CN113377843A - Data analysis system based on energy big data - Google Patents
Data analysis system based on energy big data Download PDFInfo
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- CN113377843A CN113377843A CN202110685563.9A CN202110685563A CN113377843A CN 113377843 A CN113377843 A CN 113377843A CN 202110685563 A CN202110685563 A CN 202110685563A CN 113377843 A CN113377843 A CN 113377843A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- 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
- G06F16/26—Visual data mining; Browsing structured data
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Abstract
The invention discloses a data analysis system based on energy big data, which comprises a data acquisition module, a data storage module, a data transmission module, a data division module, a data primary analysis module and a data secondary analysis module, wherein the analysis steps are as follows: carrying out data acquisition on the energy big data; storing the collected energy data to a data storage module; transferring the energy data stored by the data storage module; dividing the transferred data; performing data primary analysis on the divided data; establishing a prediction model for the data after the first analysis; importing the prediction model into a data secondary analysis module; the data analysis system has high analysis efficiency and accurate data analysis, and the data analysis system effectively improves the efficiency of data analysis and is convenient for directly and quickly displaying accurate and effective data to a user so as to facilitate the client to quickly make an improved suggestion.
Description
Technical Field
The invention relates to the technical field of energy big data processing, in particular to a data analysis system based on energy big data.
Background
Today, energy has become an indispensable basic element of human society, with the increasing shortage of energy and the deterioration of environment, the acquisition of economical, convenient and environment-friendly energy becomes an urgent problem related to human survival and sustainable development, the solution of seeking to improve the energy utilization efficiency becomes a common responsibility of all societies such as small-sized social families and large-sized enterprises and governments, various water, electricity and gas equipment and classified energy consumption are one of the main components of industrial facilities, social infrastructure, various building construction investments and daily operation costs, and the reasonable layout of energy facility configuration and management and control functions can obviously improve the facility and energy utilization efficiency and reduce the cost.
The energy management system adopts a layered distributed system structure, collects and processes various classified energy consumption data of electric power, gas, water and the like of the building, analyzes the energy consumption condition of the building, and realizes building energy conservation application and the like. Through various means such as energy planning, energy monitoring, energy statistics, energy consumption analysis, key energy consumption equipment management, energy metering equipment management and the like, an enterprise manager can accurately master the energy cost proportion and the development trend of an enterprise, and decompose the energy consumption planning task of the enterprise into workshops of various production departments, so that the responsibility of energy-saving work is clear, and the healthy and stable development of the enterprise is promoted.
However, the existing energy management system can generate a large amount of energy big data, the big data needs to be analyzed, the existing data analysis system has low efficiency and cannot meet normal use, and the detected and collected energy consumption data cannot be conveniently and quickly displayed to a user, so that the user cannot make an improved suggestion quickly.
Disclosure of Invention
The invention aims to solve the problems and designs a data analysis system based on energy big data.
The technical scheme of the invention is that the data analysis system based on the energy big data comprises a data acquisition module, a data storage module, a data transmission module, a data division module, a data primary analysis module and a data secondary analysis module, and the analysis steps are as follows:
the method comprises the following steps: carrying out data acquisition on the energy big data;
step two: storing the collected energy data to a data storage module;
step three: transferring the energy data stored by the data storage module;
step four: dividing the transferred data;
step five: performing data primary analysis on the divided data;
step six: establishing a prediction model for the data after the first analysis;
step seven: importing the prediction model into a data secondary analysis module;
step eight: and the data secondary analysis module analyzes the prediction model.
As a further description of the invention, in the first step, the energy big data is collected by the data collection module, and the collected data includes the running time, running state, energy consumption and energy conversion efficiency of the energy equipment.
As a further description of the invention, in the second step, the collected energy data is stored in the data storage module, and the data storage module analyzes and stores the stored data according to a protocol, so that the integrity of the data is maintained in the process.
As a further description of the creation of the present invention, in the third step, in the process of transferring the stored data by the data transmission module, the data transmission module needs to obtain a data transfer voice instruction input by the user first, and sends a data transfer trigger request through the data transfer voice instruction, and after the request is passed, the data transmission module starts to transfer the data.
As a further description of the creation of the present invention, in the fourth step, the data partitioning module is used to implement the partitioning processing on the shifted-out data, in this process, the data partitioning module creates a plurality of candidate partitioning planes, the energy data is temporally partitioned by the plurality of candidate partitioning planes, each candidate partitioning plane generates a plurality of generating clusters, and each generating cluster is provided with a plurality of data slices.
As a further description of the invention, in the fifth step, the data primary analysis module performs primary analysis on each data slice, and in the process, the integrity and the validity of the data are analyzed, and invalid data is removed by using a data compression and transformation method, so that the standardization of the data is ensured.
As a further description of the invention, in the sixth step, a prediction model is established according to the data after the primary analysis, and a linear regression method or a network prediction method is adopted as a method for establishing the prediction model.
As a further description of the invention, in the seventh step, the prediction model is imported into the data secondary analysis module, and in the process, the prediction model is analyzed and then imported into the data secondary analysis module.
As a further description of the invention, in the step eight, the prediction model is analyzed by the data secondary analysis module, and a data analysis result is generated after the analysis.
The data analysis system has the advantages that the data analysis system is high in analysis efficiency and accurate in data analysis, the data analysis system is applied, the data analysis efficiency is effectively improved, accurate and effective data can be directly and quickly displayed to a user conveniently, and therefore the user can make improved suggestions quickly.
Drawings
FIG. 1 is an analysis flow diagram of a data analysis system of the present invention.
Detailed Description
Firstly, the design of the invention is designed originally, today, energy becomes an indispensable basic element of human society, along with the increasing shortage of energy and the deterioration of environment, the acquisition of economical, convenient and environment-friendly energy becomes an urgent problem related to human survival and sustainable development, the solution for improving the energy utilization efficiency is sought to become the common responsibility of the whole society, such as small-sized social families, large-sized enterprises, governments and the like, an energy management system adopts a layered distributed system architecture, the energy management system collects and processes various classified energy consumption data of electric power, gas, water and the like of a building, the energy consumption condition of the building is analyzed, the energy saving application of the building is realized, the current energy management system can generate a large amount of energy big data which needs to be analyzed, the efficiency of the current data analysis system is lower, the normal use cannot be met, and the detected and collected energy consumption data cannot be conveniently and quickly displayed to users, therefore, the invention designs a data analysis system based on energy big data.
The invention is described in detail below with reference to the accompanying drawings, and as shown in fig. 1, an energy big data based data analysis system includes a data acquisition module, a data storage module, a data transmission module, a data division module, a data primary analysis module, and a data secondary analysis module, where the data acquisition module is used for acquiring energy data, the data storage module is used for storing the energy data, the data transmission module is used for transmitting the energy data stored by the data storage module, the data division module is used for dividing the energy data, the data primary analysis module is used for performing primary analysis on the energy data, and the data secondary analysis module is used for performing secondary analysis on the energy data.
The analysis process of this data analysis system will be described in detail below, and the analysis steps are as follows:
the method comprises the following steps: carrying out data acquisition on the energy big data; in the step, the energy big data are collected through the data collection module, the collected data comprise the running time, the running state, the energy consumption and the energy conversion efficiency of the energy equipment, and the running state of the equipment can be clearly and visually seen according to the collected energy data.
Step two: storing the collected energy data to a data storage module; in the step, the collected energy data are stored in the data storage module, the data storage module analyzes and stores the stored data according to the protocol, the integrity of the data is maintained in the process, and the accurate analysis result can be ensured only if the data are complete.
Step three: transferring the energy data stored by the data storage module; in the step, the data transmission module is used for transferring the stored data, the data transmission module firstly needs to acquire a data transfer voice command input by a user, a data transfer trigger request is sent through the data transfer voice command, the data transmission module starts to transfer the data after the request is passed, and the data transmission adopts 5G communication, so that the efficiency of energy transmission is effectively ensured.
Step four: dividing the transferred data; in the step, the data division module is used for dividing the shifted data, in the process, the data division module creates a plurality of candidate division planes, the energy data are temporarily divided through the candidate division planes, a plurality of generation clusters are generated in each candidate division plane, a plurality of data pieces are arranged in each generation cluster, and the data are divided into a plurality of parts through the data division module, so that the data analysis efficiency is effectively improved.
Step five: performing data primary analysis on the divided data; in the step, the data is primarily analyzed on each data slice through the data primary analysis module, the integrity and the effectiveness of the data are analyzed in the process, invalid data are removed by using a data compression and transformation method, the standardization of the data is ensured, and the accuracy and the effectiveness of the data analysis are effectively improved through the data primary analysis.
Step six: establishing a prediction model for the data after the first analysis; in the step, the prediction model is imported into a data secondary analysis module, the prediction model is analyzed in the process and then imported into the data secondary analysis module, in the step, the prediction model is built according to the data after primary analysis, a linear regression method or a network prediction method is adopted in the building method of the prediction model, and the prediction model is constructed so as to facilitate secondary analysis of the data.
