CN117277566A - Power grid data analysis power dispatching system and method based on big data - Google Patents
Power grid data analysis power dispatching system and method based on big data Download PDFInfo
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- H—ELECTRICITY
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Abstract
The invention discloses a power grid data analysis power dispatching system and method based on big data, belonging to the technical field of power dispatching, and comprising the following steps: the system comprises a power grid information acquisition module, a power grid data processing module, a power grid data analysis module, a power dispatching management and control module and a power data storage module. The method solves the problems that the prior power system cannot perform real-time monitoring analysis and power dispatching management and control on the power grid data when in operation, so that the power dispatching management and control effect is poor and the normal operation of the power system cannot be fully ensured.
Description
Technical Field
The invention relates to the technical field of power dispatching, in particular to a power dispatching system and a power dispatching method based on big data power grid data analysis.
Background
The power system comprises a power substation, a power transmission unit and a power distribution unit, wherein the power substation comprises a power grid, a power transmission unit and a power distribution unit, the power grid is used for transmitting and distributing electric energy, and the voltage is changed; the power dispatching is an effective management means for ensuring safe and stable operation of the power grid, external reliable power supply and orderly execution of various power production works.
Chinese patent publication No. CN114362149a discloses a method, system, device and medium for evaluating the power generation bearing capacity of new energy, comprising: the method comprises the steps of sending a preset fault to a new energy power generation grid-connected system, collecting power grid data of a fault injection point, analyzing and processing the power grid data, and judging whether the power grid data accords with a preset parameter index of the new energy power generation grid-connected system; if the power grid data accords with the parameter index, updating the power grid parameters by a power multiplication method, and analyzing the power grid data again until the power grid data does not accord with the preset parameter index of the new energy power generation grid connection, so as to obtain final power grid data; obtaining an evaluation result of the power generation bearing capacity of the new energy according to the final power grid data; the method solves the problems that the impedance of the new energy power generation system and the stability of the analysis system cannot be considered by the conventional method utilizing the electromechanical transient simulation. However, the above patent has the following drawbacks in practical use:
when the existing power system is operated, real-time monitoring analysis and power dispatching control cannot be carried out on power grid data, so that the power dispatching control effect is poor, and normal operation of the power system cannot be fully guaranteed.
Disclosure of Invention
The invention aims to provide a power grid data analysis power dispatching system and a power grid data analysis power dispatching method based on big data, so that when a power system is in operation, the power grid data can be monitored and analyzed in real time, the power dispatching management and control effect is improved, the normal operation of the power system can be fully ensured, and the problems in the background art are solved.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a big data based grid data analysis power dispatching system comprising:
the power grid information acquisition module is used for acquiring power grid information of the power system in an operating state in real time;
acquiring voltage, current, electric quantity and electric power picture information of an electric power system in an operation state in real time based on various sensors and high-definition cameras, and determining electric network information based on big data;
the power grid data processing module is used for processing the power grid information acquired in real time;
acquiring power grid information based on big data, searching, extracting and calculating the power grid information, and determining power grid characterization data based on the big data;
the power grid data analysis module is used for analyzing the processed power grid characterization data;
acquiring grid characterization data based on big data, indexing and extracting grid load data based on the grid characterization data, analyzing the grid characterization data based on the grid load data, and determining a grid data analysis table based on the big data;
the power dispatching management and control module is used for dispatching and controlling the power system;
acquiring a power grid data analysis table based on big data, performing deep analysis on the power grid data analysis table based on a data mining technology, determining a power dispatching control method, and performing dispatching control on a power system based on the power dispatching control method;
and the power data storage module is used for storing the power grid information and the power grid load data acquired in real time.
Preferably, the power grid information acquisition module includes:
the voltage sensor is used for acquiring voltage information of the power system in an operating state in real time;
the current sensor is used for acquiring current information of the power system in an operating state in real time;
the electric quantity sensor is used for acquiring electric quantity information of the electric power system in an operation state in real time;
the high-definition camera is used for acquiring power picture information of the power system in an operating state in real time;
and determining the power grid information based on the big data based on the voltage information, the current information, the electric quantity information and the power picture information of the power system in the running state, which are acquired in real time.
