CN111525563A - Accurate long-term power load prediction method - Google Patents
Accurate long-term power load prediction method Download PDFInfo
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- CN111525563A CN111525563A CN202010445086.4A CN202010445086A CN111525563A CN 111525563 A CN111525563 A CN 111525563A CN 202010445086 A CN202010445086 A CN 202010445086A CN 111525563 A CN111525563 A CN 111525563A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
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Abstract
The invention discloses a method for predicting the accuracy type long-term power load degree, which comprises an acquisition module, a database module, a processing module, a human-computer interaction module, a recording module and a feedback module, wherein the output end of the acquisition module is in communication connection with the input end of the database module, the output end of the database module is in communication connection with the input end of the processing module, the output end of the processing module is in communication connection with the input end of the human-computer interaction module, the output end of the human-computer interaction module is in communication connection with the input end of the feedback module, the output end of the feedback module is in communication connection with the input end of the recording module, and the output end of the recording module is in communication connection with the database module; the feedback module is used for feeding back the prediction result to the recording module and sending the prediction result to the processing module through the recording module, so that the processing module can conveniently adjust the prediction result in a self-adaptive manner, the prediction result can be used for a long time, and the prediction result is more accurate.
Description
Technical Field
The invention relates to the technical field of power detection, in particular to an accurate long-term power load prediction method.
Background
The electric load is also called as "electric load", the sum of electric power taken by electric equipment of an electric energy user to an electric power system at a certain moment is called as electric load, and the electric load can be divided into various industrial loads, agricultural loads, transportation industrial loads, people life electric loads and the like according to different load characteristics of the electric power user; the total load of the power system is the sum of total power consumed by all the electric equipment in the system; adding the power consumed by the industrial, agricultural, post and telecommunications, traffic, municipal, commercial and urban and rural residents to obtain the comprehensive power load of the power system; the power of the comprehensive power load plus the network loss is the power to be supplied by each power plant in the system, and is called the power supply load (power supply amount) of the power system; the power supply load plus the power consumed by each power plant (i.e., the service power) is the power that each generator in the system should generate, and is called the power generation load (power generation amount) of the system.
In the existing power load degree prediction method, the prediction result is not accurate because the feedback function is not provided.
Disclosure of Invention
The present invention provides an accurate long-term power load prediction method to solve the problem of inaccurate prediction result in the background art.
In order to achieve the purpose, the invention provides the following technical scheme:
a method for predicting the precision type long-term power load degree comprises an acquisition module, a database module, a processing module, a human-computer interaction module, a recording module and a feedback module, wherein the output end of the acquisition module is in communication connection with the input end of the database module, the output end of the database module is in communication connection with the input end of the processing module, the output end of the processing module is in communication connection with the input end of the human-computer interaction module, the output end of the human-computer interaction module is in communication connection with the input end of the feedback module, the output end of the feedback module is in communication connection with the input end of the recording module, and the output end of the recording module is in communication connection with the database module; the acquisition module is used for acquiring relevant data of electric power in the power grid; the database module is used for storing power load data; the processing module is used for processing and predicting the collected power load data, integrating the applied power load, predicting the remaining energy use time and sending the predicted result to the man-machine interaction module; and the recording module is used for recording the feedback prediction result.
The collection module is used for collecting relevant data of electric power in a power grid, the database module is used for storing electric power load data, the prediction result of the processing module is predicted according to the total over-power load module and the total past power consumption module, firstly, the residual electric power load is determined based on the obtained electric power load, then, the available time is predicted according to the total past power consumption module, and the predicted result is sent to the man-machine interaction module, the operation module is used for analyzing and processing the output result of the output module, so that the output result is displayed in a mode desired by a user, if different report forms are set, the report form desired by the user is obtained after the output of the report form module, excessive and poor processing of the data is avoided, or the output result is displayed in a mode of an image by operation, the data is more visually seen in the mode, and meanwhile, the reporting module is used for reporting the predicted result to a manager, the power load is conveniently detected, the feedback module is used for feeding back to the recording module according to the prediction result and sending the prediction result to the processing module through the recording module, the processing module is convenient to adaptively adjust the prediction result, the power load prediction method can be used for a long time, and the prediction result is more accurate.
As a further scheme of the invention: the acquisition module comprises a power meter.
As a further scheme of the invention: the database module comprises a power load total amount module and a past power consumption total amount module, the power load total amount module is used for storing collected data, and the past power consumption total amount module records the past power consumption total amount in a certain time period.
As a further scheme of the invention: the processing module is a DSP digital signal processor.
