CN114492976A - Scheduling operation situation global perception method and system based on artificial intelligence technology - Google Patents

Scheduling operation situation global perception method and system based on artificial intelligence technology Download PDF

Info

Publication number
CN114492976A
CN114492976A CN202210067060.XA CN202210067060A CN114492976A CN 114492976 A CN114492976 A CN 114492976A CN 202210067060 A CN202210067060 A CN 202210067060A CN 114492976 A CN114492976 A CN 114492976A
Authority
CN
China
Prior art keywords
data
power grid
module
situation
power
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202210067060.XA
Other languages
Chinese (zh)
Inventor
祝锦舟
蔡新雷
董锴
林旭
孟子杰
喻振帆
王勇超
刘佳乐
谢型浪
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Electric Power Dispatch Control Center of Guangdong Power Grid Co Ltd
Original Assignee
Electric Power Dispatch Control Center of Guangdong Power Grid Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Electric Power Dispatch Control Center of Guangdong Power Grid Co Ltd filed Critical Electric Power Dispatch Control Center of Guangdong Power Grid Co Ltd
Priority to CN202210067060.XA priority Critical patent/CN114492976A/en
Publication of CN114492976A publication Critical patent/CN114492976A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06311—Scheduling, planning or task assignment for a person or group
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0633—Workflow analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0635—Risk analysis of enterprise or organisation activities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/10—Office automation; Time management
    • G06Q10/103—Workflow collaboration or project management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

The invention discloses a scheduling operation situation global perception method and a system based on an artificial intelligence technology, belonging to the technical field of power grid scheduling situation perception, and comprising the following steps: s1, acquiring data information of the power grid system through a data acquisition module, wherein the data information comprises power grid situation data and external environment data, and the power grid situation data comprises real-time voltage data and real-time transmission power data; s2, transmitting the data information of the power grid system collected by the data collection module to a server through a wireless communication module, wherein the server stores the received data information in a data storage module, and the data storage module also stores average voltage data, average transmission power data and historical fault data; and S3, processing the data stored in the data storage module through the data processing module, and acquiring the data information of the power grid system through the data acquisition module, so as to facilitate the global feeling prediction of the scheduling operation situation of the power grid.