Preferably, the power grid data processing module includes:
the power grid data retrieval unit is used for retrieving data of power grid information acquired in real time;
acquiring power grid information based on big data, searching the power grid information based on a sequential searching method, filtering out power grid information useless for power grid data analysis and power dispatching, and determining power grid information useful for the power grid data analysis and power dispatching;
the power grid data extraction unit is used for extracting characteristics of the retrieved power grid information;
acquiring power grid information useful for power grid data analysis and power dispatching, and carrying out feature extraction on the determined power grid information useful for power grid data analysis and power dispatching based on a principal component analysis technology to determine power grid feature data based on big data;
the power grid data calculation unit is used for carrying out data calculation on the extracted power grid information;
and acquiring the power grid characteristic data based on the big data, calculating the power grid characteristic data, and determining the power grid characteristic data based on the big data.
Preferably, the power grid data analysis module includes:
the data index calling unit is used for indexing and calling out power grid load data;
acquiring grid characterization data based on big data, and indexing and retrieving grid load data matched with the grid characterization data based on the grid characterization data;
the data comparison and analysis unit is used for carrying out comparison and analysis on the power grid characterization data;
and acquiring the power grid characterization data and the power grid load data, analyzing the power grid characterization data based on the power grid load data, and determining a power grid data analysis table based on big data.
Preferably, the power dispatching management and control module includes:
the scheduling scheme making unit is used for making a power scheduling management and control method;
acquiring a power grid data analysis table based on big data, performing deep analysis on the power grid data analysis table based on a data mining technology, and determining a power dispatching management and control method based on the power grid data analysis table;
the dispatching management and control execution unit is used for dispatching and controlling the power system;
and acquiring a power dispatching control method based on the power grid data analysis table, and dispatching and controlling the power system based on the power dispatching control method.
Preferably, the power data storage module includes:
the power grid information storage unit is used for storing power grid information acquired in real time;
acquiring power grid information acquired in real time, and storing the power grid information in a power grid information storage unit;
and the power grid load storage unit is used for storing power grid load data and providing a reference basis for analyzing power dispatching of the power grid data.
According to another aspect of the present invention, there is provided a big data based power dispatching method for analyzing power of a power grid, based on the big data based power dispatching system, comprising the steps of:
s1: the method comprises the steps that power grid information of an electric power system in an operation state is collected in real time through a power grid information collection module, and the power grid information collected in real time is processed through a power grid data processing module to determine power grid representation data based on big data;
s2: and analyzing the grid characterization data based on the big data through a grid data analysis module, determining a grid data analysis table based on the big data, and scheduling and controlling the power system by utilizing a power scheduling and controlling module.
Preferably, in the step S2, the power system is scheduled and controlled, and the following operations are performed:
acquiring grid characterization data based on big data;
based on the power grid representation data, indexing and retrieving power grid load data matched with the power grid representation data;
analyzing the power grid characterization data based on the power grid load data;
aiming at the condition that the power grid representation data is in the power grid load data range, a power grid data analysis table based on big data is that the power system operates normally;
aiming at the condition that the power grid representation data is not in the power grid load data range, the power grid data analysis table based on big data is abnormal operation of the power system;
determining a power dispatching management and control method based on a power grid data analysis table of big data, and dispatching and controlling a power system based on the power dispatching management and control method;
aiming at the condition that the power grid data analysis table based on big data is abnormal in operation of the power system, the power system sends out early warning, the power system performs power scheduling, power load distribution is adjusted, and relevant power equipment is guided to operate.