Step seven: importing the prediction model into a data secondary analysis module; in the step, the prediction model is imported into a data secondary analysis module, and in the process, the prediction model is analyzed and then imported into the data secondary analysis module.
Step eight: and analyzing the prediction model by the data secondary analysis module, wherein in the step, the prediction model is analyzed by the data secondary analysis module, and a data analysis result is generated after the analysis.
The data analysis system is high in analysis efficiency and accurate in data analysis, the data analysis system is applied, the data analysis efficiency is effectively improved, accurate and effective data can be directly and quickly displayed to a user conveniently, and therefore the user can make improved suggestions quickly.
The technical solutions described above only represent the preferred technical solutions of the present invention, and some possible modifications to some parts of the technical solutions by those skilled in the art all represent the principles of the present invention, and fall within the protection scope of the present invention.
Claims (9)
1. The utility model provides a data analysis system based on energy big data which characterized in that, includes data acquisition module, data storage module, data transmission module, data division module, data primary analysis module, data secondary analysis module, and its analysis step is as follows:
the method comprises the following steps: carrying out data acquisition on the energy big data;
step two: storing the collected energy data to a data storage module;
step three: transferring the energy data stored by the data storage module;
step four: dividing the transferred data;
step five: performing data primary analysis on the divided data;
step six: establishing a prediction model for the data after the first analysis;
step seven: importing the prediction model into a data secondary analysis module;
step eight: and the data secondary analysis module analyzes the prediction model.
2. The data analysis system based on the energy big data as claimed in claim 1, wherein in the first step, the energy big data is collected by the data collection module, and the collected data includes the operation time, the operation state, the energy consumption amount, and the energy conversion efficiency of the energy equipment.
3. The system according to claim 1, wherein in the second step, the collected energy data is stored in a data storage module, and the data storage module analyzes and stores the stored data according to a protocol, so that the integrity of the data is maintained.
4. The system according to claim 1, wherein in the third step, in the data transfer process of the data transmission module on the stored data, the data transmission module first needs to obtain a data transfer voice command input by a user, and sends a data transfer trigger request through the data transfer voice command, and after the request is passed, the data transmission module starts to transfer the data.
5. The system according to claim 1, wherein in the fourth step, the data partitioning module partitions the shifted data, and in the process, the data partitioning module creates a plurality of candidate partition planes, and temporarily partitions the energy data through the plurality of candidate partition planes, and each candidate partition plane generates a plurality of generation clusters, and each generation cluster is provided with a plurality of data slices.
6. The data analysis system based on the energy big data as claimed in claim 5, wherein in the fifth step, the data is primarily analyzed by the data primary analysis module for each data slice, the integrity and the validity of the data are analyzed in the process, and invalid data is removed by using a data compression and transformation method to ensure the standardization of the data.
7. The data analysis system based on energy big data according to claim 6, wherein in the sixth step, a prediction model is built according to the data after the primary analysis, and the building method of the prediction model adopts a linear regression method or a network prediction method.
8. The data analysis system based on the energy big data as claimed in claim 1, wherein in the seventh step, the prediction model is imported into the data secondary analysis module, and in the process, the prediction model is analyzed and then imported into the data secondary analysis module.
9. The data analysis system based on the energy big data as claimed in claim 1, wherein in the eighth step, the predictive model is analyzed by the data secondary analysis module, and a data analysis result is generated after the analysis.
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| CN104484114A (en) * | 2014-11-24 | 2015-04-01 | 腾讯科技（深圳）有限公司 | Data transfer method, mobile terminal and data transfer system |
| CN107862443A (en) * | 2017-10-20 | 2018-03-30 | 杭州唐电科技有限公司 | A kind of processing method and system of energy big data |
| CN110298488A (en) * | 2019-05-31 | 2019-10-01 | 武汉烽火富华电气有限责任公司 | A kind of multi-energy data analysis method and system based on data mining |
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2021
- 2021-06-21 CN CN202110685563.9A patent/CN113377843A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN1869971A (en) * | 2005-05-25 | 2006-11-29 | 株式会社东芝 | Data division apparatus, data division method |
| WO2012124225A1 (en) * | 2011-03-15 | 2012-09-20 | 株式会社 東芝 | Energy demand prediction device and method |
| CN104484114A (en) * | 2014-11-24 | 2015-04-01 | 腾讯科技（深圳）有限公司 | Data transfer method, mobile terminal and data transfer system |
| CN107862443A (en) * | 2017-10-20 | 2018-03-30 | 杭州唐电科技有限公司 | A kind of processing method and system of energy big data |
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