Intelligent power dispatching system based on big data

Abstract

The invention relates to the cross technical field of the information technology field and the electric power energy field, and discloses an intelligent electric power dispatching system based on big data, which comprises an electric power data acquisition module, an electric power data analysis module, an electric power result diagnosis module, an electric power result evaluation module, an electric power execution module and an electric power optimization module, the electric power data acquisition module is used for acquiring data; the electric power data analysis module is used for performing data calculation; the acquired data is deeply processed by applying an algorithm formula; the electric power result diagnosis module is used for performing problem judgment on a power grid state and each electric power operation link; the electric power execution module converts diagnosis and evaluation results into actual operation, the electric power optimization module performs optimization according to system operation problems and effect feedback of the electric power execution module, and according to mutual cooperation of the modules, the problems that in an existing system, data acquisition precision is insufficient, data transmission is prone to being interfered, and the data processing speed is low are solved.

Description

Technical Field

[0001] The present invention relates to the intersecting technical field of information technology and electric power energy, and specifically to an intelligent electric power dispatching system based on big data. Background Art

[0002] In the operation and management of power systems, the accuracy, completeness and timeliness of data processing are crucial. However, the existing intelligent power dispatching system based on big data still faces some challenges.

[0003] Data collection devices such as sensors and smart meters may have measurement errors due to long-term use, environmental factors (such as temperature, humidity, electromagnetic interference and other interference), or quality problems of the equipment itself, resulting in deviations between the collected data and the actual value. This will affect the accurate judgment of the power grid status, and further affect the scientificity and effectiveness of scheduling decisions.

[0004] Communication interference is also a problem. During data transmission, electromagnetic interference, network failures and other factors may affect data loss or errors. For example, in wireless communications, signals may be blocked by buildings and mountain obstacles, or interfered with by other wireless devices, which may affect the quality of data transmission. This will cause the dispatching system to be unable to obtain complete power grid information, affecting its comprehensive control of the power grid and timely dispatching.

[0005] In addition, in the face of massive amounts of power data, the system's big data processing capabilities are limited by hardware equipment and software algorithms, resulting in slow data processing speeds, which will affect the real-time performance of the dispatching system and make it impossible to respond to changes in the power grid in a timely manner. For example, when processing peak power load data, if the processing speed is too slow, it will cause delays in dispatching decisions and affect the stability of the power grid. The existence of these defects has prompted us to continuously explore and improve the intelligent power dispatching system based on big data to improve its reliability, accuracy and efficiency. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention provides an intelligent power dispatching system based on big data, which has the advantages of high-precision data acquisition, high-reliability data transmission, efficient data processing and intelligent decision support, and solves the problems of insufficient data acquisition accuracy, susceptibility to interference in data transmission and slow data processing speed in the existing system.

[0007] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an intelligent power dispatching system based on big data, comprising a power data acquisition module, a power data analysis module, a power result diagnosis module, a power result evaluation module, a power execution module and a power optimization module;

[0008] The power data acquisition module is responsible for collecting various data in the operation of the power system;

[0009] The power data analysis module performs data calculation and uses algorithm formulas to deeply process the collected data;

[0010] The power result diagnosis module determines the status of the power grid and the problems of each power operation link;

[0011] The power result evaluation module comprehensively evaluates the diagnosis results;

[0012] The power execution module converts the diagnosis and evaluation results into actual operations;

[0013] The power optimization module will be optimized according to system operation problems and power execution module effect feedback.

[0014] Preferably, the power data acquisition module includes a sensor data acquisition unit, a communication data acquisition unit and a power load data acquisition unit.

[0015] Preferably, the sensor data acquisition unit collects sensor data in real time through a multi-source heterogeneous sensor network, and the sensor data acquisition unit performs data numbering on the sensor's measured values ​​according to the sensor data characteristics, and the sensor's measured value numbering is .

[0016] Preferably, the communication data acquisition unit acquires communication data by hybrid communication technology, and the communication data acquisition unit collects data sequences according to the characteristics of the communication data. and In the The values ​​at each moment are numbered, and the data sequence and In the The values ​​at each moment are numbered and .

[0017] Preferably, the power load data acquisition unit collects power load data through a smart meter, and the power load data acquisition unit numbers the number of valid data and the total number of data according to the power load data characteristics, and the number of valid data and the total number of data are numbered as and .

[0018] Preferably, the power data analysis module includes a sensor accuracy analysis unit, a communication interference analysis unit and a power load analysis unit.