Preferably, the method for acquiring the power grid information based on big data and searching the power grid information based on a sequential searching method, filtering the power grid information useless for analyzing the power dispatching of the power grid data, and determining the power grid information useful for analyzing the power dispatching of the power grid data includes:
determining the current statistical data type of the power grid information;
extracting a power grid information sample of the current data type from a database in the database;
classifying the power grid information samples by using a self-organizing feature mapping neural network to obtain classification results;
extracting attribute characteristic values of each category in the classification result, identifying the attribute characteristic values of each category, and constructing an attribute characteristic database;
storing the attribute characteristic values of each category in each attribute characteristic database into different data layers of the attribute characteristic database respectively;
extracting corresponding current attribute characteristic values from the power grid information by a principal component analysis method;
inputting the current attribute characteristic value into each data layer of an attribute characteristic database, and obtaining the matching degree output by each data layer;
determining a plurality of data tags of the power grid information based on the matching degree output by each data layer;
screening out the mapping power grid information of each data tag from the power grid information according to the data mapping attribute of the plurality of data tags of the power grid information and integrating the mapping power grid information into target power grid information;
searching the target power grid information based on a sequential searching method, and determining the data change rate between two adjacent power grid data according to a searching result;
screening main factors influencing the load change through correlation analysis according to the statistical data of the power grid load and various factors possibly influencing the load change;
determining the association relation between the load change of the power grid and the main factor;
determining a change rule of the power grid load under the influence of the main factors according to the association relation;
determining the change trend of the power grid data in the target power grid information according to the change rule;
determining abnormal power grid data and normal power grid data based on the change trend of the power grid data and the data change rate between two adjacent power grid data in the target power grid information;
confirming abnormal grid data as grid information which is useless for analyzing power dispatching of the grid data, and confirming normal grid data as grid information which is useful for analyzing power dispatching of the grid data;
and filtering the abnormal power grid data.
Preferably, based on a data mining technology, deep analysis is performed on a power grid data analysis table, and a power dispatching management and control method based on the power grid data analysis table is determined, including:
based on a data mining technology, carrying out deep analysis on a power grid data analysis table, and determining a power dispatching cycle and a power dispatching data sequence of the power grid data analysis table;
determining a number value of the power scheduling data sequence, and determining power scheduling congestion degree according to the number value;
determining the maximum power communication service quantity under each power dispatching data sequence according to the power dispatching congestion degree;
calculating a power dispatching cost index based on a power grid data analysis table according to the maximum power communication service quantity and the power dispatching congestion degree under each power dispatching data sequence and the power dispatching period of the power grid data analysis table:
wherein Q is represented as a power dispatching cost index based on a power grid data analysis table, T is represented as a power dispatching period of the power grid data analysis table, T' is represented as a reference period under standard power dispatching, beta is represented as a calibrated power dispatching time delay factor in the power grid data analysis table, f () is represented as a preset cost function, N is represented as the number of power dispatching data sequences, i is represented as an ith power dispatching data sequence, S i The maximum power communication traffic amount expressed as the ith power schedule data sequence, θ expressed as power schedule congestion degree, S' expressed as synchronous power communication traffic processing number maintaining stable power scheduleThe quantity, ρ, is expressed as an objectivity index of the grid data analysis table;
and determining a relaxation factor for power dispatching based on the power dispatching cost index of the power grid data analysis table, and generating a power dispatching management and control method based on the power grid data analysis table according to the relaxation factor.
Compared with the prior art, the invention has the beneficial effects that:
according to the large-data-based power grid data analysis power dispatching system and method, voltage, current, electric quantity and power picture information of a power system in an operation state are obtained in real time based on various sensors and high-definition cameras, large-data-based power grid information is determined, the large-data-based power grid information is retrieved, extracted and calculated, large-data-based power grid characterization data is determined, power grid load data is extracted in an index mode based on the power grid characterization data, the large-data-based power grid data analysis table is determined based on the power grid load data, deep analysis is performed on the power grid data analysis table, a power dispatching management and control method is determined, and the power system is dispatched and controlled based on the power dispatching management and control method, so that the power system can perform real-time monitoring analysis and power dispatching management and control on the power grid data when in operation, the power dispatching management and control effect is improved, and normal operation of the power system can be fully guaranteed.
Drawings
FIG. 1 is a block diagram of a big data based grid data analysis power dispatching system of the present invention;
FIG. 2 is a flow chart of the big data based grid data analysis power dispatching system of the present invention;
fig. 3 is an algorithm diagram of the big data based power grid data analysis power dispatching system of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to solve the problem that the existing power system cannot perform real-time monitoring analysis and power dispatching management and control on power grid data when in operation, resulting in poor power dispatching management and control effect and cannot fully ensure normal operation of the power system, referring to fig. 1-3, the embodiment provides the following technical scheme:
the power grid data analysis and power dispatching system based on the big data comprises a power grid information acquisition module, a power grid data processing module, a power grid data analysis module, a power dispatching management and control module and a power data storage module;
the power grid information acquisition module acquires power grid information of the power system in an operation state in real time and stores the power grid information acquired in real time in the power data storage module; the power grid data processing module processes the power grid information acquired in real time and determines power grid characterization data based on big data; the power grid data analysis module analyzes the processed power grid characterization data and determines a power grid data analysis table based on big data; the power dispatching management and control module is used for dispatching and controlling the power system;
the power grid information acquisition module comprises a voltage sensor, a current sensor, an electric quantity sensor and a high-definition camera;
the voltage sensor acquires voltage information of the power system in the running state in real time;
specifically, the voltage sensor is a sensor capable of sensing the measured voltage and converting the measured voltage into a usable output signal, and in various automatic detection and control systems, tracking and acquisition are often required for alternating current and direct current voltage signals which change at high speed, and spectrum analysis is performed for relatively complex voltage waveforms.
The current sensor acquires current information of the power system in the running state in real time;
specifically, the current sensor is a detection device, can sense the information of the detected current, and can convert the information sensed by detection into an electric signal or other information output in a required form according to a certain rule, so as to meet the requirements of information transmission, processing, storage, display, recording, control and the like.
It should be noted that, the electric quantity sensor acquires the electric quantity information of the electric power system in the running state in real time;
specifically, the electric quantity sensor is a detection device, can sense the information of the detected electric quantity, can convert the sensed information into an electric signal or other information output in a required form according to a certain rule so as to meet the requirements of information transmission, processing, storage, display, recording, control and the like, and is a primary link for realizing automatic detection and automatic control, and is also a device for converting the parameter of the detected electric quantity into direct current and direct voltage and isolating and outputting an analog signal or a digital signal.
It should be noted that, the high-definition camera acquires the power picture information of the power system in the running state in real time;
specifically, the high-definition camera refers to a camera of HD 1080P, HD 960P or HD 720P, and can obtain high-definition power picture information of the power system in an operation state.
And determining the power grid information based on the big data based on the voltage information, the current information, the electric quantity information and the power picture information of the power system in the running state, which are acquired in real time.
The power grid data processing module comprises a power grid data retrieval unit, a power grid data extraction unit and a power grid data calculation unit;
it should be noted that, the power grid data retrieval unit performs data retrieval on the power grid information acquired in real time;
specifically, acquiring power grid information based on big data, searching the power grid information based on a sequential searching method, filtering out power grid information useless for power grid data analysis and power dispatching, and determining power grid information useful for the power grid data analysis and power dispatching;
it should be noted that, the grid information collected in real time includes grid information with incomplete data, which is useless and valuable for the grid data analysis and power dispatching, so that the grid information with incomplete data needs to be filtered by the grid data searching unit.
The power grid data extraction unit extracts features of the retrieved power grid information;
specifically, acquiring power grid information useful for power grid data analysis and power dispatching, performing feature extraction on the determined power grid information useful for power grid data analysis and power dispatching based on a principal component analysis technology, and determining power grid feature data based on big data;
the power grid data calculation unit calculates the data of the extracted power grid information;
specifically, the power grid characteristic data based on big data is obtained, the power grid characteristic data is calculated, and the power grid characteristic data based on the big data is determined.
The power grid data analysis module comprises a data index calling unit and a data comparison analysis unit;
it should be noted that, the data index calling unit may call out the power grid load data in an index manner;
specifically, acquiring grid characterization data based on big data, and indexing and extracting grid load data matched with the grid characterization data based on the grid characterization data;
it should be noted that the data comparison analysis unit may perform comparison analysis on the power grid characterization data;
specifically, the power grid characterization data and the power grid load data are obtained, the power grid characterization data are analyzed based on the power grid load data, and a power grid data analysis table based on big data is determined.
The power dispatching management and control module comprises a dispatching scheme making unit and a dispatching management and control executing unit;
it should be noted that, the scheduling scheme making unit may make a power scheduling management and control method;
specifically, a power grid data analysis table based on big data is obtained, the power grid data analysis table is subjected to deep analysis based on a data mining technology, and a power dispatching management and control method based on the power grid data analysis table is determined;
it should be noted that the scheduling control execution unit may perform scheduling control on the power system;
specifically, a power dispatching control method based on a power grid data analysis table is obtained, and dispatching control is performed on a power system based on the power dispatching control method.
The power data storage module comprises a power grid information storage unit and a power grid load storage unit;
it should be noted that the power grid information storage unit may store power grid information collected in real time;
specifically, acquiring power grid information acquired in real time, and storing the power grid information in a power grid information storage unit;
it should be noted that the grid load storage unit may store grid load data, and provide a reference basis for the grid data analysis and power dispatching.
It should be noted that, the scheduling control for the power system includes:
acquiring grid characterization data based on big data;
based on the power grid representation data, indexing and retrieving power grid load data matched with the power grid representation data;
analyzing the power grid characterization data based on the power grid load data;
aiming at the condition that the power grid representation data is in the power grid load data range, a power grid data analysis table based on big data is that the power system operates normally;
aiming at the condition that the power grid representation data is not in the power grid load data range, the power grid data analysis table based on big data is abnormal operation of the power system;
determining a power dispatching management and control method based on a power grid data analysis table of big data, and dispatching and controlling a power system based on the power dispatching management and control method;
aiming at the condition that the power grid data analysis table based on big data is abnormal in operation of the power system, the power system sends out early warning, the power system performs power scheduling, power load distribution is adjusted, and relevant power equipment is guided to operate.
Grid characterization data as analyzed is noted P 1 The stored grid load data is denoted as P 0 ；
If P 1 ≤P 0 The power grid data analysis table based on big data is that the power system operates normally;
if P 1 ＞P 0 The power grid data analysis table based on big data is abnormal operation of the power system;
the power dispatching conditions according to the analysis of the power grid data are shown in table 1:
table 1: power grid data analysis power dispatching condition
In order to better show the power dispatching flow of the power grid data analysis based on big data, the embodiment now provides the power dispatching method of the power grid data analysis based on big data, and the power dispatching system implementation of the power grid data analysis based on big data comprises the following steps:
s1: the method comprises the steps that power grid information of an electric power system in an operation state is collected in real time through a power grid information collection module, and the power grid information collected in real time is processed through a power grid data processing module to determine power grid representation data based on big data;
s2: and analyzing the grid characterization data based on the big data through a grid data analysis module, determining a grid data analysis table based on the big data, and scheduling and controlling the power system by utilizing a power scheduling and controlling module.
In one embodiment, acquiring grid information based on big data, retrieving the grid information based on a sequential retrieval method, filtering out grid information useless for analyzing power dispatching of the grid data, and determining the grid information useful for analyzing the power dispatching of the grid data, including:
determining the current statistical data type of the power grid information;
extracting a power grid information sample of the current data type from a database in the database;
classifying the power grid information samples by using a self-organizing feature mapping neural network to obtain classification results;
extracting attribute characteristic values of each category in the classification result, identifying the attribute characteristic values of each category, and constructing an attribute characteristic database;
storing the attribute characteristic values of each category in each attribute characteristic database into different data layers of the attribute characteristic database respectively;
extracting corresponding current attribute characteristic values from the power grid information by a principal component analysis method;
inputting the current attribute characteristic value into each data layer of an attribute characteristic database, and obtaining the matching degree output by each data layer;
determining a plurality of data tags of the power grid information based on the matching degree output by each data layer;
screening out the mapping power grid information of each data tag from the power grid information according to the data mapping attribute of the plurality of data tags of the power grid information and integrating the mapping power grid information into target power grid information;
searching the target power grid information based on a sequential searching method, and determining the data change rate between two adjacent power grid data according to a searching result;
screening main factors influencing the load change through correlation analysis according to the statistical data of the power grid load and various factors possibly influencing the load change;
determining the association relation between the load change of the power grid and the main factor;
determining a change rule of the power grid load under the influence of the main factors according to the association relation;
determining the change trend of the power grid data in the target power grid information according to the change rule;
determining abnormal power grid data and normal power grid data based on the change trend of the power grid data and the data change rate between two adjacent power grid data in the target power grid information;
confirming abnormal grid data as grid information which is useless for analyzing power dispatching of the grid data, and confirming normal grid data as grid information which is useful for analyzing power dispatching of the grid data;
and filtering the abnormal power grid data.
