CN114897394A - Power consumption monitoring system and method - Google Patents
Power consumption monitoring system and method Download PDFInfo
- Publication number
- CN114897394A CN114897394A CN202210572658.4A CN202210572658A CN114897394A CN 114897394 A CN114897394 A CN 114897394A CN 202210572658 A CN202210572658 A CN 202210572658A CN 114897394 A CN114897394 A CN 114897394A
- Authority
- CN
- China
- Prior art keywords
- data
- report
- electricity
- power consumption
- electric
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 40
- 238000012544 monitoring process Methods 0.000 title claims description 52
- 238000004458 analytical method Methods 0.000 claims abstract description 63
- 238000013500 data storage Methods 0.000 claims abstract description 18
- 238000012545 processing Methods 0.000 claims abstract description 13
- 230000005611 electricity Effects 0.000 claims description 213
- 230000008569 process Effects 0.000 claims description 8
- 230000004044 response Effects 0.000 claims description 6
- 238000007781 pre-processing Methods 0.000 claims description 5
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims description 4
- 229910052799 carbon Inorganic materials 0.000 claims description 4
- 238000004140 cleaning Methods 0.000 claims description 2
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 description 72
- 229910002092 carbon dioxide Inorganic materials 0.000 description 36
- 239000001569 carbon dioxide Substances 0.000 description 36
- 238000007726 management method Methods 0.000 description 27
- 238000004590 computer program Methods 0.000 description 15
- 238000005265 energy consumption Methods 0.000 description 13
- 238000013179 statistical model Methods 0.000 description 11
- 238000003860 storage Methods 0.000 description 7
- 238000010586 diagram Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 5
- 238000011161 development Methods 0.000 description 4
- 238000005259 measurement Methods 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 238000009826 distribution Methods 0.000 description 3
- 238000000638 solvent extraction Methods 0.000 description 3
- 238000007619 statistical method Methods 0.000 description 3
- 238000007792 addition Methods 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000004134 energy conservation Methods 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 238000005192 partition Methods 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 239000002699 waste material Substances 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010835 comparative analysis Methods 0.000 description 1
- 238000003869 coulometry Methods 0.000 description 1
- 238000013079 data visualisation Methods 0.000 description 1
- 230000008034 disappearance Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000010248 power generation Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/283—Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/177—Editing, e.g. inserting or deleting of tables; using ruled lines
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/80—Management or planning
- Y02P90/82—Energy audits or management systems therefor
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Health & Medical Sciences (AREA)
- Databases & Information Systems (AREA)
- Tourism & Hospitality (AREA)
- General Engineering & Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Entrepreneurship & Innovation (AREA)
- Educational Administration (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Game Theory and Decision Science (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Data Mining & Analysis (AREA)
- Artificial Intelligence (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Computational Linguistics (AREA)
- Development Economics (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The utility model relates to the technical field of computers, and provides a power consumption supervisory system and a method, and the power consumption supervisory system comprises: the variable determining module is used for acquiring a basic variable name corresponding to the electric quantity analysis report to be developed; the data acquisition module is used for acquiring basic variable data in the electric enterprise information table and the electric equipment information table through the data warehouse tool according to the basic variable name, wherein the electric enterprise information table and the electric equipment information table are stored in different forms of data storage systems; and the data processing module is used for generating report data of the electric quantity analysis report according to the basic variable data so as to supervise the electric quantity through the report data.
Description
Technical Field
The disclosure relates to the technical field of computers, in particular to a power consumption monitoring system and a power consumption monitoring method.
Background
At present, the energy crisis is becoming more severe, the energy price is increasing, the energy becomes an important factor restricting the development of enterprises, and the energy conservation, consumption reduction and energy cost minimization are becoming huge problems to be faced. Most enterprises often use the mode of patrolling and examining and artifical control to supervise the power consumption condition, waste time and energy, and the time of finding the problem also often lags behind.
How to improve convenience and timeliness of enterprise power consumption supervision is a technical problem which needs to be solved urgently at present.
Disclosure of Invention
In view of this, the embodiments of the present disclosure provide a power consumption monitoring system and method, so as to solve the problems of difficult monitoring and low timeliness of the power consumption in the prior art.
In a first aspect of the embodiments of the present disclosure, a power consumption monitoring system is provided, where the power consumption monitoring system includes: the variable determining module is used for acquiring a basic variable name corresponding to the electric quantity analysis report to be developed; the data acquisition module is used for acquiring basic variable data in the electric enterprise information table and the electric equipment information table through the data warehouse tool according to the basic variable name, wherein the electric enterprise information table and the electric equipment information table are stored in different forms of data storage systems; and the data processing module is used for generating report data of the electric quantity analysis report according to the basic variable data so as to supervise the electric quantity through the report data.
In a second aspect of the embodiments of the present disclosure, a power consumption monitoring method is provided, where the power consumption monitoring method includes: acquiring a basic variable name corresponding to an electric quantity analysis report to be developed; acquiring basic variable data in an electric enterprise information table and an electric equipment information table through a data warehouse tool according to the basic variable name, wherein the electric enterprise information table and the electric equipment information table are stored in data storage systems in different forms; and generating report data of the electric quantity analysis report according to the basic variable data so as to supervise the electric quantity through the report data.
Compared with the prior art, the embodiment of the disclosure has the following beneficial effects: the basic variable data stored in the data storage systems of different forms are obtained through the basic variable names, and the report data is generated according to the basic variable data, so that the power consumption can be monitored conveniently, and the timeliness is high.
Drawings
To more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings needed for the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without inventive efforts.
