CN116776543A - A power big data application method for smart grid - Google Patents

Abstract

The invention discloses a power big data application method for a smart grid, which solves the problems of low operating efficiency and high operating risk of the smart grid caused by the fact that a traditional data analysis platform in the prior art cannot meet the data analysis requirement of the smart grid, and comprises the following steps: real-time monitoring is carried out on the intelligent power grid by utilizing an MR enhanced virtual technology; acquiring power big data of a smart grid, acquiring a power big data processing technology, classifying and arranging the acquired power big data, and establishing a database; acquiring business requirements of the intelligent power grid, acquiring corresponding power big data from a database according to the business requirements, and selecting a corresponding power big data processing technology; processing the service demand and making related decisions to obtain decision results; and performing operation maintenance and fault elimination of the intelligent power grid. And the large electric power data are applied to the intelligent power grid, so that the running speed of the intelligent power grid system is improved, and the electric power system is safer and more stable.

Description

A power big data application method for smart grid

Technical field

The present invention relates to the technical field of power systems, and in particular to a power big data application method for smart grids.

Background technique

With the rapid development of my country's power industry, the relevant power data in the industry has grown explosively. However, traditional data processing technology can no longer handle the explosive growth of power data, causing smart grids to be unable to keep up with market changes and hindering the development of the power industry.

In practical applications, the actual amount of data in smart grids is very large. Traditional data storage capacity is limited and its processing capabilities are lacking. Traditional data storage space is limited and the storage state is unstable, which may cause data loss, disorder, etc. . Smart grid has high requirements on the speed of data analysis and processing. The speed of data analysis and processing efficiency are important indicators to measure the data analysis and processing capabilities. The power system of the smart grid acquires massive amounts of power information every day and evaluates the data in a timely manner, which is very important for the development of the power industry. Traditional data processing platforms have technical characteristics such as isomorphism, and all resources use the same type of interface. This scale is difficult to achieve. In addition, the traditional power data platform needs to continuously replace core components to improve the data analysis capabilities of the system. However, this method has certain limitations. Once it extends to the upper limit of the device, the device equipment needs to be replaced.

With the development of smart grids, traditional data analysis platforms can no longer meet the needs of smart grid data analysis. Only through continuous reform and innovation and research into new processing technologies can we truly solve the problems existing in the development of smart grids.

Contents of the invention

The purpose of the present invention is to overcome the problems in the prior art that traditional data analysis platforms cannot meet the needs of smart grid data analysis, resulting in low smart grid operation efficiency and high operational risks, and provide a power big data application method for smart grids. , the application of power big data in smart grids improves the operation speed of smart grid systems, improves the power supply efficiency of enterprises, and ensures users' power quality, thereby making the power system more secure and stable.

In order to achieve the above objects, the present invention adopts the following technical solutions:

A power big data application method for smart grids, including the following steps:

S1: Use MR enhanced virtual technology to monitor smart grids in real time;

S2: Collect power big data from smart grids, obtain power big data processing technology, classify and arrange the collected power big data, and establish a database;

S3: Obtain smart grid business requirements, obtain corresponding power big data from the database according to business requirements, and select corresponding power big data processing technology;

S4: Based on the obtained electric power big data and electric power big data processing technology, process the business requirements and make relevant decisions, and obtain the decision results;

S5: Based on the decision-making results, perform operation, maintenance and fault elimination of the smart grid.

Applying power big data in actual power grid construction can realize the collection and processing of data on consumption and power generation within the smart grid. Big data has powerful information collection and storage functions. Smart grids based on power big data have the characteristics of large quantity, diversification, fast speed, high accuracy and high value. Smart grids based on power big data can improve the operation speed of smart grid systems, improve the power supply efficiency of enterprises, and ensure the quality of power consumption for users, thereby making the power system more secure and stable.

Preferably, processing the business requirements includes:

Use harmonic data to analyze the causes of harmonics and predict the risks harmonics pose to smart grids;

Utilize hierarchical processing of power big data to correlate various power systems for data sharing;

Utilize the hierarchical processing and hybrid storage technology of power big data to build a multi-functional information management system for smart grids.

In smart grids, various types of measuring instruments within the power system will be affected by harmonics and produce errors. Therefore, harmonics will affect the operation of the entire power system; in addition, some power equipment will also produce harmonics, and some high harmonic components It may even cause harm to the use of the equipment. Power big data can be used to analyze the causes of harmonic data and predict the risks caused by harmonics to the power system, thereby providing a more practical and reliable basis for harmonic control. Hierarchical processing and hybrid storage technology provide technical support for building multi-functional information management and improve the collection and storage capabilities of power information. At the same time, hierarchical processing technology can also be used to realize communication between power systems based on actual business needs. Association to ensure information sharing between data. Greatly improve the processing efficiency of big data and expand data storage capacity.