[0019] Preferably, the sensor accuracy analysis unit calculates the compensation error coefficient , and its calculation formula is:

[0020]

[0021] In the formula, represents the compensation error coefficient, Represents the measured value of the sensor, represents the actual value of the sensor, , , Respectively represent the temperature, humidity, and electromagnetic interference influence coefficients, , , They respectively represent the changes of the corresponding environmental factors.

[0022] Preferably, the communication interference analysis unit calculates the spatiotemporal correlation coefficient of the smart meter data , and its calculation formula is:

[0023]

[0024] In the formula, represents the spatiotemporal correlation coefficient of smart meter data, and Represents data series and In the The value of the moment, and Represents data series and The mean of Indicates the length of the data sequence.

[0025] Preferably, the power load analysis unit calculates the power data integrity score , and its calculation formula is:

[0026]

[0027] In the formula, represents the power data integrity score, Indicates the number of valid data. Indicates the total amount of data.

[0028] Preferably, the power result diagnosis module is based on the compensation error coefficient , perform sensor accuracy diagnosis to determine whether the sensor has measurement errors or accuracy degradation problems, and use the spatiotemporal correlation coefficient of smart meter data , perform data anomaly diagnosis, identify abnormal fluctuations in time and space or deviations from the normal range, and score the power data integrity. , conduct data quality diagnosis, evaluate data integrity, and determine whether there are data missing or errors, so as to determine the status of the power grid and problems in various power operation links;

[0029] The power result evaluation module performs a comprehensive performance evaluation on the above-mentioned diagnosis results.

[0030] Compared with the prior art, the present invention provides an intelligent power dispatching system based on big data, which has the following beneficial effects:

[0031] 1. The present invention calculates the compensation error coefficient , the sensor data in the system will be automatically input into the calculation formula to obtain the preset threshold value of the calculation training, and the power result diagnosis module will compensate the error coefficient , to determine whether the deviation between the sensor's measured value and the actual value is within the allowable range, when the compensation error coefficient When the preset threshold is exceeded, it is diagnosed as a decrease in sensor accuracy or a measurement error. At this time, the sensor needs to be calibrated or replaced. The system will automatically trigger the calibration procedure or switch to the backup sensor, and record the relevant data in real time for subsequent optimization, thereby ensuring the accuracy and reliability of the sensor data and solving the problem of insufficient data collection accuracy in the existing system.

[0032] 2. The present invention calculates the spatiotemporal correlation coefficient of smart meter data , according to the spatiotemporal correlation coefficient of smart meter data ,The power result diagnosis module analyzes the correlation of data in time and space. When the temporal and spatial correlation coefficient of smart meter data When it deviates from the normal range, it is diagnosed as abnormal data fluctuations caused by communication interference, equipment failure or other external factors. At this time, the abnormal data needs to be cleaned up to ensure the integrity of the data, and the communication link is optimized through an adaptive routing algorithm to reduce the data packet loss rate. Real-time warning information is sent to maintenance personnel to prompt communication interference problems so that preventive measures can be taken in time. The above operations are performed in the system to solve the problem that system data transmission is susceptible to interference.

[0033] 3. The present invention calculates the power data integrity score , according to the power data integrity score Assessing data integrity, when power data integrity scoring When the value is lower than the preset threshold, the power result diagnosis module will diagnose that the data is missing or erroneous. At this time, data cleaning or repair is required. The system will automatically clean up invalid data points and repair data based on historical data or adjacent data points to ensure data integrity and accuracy. Then, by optimizing the data processing process, the impact of invalid data on system performance is reduced, thereby improving data processing speed. Finally, according to the power data integrity score, the system will automatically clean up invalid data points and repair data based on historical data or adjacent data points to ensure data integrity and accuracy. The system dynamically adjusts the data collection strategy, increases the frequency of data verification or optimizes the data transmission protocol. When the speed is low, a real-time warning is automatically issued to the system maintenance personnel to prompt data integrity issues. Based on the above measures, the system can effectively solve the problem of slow data processing speed, improve the real-time performance of the power dispatching system, and ultimately solve the problem of slow data processing speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a flow chart of the system of the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] See also Figure 1 , an intelligent power dispatching system based on big data, including a power data acquisition module, a power data analysis module, a power result diagnosis module, a power result evaluation module, a power execution module and a power optimization module;

[0037] The power data acquisition module is responsible for collecting various data in the operation of the power system;

[0038] The power data analysis module performs data calculations and uses algorithm formulas to deeply process the collected data;

[0039] The power result diagnosis module determines the status of the power grid and the problems of each power operation link;

[0040] The power result evaluation module conducts a comprehensive evaluation of the diagnosis results;

[0041] The power execution module converts the diagnosis and evaluation results into actual operations;

[0042] The power optimization module will be optimized based on system operation problems and feedback from the power execution module.