Fig. 1 is a schematic structural diagram of a power consumption monitoring system provided in an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a report provided by an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of yet another report provided by the disclosed embodiment;
FIG. 4 is a flow chart of a power consumption monitoring method according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the disclosed embodiments. However, it will be apparent to one skilled in the art that the present disclosure may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present disclosure with unnecessary detail.
In the related technology, power utilization enterprises do not know the conditions of power consumption, carbon dioxide emission and the like, and the power consumption analysis has no data support, so that the power utilization condition data and the influence factors thereof cannot be comprehensively analyzed. In addition, the management mode of power consumption enterprise is single, when carrying out power consumption management, and data visualization is not realized to electric quantity and charges of electricity service condition, carbon dioxide emission condition etc to it is difficult to directly perceivedly discover the energy accident that appears in the power consumption in-process, can not carry out the unified management of power consumption condition. In addition, power utilization enterprises often carry out manual inspection on power utilization conditions according to the aspects of daily reports, monthly reports, annual reports and the like, and inspection and monitoring modes are backward.
In order to solve the above problems, the present disclosure provides a power consumption monitoring system and method for efficiently analyzing power usage, timely analyzing and processing energy accidents, and performing energy planning, energy prediction and quality management.
Based on the technical scheme of the embodiment of the disclosure, the power utilization enterprises can combine the reality of the enterprises, and the direction, the target, the key point and the measure of energy-saving management are determined, so that the power utilization management level of the enterprises is improved, and the energy consumption is reduced.
The following is an explanation of technical terms in the detailed description of the present disclosure:
hadoop, a distributed system infrastructure.
HDFS (Hadoop distribution File System, Hadoop distributed File System): a distributed file system stores very large files in a streaming data access mode, storing data in blocks on different machines within a business hardware cluster.
Hive: a Hadoop-based data warehouse infrastructure for processing structured data is generally divided into 4 tiers, with each tier storing tables of different types.
A power usage amount monitoring system according to an embodiment of the present disclosure will be described in detail below with reference to the accompanying drawings.
Fig. 1 is a power consumption monitoring system provided in an embodiment of the present disclosure. As shown in fig. 1, the power consumption amount monitoring system includes:
the variable determining module 101 is configured to obtain a basic variable name corresponding to the electric quantity analysis report to be developed.
Specifically, the power analysis report is developed by a user or a system in a customized manner, and different power analysis reports are different for different basic variables, that is, the power analysis report is a report for a specified basic variable. The electric quantity supervision system can obtain basic variable data in the subsequent data acquisition process according to the names of the specified basic variables.
The data acquiring module 102 is configured to acquire, according to the basic variable name, basic variable data in the power consumption enterprise information table and the power consumption equipment information table through a data warehouse tool, where the power consumption enterprise information table and the power consumption equipment information table may be stored in data storage systems in different forms.
In particular, the data warehouse tool may map structured data files into a table and provide query functionality in a structured-language-like language. Through structured query, the data acquisition module can obtain basic variable data from different forms of data storage systems. These different forms of data storage systems include, but are not limited to, HDFS.
And the data processing module 103 is configured to generate report data of the electric quantity analysis report according to the basic variable data, so as to monitor the electric quantity through the report data.
Specifically, when generating report data according to the basic variable data, part of the basic variable data may be used as a part of the report data without being processed, and part of the variable data may be used as a part of the report data after being processed, where the processing process may be any one or more of difference, sum, product, quotient, and grouping, and is not limited thereto.
According to the technical scheme of the embodiment, the electric quantity supervision system can obtain the basic variable name corresponding to the electric quantity analysis report according to the customized parameters of the electric quantity analysis report, further can query to obtain the basic variable data, and forms report data according to the basic variable data, so that the electricity consumption can be supervised according to the report data, and the electric quantity supervision system is convenient and good in timeliness.
In the embodiment of the present disclosure, the power analysis report may be customized by a user, specifically, the user operates on a front-end interface of the power monitoring system, and in response to the operation, the power monitoring system generates the power analysis instruction. The power consumption monitoring system can further comprise an instruction acquisition module, which is used for acquiring power consumption analysis instructions generated in response to the operation of the user on the front-end interface, wherein the power consumption analysis instructions comprise power consumption analysis instructions of the electric equipment in different areas and/or different time periods in the report form to be subjected to power consumption analysis.
In this embodiment of the present disclosure, the power consumption monitoring system may further include a data preprocessing module and a data storage module, where the data preprocessing module is configured to extract, clean and convert power consumption information of different source ends, and the source end includes any one of the following: the system comprises a business system, a log system and an internet of things system. The data storage module can also be used for storing the electricity utilization information of each electric equipment in different areas into the data storage system.
Specifically, the function of the data preprocessing module is the same as that of the Hive based on the Hadoop, and the data preprocessing module can be used for storing data and then performing data processing such as extraction, cleaning and conversion.
In this disclosure, the variable determination module may be further configured to obtain a basic variable name corresponding to an electric quantity analysis report to be developed according to the electric quantity analysis instruction, where the electric quantity analysis instruction includes a structured data script for structured data query. The base variable names include at least one of: the method comprises the following steps of enterprise name, enterprise type, electric equipment name, planned electricity consumption, actual electricity consumption, electricity completion ratio, electricity consumption area, electricity price, electricity consumption time, electricity fee, electricity environment and carbon emission.
In this embodiment of the disclosure, the data obtaining module may be further configured to obtain, by the structured data query engine, the basic variable data in the power consumption enterprise information table and the power consumption device information table according to the basic variable name.
Based on the technical scheme of the embodiment of the disclosure, different statistical models can be provided to count the power consumption conditions of the electric equipment in different areas and different time periods, so that the power consumption conditions of the electric equipment are analyzed in the area dimension and the time dimension respectively. Based on the statistical models, after the report data corresponding to the statistical models are obtained by adopting the technical scheme disclosed by the invention, the power consumption can be monitored according to the report data.
The statistical model for calculating the entity equipment levels of the root nodes of different stores is as follows, wherein the basic information table of the entity equipment of the root nodes of different stores comprises information such as headquarter name, headquarter ID, region ID, store ID, system code, store name, equipment ID, equipment name, access time, store number, city, store type, operation time, store area, emission factor and the like.
The statistical model named model _ inherent _ report, report _ luminal _ shop _ hop _ hour _ h is a store-hour electricity consumption summary model comprising a headquarter name, a headquarter ID, a region ID, a store ID, a system code, a store name, a device ID, a device name, an access time, a store number, a city in which a region company is located, a business time, a store type, a business time, a store area, a discharge factor, a start electricity reading, an end electricity reading, an electricity quantity, an electricity charge, a carbon dioxide discharge quantity, a unit store area electricity quantity unity ratio, a unit store area electricity charge unity ratio, a unit store area electricity charge ratio, a unit area electricity charge ratio, a plan, planning the electric charge, and partitioning according to the day.
The statistical model named model _ inherent _ report, report _ luminal _ shop _ day _ h is a store day-level electricity consumption summary model, which comprises a headquarter name, a headquarter ID, a region ID, a store ID, a system code, a store name, a device ID, a device name, an access time, a store number, a city where a regional company is located, a business time, a store type, a business time, a store area, a discharge factor, a start electricity reading, an end electricity reading, an electricity quantity, an electricity charge, a carbon dioxide discharge quantity, a unit store area electricity quantity unity ratio, a unit store area electricity charge, a unit rank store area electricity charge unity ratio, a unit store area electricity quantity unity ratio, a unit area electricity charge unity ratio, a unit area electricity quantity, a unit store area electricity quantity, a plan electricity quantity, planning the electricity charge, partitioning according to months and the like.
A statistical model III is a store monthly electricity consumption summary model which comprises a headquarter name, a headquarter ID, a region ID, a store ID, a system code, a store name, an equipment ID, an equipment name, an access time, a store number, a city where a regional company is located, business time, a store type, business time, a store area, a discharge factor, a start electricity reading, an end electricity reading, electricity quantity, electricity charge, carbon dioxide discharge, a unit store area electricity quantity geometric proportion, a unit store area electricity charge, a unit store area ranking store area electricity charge geometric proportion, a unit store area electricity quantity geometric proportion, a unit area electricity charge geometric proportion, a unit area electricity charge proportion, a unit area electricity quantity plan, planning the electricity charge, partitioning by year and the like.
The statistical model named model _ inherent _ report, report _ luminal _ shop _ year _ h is a store annual electricity consumption summary model, and comprises a headquarter name, a headquarter ID, a region ID, a store ID, a system code, a store name, a device ID, a device name, an access time, a store number, a city where a regional company is located, a business time, a store type, a business time, a store area, a discharge factor, a start electricity reading, an end electricity reading, an electricity quantity, an electricity charge, a carbon dioxide discharge quantity, a unit store area electricity quantity unity ratio, a unit store area electricity charge unity ratio, a unit store area electricity charge ratio, a unit area electricity charge ratio, a plan, planning electric charge, etc.
The following is a statistical model for calculating various time dimensions of different regional levels, including day, month and year level data.
The statistical model five named model _ inherent _ report, report _ gross _ area _ all _ h is a regional and all-time-dimension electricity utilization summarizing model and comprises information such as headquarter names, headquarter IDs, regions, region IDs, region city IDs, calculation periods, service time, store numbers, total store areas, electricity quantity, electricity charge, emission quantity, electricity quantity proportion, electricity charge proportion, highest daytime temperature, lowest nighttime temperature and average humidity.
The model _ initial _ report _ gross _ all _ h is a summary model of electricity utilization in each time dimension of headquarters, and comprises the following components: headquarter name, headquarter ID, calculation cycle, business time, store number, total store area, electricity quantity, electricity charge, emission quantity, electricity quantity proportion, electricity charge proportion, daytime highest temperature, nighttime lowest temperature, average humidity and other information.
The following model is used for calculating the electric quantity details of all entity equipment of the two-level store, wherein the detailed information table of all entity equipment of the two-level store comprises the following steps: headquarters name, headquarters ID, area ID, store ID, system code, store name, store number, equipment ID, equipment name, and the like.
The model seven is a store subentry day-level electricity utilization summary model table and comprises the following components: headquarters name, headquarters ID, area ID, store ID, system code, store name, store number, equipment ID, equipment name, service time, start power, end power, power fraction, power ring ratio, partition (monthly), and the like.
The model eight is a store itemized monthly electricity usage summary model table, and comprises: headquarters name, headquarters ID, area ID, store ID, system code, store name, store number, equipment ID, equipment name, service time, start power, end power, power fraction, power ring ratio, partition (by year), etc.
The statistical model nine (named model _ inherent _ report, report _ luminal _ device _ year _ h) is a store itemized annual electricity usage summary model table, and comprises: the information includes a headquarter name, a headquarter ID, a region ID, a store ID, a system code, a store name, a store number, an equipment ID, an equipment name, a service time, a start power amount, an end power amount, a power amount ratio, a power amount ring ratio and the like.
In the embodiment of the present disclosure, the power consumption enterprise information table and the power consumption equipment information table may be stored in the HDFS. Based on the technical scheme of the embodiment of the disclosure, basic variable data can be inquired in the HDFS, and electric quantity analysis is developed. The following is an example of a power analysis report in the embodiments of the present disclosure.