Description

Scheduling operation situation global perception method and system based on artificial intelligence technology
Technical Field
The invention relates to the technical field of power grid dispatching situation perception, in particular to a dispatching operation situation global perception method and system based on an artificial intelligence technology.
Background
With the development of microelectronics, computer technology and communication technology, the integrated automation technology has also been rapidly developed. In recent years, comprehensive automation has become a hot topic, which draws attention and attention of various departments in the power industry and becomes one of the key points for promoting technical progress in the power industry in China. The power grid dispatching is an effective management means which is adopted for ensuring safe and stable operation of the power grid, reliable external power supply and orderly operation of various power production works.
Situation awareness is an ability to dynamically and integrally know security risks based on environment, and is a way to improve the capabilities of discovery, identification, understanding, analysis, response and handling of security threats from a global perspective based on security big data, and finally falls on the ground of security capabilities for decision and action. Most of the existing power grid dispatching is observed and controlled manually, and certain operational error risks exist.
Disclosure of Invention
The invention aims to provide a scheduling operation situation global perception method and system based on an artificial intelligence technology, and aims to solve the problem that most of the existing power grid scheduling proposed in the background technology is observed and controlled manually, and certain operational errors are risky.
In order to achieve the purpose, the invention provides the following technical scheme: a scheduling operation situation global perception method based on an artificial intelligence technology comprises the following steps:
s1, acquiring data information of the power grid system through a data acquisition module, wherein the data information comprises power grid situation data and external environment data, and the power grid situation data comprises real-time voltage data and real-time transmission power data;
s2, transmitting the data information of the power grid system collected by the data collection module to a server through a wireless communication module, wherein the server stores the received data information in a data storage module, and the data storage module also stores average voltage data, average transmission power data and historical fault data;
s3, processing the data stored in the data storage module through the data processing module, wherein the processing specifically comprises: an artificial intelligence unit is integrated in the data processing module, the artificial intelligence unit forms a deep neural network unit through a deep neural network algorithm, the neural network algorithm forms the deep neural network unit through a perceptron, and collected data information is used as an input vector to form a vector
Figure BDA0003480550780000021
Defining the weight vector as
Figure BDA0003480550780000022
A contribution rate for characterizing an output, the output defined as:
Figure BDA0003480550780000023
the output of the sensor is used as the input data, and the output is defined as
Figure BDA0003480550780000024
And forming a linear function sensor, obtaining a better weight calculation result through a deep neural network algorithm, and performing global prediction on the situation of the power grid.
Preferably, the external environment data includes weather information, illumination intensity and wind power level, and the time of acquiring the external environment data corresponds to the time of acquiring the power grid situation data.
Preferably, the historical fault data is divided into a no-risk state, a first-level risk state, a second-level risk state, a third-level risk state, an ultrahigh-risk state and a fault state, the no-risk state is defined as that no fault occurs in the power grid, the first-level risk state is defined as that one abnormity occurs in the power grid but no power failure occurs, the second-level risk state is defined as that two abnormity occurs in the power grid but no power failure occurs, the third-level risk state is defined as that three abnormity occurs in the power grid but no power failure occurs, the ultrahigh-risk state and the fault state are defined as that more than three abnormity occurs in the power grid but no power failure occurs, and the fault state is defined as that the power grid is abnormally powered off.
Preferably, the login is performed through an identity authentication module, and the authentication method of the identity authentication module is face recognition.
Preferably, the data storage module stores face data information of a person allowed to log in, and the identity verification module performs comparison login through the face data information in the data storage module.
A scheduling operation situation global perception system based on artificial intelligence technology comprises a server, a data acquisition module, a wireless communication module, a data storage module, an identity verification module and a data processing module;
the identity authentication module is used for performing system login;
the data acquisition module is used for acquiring data information of the power grid system;
the wireless communication module is used for transmitting the data information acquired by the data acquisition module to the server;
the data storage module is used for storing system data;
the data processing module is used for processing the data stored in the data storage module.
Preferably, an evaluation index is constructed through the scheduling operation situation global perception system based on the artificial intelligence technology, and the evaluation index establishes an index system from three aspects of situation perception, situation perception understanding and situation perception prediction;
the situation perception is that a data acquisition module acquires data information of a power grid system, all state quantities are converted, communication delay is obtained according to the difference value between the time of the power grid system for receiving data and the time scale time of the data, a certain amount of data with time scales are subjected to communication delay averaging to obtain average communication delay, and the average communication delay is assigned to the difference value between the time of the network automation system for receiving the data and the time scale time of the data; the situation awareness understanding can adopt active measures to ensure the power supply of key loads in disasters and quickly recover the capacity of power failure loads, and can discover power supply hidden dangers and weak links in a power distribution network through reasonable situation awareness understanding, so that the faults of the power distribution network are prevented, the power supply reliability of the power distribution network is improved, and the loss of users is reduced; and predicting the risk by the situation awareness prediction.
Compared with the prior art, the invention has the beneficial effects that:
