CN113377854A - Data integration system based on energy big data - Google Patents
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Abstract
The invention discloses a data integration system based on energy big data, which comprises an energy information acquisition system, an information optimization integration system, a big data analysis system, a data prediction system, an energy big data system and an information query system, wherein the energy information acquisition system comprises an acquisition server, a firewall, a metadata server group, an optical fiber switch, a database node and a user. The energy internet cooperative system control method for improving the energy utilization rate has the advantages that the renewable energy and the non-renewable energy are reasonably analyzed and combined with the energy big data, the traditional centralized utilization is changed into the distributed utilization, the energy big data system control method is mature, the requirement of large-scale utilization of energy can be met, the energy utilization rate is greatly improved, and the waste of a large amount of energy is reduced.
Description
Technical Field
The invention relates to the technical field of energy big data control, in particular to a data integration system based on energy big data.
Background
Energy sources are resources capable of providing energy, wherein the energy generally refers to heat energy, electric energy, light energy, mechanical energy, chemical energy and the like, and the energy sources can be divided into three main types according to sources: (1) energy from the sun, including energy directly from the sun (such as solar thermal radiation energy) and energy indirectly from the sun (such as combustible minerals such as coal, oil, natural gas, oil shale, biomass energy such as firewood, water energy, wind energy and the like); (2) energy from the earth itself, one is geothermal energy stored in the earth, such as underground hot water, underground steam, hot dry rock mass; the other is nuclear energy stored in nuclear fuels such as uranium, thorium and the like in the crust; (3) the gravity of celestial bodies such as the moon and the sun on the earth generates energy such as tidal energy.
The energy can also be divided into renewable energy and non-renewable energy, the existing energy is generally combined with the internet when in use, hundreds of millions of devices, machines and systems of an energy production end, an energy transmission end and an energy consumption end are connected by using advanced sensors, control and software application programs, but the existing energy network system control method is simpler and difficult to adapt to the requirement of large-scale utilization of energy, and the energy utilization rate is lower due to the uncoordination of the energy network system, so that a large amount of energy is wasted. .
Disclosure of Invention
The invention aims to solve the problems and designs a data integration system based on energy big data.
The technical scheme of the invention is that the energy big data-based data integration system comprises an energy information acquisition system, an information optimization integration system, a big data analysis system, a data prediction system, an energy big data system and an information query system, wherein the energy information acquisition system comprises an acquisition server, a firewall, a metadata server group, an optical fiber switch, a database node and a user.
As a further description of the present invention, one end of the collection server is connected to other energy systems for collecting energy data, and the other end transmits the collected energy data information to the metadata server group through the firewall; the metadata server group transmits the energy data to the database node through the optical fiber switch after performing data analysis, processing and cleaning on the received energy data; the database nodes split the connection relation between data and configured energy data according to the energy data key fields, output the power, heat and natural gas energy conditions and the calculation results of energy conversion on a system interface, and graphically display the optimal scheme of electric power, heat power information and energy configuration flowing through each line in the power, heat, gas and traffic networks; and the user inquires the energy comprehensive information and carries out scheduling operation through a system interface.
As a further description of the present invention, the energy information collection system includes a non-renewable energy information collection system and a renewable energy information collection system, and the non-renewable energy information collection system and the renewable energy information collection system include a variety, a quantity, a distribution condition, an annual production amount, a production cycle, a quantity volatility, and controllability for energy information collection range.
As a further explanation of the present invention, the information optimization and integration system integrates information collected by the non-renewable energy information collection system and the renewable energy information collection system, merges data of the same main body of the non-renewable energy information collection system and the renewable energy information collection system, generates dual two-dimensional coordinate parameters of the use conditions of the non-renewable energy and the renewable energy according to the area, counts the difference between the non-renewable energy and the renewable energy every year according to the same year, and establishes a regional preference graph between the non-renewable energy and the renewable energy.
As a further description of the present invention, the big data analysis system includes a cloud computing center, a cloud data storage center, and a big data analysis system, the cloud computing center processes the received information obtained by the information optimization and integration system to generate related data, and then stores the related data in the cloud data storage center, and the big data analysis system analyzes the related data stored in the cloud data storage center to obtain user-oriented information, and sends the user-oriented information to the user terminal.
As a further description of the present invention, the data prediction system receives real-time update information of non-renewable energy information and renewable energy information input by the energy information acquisition system according to a preset time period, pre-processes the real-time update information of the energy to obtain pre-processed information, performs linear segmentation processing on the pre-processed information to obtain an energy data subset, performs clustering processing on the energy data subset to obtain a plurality of clustering models, performs symbol marking on the clustering models to obtain a plurality of symbol models, performs association mining on the symbol models according to a discovery algorithm of a frequent association pattern to obtain data association features, and predicts future load capacity of each region.