One type of the electric quantity analysis report is a headquarter detail report, and the following is a detailed explanation of two headquarter detail reports:
as shown in fig. 2, the report one with the sub-type monthly statement includes information such as area, total store number (store), total electricity (kWh), total electricity charge (unit), total carbon dioxide emission, average electricity/store (kWh/store), average electricity/store (unit/store), average carbon dioxide emission/store, total electricity identity ratio (%), and total electricity identity ratio (%).
Wherein, in the embodiments of the present disclosure, the emission amount of carbon dioxide is in units of tons of CO 2 . The information in the report is report data, the report data is obtained according to basic variable data, and the basic variable data is data corresponding to the names of the basic variables such as enterprise names, enterprise types, electric equipment names, planned electricity consumption, actual electricity consumption, electricity quantity completion ratios, electricity consumption areas, electricity prices, electricity consumption time, electricity charges, electricity consumption environments, carbon emission and the like.
The report II with the sub-type of annual newspaper comprises information such as an area, total store number (stores), total electric quantity (kWh), total electric charge (yuan), total carbon dioxide emission, average electric quantity/store (KWh/store), average electric charge/store (yuan/store), average carbon dioxide emission/store, total electric quantity identity ratio (%), total electric charge identity ratio (%), and the like.
In the headquarter detailed report, headquarter detailed information is obtained according to the monthly report and the annual report, so that the acquisition, management and analysis of energy consumption information can be realized, the power consumption and carbon dioxide emission conditions of an enterprise can be mastered in real time, equipment can be maintained preventively through the comparative analysis of the energy consumption information, the normal operation of production and management is guaranteed, and the energy consumption management level and the equipment management level of the enterprise are improved.
One type of the electric quantity analysis report is an area detail report, and the following is a detailed explanation of four area detail reports:
as shown in fig. 3, the third report is a schematic diagram of the third report, the third report with the subtype of daily report comprises an area, a report period, a shop number, a shop name, a shop type, an operation time, a store area (a square meter), a shop area (a square meter), a start electricity reading (kWh), an end electricity reading (kWh), an electricity quantity (kWh), an electricity charge (yuan), an average electricity price (yuan/kWh), a carbon dioxide discharge amount, a unit store area electricity quantity (kWh/square meter), a unit store area electricity quantity same ratio (%), a unit store area electricity charge (yuan/square meter), a unit store area electricity charge same ratio (%), a unit store area carbon dioxide discharge amount, carbon dioxide emission per unit store area, electricity per unit store area ranking and the like.
The report four with the subtype of monthly report comprises information such as an area, a report period, a shop number, a shop name, a shop type, operation time, a sales field area (a square meter), a shop area (a square meter), a beginning electricity quantity reading (kWh), an ending electricity quantity reading (kWh), an electricity quantity (kWh), an electricity charge (yuan), an average electricity price (yuan/kWh), carbon dioxide discharge, unit sales field area electricity quantity (kWh/square meter), unit sales field area electricity quantity per square meter (%), unit shop area electricity quantity per square meter (kWh/square meter), unit shop area electricity quantity per square meter (%), unit sales field area electricity charge (yuan/square meter), unit shop area electricity discharge quantity per square meter (%), unit shop area carbon dioxide discharge, unit shop area electricity quantity per square, unit sales field ranking and the like.
The report five with the subtype of annual report comprises an area, a report period, a shop number, a shop name, a shop type, operation time, a sales field area (square meter), a shop area (square meter), a beginning electricity quantity reading (kWh), an ending electricity quantity reading (kWh), an electricity quantity (kWh), an electricity charge (yuan), an average electricity price (yuan/kWh), carbon dioxide discharge, unit sales field area electricity quantity (kWh/square meter), unit sales field area electricity quantity per square meter (%), unit shop area electricity quantity per square meter (kWh/square meter), unit shop area electricity quantity per square meter (%), unit sales field area electricity charge (yuan/square meter), unit shop area electricity discharge per square meter (%), unit shop area carbon dioxide discharge capacity per square meter, unit shop area electricity quantity per square meter and the like.
The report six with the subtype of daily report-time period comprises a region, a report period, a shop number, a shop name, a shop type, operation time, a sales field area (square meter), a shop area (square meter), a beginning electricity reading (kWh), an ending electricity reading (kWh), an electricity quantity (kWh), an electricity charge (yuan), an average electricity price (yuan/kWh), carbon dioxide discharge, unit sales field area electricity quantity (kWh/square meter), unit sales field area electricity quantity same ratio (%), unit shop area electricity quantity (kWh/square meter), unit sales area electricity quantity same ratio (%), unit sales field area electricity charge (yuan/square meter), unit sales field area electricity charge same ratio (%), unit area shop electricity charge (yuan/square meter), unit area electricity charge same ratio (%), unit sales field area carbon dioxide discharge quantity and unit shop area carbon dioxide discharge, ranking the area electricity of the unit shop and the like.
In the area detail report, area detail information is obtained according to daily reports, monthly reports, annual reports and daily report-time periods, so that energy management links can be reduced, energy management processes are optimized, and enterprises in the energy field can realize optimization and transformation of energy monitoring and energy management processes on the basis of information analysis, and provide scientific and rigorous data support for objectively evaluating the energy consumption levels of headquarters, areas and stores and providing energy consumption reform schemes for the enterprises.