1) the data information of the power grid system is acquired through the data acquisition module, the data information comprises power grid situation data and external environment data, and the global feeling prediction of the scheduling operation situation of the power grid is facilitated;
2) the data stored in the data storage module are processed through the data processing module, an artificial intelligence unit is integrated in the data processing module, the artificial intelligence unit forms a deep neural network unit through a deep neural network algorithm, the neural network algorithm forms the deep neural network unit through a sensor, power grid situation global prediction is conducted through calculation of weight, power grid dispatching personnel are assisted to work, and the probability of misoperation is reduced.
Drawings
FIG. 1 is a schematic flow chart of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "upper", "lower", "inner", "outer", "top/bottom", etc. indicate orientations or positional relationships based on orientations or positional relationships shown in the drawings, which are merely for convenience of description and simplification of description, but do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "disposed," "sleeved/connected," "connected," and the like are to be construed broadly, e.g., "connected," which may be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Example (b):
referring to fig. 1, the present invention provides a technical solution: a scheduling operation situation global perception method based on an artificial intelligence technology comprises the following steps:
s1, acquiring data information of the power grid system through a data acquisition module, wherein the data information comprises power grid situation data and external environment data, and the power grid situation data comprises real-time voltage data and real-time transmission power data;
s2, transmitting the data information of the power grid system collected by the data collection module to a server through a wireless communication module, wherein the server stores the received data information in a data storage module, and the data storage module also stores average voltage data, average transmission power data and historical fault data;
s3, processing the data stored in the data storage module through the data processing module, wherein the processing specifically comprises: an artificial intelligence unit is integrated in the data processing module, the artificial intelligence unit forms a deep neural network unit through a deep neural network algorithm, the neural network algorithm forms the deep neural network unit through a perceptron, and collected data information is used as input vectors to form vectors
Figure BDA0003480550780000051
Defining the weight vector as
Figure BDA0003480550780000052
A contribution rate for characterizing an output, the output defined as:
Figure BDA0003480550780000053
the output of the function ranges from 0 to 1, the output of the sensor is used as the input data, and the output is defined as
Figure BDA0003480550780000054
And evaluating the error between the actual output and the target output of the deep neural network to form a linear function sensor, and obtaining a better weight calculation result through a deep neural network algorithm to perform global prediction on the power grid situation.
The external environment data comprises weather information, illumination intensity and wind power level, and the time of collecting the external environment data corresponds to the time of the power grid situation data.
The historical fault data are divided into a no-risk state, a primary risk state, a secondary risk state, a tertiary risk state, an ultrahigh risk state and a fault state, the no-risk state is defined as that no fault occurs in the power grid, the primary risk state is defined as that one part of the power grid is abnormal but power failure cannot be caused, the secondary risk state is defined as that two parts of the power grid are abnormal but power failure cannot be caused, the tertiary risk state is defined as that three parts of the power grid are abnormal but power failure cannot be caused, the ultrahigh risk state and the fault state are defined as that more than three parts of the power grid are abnormal but power failure cannot be caused, the fault state is defined as that the power grid is in abnormal power failure, and methods for solving the corresponding faults are stored in the historical fault data.
Logging in through an identity authentication module, wherein the authentication method of the identity authentication module is face recognition.
The data storage module stores face data information of persons allowed to log in, and the identity verification module performs comparison login through the face data information in the data storage module.
A scheduling operation situation global perception system based on artificial intelligence technology comprises a server, a data acquisition module, a wireless communication module, a data storage module, an identity verification module and a data processing module;
the identity authentication module is used for performing system login;
the data acquisition module is used for acquiring data information of the power grid system;
the wireless communication module is used for transmitting the data information acquired by the data acquisition module to the server;
the data storage module is used for storing system data;
the data processing module is used for processing the data stored in the data storage module.
Establishing an evaluation index through the scheduling operation situation global perception system based on the artificial intelligence technology, wherein the evaluation index establishes an index system from three aspects of situation perception, situation perception understanding and situation perception prediction;
the situation perception is that a data acquisition module acquires data information of a power grid system, all state quantities are converted, communication delay is obtained according to the difference value between the time of the power grid system for receiving data and the time scale time of the data, a certain amount of data with time scales are subjected to communication delay averaging to obtain average communication delay, and the average communication delay is assigned to the difference value between the time of the network automation system for receiving the data and the time scale time of the data; the situation awareness understanding can adopt active measures to ensure the power supply of key loads in disasters and quickly recover the capacity of power failure loads, and can discover power supply hidden dangers and weak links in a power distribution network through reasonable situation awareness understanding, so that the faults of the power distribution network are prevented, the power supply reliability of the power distribution network is improved, and the loss of users is reduced; and predicting the risk by the situation awareness prediction.
While there have been shown and described the fundamental principles and essential features of the invention and advantages thereof, it will be apparent to those skilled in the art that the invention is not limited to the details of the foregoing exemplary embodiments, but is capable of other specific forms without departing from the spirit or essential characteristics thereof; the present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein, and any reference signs in the claims are not intended to be construed as limiting the claim concerned.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims (7)

