CN114665597A - Intelligent power supply system - Google Patents
Intelligent power supply system Download PDFInfo
- Publication number
- CN114665597A CN114665597A CN202210217886.XA CN202210217886A CN114665597A CN 114665597 A CN114665597 A CN 114665597A CN 202210217886 A CN202210217886 A CN 202210217886A CN 114665597 A CN114665597 A CN 114665597A
- Authority
- CN
- China
- Prior art keywords
- power supply
- monitoring
- supply system
- value
- monitoring area
- 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
Links
- 238000012544 monitoring process Methods 0.000 claims abstract description 277
- 230000007613 environmental effect Effects 0.000 claims description 79
- 238000000034 method Methods 0.000 claims description 9
- 238000004364 calculation method Methods 0.000 claims description 8
- 238000012935 Averaging Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000010248 power generation Methods 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
Images
Classifications
-
- 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
- H02J13/00002—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 monitoring
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/003—Environmental or reliability tests
-
- 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]
-
- 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
- H02J4/00—Circuit arrangements for mains or distribution networks not specified as ac or dc
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Human Computer Interaction (AREA)
- Environmental & Geological Engineering (AREA)
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
Abstract
The invention discloses an intelligent power supply system, which belongs to the field of electric power and is used for solving the problems that the power supply system does not integrate multiple factors for grade division and does not match corresponding control force according to grade, and comprises an early warning grading module, an operation monitoring module, a data acquisition module, an environment monitoring module and a power supply control module, wherein the operation monitoring module is used for monitoring the operation condition of the power supply system in a monitoring area, the environment monitoring module is used for monitoring the environment condition of the power supply system in the monitoring area, the early warning grading module carries out early warning grading on the monitoring area according to the operation deviation coefficient and the environment deviation coefficient of the monitoring area, the power supply control module sets corresponding control measures for the monitoring area according to signals, and the invention combines the factors of operation data, environment data bureau and the like to realize the grade division of the power supply system, and meanwhile, matching corresponding control measures according to the grades.
Description
Technical Field
The invention belongs to the field of electric power, relates to an intelligent power supply technology, and particularly relates to an intelligent power supply system.
Background
Electric power is an energy source using electric energy as power. The discovery and application of electric power has raised the second industrialized climax, and is one of three technological revolution in the world, and the technology has changed the lives of people. Large-scale power systems are one of the most important achievements in the history of human engineering science, and are power generation and consumption systems consisting of links such as power generation, power transmission, power transformation, power distribution and power utilization. It converts the primary energy of nature into electric power through mechanical energy devices, and then supplies the electric power to each user through power transmission, transformation and distribution.
In the prior art, when the current power supply system carries out early warning monitoring, real-time monitoring on operation data and environment data cannot be achieved, meanwhile, multiple factors are not combined to carry out grading on the power supply system, and corresponding management and control measures are matched according to grades, so that an intelligent power supply system is provided.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide an intelligent power supply system.
The technical problem to be solved by the invention is as follows:
(1) how to combine factors such as operating data, environmental data bureau to realize the grade division of power supply system, according to the corresponding management and control measure of grade matching simultaneously.
The purpose of the invention can be realized by the following technical scheme:
an intelligent power supply system comprises a user terminal, a region distribution module, an early warning grading module, an operation monitoring module, a data acquisition module, an environment monitoring module, a power supply management and control module and a server, wherein the region distribution module is used for dividing a power supply region, dividing the power supply region into a plurality of monitoring regions, marking the monitoring regions as u, u =1, 2, … …, z and z as positive integers, sending the divided monitoring regions to the server by the region distribution module, and sending the divided monitoring regions to the operation monitoring module and the environment monitoring module by the server respectively; the data acquisition module is used for acquiring real-time operation data and real-time environment data of a power supply system in a monitoring area and sending the real-time operation data and the real-time environment data to the server, and the server sends the real-time operation data to the operation monitoring module and the real-time environment data to the environment monitoring module;
the server stores standard operating data and standard environmental data of the power supply system, transmits the standard operating data to the operation monitoring module, and transmits the standard environmental data to the environment monitoring module; the operation monitoring module is used for monitoring the operation state of the power supply system in the monitoring area, and the operation deviation coefficient of the power supply system in the monitoring area is monitored and fed back to the server; the environment monitoring module is used for monitoring the environment condition of the power supply system in the monitoring area, monitoring the environment deviation coefficient of the power supply system in the monitoring area and feeding the environment deviation coefficient back to the server, the server sends the operation deviation coefficient and the environment deviation coefficient to the early warning grading module, and the operation deviation coefficient of the monitoring area is marked as YXu, and the environment deviation coefficient is marked as HXu;
the early warning classification module carries out early warning classification to the monitoring area according to the operation deviation coefficient and the environmental deviation coefficient in monitoring area, generates high-risk early warning signal, well danger early warning signal and low-risk early warning signal and feeds back to the server, and the server sends high-risk early warning signal and well danger early warning signal to the user terminal who corresponds according to the power supply area that the staff is responsible for, and the staff goes to the monitoring area that high-risk early warning signal and well danger early warning signal correspond, simultaneously, the server sends high-risk early warning signal, well danger early warning signal and low-risk early warning signal to power supply management and control module, power supply management and control module sets for monitoring area corresponding management and control measure according to the signal.