One type of the electric quantity analysis report is an area statistical report, and the following is a detailed explanation of two types of area statistical reports:
the seventh report form with the subtype of year includes information such as the area, the year, the total shop number (shop), the total electric quantity (kWh), the total electric charge (yuan), the total carbon dioxide emission, the average electric quantity/shop (kWh/shop), the average electric charge/shop (yuan/shop), the average carbon dioxide emission/shop, the total electric quantity unity ratio (%), the total electric charge unity ratio (%), the maximum temperature (deg.c), the minimum temperature (deg.c), and the average humidity (% RH). The report eight with the subtype monthly includes information such as area, month, total shop number (shop), total electric quantity (kWh), total electric charge (yuan), total carbon dioxide emission, average electric quantity/shop (kWh/shop), average electric charge/shop (yuan/shop), average carbon dioxide emission/shop, total electric quantity unity ratio (%), total electric charge unity ratio (%), highest temperature (. degree.C.), lowest temperature (. degree.C.), average humidity (% RH), and the like.
In the regional statistical report, regional statistical information is obtained year by year and month by month, so that the operation management cost of the energy system can be reduced, and the labor productivity can be improved. The scale of industrial enterprises is huge, energy consumption equipment is numerous, areas are criss-cross, the workload of operation, maintenance and management by means of traditional means is large, and the cost is high. The establishment of the power utilization management system of the industrial enterprise can simplify energy operation management, reduce the human input of daily management, save human resource cost and improve labor productivity.
One type of the electric quantity analysis report is an area store plan report, and the following is a detailed explanation of two area store plan reports:
the report nine whose sub-type is monthly report includes information such as area, report period, store number, store type, time of operation, planned electricity amount (kWh), planned electricity rate (kWh), actual electricity amount (kWh), electricity completion ratio (%), actual electricity rate (yuan), and electricity completion ratio (%).
The report ten with the sub-type of electricity detail includes information such as store number, store name, business time, starting electricity reading (kWh), ending electricity reading (kWh), electricity (kWh), average electricity price (yuan/kWh), electricity charge (yuan) and the like.
In the regional store plan report, regional store plan information can be obtained, so that the energy consumption cost of an enterprise is controlled, and the sustainable development of the enterprise is promoted. Through scientific data report forms and analysis, the power utilization enterprises can optimize the energy management mode and method, improve the energy use mode, know the energy demand and consumption condition of the enterprises in real time, and effectively reduce the waste of ineffective energy.
One type of the electric quantity analysis report is a store statistical report, and the following is a detailed explanation of three store statistical reports:
the report form eleven with the subtype of year-by-year comprises information such as a shop number, a shop name, a shop type, service time (year), a sales field area (square meter), a shop area (square meter), a beginning electric quantity reading (kWh), an ending electric quantity reading (kWh), an electric quantity (kWh), an electric charge (yuan), an average electricity price (yuan/kWh), carbon dioxide discharge amount, unit sales field area electric quantity (kWh/square meter), unit sales field area electric quantity same proportion (%), unit shop area electric quantity (kWh/square meter), unit shop area electric quantity same proportion (%), unit sales field area electric charge (yuan/square meter), unit sales field area electric charge same proportion (%), unit shop area electric charge (yuan/square meter), unit shop area electric charge same proportion (%), unit sales field area carbon dioxide discharge amount, unit shop area carbon dioxide discharge amount and the like.
The report twelve with the subtype of month-by-month comprises the store number, the store name, the store type, the month, the sales field area (square meter), the store area (square meter), the beginning of the electricity quantity reading (kWh), the ending of the electricity quantity reading (kWh), the electricity quantity (kWh), the electricity charge (yuan), the average electricity price (yuan/kWh), the carbon dioxide emission quantity, the unit sales field area electricity quantity (kWh /) and the unit sales field area electricity quantity (same proportion (%)), the unit store area electricity quantity (kWh /) and the unit store area electricity quantity (same proportion (%), the unit sales field area electricity charge (yuan/square meter), the unit sales field area electricity charge (same proportion (%)), the unit store area electricity charge (same proportion (%), the unit sales field area carbon dioxide emission quantity and the unit carbon dioxide emission quantity.
The report thirteen with the subtype of daily includes the store number, the store name, the store type, the date, the sales field area (square meter), the store area (square meter), the beginning of the electricity quantity reading (kWh), the ending of the electricity quantity reading (kWh), the electricity quantity (kWh), the electricity charge (unit), the average electricity price (unit/kWh), the carbon dioxide discharge amount, the unit sales field area electricity quantity (kWh/square meter), the unit sales field area electricity quantity (unit/square meter), the unit sales field area electricity charge (unit/square meter), the unit sales field area store electricity charge (unit/square meter), the unit sales field carbon dioxide discharge amount, the unit sales field area carbon dioxide discharge amount and the like.
In the store statistical report, store statistical information can be obtained year by year, month by month and day by day, so that the utilization rate of energy can be improved, and the controllable management of the energy consumption and expenditure cost of enterprises can be finally realized. The power utilization enterprises can realize all-around monitoring and management analysis on energy plans, energy performance, energy balance, energy prediction, energy equipment, energy quality, production scheduling and the like by processing and analyzing the data of the report forms.
One type of the electric quantity analysis report is a store detail report, and the following is a detailed explanation of three store detail reports:
the report fourteen whose subtype is time interval includes information of store number, store name, business time, starting electricity quantity reading (kWh), ending electricity quantity reading (kWh), electricity quantity (kWh), average electricity price (yuan/kWh), electricity charge (yuan), and the like.
The report fourteen, whose subtype is whole day, includes information of store number, store name, business time, starting electricity quantity reading (kWh), ending electricity quantity reading (kWh), electricity quantity (kWh), average electricity price (yuan/kWh), electricity charge (yuan), and the like.
The report fifteen whose subtype is full month includes information of store number, store name, business time, start electricity amount reading (kWh), end electricity amount reading (kWh), electricity amount (kWh), average electricity price (yuan/kWh), electricity rate (yuan), and the like.