As a priority, the risks posed by harmonics to smart grids include:

By dividing relevant components and parameters, the fundamental wave and harmonic data of active and reactive power are stored in a table;

Calculate the fundamental and harmonic currents, and generate the corresponding harmonic content based on the calculated current;

Input the harmonic content into the harmonic risk prediction model obtained by training, and perform risk assessment on harmonics.

In the process of assessing the harmonic risk of power data, harmonics need to be brought into the prediction model, and the ARIMA model is generally used. When using this model, training must be performed first, and then the future change trend of harmonics can be predicted based on harmonic data to provide guarantee for harmonic management.

Preferably, the key technologies for power big data include:

Data analysis technology for online security analysis of smart grids;

Data management technology to extract effective data information and establish a unified data structure system;

Data processing technology for internal processing of power big data;

Data display technology for three-dimensional virtual display of power big data.

Smart grid big data is diverse. When cleaning and filtering data information, it is necessary to fully ensure the quality of the data. Therefore, the data management technology of power big data integrates a variety of data processing technologies, such as data fusion technology, data integration technology, and data cleaning. Technology, data filtering technology and data extraction technology can extract effective data information from massive data, and sort out the relationship between data to form a unified data structure system. The data display technology of power big data is used to display the internal data information of the system, usually in a three-dimensional virtual form, to realize the real-time monitoring function of the internal data of the system. Data display technology includes visualization technology, information flow display technology, etc., and uses screen interaction and interactive map technologies to make data display more concise.

Preferably, the data analysis technology includes:

Index the unit and time codes of power big data from multiple dimensions and automatically filter out interference data;

Parse the SQL language in power big data and translate SQL statements into multiple HQL segments;

Use hybrid storage technology to combine the main table with the attached table to update the stored power big data in real time, and allocate the storage location of the power big data according to the smart grid data operation requirements;

Use hierarchical processing technology to comprehensively process power big data.

There is a huge amount of stored data within the power system of the smart grid, and the storage function may affect the internal data and fail to exert its own value. In the past, corresponding data information was obtained through analysis and calculation, but the processing efficiency of this method was not high. By using data analysis technology, optimization can be performed on the previous internal storage system, thereby improving data processing capabilities and ensuring the efficiency and quality of data processing.

Preferably, the data processing technology includes:

Distributed computing technology for distributed preprocessing of power big data;

Memory computing technology for online real-time calculation of power big data;

Stream processing technology for processing power big data that arrives at just the right time, with uncontrolled speed and scale.

The data processing technology of power big data generally includes distributed computing technology, stream processing technology and memory computing technology.

Preferably, the distributed computing technology includes building a power cloud architecture model, and the power cloud architecture model includes:

The advanced access layer provides computing support for smart grid analysis and evaluation;

Application interface layer, used for authentication authority operations;

The basic application layer provides storage services, implements data permissions and encryption, and data backup;

The physical storage layer locates the storage devices of the smart grid, performs real-time data storage, virtualizes the storage, and centrally manages the storage.

The power cloud can integrate the system's data resource processor without changing the internal network and equipment of the power system to provide maximum storage space for data.

Preferably, the step S4 further includes: mapping the obtained integration results on the geographic information system GIS platform.

Make full use of the GIS system to improve the ability to judge power grid system problems, help staff allocate power resources more conveniently, and seek to maximize the benefits of power application.

Therefore, the present invention has the following beneficial effects: 1. Applying power big data in actual power grid construction can realize the collection and processing of usage, power generation and other data within the smart grid; 2. Big data has powerful information collection and processing capabilities. Storage function, smart grid based on power big data has the characteristics of large quantity, diversification, fast speed, high accuracy and high value; 3. Smart grid based on power big data can improve the operation speed of smart grid system, Improve the power supply efficiency of enterprises and ensure the quality of power consumption of users, thus making the power system more secure and stable.

Description of drawings

Figure 1 is a flow chart of the steps of the method of the present invention.

Detailed ways

The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments:

Example:

As shown in the embodiment shown in Figure 1, we can see a power big data application method for smart grids, including: Step 1, using MR enhanced virtual technology to monitor the smart grid in real time; Step 2, collecting smart grid data Electric power big data, obtain electric power big data processing technology, classify and arrange the collected electric power big data, and establish a database; Step 3: Obtain the smart grid business needs, obtain the corresponding electric power big data from the database according to the business needs, and select the corresponding electric power Big data processing technology; step four, based on the obtained power big data and power big data processing technology, process the business requirements and make relevant decisions to obtain decision results; step five, based on the decision results, perform operation and maintenance of the smart grid and troubleshooting.

Power systems generally include power generation, electricity consumption, dispatching, and production management. In the era of big data, the informatization reform of smart grid is the only way for the development of the power industry. Big data has powerful information collection and storage functions. Smart grids based on power big data have the characteristics of large quantity, diversification, fast speed, high accuracy and high value.

Smart grid increases the number of devices in each network node, and the power data resources are very huge. When analyzing and processing these data, smart grids based on power big data can collect and analyze efficiently. As the data resource system continues to expand, the number of users using smart meters and the power data generated continues to increase, so the collection and processing of power big data have always maintained high efficiency.

Electric power big data can analyze and process data through network technology and has a strong data storage function. It is also closely connected with the Internet. Power big data can use software and hardware equipment, such as storage devices, mobile terminals and servers, to provide corresponding services for smart grids. Applying power big data in actual power grid construction can realize the collection and processing of data on consumption and power generation within the smart grid. Big data has powerful information collection and storage functions. Smart grids based on power big data have the characteristics of large quantity, diversification, fast speed, high accuracy and high value. Smart grids based on power big data can improve the operation speed of smart grid systems, improve the power supply efficiency of enterprises, and ensure the quality of power consumption for users, thereby making the power system more secure and stable.

When power big data processes information, its conditional parameters are not limited by devices and hardware equipment. The application space can be expanded indefinitely without replacing equipment, reducing the cost of expanding equipment.

The solution of this embodiment is further described in detail below:

The first step: Use MR enhanced virtual technology to monitor the smart grid in real time.

Step 2: Collect power big data from smart grids, obtain power big data processing technology, classify and arrange the collected power big data, and establish a database.

Traditional data storage space is limited and the storage state is unstable, which may cause data loss, disorder, etc. With the support of computer network technology, power big data analyzes and processes power data, connects different organizations on the server, organizes data into categories, integrates disordered data in an orderly manner, and arranges them in an orderly manner. , improving the stability of data. In addition, when processing information, it is not easily affected by the surrounding environment, and it is easier to form an intelligent information processing method, further improving information processing efficiency.

Smart grids need to collect, analyze and process data, and also solve some unprocessable files, fault pictures, surveillance videos, etc., so they require a relatively high technical level to implement. Power big data processing technology for smart grids includes data analysis technology, data management technology, data processing technology and data presentation technology.

specific:

1. Data analysis technology for online security analysis of smart grids.

The processing efficiency of obtaining corresponding data information through analysis and calculation is not high. By using data analysis technology, optimization can be performed on the previous internal storage system, thereby improving data processing capabilities and ensuring the efficiency and quality of data processing. Functions such as online tracking, intelligent decision-making, and automatic identification of the power system can all be implemented using online security analysis technology, and the MES-based data model can realize the information management function of the system.

Data analysis techniques include:

Electric power big data needs to have multi-dimensional query functions and fix each query dimension. There may be slight changes in the dimensions. Index the unit and time codes of power big data from multiple dimensions, automatically filter out interference data, and ensure resource utilization.

Analyze the SQL language in power big data and translate SQL statements into multiple HQL segments, which not only avoids manual translation errors, but also reduces the difficulty of analysis and processing, ensuring the efficiency of data translation, thereby providing benefits to the power system. The overall operation is guaranteed.

Using hybrid storage technology, the main table is combined with the attached table to update the stored power big data in real time. According to the smart grid data operation requirements, the storage location of the power big data is allocated to maximize the utilization of resources.

Using hierarchical processing technology to comprehensively process power big data to ensure the correlation and independence between power systems plays an important role in realizing structured management of big data management systems.

2. Extract effective data information and establish data management technology for a unified data structure system.

Smart grid big data is diverse. When cleaning and filtering data information, it is necessary to fully ensure the quality of the data. Therefore, the data management technology of power big data integrates a variety of data processing technologies, such as data fusion technology, data integration technology, and data cleaning. Technology, data filtering technology and data extraction technology can extract effective data information from massive data, and sort out the relationship between data to form a unified data structure system.