[0043] The power data acquisition module includes a sensor data acquisition unit, a communication data acquisition unit and a power load data acquisition unit.

[0044] The sensor data acquisition unit collects sensor data (voltage, current, power and other parameters) in real time through a multi-source heterogeneous sensor network, and adopts a redundant sensor cross-check mechanism. The sensor data acquisition unit numbers the sensor's measured values ​​according to the sensor data characteristics. The sensor's measured value number is .

[0045] The communication data acquisition unit collects communication data through hybrid communication technology (optical fiber + wireless) to improve anti-interference ability and reduce data packet loss rate through adaptive routing algorithm. The communication data acquisition unit collects communication data according to the characteristics of communication data. and In the The data is numbered by the value at each moment, and the data sequence and In the The values ​​at each moment are numbered and .

[0046] The power load data acquisition unit collects power load data through smart meters, performs denoising and normalization, and marks the time and space attributes. The power load data acquisition unit numbers the number of valid data and the total number of data according to the characteristics of the power load data. The number of valid data and the total number of data are numbered as and .

[0047] The power data analysis module includes a sensor accuracy analysis unit, a communication interference analysis unit and a power load analysis unit.

[0048] The sensor accuracy analysis unit calculates the compensation error coefficient , and its calculation formula is:

[0049]

[0050] In the formula, represents the compensation error coefficient, Represents the measured value of the sensor, represents the actual value of the sensor, , , Respectively represent the temperature, humidity, and electromagnetic interference influence coefficients, , , They represent the changes of the corresponding environmental factors respectively;

[0051] The advantage is: by calculating the compensation error coefficient , the sensor data in the system will be automatically input into the calculation formula to obtain the preset threshold value of the calculation training, and the power result diagnosis module will compensate the error coefficient , to determine whether the deviation between the sensor's measured value and the actual value is within the allowable range, when the compensation error coefficient When the preset threshold is exceeded, it is diagnosed as a decrease in sensor accuracy or a measurement error. At this time, the sensor needs to be calibrated or replaced. The system will automatically trigger the calibration procedure or switch to the backup sensor, and record the relevant data in real time for subsequent optimization, thereby ensuring the accuracy and reliability of the sensor data and solving the problem of insufficient data collection accuracy in the existing system.

[0052] The communication interference analysis unit calculates the spatiotemporal correlation coefficient of smart meter data , used to identify abnormal data, by analyzing the correlation of data in time and space, to determine whether the data has abnormal fluctuations or deviates from the normal range. The calculation formula is:

[0053]

[0054] In the formula, represents the spatiotemporal correlation coefficient of smart meter data, and Represents data series and In the The value of the moment, and Represents data series and The mean of Indicates the length of the data sequence;

[0055] The advantage is: by calculating the spatiotemporal correlation coefficient of smart meter data , according to the spatiotemporal correlation coefficient of smart meter data ,The power result diagnosis module analyzes the correlation of data in time and space. When the temporal and spatial correlation coefficient of smart meter data When it deviates from the normal range, it is diagnosed as abnormal data fluctuations caused by communication interference, equipment failure or other external factors. At this time, the abnormal data needs to be cleaned up to ensure the integrity of the data, and the communication link is optimized through an adaptive routing algorithm to reduce the data packet loss rate. Real-time warning information is sent to maintenance personnel to prompt communication interference problems so that preventive measures can be taken in time, solving the problem of data transmission being susceptible to interference.

[0056] Power Load Analysis Unit Calculates Power Data Integrity Score , which is used to clean invalid or erroneous data to ensure the integrity and availability of data. The calculation formula is:

[0057]

[0058] In the formula, represents the power data integrity score, Represents the amount of valid data, that is, the number of data points that have been verified to meet certain quality and accuracy standards. Indicates the total amount of data, including all collected raw data points;

[0059] Advantages: By calculating the power data integrity score , according to the power data integrity score Assessing data integrity, when power data integrity scoring When the value is lower than the preset threshold, the power result diagnosis module will diagnose that the data is missing or erroneous. At this time, data cleaning or repair is required. The system will automatically clean up invalid data points and repair data based on historical data or adjacent data points to ensure data integrity and accuracy. Then, by optimizing the data processing process, the impact of invalid data on system performance is reduced, thereby improving data processing speed. Finally, according to the power data integrity score, the system will automatically clean up invalid data points and repair data based on historical data or adjacent data points to ensure data integrity and accuracy. The system dynamically adjusts the data collection strategy, increases the frequency of data verification or optimizes the data transmission protocol. When the speed is low, a real-time warning is automatically issued to the system maintenance personnel to prompt data integrity issues. Based on the above measures, the system can effectively solve the problem of slow data processing speed, improve the real-time performance of the power dispatching system, and ultimately solve the problem of slow data processing speed.