The beneficial effects of the technical scheme are as follows: the data filtering of the electric network information can be primarily realized by firstly removing the five sense organs electric network data in the electric network information by utilizing the data attribute. The method reduces the subsequent processing samples, improves the working efficiency and the practicability, further, determines the objective data change trend according to the hard influence factors of the power grid load, and further verifies the data change rate of real-time data in the power grid information according to the data change trend, so that abnormal data can be accurately and stably screened out and removed, and further improves the working efficiency and the precision.
In one embodiment, based on a data mining technology, a deep analysis is performed on a power grid data analysis table, and a power dispatching management and control method based on the power grid data analysis table is determined, including:
based on a data mining technology, carrying out deep analysis on a power grid data analysis table, and determining a power dispatching cycle and a power dispatching data sequence of the power grid data analysis table;
determining a number value of the power scheduling data sequence, and determining power scheduling congestion degree according to the number value;
determining the maximum power communication service quantity under each power dispatching data sequence according to the power dispatching congestion degree;
calculating a power dispatching cost index based on a power grid data analysis table according to the maximum power communication service quantity and the power dispatching congestion degree under each power dispatching data sequence and the power dispatching period of the power grid data analysis table:
wherein Q tableThe power dispatching cost index is shown as a power dispatching cost index based on a power grid data analysis table, T is shown as a power dispatching period of the power grid data analysis table, T' is shown as a reference period under standard power dispatching, beta is shown as a calibrated power dispatching time delay factor in the power grid data analysis table, f () is shown as a preset cost function, N is shown as the number of power dispatching data sequences, i is shown as an ith power dispatching data sequence, S i The maximum power communication service quantity expressed as an ith power scheduling data sequence, theta expressed as power scheduling congestion degree, S' expressed as synchronous power communication service processing quantity for maintaining stable power scheduling, and ρ expressed as objectivity index of a power grid data analysis table;
and determining a relaxation factor for power dispatching based on the power dispatching cost index of the power grid data analysis table, and generating a power dispatching management and control method based on the power grid data analysis table according to the relaxation factor.
The beneficial effects of the technical scheme are as follows: the implementation difficulty and the accuracy of the power dispatching management and control scheme of the power grid data analysis table can be intuitively evaluated by calculating the power dispatching cost index based on the power grid data analysis table, so that risks are avoided with high probability, stable dispatching work is ensured, and the practicability and the stability are further improved.
In summary, the system and the method for power dispatching analysis based on the large data of the power grid data, disclosed by the invention, acquire the voltage, the current, the electric quantity and the power picture information of the power system in the running state in real time based on various sensors and high-definition cameras, determine the power grid information based on the large data, search, extract and calculate the power grid information, determine the power grid characterization data based on the large data, retrieve the power grid load data based on the power grid characterization data, analyze the power grid characterization data based on the power grid load data, determine the power grid data analysis table based on the large data, deeply analyze the power grid data analysis table based on the data mining technology, determine the power dispatching management and control method, and dispatch and control the power system based on the power dispatching management and control method, so that the power system can perform real-time monitoring analysis and power dispatching management and control on the power grid data when running, the power dispatching management and control effect is improved, and the normal running of the power system can be fully ensured.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. The utility model provides a power dispatching system is analyzed to electric wire netting data based on big data which characterized in that includes:
the power grid information acquisition module is used for acquiring power grid information of the power system in an operating state in real time;
acquiring voltage, current, electric quantity and electric power picture information of an electric power system in an operation state in real time based on various sensors and high-definition cameras, and determining electric network information based on big data;
the power grid data processing module is used for processing the power grid information acquired in real time;
acquiring power grid information based on big data, searching, extracting and calculating the power grid information, and determining power grid characterization data based on the big data;
the power grid data analysis module is used for analyzing the processed power grid characterization data;
acquiring grid characterization data based on big data, indexing and extracting grid load data based on the grid characterization data, analyzing the grid characterization data based on the grid load data, and determining a grid data analysis table based on the big data;
the power dispatching management and control module is used for dispatching and controlling the power system;
acquiring a power grid data analysis table based on big data, performing deep analysis on the power grid data analysis table based on a data mining technology, determining a power dispatching control method, and performing dispatching control on a power system based on the power dispatching control method;
and the power data storage module is used for storing the power grid information and the power grid load data acquired in real time.