Furthermore, the server is connected with a plurality of user terminals, and the user terminals are used for registering and logging in the system after the staff input personal information and sending the personal information to the server for storage.
Further, the personal information comprises the name of the person, the mobile phone number of real-name authentication, the time of entry, a personal photo and a responsible power supply area;
the real-time operation data are a real-time current value and a real-time voltage value of the power supply system;
the real-time environmental data are an environmental temperature value, an environmental rainfall and an environmental wind force value;
the standard operation data comprises a standard current change rate and a standard voltage change rate, and the standard environmental data comprises a standard temperature value, a standard humidity value and a standard wind force value.
Further, the monitoring process of the operation monitoring module is specifically as follows:
the method comprises the following steps: setting a monitoring period of the power supply system, and setting three groups of time points Tui in the monitoring period, wherein i =1, 2, 3, i represents the number of the time points;
step two: acquiring a real-time current value LTui and a real-time voltage value YTui of a monitoring area at each time point in a monitoring period;
step three: combination formula
Calculating to obtain the real-time current change rate LBSu of the power supply system in the monitoring area in the monitoring period;
in the same way, in combination with formulas
Calculating to obtain the real-time voltage change rate YBSu of the power supply system in the monitoring area in the monitoring period;
step four: obtaining a standard current change rate and a standard voltage change rate corresponding to a power supply system in a monitoring area, comparing the standard current change rate with a real-time current change rate, and comparing the standard voltage change rate with a real-time voltage change rate to obtain a current change rate difference CLBSu and a voltage change rate difference CYBSu of the power supply system in the monitoring area;
step five: substituting the current change rate difference CLBSu and the voltage change rate difference CYBSu into a calculation formula YPu = CLBSu × a1+ CYBSu × a2 to calculate an operation deviation value YPu of the power supply system in the monitoring area; in the formula, a1 and a2 are both weight coefficients with fixed numerical values, and the values of a1 and a2 are both larger than zero;
step six: if YPu is less than X1, the operation deviation coefficient of the power supply system in the monitoring area is alpha 1;
if the X1 is not less than YPu and is more than X2, the running deviation coefficient of the power supply system in the monitoring area is alpha 2;
if X2 is less than or equal to YPu, the operation deviation coefficient of the power supply system in the monitoring area is alpha 3; wherein X1 and X2 are both running deviation thresholds, and X1 < X2.
Further, the value of the operation deviation coefficient α 1 is smaller than the value of the operation deviation coefficient α 2, and the value of the operation deviation coefficient α 2 is smaller than the value of the operation deviation coefficient α 3.
Further, the monitoring process of the environment monitoring module is specifically as follows:
step S1: acquiring an environment temperature value WTuui, an environment rainfall STui and an environment wind power value FTui of a power supply system in a monitoring area at each time point;
step S2: comparing the ambient temperature value at each time point with the standard temperature value, taking absolute values to obtain three groups of temperature difference values CWTui, adding the three groups of temperature difference values, summing and averaging to obtain an ambient temperature difference value JCWTu of the power supply system in the monitoring area;
similarly, obtaining an environmental humidity difference value JCSTU and an environmental wind power difference value JCFTu of a power supply system in a monitored area;
step S3: substituting the ambient temperature difference value JCWTu, the ambient humidity difference value JCSTU and the ambient wind difference value JCFTu into a calculation formula HPu = JCWTu × c1+ JCSTU × c2+ JCFTu × c3 to calculate an ambient deviation value HPu of the power supply system in the monitored area; in the formula, c1, c2 and c3 are all proportional coefficients with fixed numerical values, and the values of c1, c2 and c3 are all larger than zero;
step S4: if YPu is less than Y1, the environmental deviation coefficient of the power supply system in the monitoring area is beta 1;
if Y1 is not more than YPu and is more than Y2, the environmental deviation coefficient of the power supply system in the monitoring area is beta 2;
if Y2 is less than or equal to YPu, the environmental deviation coefficient of the power supply system in the monitoring area is beta 3; wherein Y1 and Y2 are both environmental deviation threshold values, and Y1 < Y2.
Further, the value of the environmental deviation coefficient β 1 is smaller than the value of the environmental deviation coefficient β 2, and the value of the environmental deviation coefficient β 2 is smaller than the value of the environmental deviation coefficient β 3.
Further, the working process of the early warning classification module is as follows:
step SS 1: if YXu is not less than M1 and HXu is not less than N1, the monitoring area is determined to be a power supply high-risk area, and a high-risk early warning signal is generated;
step SS 2: if YXu is larger than M1 and HXu is larger than or equal to N1 or YXu is larger than or equal to M1 and HXu is smaller than N1, the monitoring area is judged to be a power supply medium-risk area, and a medium-risk early warning signal is generated;
step SS 3: if YXu is larger than M1 and HXu is larger than N1, the monitoring area is judged to be a power supply low-risk area, and a low-risk early warning signal is generated; in the formula, M1 corresponds to YXu, N1 corresponds to HXu, M1 is a preset value of the running deviation coefficient, N1 is a preset value of the environmental deviation coefficient, and M1 and N1 are both fixed values.
Further, the management and control measures are specifically as follows:
if the monitoring area is a power supply high-risk area, setting a monitoring time period of twenty-four hours all day, adding a monitoring point and a monitoring station, and regularly maintaining a power supply system by workers;
if the monitoring area is a power supply medium-risk area, setting a monitoring time period with an interval period of two hours, and additionally arranging a monitoring point and a monitoring station;
and if the monitoring area is a power supply low-risk area, setting a monitoring time period of four hours per interval period.
Compared with the prior art, the invention has the beneficial effects that:
the invention monitors the operation state of the power supply system in the monitoring area through the operation monitoring module to obtain the operation deviation coefficient of the power supply system in the monitoring area, monitors the environment state of the power supply system in the monitoring area through the environment monitoring module to obtain the environment deviation coefficient of the power supply system in the monitoring area, sends the operation deviation coefficient and the environment deviation coefficient to the early warning grading module, carries out early warning grading on the monitoring area according to the operation deviation coefficient and the environment deviation coefficient of the monitoring area, judges the monitoring area as a power supply high-risk area, a power supply medium-risk area and a power supply low-risk area, generates corresponding high-risk early warning signals, medium-risk early warning signals and low-risk early warning signals, sends the high-risk early warning signals and the medium-risk early warning signals to corresponding user terminals, and workers go to the monitoring areas corresponding to the high-risk early warning signals and the medium-risk early warning signals, meanwhile, the power supply management and control module sets corresponding management and control measures for the monitoring area according to the signals, the invention realizes the grade division of the power supply system by combining multiple factors such as operation data, an environmental data bureau and the like, and simultaneously matches the corresponding management and control measures according to the grade.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is an overall system block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood 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 obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Referring to fig. 1, an intelligent power supply system includes a user terminal, a region distribution module, an early warning classification module, an operation monitoring module, a data acquisition module, an environment monitoring module, a power supply management and control module, and a server;
the server is connected with a plurality of user terminals, and the user terminals are used for registering a login system after the staff input personal information and sending the personal information to the server for storage;
the personal information comprises personnel names, mobile phone numbers authenticated by real names, time of entry, personal photos, responsible power supply areas and the like;
the region distribution module is used for dividing a power supply region into a plurality of monitoring regions, and marking the monitoring regions as u, u =1, 2, … …, z and z as positive integers;
the regional distribution module sends the divided monitoring regions to a server, and the server respectively sends the divided monitoring regions to the operation monitoring module and the environment monitoring module;
the data acquisition module is used for acquiring real-time operation data and real-time environment data of a power supply system in a monitoring area and sending the real-time power supply data and the real-time environment data to the server, the server sends the real-time operation data to the operation monitoring module, and the server sends the real-time environment data to the environment monitoring module;
in specific implementation, the data acquisition module can be a monitoring station, a monitoring point and the like set in a monitoring area;
specifically, the real-time operation data is a real-time current value, a real-time voltage value and the like of the power supply system; the real-time environmental data comprise an environmental temperature value, an environmental rainfall, an environmental wind force value and the like;
the server stores standard operating data and standard environmental data of the power supply system, transmits the standard operating data to the operation monitoring module, and transmits the standard environmental data to the environment monitoring module; the standard operation data comprises a standard current change rate, a standard voltage change rate and the like, and the standard environment data comprises a standard temperature value, a standard humidity value, a standard wind force value and the like;
the operation monitoring module is used for monitoring the operation state of the power supply system in the monitoring area, and the monitoring process is as follows:
the method comprises the following steps: setting a monitoring period of the power supply system, and setting three groups of time points Tui in the monitoring period, wherein i =1, 2, 3, i represents the number of the time points;
step two: acquiring a real-time current value LTui and a real-time voltage value YTui of a monitoring area at each time point in a monitoring period;
step three: combination formula
Calculating to obtain the real-time current change rate LBSu of the power supply system in the monitoring area in the monitoring period;
by the same token, in combination with formulas
Calculating to obtain the real-time voltage change rate YBSu of the power supply system in the monitoring area in the monitoring period;
step four: obtaining a standard current change rate and a standard voltage change rate corresponding to a power supply system in a monitoring area, comparing the standard current change rate with a real-time current change rate, and comparing the standard voltage change rate with a real-time voltage change rate to obtain a current change rate difference CLBSu and a voltage change rate difference CYBSu of the power supply system in the monitoring area;
step five: substituting the current change rate difference CLBSu and the voltage change rate difference CYBSu into a calculation formula YPu = CLBSu × a1+ CYBSu × a2 to calculate an operation deviation value YPu of the power supply system in the monitoring area; in the formula, a1 and a2 are both weight coefficients with fixed values, and the values of a1 and a2 are both greater than zero, and in specific implementation, the values of a2 and a2 are only required to have no influence on the positive-negative ratio relationship between the parameters and the result value;
step six: if YPu is less than X1, the operation deviation coefficient of the power supply system in the monitoring area is alpha 1;
if the X1 is not less than YPu and is more than X2, the running deviation coefficient of the power supply system in the monitoring area is alpha 2;
if X2 is less than or equal to YPu, the operation deviation coefficient of the power supply system in the monitoring area is alpha 3; wherein X1 and X2 are both running deviation thresholds, and X1 < X2;
understandably, the value of the operation deviation coefficient alpha 1 is smaller than that of the operation deviation coefficient alpha 2, and the value of the operation deviation coefficient alpha 2 is smaller than that of the operation deviation coefficient alpha 3;
the operation monitoring module feeds back an operation deviation coefficient of a power supply system in a monitoring area to the server;
the environment monitoring module is used for monitoring the environment condition of the power supply system in the monitoring area, and the monitoring process specifically comprises the following steps:
step S1: acquiring an environment temperature value WTuui, an environment rainfall STui and an environment wind power value FTui of a power supply system in a monitoring area at each time point;
step S2: comparing the ambient temperature values at each time point with the standard temperature values, obtaining three groups of temperature difference values CWTui after taking absolute values, adding the three groups of temperature difference values, summing and taking an average value to obtain an ambient temperature difference value JCWTu of the power supply system in the monitoring area;
similarly, obtaining an environmental humidity difference value JCSTU and an environmental wind power difference value JCFTu of a power supply system in a monitored area;
step S3: substituting the ambient temperature difference value JCWTu, the ambient humidity difference value JCSTU and the ambient wind difference value JCFTu into a calculation formula HPu = JCWTu × c1+ JCSTU × c2+ JCFTu × c3 to calculate an ambient deviation value HPu of the power supply system in the monitored area; in the formula, c1, c2 and c3 are all proportional coefficients with fixed numerical values, and the values of c1, c2 and c3 are all larger than zero; in specific implementation, the values of c1, c2 and c3 are only required to be values without influencing the positive-negative ratio relation between the parameters and the result values;
step S4: if YPu is less than Y1, the environmental deviation coefficient of the power supply system in the monitoring area is beta 1;
if Y1 is not more than YPu and is more than Y2, the environmental deviation coefficient of the power supply system in the monitoring area is beta 2;
if Y2 is less than or equal to YPu, the environmental deviation coefficient of the power supply system in the monitoring area is beta 3; wherein Y1 and Y2 are both environment deviation threshold values, and Y1 is less than Y2;
understandably, the value of the environmental deviation coefficient beta 1 is smaller than that of the environmental deviation coefficient beta 2, and the value of the environmental deviation coefficient beta 2 is smaller than that of the environmental deviation coefficient beta 3;
the environment monitoring module feeds back an environment deviation coefficient of a power supply system in a monitoring area to the server, the server sends the operation deviation coefficient and the environment deviation coefficient to the early warning grading module, the operation deviation coefficient of the monitoring area is marked as YXu, and the environment deviation coefficient of the monitoring area is marked as HXu;
the early warning grading module carries out early warning grading on the monitoring area according to the running deviation coefficient and the environmental deviation coefficient of the monitoring area, and the working process is as follows:
step SS 1: if YXu is not less than M1 and HXu is not less than N1, the monitoring area is determined to be a power supply high-risk area, and a high-risk early warning signal is generated;
step SS 2: if YXu is larger than M1 and HXu is larger than or equal to N1 or YXu is larger than or equal to M1 and HXu is smaller than N1, the monitoring area is judged to be a power supply medium-risk area, and a medium-risk early warning signal is generated;
step SS 3: if YXu is greater than M1 and HXu is greater than N1, judging that the monitoring area is a power supply low-risk area, and generating a low-risk early warning signal; in the formula, M1 corresponds to YXu, N1 corresponds to HXu, M1 is a preset value of a running deviation coefficient, N1 is a preset value of an environmental deviation coefficient, and M1 and N1 are both fixed values;
in specific implementation, the preset value of the operation deviation coefficient and the preset value of the environment deviation coefficient can be scientifically set according to the previous operation data, environment data and other factors of the monitoring area and by combining with the actual condition prediction drill;
the early warning classification module feeds back a high-risk early warning signal, a medium-risk early warning signal and a low-risk early warning signal to the server, the server sends the high-risk early warning signal and the medium-risk early warning signal to corresponding user terminals according to a power supply area responsible for workers, and the workers go to monitoring areas corresponding to the high-risk early warning signal and the medium-risk early warning signal;
simultaneously, the server sends high-risk early warning signal, well danger early warning signal and low-risk early warning signal to power supply management and control module, power supply management and control module sets for the management and control measure that corresponds for the monitoring area according to the signal, specifically does:
if the monitoring area is a power supply high-risk area, setting a monitoring time period of twenty-four hours all day, adding a monitoring point and a monitoring station, and regularly maintaining a power supply system by workers;
if the monitoring area is a power supply medium-risk area, setting a monitoring time period with an interval period of two hours, and additionally arranging a monitoring point and a monitoring station;
and if the monitoring area is a power supply low-risk area, setting a monitoring time period of four hours per interval period.
An intelligent power supply system is characterized in that when the intelligent power supply system works, a power supply area is divided into a plurality of monitoring areas u through an area distribution module, the divided monitoring areas are sent to a server through the area distribution module, and the server sends the divided monitoring areas to an operation monitoring module and an environment monitoring module respectively;
the method comprises the steps that real-time operation data and real-time environment data of a power supply system in a monitoring area are collected through a data collection module, the real-time power supply data and the real-time environment data are sent to a server, the server sends the real-time operation data to an operation monitoring module, the server sends the real-time environment data to an environment monitoring module, standard operation data and standard environment data of the power supply system are stored in the server, the standard operation data are sent to the operation monitoring module, and the standard environment data are sent to the environment monitoring module;
the method comprises the steps of monitoring the operation condition of a power supply system in a monitoring area through an operation monitoring module, setting a monitoring time period of the power supply system, setting three groups of time points Tui in the monitoring time period, obtaining a real-time current value LTui and a real-time voltage value YTui of the monitoring area at each time point in the monitoring time period, and combining a formula
Calculating to obtain the real-time current change rate LBSu of the power supply system in the monitoring area in the monitoring period, and combining the formula
Calculating to obtain a real-time voltage change rate YBSu of the power supply system in the monitoring area in a monitoring period, then obtaining a standard current change rate and a standard voltage change rate corresponding to the power supply system in the monitoring area, comparing the standard current change rate with the real-time current change rate, and comparing the standard voltage change rate with the real-time voltage change rate to obtain a current change rate difference CLBSu and a voltage change rate difference CYBSu of the power supply system in the monitoring area, substituting the current change rate difference CLBSu and the voltage change rate difference CYBSu into a calculation formula YPu = CLBSu × a1+ CYBSu × a2 to calculate an operation deviation value YPu of the power supply system in the monitoring area, if YPu is less than X1, the operation deviation coefficient of the power supply system in the monitoring area is alpha 1, if X1 is less than or equal to YPu less than X2, the operation deviation coefficient of the power supply system in the monitoring area is alpha 2, if X2 is less than or equal to YPu, the operation deviation coefficient of the power supply system in the monitoring area is alpha 3, the operation monitoring module feeds back an operation deviation coefficient of a power supply system in a monitoring area to the server;
monitoring the environmental condition of the power supply system in the monitoring area through an environmental monitoring module, and acquiring an environmental temperature value WTuui, an environmental rainfall STui and an environmental wind power value FTui of the power supply system in the monitoring area at each time point;
step S2: comparing the environmental temperature values at each time point with the standard temperature values, obtaining three groups of temperature difference values CWTui after taking absolute values, obtaining an environmental temperature difference value JCWTu of the power supply system in the monitoring area by adding and averaging the three groups of temperature difference values, obtaining an environmental humidity difference value JCSTU and an environmental wind force difference value JCFTu of the power supply system in the monitoring area by the same method, substituting the environmental temperature difference value JCWTu, the environmental humidity difference value JCSTU and the environmental wind force difference value JCFTu into a calculation formula HPu = JCWTu × c1+ JCSTU × c2+ JCFTu × c3 to obtain an environmental deviation value HPu of the power supply system in the monitoring area, and if YPu is smaller than Y1, the environmental deviation coefficient of the power supply system in the monitoring area is beta 1, if Y1 is not less than YPu and is more than Y2, if Y2 is less than or equal to YPu, the environmental deviation coefficient of the power supply system in the monitoring area is beta 2, and the environmental deviation coefficient of the power supply system in the monitoring area is beta 3, and the environmental monitoring module feeds the environmental deviation coefficient of the power supply system in the monitoring area back to the server;
the server sends the operation deviation coefficient and the environmental deviation coefficient to an early warning grading module, the operation deviation coefficient of a monitoring area is marked as YXu, the environmental deviation coefficient of the monitoring area is marked as HXu, the early warning grading module carries out early warning grading on the monitoring area according to the operation deviation coefficient and the environmental deviation coefficient of the monitoring area, if YXu is larger than or equal to M1 and HXu is larger than or equal to N1, the monitoring area is judged to be a power supply high-risk area, a high-risk early warning signal is generated, if YXu is smaller than M1 and HXu is larger than or equal to N1 or YXu is larger than or equal to M1 and HXu is smaller than N1, the monitoring area is judged to be a power supply medium-risk area, a medium-risk early warning signal is generated, if YXu is smaller than M1 and HXu is smaller than N1, the monitoring area is judged to be a power supply low-risk area, a low-risk early warning signal is generated, the early warning grading module feeds the high-risk early warning signal, the medium-risk early warning signal and the low-risk signal back to the server, the server sends the medium-risk early warning signal to corresponding user terminal according to the power supply area which is responsible for workers, the working personnel go to the monitoring areas corresponding to the high-risk early warning signal and the medium-risk early warning signal;
meanwhile, the server sends the high-risk early warning signal, the medium-risk early warning signal and the low-risk early warning signal to a power supply management and control module, corresponding management and control measures are set for a monitoring area through the power supply management and control module according to the signals, if the monitoring area is a power supply high-risk area, a monitoring period of twenty-four hours all day is set, monitoring points and monitoring stations are additionally arranged, a worker regularly maintains a power supply system, if the monitoring area is a power supply medium-risk area, a monitoring period of two hours per interval period is set, the monitoring points and the monitoring stations are additionally arranged, if the monitoring area is a power supply low-risk area, a monitoring period of four hours per interval period is set, the invention combines multiple factors such as operation data and an environmental data bureau to realize grade division of a power supply system, and simultaneously matches corresponding management and control measures according to grades.
The above formulas are all calculated by taking the numerical value of the dimension, the formula is a formula of the latest real situation obtained by collecting a large amount of data and performing software simulation, the preset parameters in the formula are set by the technical personnel in the field according to the actual situation, the scale coefficient and the weight coefficient are specific numerical values obtained by quantizing each parameter, and the subsequent comparison is convenient, and the scale coefficient and the weight coefficient can be calculated as long as the proportional relation between the parameter and the quantized numerical value is not influenced.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (9)
1. An intelligent power supply system is characterized by comprising a user terminal, a region distribution module, an early warning classification module, an operation monitoring module, a data acquisition module, an environment monitoring module, a power supply management and control module and a server, wherein the region distribution module is used for dividing a power supply region, dividing the power supply region into a plurality of monitoring regions, marking the monitoring regions as u, u =1, 2, … …, z and z as positive integers, the region distribution module sends the divided monitoring regions to the server, and the server sends the divided monitoring regions to the operation monitoring module and the environment monitoring module respectively; the data acquisition module is used for acquiring real-time operation data and real-time environment data of a power supply system in a monitoring area and sending the real-time operation data and the real-time environment data to the server, and the server sends the real-time operation data to the operation monitoring module and the real-time environment data to the environment monitoring module;
the server stores standard operating data and standard environmental data of the power supply system, transmits the standard operating data to the operation monitoring module, and transmits the standard environmental data to the environment monitoring module; the operation monitoring module is used for monitoring the operation state of the power supply system in the monitoring area, and the operation deviation coefficient of the power supply system in the monitoring area is monitored and fed back to the server; the environment monitoring module is used for monitoring the environment condition of the power supply system in the monitoring area, monitoring the environment deviation coefficient of the power supply system in the monitoring area and feeding the environment deviation coefficient back to the server, the server sends the operation deviation coefficient and the environment deviation coefficient to the early warning grading module, and the operation deviation coefficient of the monitoring area is marked as YXu, and the environment deviation coefficient is marked as HXu;
the early warning classification module carries out early warning classification to the monitoring area according to the operation deviation coefficient and the environmental deviation coefficient of the monitoring area, generates high-risk early warning signal, well danger early warning signal and low-risk early warning signal and feeds back to the server, the server sends the high-risk early warning signal and well danger early warning signal to the corresponding user terminal according to the power supply area that the staff is responsible for, the staff goes to the monitoring area that high-risk early warning signal and well danger early warning signal correspond, simultaneously, the server sends high-risk early warning signal, well danger early warning signal and low-risk early warning signal to power supply management and control module, and power supply management and control module sets for the management and control measure that corresponds for the monitoring area according to the signal.
2. The intelligent power supply system according to claim 1, wherein the server is connected with a plurality of user terminals, and the user terminals are used for registering and logging in the system after personal information is input by workers and sending the personal information to the server for storage.
3. The intelligent power supply system according to claim 2, wherein the personal information includes a person name, a mobile phone number for real name authentication, an enrollment time, a personal photo and a responsible power supply area;
the real-time operation data are a real-time current value and a real-time voltage value of the power supply system;
the real-time environmental data are an environmental temperature value, an environmental rainfall and an environmental wind force value;
the standard operation data comprises a standard current change rate and a standard voltage change rate, and the standard environmental data comprises a standard temperature value, a standard humidity value and a standard wind force value.
4. The intelligent power supply system according to claim 3, wherein a monitoring process of the operation monitoring module is specifically as follows:
the method comprises the following steps: setting a monitoring period of the power supply system, and setting three groups of time points Tui in the monitoring period, wherein i =1, 2, 3, i represents the number of the time points;
step two: acquiring a real-time current value LTui and a real-time voltage value YTui of a monitoring area at each time point in a monitoring time period;
step three: combination formula
Calculating to obtain the real-time current change rate LBSu of the power supply system in the monitoring area in the monitoring period;
in the same way, in combination with formulas
Calculating to obtain the real-time voltage change rate YBSu of the power supply system in the monitoring area in the monitoring period;
step four: obtaining a standard current change rate and a standard voltage change rate corresponding to a power supply system in a monitoring area, comparing the standard current change rate with a real-time current change rate, and comparing the standard voltage change rate with a real-time voltage change rate to obtain a current change rate difference CLBSu and a voltage change rate difference CYBSu of the power supply system in the monitoring area;
step five: substituting the current change rate difference CLBSu and the voltage change rate difference CYBSu into a calculation formula YPu = CLBSu × a1+ CYBSu × a2 to calculate an operation deviation value YPu of the power supply system in the monitoring area; in the formula, a1 and a2 are both weight coefficients with fixed values, and the values of a1 and a2 are both greater than zero;
step six: if YPu is less than X1, the operation deviation coefficient of the power supply system in the monitoring area is alpha 1;
if the X1 is not less than YPu and is more than X2, the running deviation coefficient of the power supply system in the monitoring area is alpha 2;
if X2 is less than or equal to YPu, the operation deviation coefficient of the power supply system in the monitoring area is alpha 3; wherein X1 and X2 are both running deviation thresholds, and X1 < X2.
5. The intelligent power supply system according to claim 4, wherein the value of the operational deviation coefficient α 1 is smaller than the value of the operational deviation coefficient α 2, and the value of the operational deviation coefficient α 2 is smaller than the value of the operational deviation coefficient α 3.
6. The intelligent power supply system according to claim 5, wherein the monitoring process of the environment monitoring module is as follows:
step S1: acquiring an environment temperature value WTuui, an environment rainfall STui and an environment wind power value FTui of a power supply system in a monitoring area at each time point;
step S2: comparing the ambient temperature values at each time point with the standard temperature values, obtaining three groups of temperature difference values CWTui after taking absolute values, adding the three groups of temperature difference values, summing and taking an average value to obtain an ambient temperature difference value JCWTu of the power supply system in the monitoring area;
similarly, obtaining an environmental humidity difference value JCSTU and an environmental wind power difference value JCFTu of a power supply system in a monitored area;
step S3: substituting the ambient temperature difference value JCWTu, the ambient humidity difference value JCSTU and the ambient wind difference value JCFTu into a calculation formula HPu = JCWTu × c1+ JCSTU × c2+ JCFTu × c3 to calculate an ambient deviation value HPu of the power supply system in the monitored area; in the formula, c1, c2 and c3 are all proportional coefficients with fixed numerical values, and the values of c1, c2 and c3 are all larger than zero;
step S4: if YPu is less than Y1, the environmental deviation coefficient of the power supply system in the monitoring area is beta 1;
if Y1 is not more than YPu and is more than Y2, the environmental deviation coefficient of the power supply system in the monitoring area is beta 2;
if Y2 is less than or equal to YPu, the environmental deviation coefficient of the power supply system in the monitoring area is beta 3; wherein Y1 and Y2 are both environmental deviation threshold values, and Y1 < Y2.
7. The intelligent power supply system according to claim 6, wherein the value of the environmental deviation coefficient β 1 is smaller than the value of the environmental deviation coefficient β 2, and the value of the environmental deviation coefficient β 2 is smaller than the value of the environmental deviation coefficient β 3.
8. The intelligent power supply system according to claim 7, wherein the operation process of the early warning classification module is as follows:
step SS 1: if YXu is not less than M1 and HXu is not less than N1, judging that the monitoring area is a power supply high-risk area, and generating a high-risk early warning signal;
step SS 2: if YXu is larger than M1 and HXu is larger than or equal to N1 or YXu is larger than or equal to M1 and HXu is smaller than N1, the monitoring area is judged to be a power supply medium-risk area, and a medium-risk early warning signal is generated;
step SS 3: if YXu is larger than M1 and HXu is larger than N1, the monitoring area is judged to be a power supply low-risk area, and a low-risk early warning signal is generated; in the formula, M1 corresponds to YXu, N1 corresponds to HXu, M1 is a preset value of the running deviation coefficient, N1 is a preset value of the environmental deviation coefficient, and M1 and N1 are both fixed values.
9. The intelligent power supply system according to claim 8, wherein the management and control measures are specifically:
if the monitoring area is a power supply high-risk area, setting a monitoring time period of twenty-four hours all day, adding a monitoring point and a monitoring station, and regularly maintaining a power supply system by workers;
if the monitoring area is a power supply medium-risk area, setting a monitoring time period with an interval period of two hours, and additionally arranging a monitoring point and a monitoring station;
and if the monitoring area is a power supply low-risk area, setting a monitoring time period of four hours per interval period.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210217886.XA CN114665597A (en) | 2022-03-08 | 2022-03-08 | Intelligent power supply system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210217886.XA CN114665597A (en) | 2022-03-08 | 2022-03-08 | Intelligent power supply system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114665597A true CN114665597A (en) | 2022-06-24 |
Family
ID=82029244
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210217886.XA Pending CN114665597A (en) | 2022-03-08 | 2022-03-08 | Intelligent power supply system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114665597A (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115378141A (en) * | 2022-10-18 | 2022-11-22 | 华能辛店发电有限公司 | Power cable fault diagnosis and early warning system and method based on data analysis |
| CN115390513A (en) * | 2022-07-14 | 2022-11-25 | 深圳市博硕科技股份有限公司 | Remote intelligent monitoring system of automatic laminating machine |
| CN115389854A (en) * | 2022-10-25 | 2022-11-25 | 智洋创新科技股份有限公司 | Safety monitoring system and method for direct-current power supply system |
| CN115425737A (en) * | 2022-08-22 | 2022-12-02 | 黄河科技学院 | Intelligent control system of high-voltage fixed-frequency voltage-regulating stabilized power supply |
| CN115623034A (en) * | 2022-09-28 | 2023-01-17 | 泉州年盛信息科技有限公司 | Enterprise energy management system based on industrial internet platform |
| CN115979351A (en) * | 2023-03-22 | 2023-04-18 | 青岛市人防建筑设计研究院有限公司 | Unattended people's air defense early warning system based on data analysis |
| CN116222806A (en) * | 2023-02-28 | 2023-06-06 | 临沂市检验检测中心 | Remote environment monitoring and calibrating system and method |
| CN116846080A (en) * | 2023-07-13 | 2023-10-03 | 国网山东省电力公司聊城供电公司 | Outdoor ring main unit running state supervision system and method based on data analysis |
| CN117092578A (en) * | 2023-10-18 | 2023-11-21 | 青岛悠进电装有限公司 | Wire harness conduction intelligent detection system based on data acquisition and processing |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150263522A1 (en) * | 2014-03-17 | 2015-09-17 | Alstom Grid Inc. | Powergrid operation and supervision system |
| CN113051519A (en) * | 2021-06-01 | 2021-06-29 | 北方卓越(北京)勘测技术有限公司 | Ground settlement early warning monitoring system based on geophysics |
| CN114114003A (en) * | 2021-11-29 | 2022-03-01 | 山东汇能电气有限公司 | Circuit breaker operation detection system based on data monitoring |
-
2022
- 2022-03-08 CN CN202210217886.XA patent/CN114665597A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150263522A1 (en) * | 2014-03-17 | 2015-09-17 | Alstom Grid Inc. | Powergrid operation and supervision system |
| CN113051519A (en) * | 2021-06-01 | 2021-06-29 | 北方卓越(北京)勘测技术有限公司 | Ground settlement early warning monitoring system based on geophysics |
| CN114114003A (en) * | 2021-11-29 | 2022-03-01 | 山东汇能电气有限公司 | Circuit breaker operation detection system based on data monitoring |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115390513A (en) * | 2022-07-14 | 2022-11-25 | 深圳市博硕科技股份有限公司 | Remote intelligent monitoring system of automatic laminating machine |
| CN115425737A (en) * | 2022-08-22 | 2022-12-02 | 黄河科技学院 | Intelligent control system of high-voltage fixed-frequency voltage-regulating stabilized power supply |
| CN115425737B (en) * | 2022-08-22 | 2023-10-24 | 黄河科技学院 | Intelligent control system of high-voltage fixed-frequency voltage-regulating stabilized power supply |
| CN115623034A (en) * | 2022-09-28 | 2023-01-17 | 泉州年盛信息科技有限公司 | Enterprise energy management system based on industrial internet platform |
| CN115623034B (en) * | 2022-09-28 | 2023-08-22 | 长峡数字能源科技(湖北)有限公司 | Enterprise Energy Management System Based on Industrial Internet Platform |
| CN115378141A (en) * | 2022-10-18 | 2022-11-22 | 华能辛店发电有限公司 | Power cable fault diagnosis and early warning system and method based on data analysis |
| CN115378141B (en) * | 2022-10-18 | 2023-02-28 | 华能辛店发电有限公司 | Power cable fault diagnosis early warning system and method based on data analysis |
| CN115389854B (en) * | 2022-10-25 | 2023-03-21 | 智洋创新科技股份有限公司 | Safety monitoring system and method for direct-current power supply system |
| CN115389854A (en) * | 2022-10-25 | 2022-11-25 | 智洋创新科技股份有限公司 | Safety monitoring system and method for direct-current power supply system |
| CN116222806A (en) * | 2023-02-28 | 2023-06-06 | 临沂市检验检测中心 | Remote environment monitoring and calibrating system and method |
| CN116222806B (en) * | 2023-02-28 | 2023-09-26 | 临沂市检验检测中心 | Remote environment monitoring and calibrating system and method |
| CN115979351A (en) * | 2023-03-22 | 2023-04-18 | 青岛市人防建筑设计研究院有限公司 | Unattended people's air defense early warning system based on data analysis |
| CN116846080A (en) * | 2023-07-13 | 2023-10-03 | 国网山东省电力公司聊城供电公司 | Outdoor ring main unit running state supervision system and method based on data analysis |
| CN116846080B (en) * | 2023-07-13 | 2024-03-26 | 国网山东省电力公司聊城供电公司 | Outdoor ring main unit running state supervision system and method based on data analysis |
| CN117092578A (en) * | 2023-10-18 | 2023-11-21 | 青岛悠进电装有限公司 | Wire harness conduction intelligent detection system based on data acquisition and processing |
| CN117092578B (en) * | 2023-10-18 | 2024-01-16 | 青岛悠进电装有限公司 | Wire harness conduction intelligent detection system based on data acquisition and processing |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114665597A (en) | Intelligent power supply system | |
| CN113904448B (en) | Intelligent power distribution operation and maintenance service system based on multidimensional monitoring | |
| CN115378141B (en) | Power cable fault diagnosis early warning system and method based on data analysis | |
| CN106228278A (en) | Photovoltaic power prognoses system | |
| CN103065201B (en) | Based on temperature and festivals or holidays factor electric power electro-load forecast method | |
| CN115166500A (en) | Direct current breaker equipment state analysis system based on power grid resource business middle platform | |
| CN113962518B (en) | Power big data-based sewage enterprise abnormality judgment method | |
| CN115730749B (en) | Power dispatching risk early warning method and device based on fusion power data | |
| CN108448721A (en) | The method of electric system main station monitoring signal and standard signal Auto-matching | |
| CN115907168A (en) | Abnormal data processing system for power load prediction | |
| CN107862391A (en) | A kind of equipment operation condition test system based on cloud computing | |
| CN112414576A (en) | Factory environment temperature detection system based on wireless sensor network | |
| CN115481918A (en) | Active sensing and predictive analysis system for unit state based on source network load storage | |
| CN116933952B (en) | Park low-carbon energy scheduling system based on visualization of Internet of things | |
| CN105958474A (en) | Power transmission line dynamic capacity increasing method and system used for power grid regulation and control system | |
| CN111507576A (en) | Balanced scheduling method for comprehensive energy management of industrial park | |
| CN117117983A (en) | Thermal power plant peak regulation management method and system combining power distribution network requirements | |
| CN110190811A (en) | Solar panel on-line monitoring system and equipment | |
| CN116384548A (en) | Environmental feedback-based power grid short-term power load prediction method | |
| CN107871177B (en) | Implementation method of new energy power prediction centralized framework | |
| CN114707860A (en) | ECI-based user power utilization information management system | |
| CN113824213A (en) | Power information monitoring system and networking method thereof | |
| CN113595100A (en) | Electric power compensation system | |
| CN115021222B (en) | Intelligent arc discharge protection device | |
| CN115441591B (en) | Intelligent remote monitoring power consumption management system based on communication network |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20220624 |