[0060] The power result diagnosis module is based on the compensation error coefficient , perform sensor accuracy diagnosis to determine whether the sensor has measurement errors or accuracy degradation problems, and use the spatiotemporal correlation coefficient of smart meter data , perform data anomaly diagnosis, identify abnormal fluctuations in time and space or deviations from the normal range, and score the power data integrity. , conduct data quality diagnosis, evaluate data integrity, and determine whether there are data missing or errors, so as to determine the status of the power grid and problems in various power operation links;

[0061] The power result evaluation module conducts a comprehensive performance evaluation on the above diagnostic results and collects optimization strategy corrective measures, including but not limited to adjusting sensor calibration parameters, optimizing communication link configuration, cleaning or repairing invalid data, adjusting data processing algorithms, etc., to improve the overall performance and reliability of the system.

[0062] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent power dispatching system based on big data, characterized in that: It includes a power data acquisition module, a power data analysis module, a power result diagnosis module, a power result evaluation module, a power execution module and a power optimization module; The power data acquisition module is responsible for collecting various data in the operation of the power system; The power data analysis module performs data calculation and uses algorithm formulas to deeply process the collected data; The power result diagnosis module determines the status of the power grid and the problems of each power operation link; The power result evaluation module comprehensively evaluates the diagnosis results; The power execution module converts the diagnosis and evaluation results into actual operations; The power optimization module will be optimized according to system operation problems and power execution module effect feedback.

2. According to the big data-based intelligent power dispatching system of claim 1, it is characterized by: The power data acquisition module includes a sensor data acquisition unit, a communication data acquisition unit and a power load data acquisition unit.

3. According to the big data-based intelligent power dispatching system of claim 2, it is characterized by: The sensor data acquisition unit collects sensor data in real time through a multi-source heterogeneous sensor network. The sensor data acquisition unit numbers the sensor's measured values ​​according to the sensor data characteristics. The sensor's measured value number is .

4. The intelligent power dispatching system based on big data according to claim 2 is characterized in that: The communication data acquisition unit collects communication data through hybrid communication technology, and the communication data acquisition unit collects data sequences according to the characteristics of the communication data. and In the The values ​​at each moment are numbered, and the data sequence and In the The values ​​at each moment are numbered and .

5. The intelligent power dispatching system based on big data according to claim 2 is characterized in that: The power load data acquisition unit collects power load data through a smart meter. The power load data acquisition unit numbers the number of valid data and the total number of data according to the power load data characteristics. The number of valid data and the total number of data are numbered as and .

6. The intelligent power dispatching system based on big data according to claim 1 is characterized in that: The power data analysis module includes a sensor accuracy analysis unit, a communication interference analysis unit and a power load analysis unit.

7. The intelligent power dispatching system based on big data according to claim 5 is characterized in that: The sensor accuracy analysis unit calculates the compensation error coefficient , and its calculation formula is: , in the formula, represents the compensation error coefficient, Represents the measured value of the sensor, represents the actual value of the sensor, , , Respectively represent the temperature, humidity, and electromagnetic interference influence coefficients, , , They respectively represent the changes of the corresponding environmental factors.

8. The intelligent power dispatching system based on big data according to claim 5 is characterized in that: The communication interference analysis unit calculates the spatiotemporal correlation coefficient of the smart meter data , and its calculation formula is: , in the formula, represents the spatiotemporal correlation coefficient of smart meter data, and Represents data series and In the The value of the moment, and Represents data series and The mean of Indicates the length of the data sequence.

9. The intelligent power dispatching system based on big data according to claim 5 is characterized in that: The power load analysis unit calculates the power data integrity score , and its calculation formula is: , in the formula, represents the power data integrity score, Indicates the number of valid data. Indicates the total amount of data.

10. The intelligent power dispatching system based on big data according to claim 9, characterized in that: The power result diagnosis module is based on the compensation error coefficient , perform sensor accuracy diagnosis to determine whether the sensor has measurement errors or accuracy degradation problems, and use the spatiotemporal correlation coefficient of smart meter data , perform data anomaly diagnosis, identify abnormal fluctuations in time and space or deviations from the normal range, and score the power data integrity. , conduct data quality diagnosis, evaluate data integrity, and determine whether there are data missing or errors, so as to determine the status of the power grid and problems in various power operation links; The power result evaluation module performs a comprehensive performance evaluation on the above-mentioned diagnosis results.

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