As a further scheme of the invention: the human-computer interaction module comprises an output module, an operation module, a report module, an image module and a reporting module, wherein the input end of the output module is connected with the output end of the processing module, the output end of the output module is in communication connection with the input end of the operation module, and the output end of the operation module is also in communication connection with the report module, the image module and the reporting module respectively.
As a further scheme of the invention: the output module is used for receiving and outputting the processing structure of the processing module, the operation module is used for analyzing and processing the output result of the output module so as to display the output result in a mode desired by a user, and the reporting module is used for reporting the prediction result to an administrator.
As a further scheme of the invention: the feedback module is used for feeding back the prediction result to the recording module and sending the prediction result to the processing module through the recording module, so that the processing module can conveniently adjust the prediction result in a self-adaptive manner.
As a further scheme of the invention: the recording module comprises a storage module, an analysis module and an alarm module, wherein the input end of the storage module is in communication connection with the output end of the feedback module, the input end of the storage module is also in communication connection with the processing module, the output end of the storage module is in communication connection with the input end of the analysis module, and the output end of the analysis module is in communication connection with the alarm module.
As a further scheme of the invention: the storage module is used for storing the book of the prediction result, the analysis module is used for analyzing the data in the storage module, and when the prediction result shows that the power load is insufficient, the alarm module gives an alarm.
As a further scheme of the invention: the alarm module alarms by sending a short message to a mobile terminal, wherein the mobile terminal comprises a mobile phone and a tablet.
Compared with the prior art, the invention has the beneficial effects that:
1. the collection module is used for collecting relevant data of electric power in a power grid, the database module is used for storing electric power load data, the electric power load total amount module is used for storing the collected data, the past electric power consumption total amount module records the total amount of electric power used in a certain past time period, it can be understood that the certain time period can be specifically set, for example, one month or ten days or one day, a user can select and set according to actual conditions, the prediction result of the processing module is predicted according to the electric power load total amount module and the past electric power consumption total amount module, firstly, the residual electric power load is determined based on the obtained electric power load, then, the available time can be predicted according to the past electric power consumption total amount module, and the predicted result is sent to the human-computer interaction module, the operation module is used for analyzing and processing the output result of the output module, so that the output result is displayed in a mode, if different report forms are set, the report forms desired by the user are obtained after the report forms are output through the report forms module, excessive and poor processing of data is avoided, or the output result is displayed in an image mode through operation, the data can be seen more visually in the image mode, meanwhile, the reporting module is used for reporting the prediction result to a manager, power load detection is facilitated, the feedback module is used for feeding back the prediction result to the recording module according to the prediction result and sending the prediction result to the processing module through the recording module, the processing module is convenient to adjust the prediction result in a self-adaptive mode, long-term use is achieved, and the prediction result is more accurate.
2. The storage module is used for storing books of the prediction result, the analysis module is used for analyzing data in the storage module, when the prediction result shows that the power load is insufficient, the alarm module gives an alarm through an alarm lamp or sends a short message to the mobile terminal for alarming, and the mobile terminal can be a mobile phone, a tablet and the like.
Drawings
Fig. 1 is a schematic flow chart provided in embodiment 1 of the present invention.
Fig. 2 is a schematic structural diagram of a database module provided in embodiment 1 of the present invention.
Fig. 3 is a schematic flowchart of a human-computer interaction module according to embodiment 1 of the present invention.
Fig. 4 is a schematic flow chart of a recording module according to embodiment 1 of the present invention.
Fig. 5 is a schematic flow chart provided in embodiment 2 of the present invention.
1-an acquisition module, 2-a database module, 201-a power load total amount module, 202-a passing power total amount module, 3-a processing module, 4-a human-computer interaction module, 401-an output module, 402-an operation module, 403-a report module, 404-an image module, 405-a reporting module, 5-a recording module, 501-a storage module, 502-an analysis module, 503-an alarm module, 6-a feedback module, 7-an isolation device module and 8-a power grid server.
Detailed Description
The technical solution of the present patent will be described in further detail with reference to the following embodiments.
Example 1
Referring to fig. 1-4, a method for predicting a precise long-term power load includes an acquisition module 1, a database module 2, a processing module 3, a human-computer interaction module 4, a recording module 5 and a feedback module 6, wherein an output end of the acquisition module 1 is in communication connection with an input end of the database module 2, an output end of the database module 2 is in communication connection with an input end of the processing module 3, an output end of the processing module 3 is in communication connection with an input end of the human-computer interaction module 4, an output end of the human-computer interaction module 4 is in communication connection with an input end of the feedback module 6, an output end of the feedback module 6 is in communication connection with an input end of the recording module 5, and an output end of the recording module 5 is in communication connection with the database module 2.