In the store detail report, store detail information is obtained according to time intervals, whole days and whole months, and an enterprise can obtain scientific and accurate data according to the report, so that a manager can more scientifically optimize and make decisions on various energy sources, timely know and master production, use and operation conditions of the various energy sources, and achieve scientific decisions and correct command.
One type of the coulometric analysis report is a store plan report. In the store plan report, the report sixteen, whose sub-type is monthly, includes information such as an area, a report period, a store number, a store type, a time of operation, a planned electric power amount (kWh), a planned electric power rate (kWh), an actual electric power amount (kWh), an electric power completion ratio (%), an actual electric power rate (yuan), and an electric power completion ratio (%).
In the store plan report, the acquired store plan information monthly report can help enterprises to improve the energy management level, reduce the energy consumption cost of the enterprises, realize lean conversion of energy management and further realize datamation, intellectualization and automation.
One type of the electric quantity analysis report forms are sub-item measurement report forms, and the following is a detailed explanation of four sub-item measurement report forms:
the report seventeen whose subtype is daily includes information such as store name, store number, equipment name, start power reading (kWh), end power reading (kWh), power proportion (%) and the like.
Eighteen report forms of which the sub-types are monthly reports include information such as store names, store numbers, business times, equipment names, starting electricity quantity readings (kWh), ending electricity quantity readings (kWh), electricity quantities (kWh), electricity quantity duty ratios (%), electricity quantity ring ratios (%), and the like.
The report form nineteen of which the sub-type is a yearly report includes information such as a store name, a store number, an equipment name, a starting electricity quantity reading (kWh), an ending electricity quantity reading (kWh), an electricity quantity ratio (%), an electricity quantity loop ratio (%), and the like.
The report twenty of which the sub-type is the daily report-time period includes information such as a store name, a store number, a business time, an equipment name, a start power reading (kWh), an end power reading (kWh), a power proportion (%), a power loop proportion (%), and the like.
In the subentry measurement report form, subentry measurement information is obtained according to daily reports, monthly reports, annual reports and daily report-time periods, so that refined management and control on the use condition of electric quantity can be realized, an energy utilization structure is optimized, energy is safely supplied, energy consumption is reduced, sustainable development is realized, energy conservation and emission reduction are realized, energy consumption expenditure is reduced, the energy management level is improved, and the like.
Through customized development of the electric quantity analysis report, the basic variable data can be obtained according to the basic variable name in the electric quantity analysis report, and then report data of the electric quantity analysis report is obtained. And the electric quantity can be timely monitored according to the report data.
The power consumption monitoring system also comprises a display module which is used for forming a report image according to the report data and sending the report image to a display device for displaying. And after the result is displayed according to the report, the report can be used for large-screen display, and is convenient for data statistical analysis or leader decision.
By adopting the technical scheme of the embodiment of the disclosure, the electricity consumption use condition, the carbon dioxide emission amount condition and the electricity charge use condition are subjected to statistical analysis from multiple aspects such as headquarters, areas and stores of enterprises, and the response speed and the response capability to electricity utilization faults and exception handling can be improved. The operation and maintenance personnel can master the electricity using condition at any time 24 hours a day by checking the result of the report platform, so that corresponding measures can be taken in time, and the economic and production losses caused by the expansion of the situation influence are avoided.
By adopting the technical scheme of the embodiment of the disclosure, energy monitoring can be carried out and problems can be eliminated. Energy monitoring is required for factories, parks and governments of external enterprises, and energy consumption inquiry is also required for owners. By adopting the power consumption monitoring system of the embodiment of the disclosure, the daily power consumption of the energy utilization equipment can be known. If the report data has an expected external deviation, the owner can be helped to investigate the cause of the problem, and the reason that the deviation is cause is that the yarn electric equipment is abnormal in operation due to report errors.
By adopting the technical scheme of the embodiment of the disclosure, the requirements of management, statistical analysis and decision can be met. For example, factory floor management requires statistics of electricity consumption data, and owners have data requirements for hourly profiling and recording usage. In addition, energy efficiency comparison is carried out, production cost, income, expenditure and the like are calculated according to the electric quantity data, and the electric quantity statistics can be used for analyzing the rule of the data and providing scientific real-time decision for related enterprises.
By adopting the technical scheme of the embodiment of the disclosure, the data correctness can be improved, and the accuracy of power supply and demand and planning can be improved. The ammeter statistics of electric quantity receives artificial interference, has the repeated calculation, and factors such as data disappearance have probably influenced correctness, timeliness, the wholeness of meter to the ammeter data statistics of each energy garden is very scattered, so through the report show back, not only can avoid the influence of human factor, can gather data moreover, sees that the power consumption is more directly perceived, also can see data distribution trend and law. In general, the power supply is greater than the demand, so that the demand of power consumption is met, and a certain surplus of power generation amount is reserved to deal with the short-term surge of power consumption, which leaves away from a power consumption monitoring system.
The power consumption monitoring system in the embodiment of the disclosure determines the name of the basic variable according to the power analysis instruction generated by the operation of the user on the front-end interface, acquires the data of the basic variable from the data storage system according to the name of the basic variable, and further generates the report data to monitor the power consumption, thereby solving the problems of high difficulty and low timeliness of power consumption monitoring in the prior art, and improving the convenience and timeliness of enterprise power consumption monitoring.
The following are embodiments of the disclosed method, which are performed by a system in embodiments of the disclosed system. The power consumption monitoring method described below and the power consumption monitoring system described above may be referred to in correspondence with each other. For details not disclosed in the embodiments of the disclosed method, refer to the embodiments of the disclosed system.