1. A scheduling operation situation global perception method based on artificial intelligence technology is characterized in that: the method comprises the following steps:
s1, acquiring data information of the power grid system through a data acquisition module, wherein the data information comprises power grid situation data and external environment data, and the power grid situation data comprises real-time voltage data and real-time transmission power data;
s2, transmitting the data information of the power grid system acquired by the data acquisition module to a server through a wireless communication module, storing the received data information in a data storage module by the server, and storing average voltage data, average transmission power data and historical fault data by the data storage module;
s3, processing the data stored in the data storage module through the data processing module, wherein the processing specifically comprises: an artificial intelligence unit is integrated in the data processing module, the artificial intelligence unit forms a deep neural network unit through a deep neural network algorithm, the neural network algorithm forms the deep neural network unit through a perceptron, and collected data information is used as an input vector to form a vector
Figure FDA0003480550770000011
Defining the weight vector as
Figure FDA0003480550770000012
A contribution rate for characterizing an output, the output defined as:
Figure FDA0003480550770000013
the output of the sensor is used as the input data, and the output is defined as
Figure FDA0003480550770000014
And forming a linear function perceptron, obtaining a more optimal weight calculation result through a deep neural network algorithm, and performing global prediction on the situation of the power grid.
2. The scheduling operation situation global perception method based on the artificial intelligence technology is characterized in that: the external environment data comprises weather information, illumination intensity and wind power level, and the time of collecting the external environment data corresponds to the time of the power grid situation data.
3. The scheduling operation situation global perception method based on the artificial intelligence technology is characterized in that: the historical fault data is divided into a no-risk state, a first-level risk state, a second-level risk state, a third-level risk state, an ultrahigh-risk state and a fault state, the no-risk state is defined as that no fault occurs in the power grid, the first-level risk state is defined as that one part of the power grid is abnormal but power failure cannot be caused, the second-level risk state is defined as that two parts of the power grid are abnormal but power failure cannot be caused, the third-level risk state is defined as that three parts of the power grid are abnormal but power failure cannot be caused, the ultrahigh-risk state and the fault state are defined as that more than three parts of the power grid are abnormal but power failure cannot be caused, and the fault state is defined as that the power grid is abnormally caused by power failure.
4. The scheduling operation situation global perception method based on the artificial intelligence technology is characterized in that: logging in through an identity authentication module, wherein the authentication method of the identity authentication module is face recognition.
5. The scheduling operation situation global perception method based on the artificial intelligence technology is characterized in that: the data storage module stores face data information of persons allowed to log in, and the identity verification module performs comparison login through the face data information in the data storage module.
6. An artificial intelligence technology based scheduling operation situation global perception system according to any one of claims 1-5, characterized in that: the system comprises a server, a data acquisition module, a wireless communication module, a data storage module, an identity verification module and a data processing module;
the identity authentication module is used for performing system login;
the data acquisition module is used for acquiring data information of the power grid system;
the wireless communication module is used for transmitting the data information acquired by the data acquisition module to the server;
the data storage module is used for storing system data;
the data processing module is used for processing the data stored in the data storage module.
7. The scheduling operation situation global perception system based on the artificial intelligence technology is characterized in that: establishing an evaluation index through the scheduling operation situation global perception system based on the artificial intelligence technology, wherein the evaluation index establishes an index system from three aspects of situation perception, situation perception understanding and situation perception prediction;
the situation awareness perception is to acquire data information of a power grid system by a data acquisition module, convert all state quantities, obtain communication delay according to the difference between the data receiving time of the power grid system and the data time scale time, average a certain number of data communication delays with time scales to obtain average communication delay, and assign the difference between the data receiving time of the network automation system and the data time scale time to the average communication delay; the situation awareness understanding can adopt active measures to ensure the power supply of key loads in disasters and quickly recover the capacity of power failure loads, and can discover power supply hidden dangers and weak links in a power distribution network through reasonable situation awareness understanding, so that the faults of the power distribution network are prevented, the power supply reliability of the power distribution network is improved, and the loss of users is reduced; and predicting the risk by the situation awareness prediction.
CN202210067060.XA 2022-01-20 2022-01-20 Scheduling operation situation global perception method and system based on artificial intelligence technology Pending CN114492976A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210067060.XA CN114492976A (en) 2022-01-20 2022-01-20 Scheduling operation situation global perception method and system based on artificial intelligence technology