Further, the acquisition module 1 is configured to acquire data related to power in a power grid, specifically, the acquisition module 1 includes a power meter, so as to acquire a power load degree in real time, and the acquisition module 1 may also perform statistics by inputting related load information by a user;
the database module 2 comprises an electric load total amount module 201 and a past electric consumption total amount module 202, the database module 2 is used for storing electric load data, the electric load total amount module 201 is used for storing collected data, the past electric consumption total amount module 202 records the electric consumption total amount of a past certain time period, and it can be understood that the certain time period can be specifically set, for example, one month, ten days or one day, and a user can select and set the time period according to actual conditions;
the processing module 3 is used for processing and predicting the collected power load data, integrating the applied power load and predicting the remaining usable time, and sending the predicted result to the man-machine interaction module 4.
It should be noted that the processing module 3 is a DSP digital signal processor, and the digital signal processor has been developed from a dedicated signal processor in the 70 s of the 20 th century to a VLSI array processor, and its application field has been developed from the processing of low-frequency signals such as voice and sonar to the signal processing of large amount of video data such as radar and image. Due to the utilization of floating point operation and parallel processing technology, the signal processor physical capacity is greatly improved. The digital signal processor will continue to develop a data stream structure on the architecture along two directions of improving the processing speed and the operation precision, and the data stream structure can become a basic structure mode of the next generation digital signal processor; the prediction result of the processing module 3 is predicted according to the total excess power load module 201 and the total past power consumption module 202, the remaining power load is determined based on the acquired power load, and the available time is predicted according to the total past power consumption module 202.
The human-computer interaction module 4 comprises an output module 401, an operation module 402, a report module 403, an image module 404 and a reporting module 405, wherein an input end of the output module 401 is connected with an output end of the processing module 3, an output end of the output module 401 is connected with an input end of the operation module 402 in a communication manner, an output end of the operation module 402 is further connected with the report module 403, the image module 404 and the reporting module 405 in a communication manner, the output module 401 is used for receiving and outputting a processing structure of the processing module 3, the operation module 402 is used for analyzing and processing an output result of the output module 401, so that the output result is displayed in a mode desired by a user, for example, different report forms are set, a report desired by the user is obtained after being output by the report module 403, excessive and bad processing of data is avoided, or the output result is displayed in a mode of an image by operation, the image mode shows data more intuitively, and the reporting module 405 is used for reporting the prediction result to an administrator, so that the power load can be conveniently detected.
The feedback module 6 is used for feeding back the prediction result to the recording module 5 and sending the prediction result to the processing module 3 through the recording module 5, so that the processing module 3 can conveniently adjust the prediction result in a self-adaptive manner, and the prediction result is more accurate.
The recording module 5 comprises a storage module 501, an analysis module 502 and an alarm module 503, wherein the input end of the storage module 501 is in communication connection with the output end of the feedback module 6, the input end of the storage module 501 is also in communication connection with the processing module 3, the output end of the storage module 501 is in communication connection with the input end of the analysis module 502, the output end of the analysis module 502 is in communication connection with the alarm module 503, the recording module 5 is used for recording a feedback prediction result, the storage module 501 is used for storing a book of the prediction result, the analysis module 502 is used for analyzing data in the storage module 501, when the prediction result finds that the power load is insufficient, an alarm is sent out through the alarm module 503, the alarm module 503 can give an alarm through an alarm lamp or send a short message to a mobile terminal, and the mobile terminal can be a mobile phone, Flat plate, etc., to improve safety.
The working principle of the invention is as follows:
the collection module 1 is used for collecting relevant data of electric power in a power grid, the database module 2 is used for storing electric power load data, the electric power load total amount module 201 is used for storing collected data, the past electric power total amount module 202 records the total amount of electric power used in a past certain time period, it can be understood that a certain time period can be specifically set, for example, one month, ten days or one day, a user can select and set according to actual conditions, the prediction result of the processing module 3 is predicted according to the electric power load total amount module 201 and the past electric power total amount module 202, firstly, the remaining electric power load is determined based on the obtained electric power load, then, the available time is predicted according to the past electric power total amount module 202, the predicted result is sent to the human-computer interaction module 4, and the operation module 402 is used for analyzing the output result of the output module 401, the output result is displayed in a mode desired by the user, if different report forms are set, the report desired by the user is obtained after the output result is output through the report module 403, excessive and poor processing of data is avoided, or the output result is displayed in an image mode by operation, the data is more visually seen in the image mode, meanwhile, the reporting module 405 is used for reporting the prediction result to an administrator for conveniently detecting the power load, the feedback module 6 is used for feeding back the prediction result to the recording module 5 according to the prediction result and sending the prediction result to the processing module 3 through the recording module 5, the processing module 3 is convenient for adaptively adjusting the prediction result, the prediction result can be used for a long time and is more accurate, the storage module 501 is used for storing the book of the prediction result, the analysis module 502 is used for analyzing the data in the storage module 501, when the prediction result finds that the power load is insufficient, the alarm module 503 sends an alarm, and the alarm module 503 may send an alarm through an alarm lamp or a short message to a mobile terminal, where the mobile terminal may be a mobile phone, a tablet, or the like.
Example 2
Referring to fig. 2-5, a method for predicting a precise long-term power load includes an acquisition module 1, a database module 2, a processing module 3, a human-computer interaction module 4, a recording module 5, and a feedback module 6, where an output end of the acquisition module 1 is communicatively connected to an input end of the database module 2, an output end of the database module 2 is communicatively connected to an input end of the processing module 3, an output end of the processing module 3 is communicatively connected to an input end of the human-computer interaction module 4, an output end of the human-computer interaction module 4 is communicatively connected to an input end of the feedback module 6, an output end of the feedback module 6 is communicatively connected to an input end of the recording module 5, and an output end of the recording module 5 is communicatively connected to the database module 2.
Further, the acquisition module 1 is configured to acquire data related to power in a power grid, specifically, the acquisition module 1 includes a power meter, so as to acquire a power load degree in real time, and the acquisition module 1 may also perform statistics by inputting related load information by a user;
the database module 2 comprises an electric load total amount module 201 and a past electric consumption total amount module 202, the database module 2 is used for storing electric load data, the electric load total amount module 201 is used for storing collected data, the past electric consumption total amount module 202 records the electric consumption total amount of a past certain time period, and it can be understood that the certain time period can be specifically set, for example, one month, ten days or one day, and a user can select and set the time period according to actual conditions;
the processing module 3 is used for processing and predicting the collected power load data, integrating the applied power load and predicting the remaining usable time, and sending the predicted result to the man-machine interaction module 4.
It should be noted that the processing module 3 is a DSP digital signal processor, and the digital signal processor has been developed from a dedicated signal processor in the 70 s of the 20 th century to a VLSI array processor, and its application field has been developed from the processing of low-frequency signals such as voice and sonar to the signal processing of large amount of video data such as radar and image. Due to the utilization of floating point operation and parallel processing technology, the signal processor physical capacity is greatly improved. The digital signal processor will continue to develop a data stream structure on the architecture along two directions of improving the processing speed and the operation precision, and the data stream structure can become a basic structure mode of the next generation digital signal processor; the prediction result of the processing module 3 is predicted according to the total excess power load module 201 and the total past power consumption module 202, the remaining power load is determined based on the acquired power load, and the available time is predicted according to the total past power consumption module 202.
The human-computer interaction module 4 comprises an output module 401, an operation module 402, a report module 403, an image module 404 and a reporting module 405, wherein an input end of the output module 401 is connected with an output end of the processing module 3, an output end of the output module 401 is connected with an input end of the operation module 402 in a communication manner, an output end of the operation module 402 is further connected with the report module 403, the image module 404 and the reporting module 405 in a communication manner, the output module 401 is used for receiving and outputting a processing structure of the processing module 3, the operation module 402 is used for analyzing and processing an output result of the output module 401, so that the output result is displayed in a mode desired by a user, for example, different report forms are set, a report desired by the user is obtained after being output by the report module 403, excessive and bad processing of data is avoided, or the output result is displayed in a mode of an image by operation, the image mode shows data more intuitively, and the reporting module 405 is used for reporting the prediction result to an administrator, so that the power load can be conveniently detected.
The feedback module 6 is used for feeding back the prediction result to the recording module 5 and sending the prediction result to the processing module 3 through the recording module 5, so that the processing module 3 can conveniently adjust the prediction result in a self-adaptive manner, and the prediction result is more accurate.