This embodiment adopts the unified public model of electric power data for data management. The unified public model of electric power data is a global data model and is not targeted at a specific business in the system. This model can associate and couple multiple classes in the system to achieve data exchange within the system. This model realizes data sharing through data description and view methods, making data exchange more convenient and providing a basis for the expansion of the entire power system.

3. Data processing technology for internal processing of power big data.

Data processing technology includes: splitting the internal programs of power big data, distributed computing technology to achieve distributed pre-processing, memory computing technology for online real-time calculation of power big data, processing data that arrives in a timely manner and the speed and scale are not controlled. Stream processing technology for electric power big data.

For the distributed power system, it includes the first-level power grid, the second-level power grid, the third-level power grid, etc., and the power grid serves as the main cloud, and the other power grids serve as sub-clouds to form a power cloud.

The power cloud can integrate the system's data resource processor without changing the internal network and equipment of the power system to provide maximum storage space for data. In order to ensure the internal data calculation requirements of the power system, the power cloud can develop the system in layers and build a power cloud architecture model.

The power cloud architecture model includes:

The advanced access layer is the top layer of the model and generally includes basic and advanced applications. It can provide an operating platform for each application and provide computing support for stability analysis, economic evaluation, power flow analysis and state estimation of the power system;

The wide area network within the power system is located at the application interface layer. The application interface layer is used for connection, authentication, and permission operations, and is the most active part of the entire power cloud;

The basic application layer is used for the power cloud scheduling conflict mechanism, content distribution and sharing, data permissions and encryption, and data backup, etc., to provide better storage services for the upper structure and achieve collaboration within the system;

The physical storage layer can locate storage devices within the power system and connect these storage devices through certain technical means to achieve real-time data storage functions. In addition, this layer can virtualize storage and achieve centralized management of storage. Status monitoring, maintenance and upgrades within the power system are all implemented at this layer.

4. Data display technology for three-dimensional virtual display of power big data.

The data display technology of power big data is used to display the internal data information of the power system, usually in a three-dimensional virtual form, to realize the real-time monitoring function of the internal data of the power system. Data display technology includes visualization technology, information flow display technology, etc., and uses screen interaction and interactive map technologies to make data display more concise.

Specifically: The three-dimensional virtual substation mainly implements the visual management and monitoring of data. It generally consists of two parts, namely the three-dimensional visual display platform of the substation and the application service integration interface. The former's virtual display platform can combine three-dimensional virtual and digital visualization technology to form a system capable of real-time monitoring, including PMIS system, SCADA system, safety prevention and control system and fire alarm system, thereby realizing the three-dimensional virtual integrated display function of the substation . The basis of the three-dimensional virtual integrated display service is the server within the system, which is generally completed using the application service integration interface.

Step 3: Obtain the smart grid business requirements, obtain the corresponding power big data from the database according to the business requirements, and select the corresponding power big data processing technology.

Business requirements include smart grid operation risk assessment, smart grid power resource allocation, smart grid data management, etc.

Step 4: Based on the obtained electric power big data and electric power big data processing technology, process the business requirements and make relevant decisions to obtain decision results.

Addressing business requirements includes:

1. Use harmonic data to analyze the causes of harmonics and predict the risks harmonics pose to smart grids.

Various types of measuring instruments within the power system will be affected by harmonics and produce errors. Therefore, harmonics will affect the operation of the entire power system. There are many reasons for the generation of harmonics. For example, the system will produce tiny harmonic components during the power transmission process. In addition, some power equipment will also produce harmonics. Some high harmonic components may even cause harm to the use of the equipment. Power big data technology can analyze the causes of harmonics based on data and predict the risks harmonics pose to the power system, thereby providing a more practical and reliable basis for harmonic control.

The specific methods are:

By dividing relevant components and parameters, the fundamental wave and harmonic data of active and reactive power are stored in a table, which is more conducive to data query and extraction;

Calculate the fundamental and harmonic currents, and generate the corresponding harmonic content based on the calculated current;

After completing the storage and calculation of harmonic data, harmonic risk assessment needs to be carried out to further ensure the safety of the power system. In the process of assessing the harmonic risk of power data, harmonics need to be brought into the prediction model, and the ARIMA model is generally used. When using this model, training must be performed first, and then the future change trend of harmonics can be predicted based on harmonic data to provide guarantee for harmonic management.