Fig. 4 is a schematic flow chart of a power consumption monitoring method according to an embodiment of the present disclosure. The method provided by the embodiment of the present disclosure can be executed by any electronic device with computer processing capability, such as a terminal or a server. As shown in fig. 4, the method for monitoring power consumption provided by the embodiment of the present disclosure includes:
s401, acquiring a basic variable name corresponding to the electric quantity analysis report to be developed.
S402, acquiring basic variable data in an electric enterprise information table and an electric equipment information table through a data warehouse tool according to the basic variable names, wherein the electric enterprise information table and the electric equipment information table are stored in data storage systems in different forms.
And S403, generating report data of the electric quantity analysis report according to the basic variable data so as to monitor the electric quantity consumption through the report data.
According to the technical scheme of the embodiment, the electric quantity supervision system can obtain the basic variable name corresponding to the electric quantity analysis report according to the customized parameters of the electric quantity analysis report, further can inquire to obtain the basic variable data, and forms report data according to the basic variable data, so that the power consumption can be supervised according to the report data, and the electric quantity supervision system is convenient and good in timeliness.
Before step S401, power analysis instructions generated in response to a user operating the front-end interface may be obtained, where the power analysis instructions include power consumption analysis instructions of power-consuming equipment in different areas and/or different time periods in the report to be power analyzed.
In step S403, at least one of the following processes may be performed according to the basic variable data to generate report data: differencing, summing, multiplying, quoting and grouping.
Before step S401, the power consumption information of different sources may be extracted, cleaned, and converted, and the power consumption information of each power consumption device in different areas may be stored in the data storage system. The source end comprises any one of the following: the system comprises a business system, a log system and an internet of things system.
Before step S401, a basic variable name corresponding to a power analysis report to be developed may also be obtained according to a power analysis instruction, where the power analysis instruction includes a structured data script for structured data query. Wherein the base variable names include at least one of: the method comprises the following steps of enterprise name, enterprise type, electric equipment name, planned electricity consumption, actual electricity consumption, electricity completion ratio, electricity consumption area, electricity price, electricity consumption time, electricity fee, electricity environment and carbon emission.
In step S402, the electricity enterprise information table and the basic variable data in the electricity device information table may be obtained through the structured data query engine according to the basic variable name.
In the technical scheme of the embodiment of the disclosure, a report image can be formed according to the report data and sent to the display device for display.
For details which are not disclosed in the embodiments of the method for monitoring the power consumption, reference is made to the embodiments of the power consumption monitoring system described above in the present disclosure for the details which are not disclosed in the embodiments of the method for monitoring the power consumption.
All the above optional technical solutions may be combined arbitrarily to form optional embodiments of the present application, and are not described herein again.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.
According to the power consumption monitoring method in the embodiment of the disclosure, the basic variable name is determined according to the power analysis instruction generated by the operation of the user on the front-end interface, the basic variable data is acquired in the data storage system according to the basic variable name, and the report data is further generated to monitor the power consumption, so that the problems of high difficulty and low timeliness in power consumption monitoring in the prior art are solved, and the convenience and timeliness in enterprise power consumption monitoring are improved.
The disclosed embodiment also provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the above power consumption monitoring method are implemented.
The embodiment of the disclosure also provides a computer readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the steps of the power consumption monitoring method are implemented.
Fig. 5 is a schematic diagram of an electronic device 5 provided by the embodiment of the present disclosure. As shown in fig. 5, the electronic apparatus 5 of this embodiment includes: a processor 501, a memory 502, and a computer program 503 stored in the memory 502 and operable on the processor 501. The steps in the various method embodiments described above are implemented when the processor 501 executes the computer program 503. Alternatively, the processor 501 implements the functions of the respective modules in the above-described respective apparatus embodiments when executing the computer program 503.
The electronic device 5 may be a desktop computer, a notebook, a palm computer, a cloud server, or other electronic devices. The electronic device 5 may include, but is not limited to, a processor 501 and a memory 502. Those skilled in the art will appreciate that fig. 5 is merely an example of the electronic device 5, and does not constitute a limitation of the electronic device 5, and may include more or less components than those shown, or different components.
The Processor 501 may be a Central Processing Unit (CPU), other general purpose Processor, 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 component, or the like.
The storage 502 may be an internal storage unit of the electronic device 5, for example, a hard disk or a memory of the electronic device 5. The memory 502 may also be an external storage device of the electronic device 5, such as a plug-in hard disk provided on the electronic device 5, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. The memory 502 may also include both internal and external storage units of the electronic device 5. The memory 502 is used for storing computer programs and other programs and data required by the electronic device.
It should be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional units and modules is only used for illustration, and in practical applications, the above function distribution may be performed by different functional units and modules as needed, that is, the internal structure of the device is divided into different functional units or modules, so as to perform all or part of the above described functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit.
The integrated module, if implemented in the form of a software functional unit and sold or used as a separate product, may be stored in a computer readable storage medium. Based on such understanding, the present disclosure may implement all or part of the flow of the method in the above embodiments, and may also be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of the above methods and embodiments. The computer program may comprise computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain suitable additions or additions that may be required in accordance with legislative and patent practices within the jurisdiction, for example, in some jurisdictions, computer readable media may not include electrical carrier signals or telecommunications signals in accordance with legislative and patent practices.
The above examples are only intended to illustrate the technical solutions of the present disclosure, not to limit them; although the present disclosure has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present disclosure, and are intended to be included within the scope of the present disclosure.