The recording module 5 comprises a storage module 501, an analysis module 502 and an alarm module 503, wherein the input end of the storage module 501 is in communication connection with the output end of the feedback module 6, the input end of the storage module 501 is also in communication connection with the processing module 3, the output end of the storage module 501 is in communication connection with the input end of the analysis module 502, the output end of the analysis module 502 is in communication connection with the alarm module 503, the recording module 5 is used for recording a feedback prediction result, the storage module 501 is used for storing a book of the prediction result, the analysis module 502 is used for analyzing data in the storage module 501, when the prediction result finds that the power load is insufficient, an alarm is sent out through the alarm module 503, the alarm module 503 can give an alarm through an alarm lamp or send a short message to a mobile terminal, and the mobile terminal can be a mobile phone, Flat plate, etc., to improve safety.
The system is characterized by further comprising an isolating device module 7 and a power grid server 8, wherein the output end of the isolating device module 7 is in communication connection with the input end of the power grid server 1, the input end of the isolating device module 7 is in communication connection with the power grid server 8, and the isolating device module 7 is used for guaranteeing the mode that data are transmitted in a one-way mode in an E language format, so that the safety of information transmission is guaranteed.
Although the preferred embodiments of the present patent have been described in detail, the present patent is not limited to the above embodiments, and various changes can be made without departing from the spirit of the present patent within the knowledge of those skilled in the art.
Claims (10)
1. A method for predicting the accurate long-term power load degree is characterized by comprising an acquisition module (1), a database module (2), a processing module (3), a human-computer interaction module (4), a recording module (5) and a feedback module (6), wherein the output end of the acquisition module (1) is in communication connection with the input end of the database module (2), the output end of the database module (2) is in communication connection with the input end of the processing module (3), the output end of the processing module (3) is in communication connection with the input end of the man-machine interaction module (4), the output end of the human-computer interaction module (4) is in communication connection with the input end of the feedback module (6), the output end of the feedback module (6) is in communication connection with the input end of the recording module (5), the output end of the recording module (5) is in communication connection with the database module (2); the acquisition module (1) is used for acquiring relevant data of electric power in a power grid; the database module (2) is used for storing power load data; the processing module (3) is used for processing and predicting the collected power load data, integrating the applied power load and predicting the remaining usable time, and sending the predicted result to the man-machine interaction module (4).
2. The method of claim 1, wherein the collection module (1) comprises a power meter.
3. The accurate long-term power load forecasting method according to claim 1, wherein the database module (2) comprises a power load total amount module (201) and a past power consumption total amount module (202), the power load total amount module (201) is used for storing collected data, and the past power consumption total amount module (202) records power consumption total amount in a certain past time period.
4. The method of claim 1, wherein the processing module (3) is a DSP digital signal processor.
5. The method for predicting the accurate long-term power load according to claim 1, wherein the human-computer interaction module (4) comprises an output module (401), an operation module (402), a report module (403), an image module (404) and a reporting module (405), wherein an input end of the output module (401) is connected with an output end of the processing module (3), an output end of the output module (401) is in communication connection with an input end of the operation module (402), and an output end of the operation module (402) is in communication connection with the report module (403), the image module (404) and the reporting module (405) respectively.
6. The method according to claim 5, wherein the output module (401) is configured to receive and output a processing structure of the processing module (3), the operation module (402) is configured to analyze an output result of the output module (401) so that the output result is displayed in a manner desired by a user, and the reporting module (405) is configured to report the prediction result to an administrator.
7. The method for predicting the accurate long-term power load according to claim 1, wherein the feedback module (6) is configured to feed back the prediction result to the recording module (5) and send the prediction result to the processing module (3) through the recording module (5), so that the processing module (3) can adaptively adjust the prediction result.
8. The accurate long-term power load prediction method according to claim 1, wherein the recording module (5) is configured to record a feedback prediction result, the recording module (5) includes a storage module (501), an analysis module (502), and an alarm module (503), an input of the storage module (501) is communicatively connected to an output of the feedback module (6), an input of the storage module (501) is further communicatively connected to the processing module (3), an output of the storage module (501) is communicatively connected to an input of the analysis module (502), and an output of the analysis module (502) is communicatively connected to the alarm module (503).
9. The method for predicting the accurate long-term power load according to claim 8, wherein the storage module (501) is used for storing a book of the prediction result, the analysis module (502) is used for analyzing the data in the storage module (501), and when the prediction result shows that the power load is insufficient, an alarm is given out through the alarm module (503).
10. The method of claim 8, wherein the alarming module (503) comprises alarming via an alarm lamp, and further comprises sending a short message to a mobile terminal for alarming, wherein the mobile terminal comprises a mobile phone and a tablet.
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| CN113657755A (en) * | 2021-08-17 | 2021-11-16 | 国网河北省电力有限公司 | Power system load regulation and control system based on big data analysis |
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