listed in this embodiment. All solutions implemented by adding, reducing or replacing steps in the prior art based on the principles of the present application are included in the protection scope of the present application.

[0098] In summary, the embodiments of the present application provide a multi-node energy analysis method, system, medium and device. The multi-node energy analysis method, system, medium and device can automatically batch read the site name, water level, flow data and other water information of the official port water condition data file, and automatically write it to the specified location of other files, which greatly improves the efficiency of water condition data entry and user experience, while reducing the possibility of errors.

[0099] The above embodiments are merely illustrative of the principles and effects of the present application and are not intended to limit the present application. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed in the present application shall still be covered by the claims of the present application.

Claims

1. A multi-node energy analysis method, characterized in that: include: A model database is established based on the energy consumption data of each electrical device to generate multiple monitoring nodes; Acquire actual energy consumption value based on energy consumption data of a plurality of monitoring nodes; Obtaining a threshold value point of the actual energy consumption value and a prompt point of the standard consumption value to determine the energy usage of the monitoring node; The abnormal causes are analyzed based on the energy usage to form a visualization data set.

2. The multi-node energy analysis method according to claim 1, characterized in that: Building a model database based on energy consumption data to generate multiple monitoring nodes includes: Acquiring current energy consumption data characteristics based on the energy consumption data of each electrical device; Projecting the current energy consumption data features based on the feature analysis standard of the three-dimensional model and encrypting them to form a model database; A plurality of monitoring nodes individually paired with each of the electrical devices are generated based on the model database.

3. The multi-node energy analysis method according to claim 1, characterized in that: Acquiring the actual energy consumption value based on the energy consumption data of the plurality of monitoring nodes includes: generating thermal energy information of each electrical device based on the energy consumption data; The actual energy consumption value of the current device is obtained based on the thermal energy information and the total energy consumption of the current device.

4. The multi-node energy analysis method according to claim 3, characterized in that: Obtaining the threshold value of the actual energy consumption value and the prompt point of the standard consumption value to determine the energy usage of the monitoring node includes: If the threshold point of the actual energy consumption value is greater than the prompt point of the standard consumption value, determining the corresponding abnormal monitoring node; If the threshold value of the actual energy consumption value is not greater than the standard consumption value prompt point, the corresponding normal monitoring node is determined; wherein, The standard consumption value prompt point corresponds to the total energy consumption of the current device.

5. The multi-node energy analysis method according to claim 4, characterized in that: Analyzing the abnormal causes based on the energy usage to form a visualization data set includes: Forming an abnormal cause result set based on the energy activity trajectory of the abnormal monitoring node; Data conversion is performed on the abnormal cause result set and parameters are configured to form a visualization data set.

6. The multi-node energy analysis method according to claim 5, characterized in that: The abnormal cause result set formed based on the energy activity trajectory of the abnormal monitoring node includes: The historical energy activity trajectory of the abnormal monitoring node is tracked and scanned by node dimensionality reduction to establish a trend diagram of future energy activity trajectory changes.

7. The multi-node energy analysis method according to claim 5, characterized in that: The configuration parameters include extraction amount, extraction frequency, extraction range and extraction object.

8. A multi-node energy analysis system, characterized in that: include: A generation module, used to establish a model database based on the energy consumption data of each electrical device to generate multiple monitoring nodes; A monitoring module, used for obtaining actual energy consumption values ​​based on energy consumption data of a plurality of monitoring nodes; A judgment module, used to obtain the threshold value of the actual energy consumption value and the prompt point of the standard consumption value to judge the energy usage of the monitoring node; The analysis module is used to analyze abnormal causes based on the energy usage to form a visual data set.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the multi-node energy analysis method according to any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: The electronic device comprises: A memory storing a computer program; A processor is communicatively connected to the memory, and executes the multi-node energy analysis method according to any one of claims 1 to 7 when calling the computer program.

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