2. The big data based grid data analysis power dispatching system of claim 1, wherein the grid information collection module comprises:
the voltage sensor is used for acquiring voltage information of the power system in an operating state in real time;
the current sensor is used for acquiring current information of the power system in an operating state in real time;
the electric quantity sensor is used for acquiring electric quantity information of the electric power system in an operation state in real time;
the high-definition camera is used for acquiring power picture information of the power system in an operating state in real time;
and determining the power grid information based on the big data based on the voltage information, the current information, the electric quantity information and the power picture information of the power system in the running state, which are acquired in real time.
3. The big data based grid data analysis power dispatching system of claim 2, wherein the grid data processing module comprises:
the power grid data retrieval unit is used for retrieving data of power grid information acquired in real time;
acquiring power grid information based on big data, searching the power grid information based on a sequential searching method, filtering out power grid information useless for power grid data analysis and power dispatching, and determining power grid information useful for the power grid data analysis and power dispatching;
the power grid data extraction unit is used for extracting characteristics of the retrieved power grid information;
acquiring power grid information useful for power grid data analysis and power dispatching, and carrying out feature extraction on the determined power grid information useful for power grid data analysis and power dispatching based on a principal component analysis technology to determine power grid feature data based on big data;
the power grid data calculation unit is used for carrying out data calculation on the extracted power grid information;
and acquiring the power grid characteristic data based on the big data, calculating the power grid characteristic data, and determining the power grid characteristic data based on the big data.
4. A big data based grid data analysis power dispatching system according to claim 3, wherein the grid data analysis module comprises:
the data index calling unit is used for indexing and calling out power grid load data;
acquiring grid characterization data based on big data, and indexing and retrieving grid load data matched with the grid characterization data based on the grid characterization data;
the data comparison and analysis unit is used for carrying out comparison and analysis on the power grid characterization data;
and acquiring the power grid characterization data and the power grid load data, analyzing the power grid characterization data based on the power grid load data, and determining a power grid data analysis table based on big data.
5. The big data based grid data analysis power dispatching system of claim 4, wherein the power dispatching management module comprises:
the scheduling scheme making unit is used for making a power scheduling management and control method;
acquiring a power grid data analysis table based on big data, performing deep analysis on the power grid data analysis table based on a data mining technology, and determining a power dispatching management and control method based on the power grid data analysis table;
the dispatching management and control execution unit is used for dispatching and controlling the power system;
and acquiring a power dispatching control method based on the power grid data analysis table, and dispatching and controlling the power system based on the power dispatching control method.
6. The big data based grid data analysis power dispatching system of claim 5, wherein the power data storage module comprises:
the power grid information storage unit is used for storing power grid information acquired in real time;
acquiring power grid information acquired in real time, and storing the power grid information in a power grid information storage unit;
and the power grid load storage unit is used for storing power grid load data and providing a reference basis for analyzing power dispatching of the power grid data.
7. The big data-based power dispatching method for power grid data analysis based on the big data-based power dispatching system is realized by the big data-based power dispatching system, and is characterized by comprising the following steps:
s1: the method comprises the steps that power grid information of an electric power system in an operation state is collected in real time through a power grid information collection module, and the power grid information collected in real time is processed through a power grid data processing module to determine power grid representation data based on big data;
s2: and analyzing the grid characterization data based on the big data through a grid data analysis module, determining a grid data analysis table based on the big data, and scheduling and controlling the power system by utilizing a power scheduling and controlling module.
8. The big data based power grid data analysis power dispatching method according to claim 7, wherein in S2, the power system is dispatched and controlled, and the following operations are performed:
acquiring grid characterization data based on big data;
based on the power grid representation data, indexing and retrieving power grid load data matched with the power grid representation data;
analyzing the power grid characterization data based on the power grid load data;
aiming at the condition that the power grid representation data is in the power grid load data range, a power grid data analysis table based on big data is that the power system operates normally;
aiming at the condition that the power grid representation data is not in the power grid load data range, the power grid data analysis table based on big data is abnormal operation of the power system;
determining a power dispatching management and control method based on a power grid data analysis table of big data, and dispatching and controlling a power system based on the power dispatching management and control method;
aiming at the condition that the power grid data analysis table based on big data is abnormal in operation of the power system, the power system sends out early warning, the power system performs power scheduling, power load distribution is adjusted, and relevant power equipment is guided to operate.
9. The big data based power grid data analysis power dispatching method according to claim 3, wherein the obtaining of the big data based power grid information, the retrieving of the power grid information based on the sequential retrieving method, the filtering of the power grid information useless for the power grid data analysis power dispatching, and the determining of the power grid information useful for the power grid data analysis power dispatching, comprises:
determining the current statistical data type of the power grid information;
extracting a power grid information sample of the current data type from a database in the database;
classifying the power grid information samples by using a self-organizing feature mapping neural network to obtain classification results;
extracting attribute characteristic values of each category in the classification result, identifying the attribute characteristic values of each category, and constructing an attribute characteristic database;
storing the attribute characteristic values of each category in each attribute characteristic database into different data layers of the attribute characteristic database respectively;
extracting corresponding current attribute characteristic values from the power grid information by a principal component analysis method;
inputting the current attribute characteristic value into each data layer of an attribute characteristic database, and obtaining the matching degree output by each data layer;
determining a plurality of data tags of the power grid information based on the matching degree output by each data layer;
screening out the mapping power grid information of each data tag from the power grid information according to the data mapping attribute of the plurality of data tags of the power grid information and integrating the mapping power grid information into target power grid information;
searching the target power grid information based on a sequential searching method, and determining the data change rate between two adjacent power grid data according to a searching result;
screening main factors influencing the load change through correlation analysis according to the statistical data of the power grid load and various factors possibly influencing the load change;
determining the association relation between the load change of the power grid and the main factor;
determining a change rule of the power grid load under the influence of the main factors according to the association relation;
determining the change trend of the power grid data in the target power grid information according to the change rule;
determining abnormal power grid data and normal power grid data based on the change trend of the power grid data and the data change rate between two adjacent power grid data in the target power grid information;
confirming abnormal grid data as grid information which is useless for analyzing power dispatching of the grid data, and confirming normal grid data as grid information which is useful for analyzing power dispatching of the grid data;
and filtering the abnormal power grid data.
10. The big data-based power dispatching method for power grid data analysis according to claim 5, wherein the deep analysis is performed on the power grid data analysis table based on a data mining technology, and the power dispatching management and control method based on the power grid data analysis table is determined, and the method comprises the following steps:
based on a data mining technology, carrying out deep analysis on a power grid data analysis table, and determining a power dispatching cycle and a power dispatching data sequence of the power grid data analysis table;
determining a number value of the power scheduling data sequence, and determining power scheduling congestion degree according to the number value;
determining the maximum power communication service quantity under each power dispatching data sequence according to the power dispatching congestion degree;
calculating a power dispatching cost index based on a power grid data analysis table according to the maximum power communication service quantity and the power dispatching congestion degree under each power dispatching data sequence and the power dispatching period of the power grid data analysis table:
wherein Q is represented as a power dispatching cost index based on a power grid data analysis table, T is represented as a power dispatching period of the power grid data analysis table, T' is represented as a reference period under standard power dispatching, beta is represented as a calibrated power dispatching time delay factor in the power grid data analysis table, f () is represented as a preset cost function, N is represented as the number of power dispatching data sequences, i is represented as an ith power dispatching data sequence, S i The maximum power communication service quantity expressed as an ith power scheduling data sequence, theta expressed as power scheduling congestion degree, S' expressed as synchronous power communication service processing quantity for maintaining stable power scheduling, and ρ expressed as objectivity index of a power grid data analysis table;
and determining a relaxation factor for power dispatching based on the power dispatching cost index of the power grid data analysis table, and generating a power dispatching management and control method based on the power grid data analysis table according to the relaxation factor.
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