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210067060.XA CN114492976A (en) 2022-01-20 2022-01-20 Scheduling operation situation global perception method and system based on artificial intelligence technology

Publications (1)

Publication Number Publication Date
CN114492976A true CN114492976A (en) 2022-05-13

Family

ID=81472580

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210067060.XA Pending CN114492976A (en) 2022-01-20 2022-01-20 Scheduling operation situation global perception method and system based on artificial intelligence technology

Country Status (1)

Country Link
CN (1) CN114492976A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116365513A (en) * 2023-04-17 2023-06-30 国网江苏省电力有限公司 Command network interaction method and system based on power grid situation

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116365513A (en) * 2023-04-17 2023-06-30 国网江苏省电力有限公司 Command network interaction method and system based on power grid situation
CN116365513B (en) * 2023-04-17 2023-10-27 国网江苏省电力有限公司 Command network interaction method and system based on power grid situation

Similar Documents

Publication Publication Date Title
KR102016661B1 (en) Smart city service and integrated platform providing system
CN111092862B (en) Method and system for detecting communication traffic abnormality of power grid terminal
CN109544399B (en) Power transmission equipment state evaluation method and device based on multi-source heterogeneous data
CN116148679B (en) Battery health state prediction method and related device
CN112327100B (en) Power failure detection method and system based on Internet of things
KR101896015B1 (en) Ai type remote meter reading system
CN103246265A (en) Detection and maintenance system and method for electromechanical device
CN112990656B (en) Health evaluation system and health evaluation method for IT equipment monitoring data
CN116366374B (en) Security assessment method, system and medium for power grid network management based on big data
CN109974780A (en) A kind of electrical equipment status monitoring system based on Internet of Things
CN110008350A (en) A kind of pump Ankang knowledge base lookup method based on Bayesian inference
CN113177646B (en) Power distribution equipment online monitoring method and system based on self-adaptive edge proxy
CN110223193A (en) The method of discrimination and system of operation of power networks state are used for based on fuzzy clustering and RS-KNN model
CN110458039A (en) A kind of construction method of industrial process fault diagnosis model and its application
CN114492976A (en) Scheduling operation situation global perception method and system based on artificial intelligence technology
CN113391239A (en) Transformer abnormality monitoring method and system based on edge calculation
CN109615273A (en) A kind of electric car electrically-charging equipment method for evaluating state and system
Meenakshi et al. Wireless Sensor Networks for Disaster Management and Emergency Response using SVM Classifier
CN113708350B (en) Cloud edge cooperation-based power distribution area heavy overload abnormality judgment method and system
CN110175745A (en) A kind of electric power telecommunication network risk assessment method and system based on fault modeling
CN113919826A (en) Land development, operation and planning system and method
CN111143763B (en) Method and device for evaluating state of power equipment and storage medium thereof
CN112858926A (en) Lithium battery module safety monitoring management system and management method thereof
CN112649101A (en) Battery module early warning method and system and fire detection device
CN109670560A (en) A kind of logistics information acquisition system reading and veritify function with identity

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination