CN109067002A - A kind of distribution line monitoring system and its working method based on Cloud Server - Google Patents
A kind of distribution line monitoring system and its working method based on Cloud Server Download PDFInfo
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- 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
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- 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
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- 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
- Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
- Y04S40/12—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment
- Y04S40/126—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment using wireless data transmission
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Abstract
The present invention relates to a kind of distribution line monitoring system and its working method based on Cloud Server, the distribution line monitoring system based on Cloud Server include: Cloud Server, monitor terminal and the monitoring device for being separately positioned on each section circuit monitoring point of power distribution network；Wherein the monitoring device includes: control module, the data acquisition module and communication module being connected with the control module；The data acquisition module is suitable for collected data information being transmitted to Cloud Server by communication module；And the Cloud Server is suitable for storing data information, and data information is sent to monitor terminal；The present invention is based on the distribution line monitoring systems of Cloud Server remotely to monitor the electric power thus supplied of each circuit monitoring point by monitoring device, and the information monitored is stored and is sent to monitor terminal, staff is set to find failure in first time, to carry out inspection maintenance to route in time, the time is saved, provides basic guarantee for being normally carried out of producing and live.
Description
Technical field
The invention belongs to power supply monitoring technical field more particularly to a kind of distribution line monitoring systems based on Cloud Server
And its working method.
Background technique
With economic fast development, the substantial increase of power load proposes more power supply reliability and power supply quality
Carry out higher requirement, power distribution network is directly facing user, and the influence to customer power supply quality and power supply reliability is also the most direct, phase
For power transmission network, distribution protection, the configuration of control device are relatively easy, easily by failure caused by various factors.
According to statistics, most power outages are because of distribution network failure, and system for distribution network of power feeder line Numerous, supply district is wide, equipment
Enormous amount.Not only loss is big when line failure, and the investigation of fault point is also extremely difficult.Especially in urban power distribution network
In, underground cable power supply mode is applied increasingly extensive, and the difficulty of investigation is even more increased.In order to find out specific abort situation,
Operator's bracing wire power failure and artificial line walking are generally required to search fault point, spends the time long, manpower and material resources expend greatly, easy
Extend power off time, reduces power supply reliability.
Summary of the invention
The purpose of the present invention is to provide a kind of distribution line monitoring system and its working method based on Cloud Server, it is real
Now to the monitoring of distribution line.
The distribution line monitoring system based on Cloud Server that in order to solve the above-mentioned technical problems, the present invention provides a kind of,
It include: Cloud Server, monitor terminal and the monitoring device for being separately positioned on each section circuit monitoring point of power distribution network；The wherein prison
Controlling device includes: control module, the data acquisition module and communication module being connected with the control module；The data acquisition module
Suitable for collected data information is transmitted to Cloud Server by communication module；And the Cloud Server is suitable for storing data
Information, and data information is sent to monitor terminal.
Further, the data acquisition module includes: power supply line's data acquisition module and switch data acquisition module；Institute
Power supply line's data acquisition module is stated for acquiring the voltage and current signals and switch data acquisition mould of power supply line
Block is used to acquire the acting characteristic of switch and the temperature signal of contact.
Further, the monitor terminal includes smart machine；The smart machine includes front-end processing unit, for defeated
The voice signal entered is pre-processed；Voice signal output circuit；Double-core CPU, for the voice signal progress to input and output
Processing；ARM microprocessor works for manipulating smart machine according to user instruction；And intelligent power, with double-core CPU
It is connected, and powers to multiple functional modules.
Further, the intelligent power includes: input voltage+VC~-VC, and left inductance group and right inductance group all have centre
Transformer T1, transformer T2, the transformer T3 of magnetic core, switch element S1, switch element S2, diode D1, diode D2, two poles
Pipe D3, diode D4, diode D5, diode D6, diode D7, diode D8, compensation diode Ds1, compensation diode
Ds2, diode Ds3, capacitor C1, capacitor C2, compensating electric capacity Cs1, compensating electric capacity Cs2, feedback capacitor CB are compensated；Wherein transformer
T1 is the right inductance group Lsc1 that left side is equipped with intermediate magnetic core；Transformer T2 is the right inductance group Lsc2 that left side is equipped with intermediate magnetic core；
Transformer T3 is that left side is equipped with the right inductance group Lsc3 of intermediate magnetic core and with right inductance group Lsc3 at the upper left inductance group of image, a left side
Lower inductance group；The collector of the end input voltage+VC connection switch element S1；The collector of its end-VC connection switch element S2；It is defeated
Enter the end voltage+VC and is also respectively connected with the cathode of diode D1, the cathode of compensating electric capacity Cs1, the anode of diode D2, diode
The cathode of D8, diode D6；The end input voltage-VC is also respectively connected with feedback resistors R1, the anode of diode D2, compensating electric capacity
The anode of Cs2, capacitor C1, capacitor C2, diode D7；Compensate diode Ds1 cathode, compensate diode Ds3 cathode with
The anode of diode D1 is connected；The anode of compensation diode Ds1 is connected with the anode of right inductance group Lsc3；Compensate diode
The anode of Ds3 is connected with the anode of right inductance group Lsc1；The anode of diode D6 is connected with the anode of right inductance group Lsc2；
The opposite end of the collector of switch element S1 is connected with the secondary end of upper left inductance group；The opposite end of the collector of switch element S2
It is connected with the anode of lower-left inductance group；One end phase of the tie point of upper left inductance group and lower-left inductance group and feedback capacitor CB
Even；The other end of feedback capacitor CB is connected with feedback resistors R1；The opposite end of the collector of switch element S2 also passes through connection and mends
The anode for repaying diode Ds2 is connected with the secondary end of right inductance group Lsc3 and compensating electric capacity Cs2 respectively；The cathode of diode D5 with
The secondary end of right inductance group Lsc1 is connected；And the cathode of diode D2 also pass through connection diode D3 anode respectively with right electricity
The secondary end of sense group Lsc2 is connected with capacitor C2.
Further, the front-end processing unit include: sample circuit, signal amplification circuit, shaping circuit, filter circuit and
A/D converter；Wherein a microphone successively turns through over-sampling circuit, signal amplification circuit, shaping circuit, filter circuit and A/D
Parallel operation connects with the input terminal of double-core CPU；The input terminal of the double-core CPU is also connected to respectively for by the micro- place double-core CPU and ARM
Manage RS232 serial communication interface, memory and the intelligent power for stored voice message that device carries out two-way communication；
The voice signal output circuit includes: voice playing circuit module and power amplification circuit module；The output of the double-core CPU
End passes sequentially through voice playing circuit module and power amplification circuit module connects with a loudspeaker；And the ARM micro process
The output end of device is connected by drive module with execution unit.
Further, the intelligent power further includes voltage correction module and current correction module；Voltage correction module and electricity
Stream correction module is all made of eight quadrant interpolation methods and is corrected；The smart machine further include one be connected with double-core CPU it is wireless
Control module；Wireless control module send information to the smart phone of distal end by WIFI module, receives smart phone feedback
Operation signal simultaneously sends back wireless control module, is further processed by double-core CPU according to the operation signal；And it is described
Smart phone is the first priority.
Further, following step is used to eight quadrant interpolation methods of current data correction:
Step S1 selects any one current data I from the data acquired in certain period of time, is vertical with its amplitude
Axis, time are horizontal axis, angularly divide eight quadrants, are successively searched in each quadrant apart from nearest several of current data I
Data point, search radius be initially first threshold, if the current data number that can be found in certain quadrant less than 3, radius by
Secondary to increase to second threshold, maximum is no more than the 5th threshold value, forms a data set DS (st, qua, stx, dit), wherein st
It is current data I, qua is quadrant number, and stx is consecutive number strong point number, and dit is the distance of stx distance st；
Each current data parameters are calculated in DS from the measurement time in past half a minute, in 1 minute, 1 point
Variation difference Df (st, stx, elem, t, dt) in clock half, in 2 minutes, wherein dt refers to above-mentioned time interval；
Using quadrant as grouping unit, using interpolation algorithm calculate each variation difference Df (st, stx, elem, t, dt) away from
Interpolation PI (st, qua, stx, elem, t, dt) from current data I；Suspicious (50 < Ar≤90) or wrong are belonged to for confidence level Ar
The accidentally element value of (Ar≤50), is not involved in interpolation calculation；
The eight quadrant interpolation algorithm formula that this step uses are as follows:
In above formula, m is the quantity of current data in a certain quadrant qua in data set DS；Dit is a certain electric current number in qua
According to the distance between I ' and current data I；Ag_dit be in qua all current datas to current data I distance arithmetic it is flat
Mean value；Ag_dit ' is that (with current data I ' for the center of circle, first threshold is radius, searches for the range on the basis of current data I '
Interior all current datas, if the current data quantity searched is less than 3, radius gradually increases to second threshold, maximum
No more than the 5th threshold value), within the scope of this all current datas to current data I ' distance algorithm average value；
Step S2 is on the basis of current data I ', to each current data in its search range with step S1, Df '
Df carry out interpolation calculation obtain as a result, the interpolation formula are as follows:
In above formula, n is the quantity of current data in search range on the basis of current data I '；Dit ' is this range
The distance between interior a certain current data and current data I '；Df ' is the Df and electric current of a certain current data itself within the scope of this
The difference of the Df of data I '；The meaning of Ag_dit ' is same as above；And
Step S3, correcting current data are W=PI+Df '.
Further, the smart machine further include: electricity consumption statistic device；The electricity consumption statistic device includes:
Return processing module and energy consumption section module；Wherein the processing module that returns is born what is read out in electric quantity monitor database
It carries energy consumption data and creation data is converted to the training data of regression model, and utilize the regression function f in regression model
(x) training data is pre-processed；And energy consumption section module is used to supervise electricity according to Estimating Confidence Interval method
Historical energy consumption data in control device database is analyzed, and confidence level 1- α is given, and obtains the normal interval of energy consumption prediction.
Further, the pretreatment is will to load energy consumption data and creation data is converted to the training number of regression model
According to energy consumption data { f (x will be loaded that is, according to the time of acquisition1), f (x2) ..., f (xn) and corresponding creation data { x1,
x2..., xnIt is used as one group of data < f (xi), xi>, i=1,2 ..., n, for training regression function f (x)=wx+b, w and
B is respectively the hyperplane parameter for being fitted training data, and training process is by way of solving equation, with multi-group data < f
(xi), xi>, i=1,2 ..., n calculate the process of hyperplane parameter w and b；
X1, X2 ... Xn obeys sample distribution (μ, σ2),And S2Respectively indicate the sample average and sample of prediction power consumption
Variance, then stochastic variable
For given confidence level 1- α,Wherein P indicates probability, then in advance
The confidence interval of mean μ for surveying power consumption is
Another aspect, the working method for the distribution line monitoring system based on Cloud Server that the present invention also provides a kind of,
It include: Cloud Server, monitor terminal and the monitoring device for being separately positioned on each section circuit monitoring point of power distribution network；The wherein prison
Controlling device includes: control module, the data acquisition module and communication module being connected with the control module；The data acquisition module
Suitable for collected data information is transmitted to Cloud Server by communication module；And the Cloud Server is suitable for storing data
Information, and data information is sent to monitor terminal.
The invention has the benefit that the present invention is based on the distribution line monitoring systems of Cloud Server to pass through monitoring device pair
The electric power thus supplied of each circuit monitoring point is remotely monitored, and stores and be sent to monitor terminal the information monitored, makes work
Failure can be found in first time by making personnel, to carry out inspection maintenance to route in time, the time be saved, to produce and living
Offer basic guarantee is provided.
Detailed description of the invention
Present invention will be further explained below with reference to the attached drawings and examples.
Fig. 1 is the functional block diagram of the distribution line monitoring system the present invention is based on Cloud Server；
Fig. 2 is the functional block diagram of smart machine in the distribution line monitoring system the present invention is based on Cloud Server；
Fig. 3 is the circuit diagram of intelligent power in the distribution line monitoring system the present invention is based on Cloud Server.
Specific embodiment
In conjunction with the accompanying drawings, the present invention is further explained in detail.These attached drawings are simplified schematic diagram, only with
Illustration illustrates basic structure of the invention, therefore it only shows the composition relevant to the invention.
Embodiment 1
As shown in Figure 1, the present embodiment 1 provides a kind of distribution line monitoring system based on Cloud Server, comprising: cloud clothes
Business device, monitor terminal and the monitoring device for being separately positioned on each section circuit monitoring point of power distribution network；The wherein monitoring device packet
It includes: control module, the data acquisition module and communication module being connected with the control module；The data acquisition module is suitable for adopt
The data information collected is transmitted to Cloud Server by communication module；And the Cloud Server is suitable for storing data information, and
Data information is sent to monitor terminal.
Specifically, the controller such as, but not limited to uses PLC controller；The communication module uses Ethernet interface
Module, WiFi module etc..
The data acquisition module includes: power supply line's data acquisition module and switch data acquisition module；The power supply
The voltage and current signals and the switch data acquisition module that track data acquisition module is used to acquire power supply line are used for
Acquire the acting characteristic of switch and the temperature signal of contact.
Specifically, the distribution line monitoring system based on Cloud Server of the present embodiment supervises each route by monitoring device
The electric power thus supplied of control point is remotely monitored, and stores and be sent to monitor terminal the information monitored, enables staff
First time find failure, thus in time to route carry out inspection maintenance, save the time, for produce and live it is normal into
Row provides basic guarantee.
Further, in order to ensure based on the effective monitoring of the distribution line monitoring system of Cloud Server, the monitoring is eventually
End is monitored using smart machine, the smart machine high reliablity, long service life.
Specifically, as shown in Fig. 2, the smart machine includes for carrying out pretreated front end to the voice signal of input
Processing unit, voice signal output circuit, the double-core CPU for being handled the voice signal of input and output and for manipulating
The ARM microprocessor that smart machine works according to user instruction, and connect double-core CPU and power to multiple functional modules
Intelligent power.
As shown in figure 3, the intelligent power includes input voltage+VC~-VC, during left inductance group and right inductance group all have
Between magnetic core transformer T1, transformer T2, transformer T3, switch element S1, switch element S2, diode D1, diode D2, two
Pole pipe D3, diode D4, diode D5, diode D6, diode D7, diode D8, compensation diode Ds1, compensation diode
Ds2, diode Ds3, capacitor C1, capacitor C2, compensating electric capacity Cs1, compensating electric capacity Cs2, feedback capacitor CB are compensated；Wherein transformer
T1 is the right inductance group Lsc1 that left side is equipped with intermediate magnetic core, and transformer T2 is the right inductance group Lsc2 that left side is equipped with intermediate magnetic core,
Transformer T3 is that left side is equipped with the right inductance group Lsc3 of intermediate magnetic core and with right inductance group Lsc3 at the upper left inductance group of image, a left side
Lower inductance group；The collector of the end voltage+VC connection switch element S1, the collector of the end voltage-VC connection switch element S2；Voltage
The end+VC connects the cathode of diode D1, the cathode of compensating electric capacity Cs1, the anode of diode D2, diode D8, diode D6
Cathode；The end voltage-VC connects feedback resistors R1, diode D2 anode, compensating electric capacity Cs2, capacitor C1, capacitor C2, diode
The anode of D7；The cathode for compensating diode Ds1, the cathode for compensating diode Ds3 are connected with the anode of diode D1；Compensation two
The anode of pole pipe Ds1 is connected with the anode of right inductance group Lsc3, compensates the anode and right inductance group Lsc1 of diode Ds3
Anode be connected；The anode of diode D6 is connected with the anode of right inductance group Lsc2；The collector of switch element S1
Opposite end is connected with the secondary end of upper left inductance group, the opposite end of the collector of switch element S2 and the anode phase of lower-left inductance group
The tie point of connection, upper left inductance group and lower-left inductance group is connected with feedback capacitor CB, the feedback capacitor CB other end and feedback electricity
Hinder R1It is connected；The opposite end of the collector of switch element S2 also pass through connection compensation diode Ds2 anode, then with right inductance
The secondary end of group Lsc3, compensating electric capacity Cs2 are connected；The cathode of diode D5 is connected with the secondary end of right inductance group Lsc1；Two poles
The cathode of pipe D2 also passes through the anode of connection diode D3, is then connected with the secondary end of right inductance group Lsc2, capacitor C2.
Two switch elements S1, S2 are when connecting, because electric current crosses negative effect, no longer generate switching losses；It is multiple simultaneously
Low, power density height is lost so that not generating extra power capacity in the specific cooperation of inductance group and corresponding electric appliance element,
Improve the working life and reliability of smart machine and its power supply.
The front-end processing unit includes sample circuit, signal amplification circuit, shaping circuit, filter circuit and A/D conversion
Device, microphone is successively through over-sampling circuit, signal amplification circuit, shaping circuit, filter circuit and A/D converter and double-core CPU
Input terminal connect, the input terminal of the double-core CPU is further connected with for double-core CPU and ARM microprocessor to be carried out two-way communication
RS232 serial communication interface, the intelligence for the 64G memory of stored voice message and for powering for each unit module
Power supply, the voice signal output circuit include voice playing circuit module and power amplification circuit module, the output of double-core CPU
End passes sequentially through voice playing circuit module and power amplification circuit module connects with loudspeaker, the ARM microprocessor it is defeated
Connected out by drive module with execution unit, the intelligent power can be automatically regulated to be suspend mode when not in use.
When the smart machine realizes human-computer interaction, activation system, user is instructed by microphone input voice signal, voice
Signal is sent into double-core CPU after front-end processing, and double-core CPU passes through RS232 after being analyzed and processed to the received voice signal of institute
Serial communication interface gives information to ARM microprocessor, and ARM microprocessor passes through drive module according to the received command information of institute
Control execution unit executes corresponding operation order, while microprocessor passes through RS232 serial communication interface for corresponding voice
Output signal is transmitted to double-core CPU, controls loudspeaker by voice playing circuit module and power amplification circuit module by double-core CPU
Export voice signal.
When multiple functional modules of the smart machine constantly start, intelligent power its electric current, voltage instability in conversion,
It is not easy to determine to be therefore to need to be arranged corresponding correction module in order to judge and further in normal condition or abnormality
Ground uses.The intelligent power further includes voltage correction module and current correction module, voltage correction module and current correction mould
Block is all made of eight quadrant interpolation methods and is corrected.By taking electric current as an example, it is corrected using eight quadrant interpolation methods.
Following step is used to eight quadrant interpolation methods of current data correction: from the data of the acquisition in certain period of time
Any one current data (current data I might as well be defined as) is selected, using its amplitude as the longitudinal axis, the time is horizontal axis, is angularly drawn
Point eight quadrants successively search several data points nearest apart from current data I in each quadrant, search radius and are initially the
One threshold value, if the current data number that can be found in certain quadrant is less than 3, radius gradually increases to second threshold, most very much not
More than the 5th threshold value, a data set DS (st, qua, stx, dit) is formed, wherein qua is quadrant number, and stx is consecutive number
Strong point number, dit is the distance of stx distance st (i.e. current data I)；Each current data parameters in DS are calculated to survey certainly
Measure from the time in past half a minute, in 1 minute, variation difference Df in 1 minute half, in 2 minutes (st, stx, elem, t,
Dt), wherein dt refers to above-mentioned time interval.
Using quadrant as grouping unit, using interpolation algorithm calculate each variation difference Df (st, stx, elem, t, dt) away from
Interpolation PI (st, qua, stx, elem, t, dt) from current data I；For confidence level Ar belong to suspicious (50 Ar≤90 <) or
The element value of mistake (Ar≤50), is not involved in interpolation calculation；The interpolation algorithm formula that this step uses are as follows:
In above formula, m is the quantity of current data in a certain quadrant qua in data set DS；Dit is a certain electric current number in qua
According to the distance between (I ' might as well be defined as) and current data I；Ag_dit be in qua all current datas to current data I
The arithmetic mean of instantaneous value of distance；Ag_dit ' is that (with current data I ' for the center of circle, first threshold is half on the basis of current data I '
Diameter searches for current data all within the scope of this, if the current data quantity searched is less than 3, radius gradually increases to
Second threshold, maximum be no more than the 5th threshold value), within the scope of this all current datas to current data I ' distance algorithm be averaged
Value.
Same method, Df ' are to carry out interpolation meter to the Df of each current data in its search range on the basis of current data I '
It is obtaining as a result, the interpolation formula are as follows:
In above formula, n is the quantity of current data in search range on the basis of current data I '；Dit ' is this range
The distance between interior a certain current data and current data I '；Df " is the Df and electric current of a certain current data itself within the scope of this
The difference of the Df of data I '；The meaning of Ag_dit ' is same as above.
Correcting current data are W=PI+Df '.
The voltage data that above-mentioned method obtains correction also can be used.Essence is obtained using unique eight quadrants interpolation method
Really, whether stable electric current and voltage data are in normal according to above-mentioned accurate data judging smart machine and its power supply
Use state or abnormality are convenient for subsequent processing.
In order to improve the operation convenience of smart machine, in addition to manual control switch, can also be arranged a wireless control module with
Double-core CPU is connected with each other, and wireless control module send information to the smart phone of distal end by WIFI module, receives smart phone
The operation signal of feedback simultaneously sends back wireless control module, is further processed by double-core CPU according to the operation signal.It can
Selectively, smart phone is the first priority, i.e. the manual operation of wireless remote is preferred operations.
The smart machine further includes electricity consumption statistic device, to count the electricity consumption system of the smart machine different periods
Meter, consequently facilitating it is clear, and then adjust and guarantee the operating time of the smart machine.
Electricity consumption statistic device includes returning processing module and energy consumption section module；By taking electric quantity monitor as an example, wherein
It returns processing module and the load energy consumption data and creation data that read out in electric quantity monitor database is converted into machines for regression
The pretreatment of the training data of type, utilizing is regression function f (x) in regression model；Energy consumption section module is used for basis
Estimating Confidence Interval method analyzes the historical energy consumption data in electric quantity monitor database, gives confidence level 1- α, obtains
The normal interval of energy consumption prediction.
The pretreatment is will to load energy consumption data and creation data is converted to the training data of regression model, i.e., according to
The time of acquisition will load energy consumption data { f (x1), f (x2) ..., f (xn) and corresponding creation data { x1, x2..., xn}
As one group of data < f (xi), xi>, i=1,2 ..., n are quasi- for training regression function f (x)=wx+b, w and b respectively
The hyperplane parameter of training data is closed, training process is by way of solving equation, with multi-group data < f (xi), xi>, i=
The process of 1,2 ..., n calculating hyperplane parameter w and b；
X1, X2 ... Xn obeys sample distribution (μ, σ2),And S2The sample average and sample variance of prediction power consumption are respectively indicated,
Then stochastic variableFor given confidence level 1- α,
Wherein P indicates probability, then predicts that the confidence interval of the mean μ of power consumption is
In short, the smart machine of the present embodiment can realize human-computer interaction, power supply selects the intelligent power of specific circuit design,
There is no switching losses, loss is low, and power density is high, improves the working life and reliability of smart machine and its power supply；Using
Unique eight quadrants interpolation method obtains accurate, stable electric current and voltage data, is convenient for subsequent processing.
Embodiment 2
On the basis of the present embodiment 1, the present embodiment 2 provides a kind of distribution line monitoring system based on Cloud Server
System, comprising: Cloud Server, monitor terminal and the monitoring device for being separately positioned on each section circuit monitoring point of power distribution network；Wherein institute
Stating monitoring device includes: control module, the data acquisition module and communication module being connected with the control module；The data acquisition
Module is suitable for collected data information being transmitted to Cloud Server by communication module；And the Cloud Server is suitable for storage
Data information, and data information is sent to monitor terminal.
Specifically, the working principle of the distribution line monitoring system described in the present embodiment based on Cloud Server, work side
Method and the course of work are identical as the distribution line monitoring system based on Cloud Server in embodiment 1, and details are not described herein again.
The above content is a further detailed description of the present invention in conjunction with specific preferred embodiments, and it cannot be said that
Specific implementation of the invention is only limited to these instructions.For those of ordinary skill in the art to which the present invention belongs, exist
Under the premise of not departing from present inventive concept, a number of simple deductions or replacements can also be made, all shall be regarded as belonging to of the invention
Protection scope.
Claims (10)
1. a kind of distribution line monitoring system based on Cloud Server characterized by comprising
Cloud Server, monitor terminal and the monitoring device for being separately positioned on each section circuit monitoring point of power distribution network；Wherein
The monitoring device includes: control module, the data acquisition module and communication module being connected with the control module；
The data acquisition module is suitable for collected data information being transmitted to Cloud Server by communication module；And
The Cloud Server is suitable for storing data information, and data information is sent to monitor terminal.
2. the distribution line monitoring system according to claim 1 based on Cloud Server, which is characterized in that
The data acquisition module includes: power supply line's data acquisition module and switch data acquisition module；
Power supply line's data acquisition module is used to acquire the voltage and current signals of power supply line, and
The switch data acquisition module is used to acquire the acting characteristic of switch and the temperature signal of contact.
3. the distribution line monitoring system according to claim 2 based on Cloud Server, which is characterized in that
The monitor terminal includes smart machine；
The smart machine includes:
Front-end processing unit, for being pre-processed to the voice signal of input；
Voice signal output circuit；
Double-core CPU, for handling the voice signal of input and output；
ARM microprocessor works for manipulating smart machine according to user instruction；And
Intelligent power is connected with double-core CPU, and powers to multiple functional modules.
4. the distribution line monitoring system according to claim 3 based on Cloud Server, which is characterized in that the intelligence electricity
Source includes:
Input voltage+VC~-VC, left inductance group and right inductance group all have the transformer T1 of intermediate magnetic core, transformer T2, transformation
Device T3, switch element S1, switch element S2, diode D1, diode D2, diode D3, diode D4, diode D5, two poles
Pipe D6, diode D7, diode D8, compensation diode Ds1, compensation diode Ds2, compensation diode Ds3, capacitor C1, capacitor
C2, compensating electric capacity Cs1, compensating electric capacity Cs2, feedback capacitor CB；Wherein
Transformer T1 is the right inductance group Lsc1 that left side is equipped with intermediate magnetic core；
Transformer T2 is the right inductance group Lsc2 that left side is equipped with intermediate magnetic core；
Transformer T3 is that left side is equipped with the right inductance group Lsc3 of intermediate magnetic core and with right inductance group Lsc3 at the upper left inductance of image
Group, lower-left inductance group；
The collector of the end input voltage+VC connection switch element S1；The collector of its end-VC connection switch element S2；
The end input voltage+VC is also respectively connected with the cathode of diode D1, the cathode of compensating electric capacity Cs1, the anode of diode D2, two
The cathode of pole pipe D8, diode D6；
The end input voltage-VC is also respectively connected with feedback resistors R1, the anode of diode D2, compensating electric capacity Cs2, capacitor C1, capacitor
The anode of C2, diode D7；
The cathode for compensating diode Ds1, the cathode for compensating diode Ds3 are connected with the anode of diode D1；
The anode of compensation diode Ds1 is connected with the anode of right inductance group Lsc3；
The anode of compensation diode Ds3 is connected with the anode of right inductance group Lsc1；
The anode of diode D6 is connected with the anode of right inductance group Lsc2；
The opposite end of the collector of switch element S1 is connected with the secondary end of upper left inductance group；
The opposite end of the collector of switch element S2 is connected with the anode of lower-left inductance group；
The tie point of upper left inductance group and lower-left inductance group is connected with one end of feedback capacitor CB；
The other end of feedback capacitor CB is connected with feedback resistors R1；
The opposite end of the collector of switch element S2 also pass through connection compensation diode Ds2 anode respectively with right inductance group Lsc3
Secondary end be connected with compensating electric capacity Cs2；
The cathode of diode D5 is connected with the secondary end of right inductance group Lsc1；And
The cathode of diode D2 also pass through connection diode D3 anode respectively with the secondary end of right inductance group Lsc2 and capacitor C2 phase
Connection.
5. the distribution line monitoring system according to claim 3 based on Cloud Server, which is characterized in that
The front-end processing unit includes:
Sample circuit, signal amplification circuit, shaping circuit, filter circuit and A/D converter；Wherein
One microphone is successively through over-sampling circuit, signal amplification circuit, shaping circuit, filter circuit and A/D converter and double-core
The input terminal of CPU connects；
The input terminal of the double-core CPU is also connected to respectively for double-core CPU and ARM microprocessor to be carried out two-way communication
RS232 serial communication interface, memory and the intelligent power for stored voice message；
The voice signal output circuit includes: voice playing circuit module and power amplification circuit module；
The output end of the double-core CPU passes sequentially through voice playing circuit module and power amplification circuit module and a loudspeaker phase
It connects；And
The output end of the ARM microprocessor is connected by drive module with execution unit.
6. according to the described in any item distribution line monitoring systems based on Cloud Server of claim 3~5, which is characterized in that
The intelligent power further includes voltage correction module and current correction module；Wherein
Voltage correction module and current correction module are all made of eight quadrant interpolation methods and are corrected；
The smart machine further includes a wireless control module being connected with double-core CPU；
Wireless control module send information to the smart phone of distal end by WIFI module, receives the operation letter of smart phone feedback
Number and send back wireless control module, be further processed by double-core CPU according to the operation signal；And
The smart phone is the first priority.
7. the distribution line monitoring system according to claim 6 based on Cloud Server, which is characterized in that
Following step is used to eight quadrant interpolation methods of current data correction:
Step S1 selects any one current data I from the data acquired in certain period of time, using its amplitude as the longitudinal axis, when
Between be horizontal axis, angularly divide eight quadrants, successively search nearest apart from current data I several data in each quadrant
Point searches radius and is initially first threshold, if the current data number that can be found in certain quadrant is less than 3, radius gradually increases
It is added to second threshold, maximum is no more than the 5th threshold value, forms a data set DS (st, qua, stx, dit), wherein st is electricity
Flow data I, qua are quadrant numbers, and stx is consecutive number strong point number, and dit is the distance of stx distance st；
Each current data parameters are calculated in DS from the measurement time in past half a minute, in 1 minute, 1 minute half
Variation difference Df (st, stx, elem, t, dt) interior, in 2 minutes, wherein dt refers to above-mentioned time interval；
Using quadrant as grouping unit, each variation difference Df (st, stx, elem, t, dt) distance electricity is calculated using interpolation algorithm
The interpolation PI (st, qua, stx, elem, t, dt) of flow data I；
The element value for belonging to suspicious (50 Ar≤90 <) or wrong (Ar≤50) for confidence level Ar, is not involved in interpolation calculation；
The eight quadrant interpolation algorithm formula that this step uses are as follows:
In above formula, m is the quantity of current data in a certain quadrant qua in data set DS；Dit is a certain current data I ' in qua
The distance between current data I；Ag_dit be in qua all current datas to current data I distance arithmetic mean of instantaneous value；
Ag_dit ' is that (with current data I ' for the center of circle, first threshold is radius, searches for institute within the scope of this on the basis of current data I '
Some current datas, if the current data quantity searched is less than 3, radius gradually increases to second threshold, most very much not surpasses
Cross the 5th threshold value), within the scope of this all current datas to current data I ' distance algorithm average value；
Step S2, with step S1, Df ' be on the basis of current data I ', to the Df of each current data in its search range into
It is that row interpolation is calculated as a result, the interpolation formula are as follows:
In above formula, n is the quantity of current data in search range on the basis of current data I '；Dit ' is certain within the scope of this
The distance between one current data and current data I '；Df ' ' is the Df and current data of a certain current data itself within the scope of this
The difference of the Df of I '；The meaning of Ag_dit ' is same as above；And
Step S3, correcting current data are W=PI+Df '.
8. the distribution line monitoring system according to claim 6 based on Cloud Server, which is characterized in that
The smart machine further include: electricity consumption statistic device；
The electricity consumption statistic device includes: to return processing module and energy consumption section module；Wherein
The load energy consumption data and creation data that the recurrence processing module will be read out in electric quantity monitor database are converted to
The training data of regression model, and training data is pre-processed using the regression function f (x) in regression model；With
And
Energy consumption section module is used for according to Estimating Confidence Interval method to the history energy consumption number in electric quantity monitor database
According to being analyzed, confidence level 1- α is given, obtains the normal interval of energy consumption prediction.
9. the distribution line monitoring system according to claim 8 based on Cloud Server, which is characterized in that
The pretreatment is will to load energy consumption data and creation data is converted to the training data of regression model, i.e., according to acquisition
Time, will load energy consumption data { f (x1), f (x2) ..., f (xn) and corresponding creation data { x1, x2..., xnConduct
One group of data < f (xi), xi>, i=1,2 ..., n are fitting instructions for training regression function f (x)=wx+b, w and b respectively
Practice the hyperplane parameter of data, training process is by way of solving equation, with multi-group data < f (xi), xi>, i=1,
The process of 2 ..., n calculating hyperplane parameter w and b；
X1, X2 ... Xn obeys sample distribution (μ, σ2),And S2The sample average and sample variance of prediction power consumption are respectively indicated,
Then stochastic variable
For given confidence level 1- α,Wherein P indicates probability, then predicts power consumption
The confidence interval of the mean μ of amount is
10. a kind of working method of the distribution line monitoring system based on Cloud Server characterized by comprising
Cloud Server, monitor terminal and the monitoring device for being separately positioned on each section circuit monitoring point of power distribution network；Wherein
The monitoring device includes: control module, the data acquisition module and communication module being connected with the control module；
The data acquisition module is suitable for collected data information being transmitted to Cloud Server by communication module；And
The Cloud Server is suitable for storing data information, and data information is sent to monitor terminal.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110048507A (en) * | 2019-03-29 | 2019-07-23 | 国网山东省电力公司邹城市供电公司 | A kind of automatic detecting method and system of electrical power distribution automatization system |
| CN111864904A (en) * | 2020-07-27 | 2020-10-30 | 张琴光 | Power distribution monitoring terminal |
| CN112653141A (en) * | 2020-12-18 | 2021-04-13 | 国网冀北综合能源服务有限公司 | Bidirectional interactive power distribution side electric energy response system and control method thereof |
-
2018
- 2018-09-30 CN CN201811165370.5A patent/CN109067002A/en not_active Withdrawn
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110048507A (en) * | 2019-03-29 | 2019-07-23 | 国网山东省电力公司邹城市供电公司 | A kind of automatic detecting method and system of electrical power distribution automatization system |
| CN110048507B (en) * | 2019-03-29 | 2023-04-11 | 国网山东省电力公司邹城市供电公司 | Automatic inspection method and system for power distribution automation system |
| CN111864904A (en) * | 2020-07-27 | 2020-10-30 | 张琴光 | Power distribution monitoring terminal |
| CN112653141A (en) * | 2020-12-18 | 2021-04-13 | 国网冀北综合能源服务有限公司 | Bidirectional interactive power distribution side electric energy response system and control method thereof |
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Application publication date: 20181221 |