As a further description of the present invention, the information query system establishes a distributed energy query module, wherein the distributed energy query module is used for querying a user terminal and a control terminal, and the distributed energy query module can be used to rapidly query the nearest energy distribution point, energy storage amount, and energy type.
As a further illustration of the present invention, the system comprises the following operational steps:
step S1, connecting the system acquisition server with the PMS, OMS, GIS system, heat supply management system, natural gas energy management system and traffic system of electric power through interfaces;
s2, transmitting the collected energy data to an unstructured data server of a metadata server group, and analyzing, translating and cleaning the collected unstructured data in the unstructured data server to generate structured data required by the system;
step S3, splitting the structured data processed in the step 2 and the acquired structured data according to the key fields of the data;
step S4, performing condition matching on key fields of each type of energy data splitting, establishing a connection relation according with the conditions, and storing the connection relation information into a corresponding data table;
and step S5, randomly storing the integrated energy data table into the database node, and returning the storage position of each resource to the metadata server of the system.
The energy internet cooperative system control method for improving the energy utilization rate has the advantages that 1, the renewable energy and the non-renewable energy are reasonably analyzed and combined with the energy big data, the traditional centralized utilization is changed into the distributed utilization, the energy big data system control method is mature, the requirement of large-scale utilization of energy can be met, the energy utilization rate is greatly improved, and the waste of a large amount of energy is reduced.
According to the energy big data collaborative system control method for improving the energy utilization rate, the cooperativity of the energy big data is obviously improved by generating a large amount of data and graphs, and great convenience is provided for energy users through a large amount of data and an information query system.
Energy is mined through analysis of a large amount of energy data and incidence relations, the energy data are displayed in a graphical mode, an optimal configuration scheme of energy is calculated, the problem that the utilization rate of electric energy, stored energy and heat energy is low is solved, and energy interconnection integration and complementary fusion are achieved.
Drawings
Fig. 1 is a schematic structural view of the present invention.
Detailed Description
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 integration system includes an energy information collection system, an information optimization integration system, a big data analysis system, a data prediction system, an energy big data system, and an information query system, where the energy information collection system includes a collection server, a firewall, a metadata server group, an optical fiber switch, a database node, and a user.
One end of the acquisition server is connected with other energy systems and used for acquiring energy data, and the other end of the acquisition server transmits the acquired energy data information to the metadata server group through a firewall; the metadata server group transmits the energy data to the database node through the optical fiber switch after performing data analysis, processing and cleaning on the received energy data; the database nodes split the connection relation between data and configured energy data according to the energy data key fields, output the power, heat and natural gas energy conditions and the calculation results of energy conversion on a system interface, and graphically display the optimal scheme of electric power, heat power information and energy configuration flowing through each line in the power, heat, gas and traffic networks; and the user inquires the energy comprehensive information and carries out scheduling operation through a system interface.
The energy information acquisition system comprises a non-renewable energy information acquisition system and a renewable energy information acquisition system, wherein the non-renewable energy information acquisition system and the renewable energy information acquisition system have the advantages of variety, quantity, distribution condition, annual mining quantity, production cycle, quantity volatility and controllability of energy information acquisition ranges.
The information optimization and integration system integrates information acquired by the non-renewable energy information acquisition system and the renewable energy information acquisition system, combines data of the same main bodies of the non-renewable energy information acquisition system and the renewable energy information acquisition system, generates dual two-dimensional coordinate parameters of the use conditions of the non-renewable energy and the renewable energy according to the region, counts the difference between the non-renewable energy and the renewable energy every year according to the same year, and establishes a region preference curve graph between the non-renewable energy and the renewable energy.
The big data analysis system comprises a cloud computing center, a cloud data storage center and a big data analysis system, wherein the cloud computing center processes received information obtained by the information optimization integration system to generate related data, the related data are stored in the cloud data storage center, and the big data analysis system analyzes the related data stored in the cloud data storage center to obtain user-oriented information and sends the user-oriented information to the user terminal.
The data prediction system receives real-time updating information of non-renewable energy information and renewable energy information input by the energy information acquisition system according to a preset time period, preprocesses the real-time energy updating information to obtain preprocessing information, carries out linear segmentation processing on the preprocessing information to obtain an energy data subset, carries out clustering processing on the energy data subset to obtain a plurality of clustering models, carries out symbol marking on the clustering models to obtain a plurality of symbol models, carries out association mining on the symbol models according to a discovery algorithm of a frequent association mode to obtain data association characteristics, and predicts the future load capacity of each region.
The information query system establishes a distributed energy query module, wherein the distributed energy query module is used for querying a user terminal and a control terminal, and the distributed energy query module can be used for rapidly querying the nearest energy distribution point, energy storage capacity and energy variety.
The system comprises the following operation steps:
step S1, connecting the system acquisition server with the PMS, OMS, GIS system, heat supply management system, natural gas energy management system and traffic system of electric power through interfaces;
s2, transmitting the collected energy data to an unstructured data server of a metadata server group, and analyzing, translating and cleaning the collected unstructured data in the unstructured data server to generate structured data required by the system;
step S3, splitting the structured data processed in the step 2 and the acquired structured data according to the key fields of the data;
step S4, performing condition matching on key fields of each type of energy data splitting, establishing a connection relation according with the conditions, and storing the connection relation information into a corresponding data table;
and step S5, randomly storing the integrated energy data table into the database node, and returning the storage position of each resource to the metadata server of the system.
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 (8)
1. The data integration system based on the energy big data is characterized by comprising an energy information acquisition system, an information optimization integration system, a big data analysis system, a data prediction system, an energy big data system and an information query system, wherein the energy information acquisition system comprises an acquisition server, a firewall, a metadata server group, an optical fiber switch, a database node and a user.
2. The system for integrating data based on energy big data according to claim 1, wherein one end of the collection server is connected to other energy systems for collecting energy data, and the other end transmits the collected energy data information to the metadata server group through a firewall; the metadata server group transmits the energy data to the database node through the optical fiber switch after performing data analysis, processing and cleaning on the received energy data; the database nodes split the connection relation between data and configured energy data according to the energy data key fields, output the power, heat and natural gas energy conditions and the calculation results of energy conversion on a system interface, and graphically display the optimal scheme of electric power, heat power information and energy configuration flowing through each line in the power, heat, gas and traffic networks; and the user inquires the energy comprehensive information and carries out scheduling operation through a system interface.
3. The data integration system based on the energy big data as claimed in claim 1, wherein the energy information collection system comprises a non-renewable energy information collection system and a renewable energy information collection system, and the non-renewable energy information collection system and the renewable energy information collection system have energy information collection ranges including type, quantity, distribution, annual output, production cycle, quantity fluctuation and controllability.
4. The system according to claim 1, wherein the information optimization integration system integrates the information collected by the non-renewable energy information collection system and the renewable energy information collection system, combines the data of the same subject of the non-renewable energy information collection system and the renewable energy information collection system, generates dual two-dimensional coordinate parameters of the use conditions of the non-renewable energy and the renewable energy according to the region, counts the difference between the non-renewable energy and the renewable energy every year according to the same year, and establishes the regional preference graph between the non-renewable energy and the renewable energy.
5. The energy big data-based data integration system according to claim 1, wherein the big data analysis system comprises a cloud computing center, a cloud data storage center and a big data analysis system, the cloud computing center processes received information obtained by the information optimization integration system to generate related data, the related data is stored in the cloud data storage center, and the big data analysis system analyzes the related data stored in the cloud data storage center to obtain user-oriented information and sends the user-oriented information to the user terminal.
6. The system according to claim 1, wherein the data prediction system receives real-time updated information of the non-renewable energy information and the renewable energy information input by the energy information collection system according to a preset time period, pre-processes the real-time updated information of the energy to obtain pre-processed information, performs linear segmentation on the pre-processed information to obtain energy data subsets, performs clustering on the energy data subsets to obtain a plurality of clustering models, performs symbol marking on the clustering models to obtain a plurality of symbol models, performs association mining on the symbol models according to a discovery algorithm of a frequent association model to obtain data association features, and predicts future load capacity of regions of each area.
7. The system according to claim 1, wherein the information query system establishes a distributed energy query module, wherein the distributed energy query module is used for querying by the user terminal and the control terminal, and the distributed energy query module can rapidly query the nearest energy distribution point, energy storage amount and energy type.
8. The system for data integration based on energy big data according to claim 1, wherein the system comprises the following operation steps:
step S1, connecting the system acquisition server with the PMS, OMS, GIS system, heat supply management system, natural gas energy management system and traffic system of electric power through interfaces;
s2, transmitting the collected energy data to an unstructured data server of a metadata server group, and analyzing, translating and cleaning the collected unstructured data in the unstructured data server to generate structured data required by the system;
step S3, splitting the structured data processed in the step 2 and the acquired structured data according to the key fields of the data;
step S4, performing condition matching on key fields of each type of energy data splitting, establishing a connection relation according with the conditions, and storing the connection relation information into a corresponding data table;
and step S5, randomly storing the integrated energy data table into the database node, and returning the storage position of each resource to the metadata server of the system.
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| CN115934801A (en) * | 2022-12-12 | 2023-04-07 | 国家电网有限公司大数据中心 | Statistical data model construction method and device, electronic equipment and storage medium |
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