2. Utilize hierarchical processing of power big data to correlate various power systems for data sharing.

3. Utilize the hierarchical processing and hybrid storage technology of power big data to build a smart grid multi-functional information management system, which improves the collection and storage capabilities of power information and can also be based on actual business needs.

4. Cloud computing and SQL technology can perform real-time analysis and calculation on data, greatly improving the processing efficiency of big data and expanding data storage capacity.

Map the obtained integration results on the GIS platform

Based on the geographical information system GIS, the GIS system is fully utilized to improve the ability to judge power grid system problems. The display data obtained through the big data platform is associated with geographical information to intuitively display the full picture of power grid production and operation, and provide operators with operational management Technical support helps staff allocate power resources more conveniently and seek to maximize the benefits of power application.

Step 5: Based on the decision-making results, carry out operation, maintenance and fault elimination of the smart grid.

Reasonably and effectively utilize power big data information to ensure the safe and stable operation of smart grids and improve the overall performance of the power system.

The above-described embodiment is only a preferred solution of the present invention and does not limit the present invention in any form. There are other variations and modifications without exceeding the technical solution described in the claims.

Claims (8)

1. The intelligent power grid-oriented power big data application method is characterized by comprising the following steps of:

s1: real-time monitoring is carried out on the intelligent power grid by utilizing an MR enhanced virtual technology;

s2: acquiring power big data of a smart grid, acquiring a power big data processing technology, classifying and arranging the acquired power big data, and establishing a database;

s3: acquiring business requirements of the intelligent power grid, acquiring corresponding power big data from a database according to the business requirements, and selecting a corresponding power big data processing technology;

s4: based on the acquired power big data and the power big data processing technology, processing the service demand and making relevant decisions to obtain decision results;

s5: and based on the decision result, performing operation maintenance and fault elimination of the intelligent power grid.

2. The smart grid-oriented power big data application method of claim 1, wherein processing the business requirements comprises:

analyzing a harmonic generation reason by utilizing harmonic data, and predicting the risk of the harmonic to the intelligent power grid;

using layering processing of the power big data, associating each power system, and carrying out data sharing;

and constructing a multifunctional informatization management system of the intelligent power grid by using a layering processing and hybrid storage technology of the electric power big data.

3. The smart grid-oriented power big data application method according to claim 2, wherein in the step S3, predicting the risk of the harmonic wave to the smart grid comprises:

storing active and reactive fundamental wave and harmonic wave data in a table by dividing related elements and parameters;

calculating currents of fundamental waves and harmonic waves, and generating corresponding harmonic content according to the calculated currents;

and inputting the harmonic content into a harmonic risk prediction model obtained by training, and carrying out risk assessment on the harmonic.

4. The smart grid-oriented power big data application method of claim 1, wherein the power big data processing technology comprises:

performing data analysis technology of intelligent power grid safety online analysis;

extracting effective data information and establishing a data management technology of a unified data structure system;

a data processing technique for processing the inside of the large power data;

and a data display technology for performing three-dimensional virtual display on the electric power big data.

5. The smart grid-oriented power big data application method of claim 4, wherein the data analysis technique comprises:

indexing the unit and time code of the large power data from multiple dimensions, and automatically filtering interference data;

analyzing SQL language in the electric power big data, and translating SQL sentences into a plurality of HQL language segments;

combining the main table with the auxiliary table by utilizing a hybrid storage technology, updating stored electric power big data in real time, and distributing the storage position of the electric power big data according to the data operation requirement of the intelligent power grid;

and comprehensively processing the power big data by using a hierarchical processing technology.

6. The smart grid-oriented power big data application method according to claim 4 or 5, wherein the data processing technology comprises:

a distributed computing technique for performing distributed preprocessing on the inside of the large power data;

a memory computing technology for performing online real-time computation of the power big data;

techniques for streaming large power data arriving at a timely time, with uncontrolled speed and scale.

7. The smart grid-oriented power big data application method of claim 6, wherein the distributed computing technology comprises building a power cloud architecture model, the power cloud architecture model comprising:

the advanced access layer provides calculation support for analysis and evaluation of the smart grid;

an application interface layer for authenticating the rights operation;

the basic application layer provides storage service to realize authority and encryption of data and backup of the data;

and the physical storage layer is used for positioning storage equipment of the intelligent power grid, carrying out real-time data storage, virtualizing storage and carrying out centralized management on the storage.

8. The smart grid-oriented power big data application method according to any one of claims 1 to 5, wherein the step S4 further includes: and mapping the obtained integration result on a Geographic Information System (GIS) platform.