Claims (10)
1. A power usage monitoring system, comprising:
the variable determining module is used for acquiring a basic variable name corresponding to the electric quantity analysis report to be developed;
the data acquisition module is used for acquiring basic variable data in an electric enterprise information table and an electric equipment information table through a data warehouse tool according to the basic variable name, wherein the electric enterprise information table and the electric equipment information table are stored in different forms of data storage systems;
and the data processing module is used for generating report data of the electric quantity analysis report according to the basic variable data so as to supervise the electricity consumption through the report data.
2. The power usage monitoring system of claim 1, further comprising an instruction acquisition module to:
and acquiring a power consumption analysis instruction generated in response to the operation of a user on a front-end interface, wherein the power consumption analysis instruction comprises power consumption analysis instructions of electric equipment in different areas and/or different time periods in the power consumption analysis report.
3. The power consumption monitoring system of claim 1, wherein the data processing module is configured to perform at least one of the following processes according to the basic variable data to generate the report data:
differencing, summing, multiplying, quoting and grouping.
4. The power consumption monitoring system of claim 1, further comprising a data storage module for storing power consumption information of each of the power consumers in different areas in the data storage system.
5. The power usage monitoring system of claim 1, wherein the base variable names include at least one of: the method comprises the following steps of enterprise name, enterprise type, electric equipment name, planned electricity consumption, actual electricity consumption, electricity completion ratio, electricity consumption area, electricity price, electricity consumption time, electricity fee, electricity environment and carbon emission.
6. The power consumption monitoring system according to claim 2, wherein the variable determining module is configured to obtain a base variable name corresponding to a power analysis report to be developed according to the power analysis command, where the power analysis command includes a structured data script for structured data query.
7. The power consumption monitoring system of claim 6, wherein the data obtaining module is configured to obtain the basic variable data in the power consumption enterprise information table and the power consumption equipment information table through a structured data query engine according to the basic variable name.
8. The power consumption monitoring system according to claim 1, further comprising a display module for forming a report image according to the report data and sending the report image to a display device for display.
9. The power consumption monitoring system of claim 4, further comprising a data preprocessing module for extracting, cleaning and converting the power consumption information of different sources, wherein the sources include any one of the following: the system comprises a business system, a log system and an internet of things system.
10. A method for supervising power consumption, the method comprising:
acquiring a basic variable name corresponding to an electric quantity analysis report to be developed;
acquiring basic variable data in an electric enterprise information table and an electric equipment information table through a data warehouse tool according to the basic variable name, wherein the electric enterprise information table and the electric equipment information table are stored in data storage systems in different forms;
and generating report data of the electric quantity analysis report according to the basic variable data so as to monitor the electric quantity through the report data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210572658.4A CN114897394A (en) | 2022-05-24 | 2022-05-24 | Power consumption monitoring system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210572658.4A CN114897394A (en) | 2022-05-24 | 2022-05-24 | Power consumption monitoring system and method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114897394A true CN114897394A (en) | 2022-08-12 |
Family
ID=82725464
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210572658.4A Pending CN114897394A (en) | 2022-05-24 | 2022-05-24 | Power consumption monitoring system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114897394A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116436166A (en) * | 2023-06-12 | 2023-07-14 | 青岛恒源新电力科技有限公司 | Electric power data analysis and monitoring method and system based on Internet of things |
-
2022
- 2022-05-24 CN CN202210572658.4A patent/CN114897394A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116436166A (en) * | 2023-06-12 | 2023-07-14 | 青岛恒源新电力科技有限公司 | Electric power data analysis and monitoring method and system based on Internet of things |
| CN116436166B (en) * | 2023-06-12 | 2023-09-05 | 青岛恒源新电力科技有限公司 | Electric power data analysis and monitoring method and system based on Internet of things |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107402976B (en) | Power grid multi-source data fusion method and system based on multi-element heterogeneous model | |
| CN111104394A (en) | Energy data warehouse system construction method and device | |
| CN104281130B (en) | Hydroelectric equipment monitoring and fault diagnosis system based on big data technology | |
| US20120130659A1 (en) | Analysis of Large Data Sets Using Distributed Polynomial Interpolation | |
| CN105678398A (en) | Power load forecasting method based on big data technology, and research and application system based on method | |
| CN108470228A (en) | Financial data auditing method and audit system | |
| CN113822547B (en) | Comprehensive information platform system for refined demand side management and management method | |
| CN109118012B (en) | Industrial dynamic multi-dimensional energy consumption cost prediction method, system, storage medium and terminal | |
| CN111524027B (en) | Electric power information statistical method, device, equipment and storage medium | |
| CN110991985A (en) | Project progress data processing method | |
| CN115882456B (en) | Power control method and system based on large-scale power grid tide | |
| CN111833018A (en) | Patent analysis method and system for science and technology project | |
| CN111160865A (en) | Workflow management method and device | |
| Sanyal et al. | Simulation and big data challenges in tuning building energy models | |
| CN114036746A (en) | Energy data acquisition system and method based on cloud platform and computer equipment | |
| CN114897394A (en) | Power consumption monitoring system and method | |
| CN116933157A (en) | Electricity larceny detection method | |
| CN112948353B (en) | Data analysis method, system and storage medium applied to DAstudio | |
| Jeon et al. | Measuring variability on electrical power demands in manufacturing operations | |
| CN113673842A (en) | Production efficiency diagnosis method, device, equipment and storage medium based on big data | |
| CN113255307A (en) | Intelligent reporting method and system for power system | |
| CN112256681A (en) | Air traffic control digital index application system and method | |
| CN116431701A (en) | Comprehensive power plant production data analysis and statistics system | |
| CN114757482A (en) | Method, system, device and medium for analyzing electric quantity use trend of user group | |
| CN115097797A (en) | Distributed energy cloud management and control system based on internet |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |