CN106154082A - A kind of intelligent measure harvester of part throttle characteristics on-line analysis - Google Patents
A kind of intelligent measure harvester of part throttle characteristics on-line analysis Download PDFInfo
- Publication number
- CN106154082A CN106154082A CN201610447063.0A CN201610447063A CN106154082A CN 106154082 A CN106154082 A CN 106154082A CN 201610447063 A CN201610447063 A CN 201610447063A CN 106154082 A CN106154082 A CN 106154082A
- Authority
- CN
- China
- Prior art keywords
- load
- data
- power
- flush bonding
- bonding processor
- 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
Classifications
-
- 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
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The embodiment of the invention discloses the intelligent measure harvester of a kind of part throttle characteristics on-line analysis, including: analog-digital converter, digital signal processing circuit and flush bonding processor；The outfan of analog-digital converter is connected with the input of digital signal processing circuit, and the outfan of digital signal processing circuit is connected with flush bonding processor；Analog-digital converter is used for gathering analog sampling signal, analog sampling signal is converted to digital sampled signal, and transmits digital sampled signal to digital signal processing circuit；Digital signal processing circuit is for determining online information on load according to digital sampled signal；Flush bonding processor is for determining load model parameters according to online information on load, and carries out Load Characteristic Analysis according to load model parameters.This intelligent measure harvester can carry out statistical analysis, the load condition of real-time exhibition power load equipment online to power load equipment, facilitates user's monitoring to line load.
Description
Technical field
The present invention relates to Load Characteristic Analysis technical field, particularly to the intelligent measure of a kind of part throttle characteristics on-line analysis
Harvester.
Background technology
The mathematical model of each element of power system is the basis that electric system simulation calculates, about sending out in electric system simulation
Motor, excitation system, governing system, transformator, the detail mathematic model of transmission line of electricity and modeling technique have been obtained for very well
Development.But for a long time, as the load of one of power system critical elements, due to its complexity, distributivity, time variation
And the factor such as randomness, determine the difficulty of its Mathematical Models.
The power that load cell absorbs in power system is as load side voltage and the change of frequency and changes.Work as electricity
After Force system generation disturbance, the dynamic characteristic of system voltage and the change of frequency and load self determines what load was absorbed
Active power and the size of reactive power.But, in most cases these changes are extremely complex and are difficult to use mathematical model
Accurately describe, therefore in actual engineer applied and systematic analysis, generally ideally load model is processed as constant-resistance
Anti-(Z), the static models that constant current (I) and invariable power (P) are constituted, or use constant-impedance and the dynamic of induction conductivity composition to bear
Lotus model.But these models are not enough to describe the overall characteristic of load under many circumstances, draw sometimes and differ with reality
The most remote simulation result.
System load characteristic real-time analyzer of standing is to be filled by the intelligent measure collection being arranged on 110kV transformer station outgoing line side
Put and be deployed in the station system load characteristic on-line analysis platform composition of 220kV (330kV) transformer station.System load characteristic of standing is real
Time analysis platform integrated application multiple load model on-line identification method, on-line identification can accurately reflect the load mould of part throttle characteristics
Type and model parameter, realize the on-line amending of load model parameters simultaneously.Intelligent measure harvester mainly realizes 110kV power transformation
Standing the online acquisition, locally stored of outgoing line side electric load, and carry out the preliminary identification of model and upload with data, it is that station system is born
Visual plant in lotus characteristic on-line analysis system, its major function is the instantaneous flow data gathering power circuit, including three
The data such as phase voltage, three-phase current, active power, reactive power, power factor, simultaneously to the power load equipment on circuit
Power load carries out statistical computation analysis, draws the composition of this load point each moment various power load equipment, further according to dynamically
Simulation test or representative value determine the part throttle characteristics parameter of each power load equipment, calculate constant-impedance during static load is constituted,
Constant current, the ratio of invariable power, be finally uploaded to system main website by the data summarization obtained, by using after main website cohersive and integrated data
The many algorithms such as static load is equivalent, dynamic load is equivalent, distribution network is equivalent carry out load modeling.
Energy data in early days measures the many employings of harvester 8,16 single-chip microcomputers as hardware platform, function ratio
Relatively simple, the data volume of storage is little.Current existing technical scheme is mainly by load model information management subsystem and load
Model building device forms, and wherein load management subsystem includes server, record ripple client, load modeling client and safeguards client
End, load modeling device includes failure wave-recording subsystem, load model parameters identification subsystem and load data acquisition platform.
Its major function is: gathers data by load data acquisition platform, then sends data to failure wave-recording by Ethernet
Subsystem and load model parameters identification subsystem, load model parameters identification subsystem carries out pretreatment to gathering data, bears
Lotus modeling and parameter identification, finally transfer data to load model information management subsystem.The shortcoming of this technical scheme is: negative
Lotus model building device composition is more complicated, is unfavorable for that extensive in-site installation uses, and this device lacks whole collection point simultaneously
Power load data are analyzed, and user cannot understand the percentage ratio of total amount shared by every kind of power load equipment.
In realizing process of the present invention, inventor finds that in prior art, at least there are the following problems:
The most existing electrical energy data acquiring protocol collection period is the shortest 1 minute, it is impossible to meet load on-line analysis at a high speed
The requirement gathered.
2. lack the function that analysis of power consumption load calculates.
3. lack the function of power load statistics.
Summary of the invention
It is an object of the invention to provide the intelligent measure harvester of a kind of part throttle characteristics on-line analysis, thus overcome existing
There is the harvester can not high speed acquisition the defect of on-line analysis.
The intelligent measure harvester of a kind of part throttle characteristics on-line analysis that the embodiment of the present invention provides, including: modulus turns
Parallel operation, digital signal processing circuit and flush bonding processor；The outfan of analog-digital converter is defeated with digital signal processing circuit
Enter end to be connected, and the outfan of digital signal processing circuit is connected with flush bonding processor；
Analog-digital converter is used for gathering analog sampling signal, and analog sampling signal is converted to digital sampled signal, and will
Digital sampled signal is transmitted to digital signal processing circuit；
Digital signal processing circuit is for determining online information on load, online information on load bag according to digital sampled signal
Include: one or more in magnitude of voltage, current value, mains frequency, active power, reactive power, merit angle；
Flush bonding processor is for determining load model parameters according to online information on load, and enters according to load model parameters
Row Load Characteristic Analysis.
In a kind of possible implementation, also include: memorizer；
Memorizer is connected with flush bonding processor, is used for storing database information, and database information includes that digital sample is believed
Number, one or more in online information on load and load model parameters.
In a kind of possible implementation, flush bonding processor is provided with data access interface；
When data access interface receives data access request, access according to the process ID that data access request is corresponding
Database information, and backward reference result.
In a kind of possible implementation, flush bonding processor is additionally operable to database information is carried out data pick-up；Logical
Cross Data Integration and set up the mapping relations of the association between variety classes database information and inter-system data, form data warehouse；
And data warehouse is carried out data integration, form cube metadata information.
In a kind of possible implementation, flush bonding processor specifically for: determine believing at specific electric load of online collection
Breath, arranged by offline user investigation and analysis simultaneously obtain various typical outlets the power load equipment ratio of confession, according to
Online information on load and the composition of power load equipment ratio-dependent load bus each moment various electrical equipment；According to dynamic analog
Plan test or representative value determine the part throttle characteristics parameter of various power load equipment, utilize static load equivalence method to calculate static state
The ratio of constant-impedance, constant current, invariable power in load structure, and then determine load model parameters online.
In a kind of possible implementation, according to online information on load and power load equipment ratio-dependent load bus
The composition of various electrical equipment of each moment, including:
Off-line carries out user's sampling survey, each load type transformer station chooses some typical 10kV or 6kV outlets and enters
Row load characteristics investigation, analysis and arrangement obtains the electrical equipment of 10kV or the 6kV outlet of each load type and constitutes situation: include using
Electricity device type i and each electrical equipment proportion ρi；Load type includes: industrial load type, Commercial Load type, resident
Load type or agricultural load type；
The voltage V of online acquisition 110kV/35kV every 10kV outlet circuit jj, electric current Ij, power factor PFj, calculating obtains
Obtain this circuit 10kV side outlet power Pj=VjIjPFj；
By the jth sampling survey 10kV in the i-th type load including industry class, commercial, resident's class, agriculture or
6kV outlet institute electricity supply and use equipment constitutes situation, popularization and application to other 10kV or 6kV outlets, and statistics draws this period all kinds of use
The general power of electricity equipment, divided by the general power of this period whole load bus, can obtain this period whole 220kV transformer station each
Ratio k of class electrical equipment ii:If this transformer station a total of n bar 10kV or 6kV outlet.
In a kind of possible implementation, also including: communication module, communication module is connected with flush bonding processor；
Communication module for communicating with host computer, receive control instruction that host computer sends or by information on load and/
Or load model parameters is uploaded to host computer.
In a kind of possible implementation, also including: touch screen, touch screen is connected with flush bonding processor；
Touch screen is for showing corresponding information on load according to the instruction of user's input.
In a kind of possible implementation, also including: keypad, keypad is connected with flush bonding processor；Keypad
For receiving the operational order of user's input.
The intelligent measure harvester of a kind of part throttle characteristics on-line analysis that the embodiment of the present invention provides, can online at a high speed
Gather analogue signal, close the border the signal according to collecting and determine online information on load online, the most permissible by flush bonding processor
Online information on load is processed, and determines load model parameters, without the process by host computer.It is determined by bearing
The composition of lotus node each moment various electrical equipment, and the part throttle characteristics parameter of true various power load equipment, and then can be
Line determines load model parameters, and power load equipment i.e. can carry out statistical analysis, the symbol of real-time exhibition power load equipment
Conjunction state.The data that intelligent measure harvester can be collected by big data processing module carry out initial processing, from different
Data are analyzed by dimension, provide big data support for load management department, provide reference proposition for spatial load forecasting decision-making.Logical
Data in data base are extracted, change, are processed to form data warehouse by the technology that excessive data process, and data content is contained
The whole service cycle, and then the data analysis rationalized can be carried out, finally give close to actual load model.Pass through data
Database management module is managed improving data storage efficiency to mass data, improves data access speed.
The intelligent measure harvester of a kind of part throttle characteristics on-line analysis that the embodiment of the present invention provides, by data acquisition,
The functions such as data process, load Analysis, load modeling, load parameter correction are integrated among a station terminal, except facilitating user
Outside safeguarding and using, additionally it is possible to the percentage ratio that various for load collection point power load equipment account for total amount is presented to use in real time
Family, facilitates user's monitoring to line load.
Other features and advantages of the present invention will illustrate in the following description, and, partly become from description
Obtain it is clear that or understand by implementing the present invention.The purpose of the present invention and other advantages can be by the explanations write
Structure specifically noted in book, claims and accompanying drawing realizes and obtains.
Accompanying drawing explanation
Accompanying drawing is for providing a further understanding of the present invention, and constitutes a part for description, with the reality of the present invention
Execute example together for explaining the present invention, be not intended that limitation of the present invention.In the accompanying drawings:
Fig. 1 is the first structure chart of the intelligent measure harvester of part throttle characteristics on-line analysis in the embodiment of the present invention；
Fig. 2 is the second structure chart of the intelligent measure harvester of part throttle characteristics on-line analysis in the embodiment of the present invention；
Fig. 3 is the structured flowchart of big data processing module in the embodiment of the present invention；
Fig. 4 is the structural representation of flush bonding processor in the embodiment of the present invention.
Detailed description of the invention
Below in conjunction with the accompanying drawings, the detailed description of the invention of the present invention is described in detail, it is to be understood that the guarantor of the present invention
Scope of protecting is not limited by detailed description of the invention.
For making the purpose of the embodiment of the present invention, technical scheme and advantage clearer, below in conjunction with the embodiment of the present invention
In accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is
The a part of embodiment of the present invention rather than whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art
The every other embodiment obtained under not making creative work premise, broadly falls into the scope of protection of the invention.Unless
Separately have other to explicitly indicate that, otherwise in entire disclosure and claims, term " include " or its conversion such as " comprising " or
" include " etc. and will be understood to comprise stated element or ingredient, and do not get rid of other element or other composition
Part.
The most special word " exemplary " means " as example, embodiment or illustrative ".Here as " exemplary "
Illustrated any embodiment should not necessarily be construed as preferred or advantageous over other embodiments.
It addition, in order to better illustrate the present invention, detailed description of the invention below gives numerous details.
It will be appreciated by those skilled in the art that do not have some detail, the present invention equally implements.In some instances, for
Method well known to those skilled in the art, means, element are not described in detail, in order to highlight the purport of the present invention.
Explicitly indicating that unless otherwise other, otherwise in entire disclosure and claims, term " includes " or it becomes
Change and such as " comprising " or " including " etc. will be understood to comprise stated element or ingredient, and do not get rid of other yuan
Part or other ingredient.
According to embodiments of the present invention, it is provided that the intelligent measure harvester of a kind of part throttle characteristics on-line analysis, Fig. 1 is for being somebody's turn to do
The structure chart of device, specifically includes: analog-digital converter 10, digital signal processing circuit 20 and flush bonding processor 30；Wherein, mould
The outfan of number converter 10 is connected with the input of digital signal processing circuit 20, and the output of digital signal processing circuit 20
End is connected with flush bonding processor 30.
Analog-digital converter 10 is used for gathering analog sampling signal, and analog sampling signal is converted to digital sample letter simultaneously
Number, and digital sampled signal is transmitted to digital signal processing circuit 20.Concrete, in the embodiment of the present invention, analog-digital converter
10 are used for high speed acquisition analog sampling signal, and frequency to reach 50 times per second, and i.e. every 20ms gathers once, in order to improve measurement essence
Degree, the sampling section of intelligent measure acquisition terminal can use 24 ADC (analog-digital converter) to adopt analog sampling signal
Sample.
Digital signal processing circuit 20 is used for determining online information on load according to digital sampled signal, this online information on load
Including: one or more in magnitude of voltage, current value, mains frequency, active power, reactive power, merit angle.Due to can be direct
The analog sampling signal measured only has voltage and the magnitude of current, therefore in the embodiment of the present invention enters the digital sampled signal after sampling
Row high-speed dsp (Digital Signal Processing, Digital Signal Processing) calculates in real time and obtains other various instantaneous flows,
Such as active power, reactive power, merit angle etc., finally determine this online information on load.
Flush bonding processor 30 is used for determining load model parameters according to online information on load, and according to load model parameters
Carry out Load Characteristic Analysis.
Concrete, flush bonding processor 30 is used for: determines the online information on load of online collection, passes through offline user simultaneously
Investigation and analysis arrange obtain various typical outlets the power load equipment ratio of confession, bear according to online information on load and electricity consumption
The composition of lotus equipment ratio-dependent load bus each moment various electrical equipment, hundred of total amount shared by i.e. every kind power load equipment
Proportion by subtraction；Determine the part throttle characteristics parameter of various power load equipment according to dynamic analog test or representative value, utilize static load
Equivalence method calculates constant-impedance, constant current, the ratio of invariable power during static load is constituted, and then determines that load model is joined online
Number.
In the embodiment of the present invention, load type includes: industrial load type, Commercial Load type, resident load type or
Agricultural load type；Corresponding power load equipment is also classified into industry class, commercial, resident's class and agriculture etc..Power system
The energy production that is made up of power plant, power transmission network and electric load three parts, transmit and use system.Power plant is electricity
The person of sending of energy, these electric energy are sent to each user through grid and low-voltage network, and are arranged at user
Electrical equipment consumed.Electric load is exactly the general name of these electrical equipments, the most also includes distribution network, and is called for short
For load.Power system has load miscellaneous, from the point of view of electricity consumption main body, industrial load, city can be divided into civilian negative
Lotus, Commercial Load, agricultural load and other loads.City appliance load is mainly the household electrical appliance load of urbanite, business
It is the load for business Yu industrial service with industrial load.Agricultural load is the general name of all loads in rural area, civilian including rural area
Electricity, production and irrigation and drainage electricity consumption and rural commerce electricity consumption etc..Other loads include municipal administration electricity consumption, public utilities electricity consumption, government
Electricity consumption, railway and electric car electricity consumption etc..
Owing to power load equipment ratio cannot gather the acquisition of 10kV or 6kV outlet data by measuring, therefore load is special
Property on-line analysis realization first have to by offline user investigation and analysis arrange obtain various typical 10kV or 6kV outlets supplied
Power load equipment ratio and determine the part throttle characteristics of various power load equipment according to dynamic analog test or representative value
Parameter, is issued to intelligent measure harvester or by the manual method arranged to intelligent measure as parameter by main website
Harvester carries out parameter setting；Then utilize intelligent measure harvester collection load bus every 10kV to be studied or
The online actual power data (i.e. online information on load) of 6kV outlet；Various by the power data collected and collected offline
Typical 10kV or 6kV outlet the power load equipment scale parameter data of confession carry out COMPREHENSIVE CALCULATING, show that this load point is each
The composition of moment various power load equipment, the percentage ratio of total amount shared by i.e. every kind power load equipment；Bear further according to each electricity consumption
The part throttle characteristics parameter of lotus equipment, utilizes static load equivalence method to calculate constant-impedance during static load is constituted, constant current, permanent merit
The ratio of rate, reaches the purpose of load modeling.
Wherein, active power and the reactive power of load absorption is as load busbar voltage and the change of frequency and changes
, here it is the voltage of load, frequency characteristic.It is referred to as load model for describing the math equation of part throttle characteristics.Set up load
Model seeks to determine the form of the math equation describing part throttle characteristics and parameter therein, is called for short load modeling.
The intelligent measure harvester of a kind of part throttle characteristics on-line analysis that the embodiment of the present invention provides, can be with high speed acquisition
Analogue signal, closes the border and determines online information on load online according to the signal that collects, by flush bonding processor i.e. can to
Specific electric load information processes, and determines load model parameters, without the process by host computer.It is determined by load joint
The composition of point various electrical equipment of each moment, and the part throttle characteristics parameter of true various power load equipment, and then can be the most true
Constant load model parameter, i.e. can carry out statistical analysis to power load equipment, real-time exhibition power load equipment meet shape
State.
Preferably, the step of above-mentioned load Analysis is specific as follows:
Step A1, determine the part throttle characteristics parameter of each electrical equipment according to dynamic analog test or representative value；
Step A2, user side power information data according to load control system collection determine 220kV transformer station and subordinate
The load structure situation of 110kV and 35kV transformer station；
Step A3, load structure situation according to each load bus, determine each load bus the load type of confession；
Step A4, off-line carry out user's sampling survey, and each load type transformer station is chosen some typical 10kV or 6kV
Outlet carries out load characteristics investigation, and analysis and arrangement obtains each load type: include industry, business, resident or agricultural load type
10kV or 6kV outlet electrical equipment constitute situation: include electrical equipment type i and each electrical equipment proportion ρi；
Step A5, the voltage V of online acquisition 110kV/35kV every 10kV outlet circuit jj, electric current Ij, power factor PFj,
Calculate and obtain this circuit 10kV side outlet power Pj=VjIjPFj；
Step A6, for including that the jth sampling in the i-th type load of industry class, commercial, resident's class, agriculture is adjusted
Looking into 10kV outlet institute electricity supply and use equipment and constitute situation, it promotes the use of similar 10kV outlet, statistics show that this period is each
The general power of class electrical equipment, divided by the general power of this period whole load bus, can obtain the power transformation of this period whole 220kV
Ratio ki of all kinds of electrical equipment i of standing:If this transformer station a total of n bar 10kV or 6kV outlet；
Step A7, part throttle characteristics parameter according to each electrical equipment, utilize static load equivalence method, calculates static load
Model parameter.
Wherein, static load model structure is to be polynomial equation form by the relationship description between load power and voltage
Multinomial load model (Polynomial Load Model), the general type of this model is as shown in formula 1 and formula 2:
P=Po[a×(V/Vo)2+b×(V/Vo)+c] (formula 1)
Q=Qo[α×(V/Vo)2+β×(V/Vo)+γ] (formula 2)
Multinomial active power load model coefficient is a, b, c, and reactive power load model coefficient is α, β, γ and load
Power factor (PF), this load model is referred to as " ZIP " model, because it contains constant-impedance (Z), constant current (I) and invariable power
(P), this model is used for describing specific load equipment or load cell, VoRepresent the rated voltage of load, PoAnd QoThen distinguish table
Show in rated voltage VoThe specified active power of lower load and reactive power, if describing the synthetic load of bus with this model
Time, Vo、PoAnd QoIt is conventionally used to indicate the numerical value under system initial launch operating mode；
The equivalence of static load is mainly FACTOR Po, a, b, c and Qo, the equivalence of α, β, γ, to multinomial load model
Equivalence be based on the load power sensitivity to load side voltage, i.e.
P1, P2…PnAnd Q1, Q2…QnFor active power and the reactive power of each static load, according to all kinds of electrical equipments
Ratio ki of i may determine that.Corresponding multinomial load model coefficient is respectively Po1…Pon、a1…an、b1…bn、c1…cnWith
And Qo1…Qon、α1…αn、β1…βn、γ1…γn.Have as V=Vo:
After determining load model parameters, i.e. may determine that the load model in formula 1 and formula 2, and then load can be carried out
Analyze.
Preferably, shown in Figure 2, this device also includes: memorizer 40；Memorizer 40 and flush bonding processor 30 phase
Even, being used for storing database information, this database information specifically includes digital sampled signal, online information on load and load model
One or more in parameter.
The intelligent measure harvester of the part throttle characteristics on-line analysis that the embodiment of the present invention provides also uses big data technique
Data are stored and processes.Wherein, flush bonding processor 30 is additionally operable to database information is carried out data pick-up；By number
According to integrating the mapping relations setting up the association between variety classes database information and inter-system data, form data warehouse；And it is right
Data warehouse carries out data integration, forms cube metadata information.
Concrete, flush bonding processor 30 is provided with the big data processing module processing big data, its overall frame
Frame is as it is shown on figure 3, data source reaches data through data pick-up, Data Integration, data integration and four steps of market demand
The purpose represented.Data source includes various supplemental characteristic, various data dictionary, real time data, historical data, system data, thing
Number of packages evidence, other data etc..Data pick-up obtains data by the way of cleaning, changing from data source, then passes through data
Integrate and set up the association between variety classes data and inter-system data mapping relations, form data warehouse, then with data warehouse
Data, for relying on, are organized data to form information cube centered by business-subject and are completed data integration, finally stand with information
Based on cube, provide data display to upper strata.Intelligent measure can be adopted by the biggest data processing module
The data that acquisition means collects carry out initial processing, are analyzed data from different dimensions, provide for load management department
Big data support, provides reference proposition for spatial load forecasting decision-making.
In the embodiment of the present invention, big data processing module is the process that a background is run, can be according to regular time
Interval is activated, it is also possible to is triggered by external condition and activates.Data in data base can extract, clear up by it, follow-up add
Work, collecting and arrange formation data warehouse, the data in data warehouse are mainly used to carry out decision analysis, involved data behaviour
Make mainly data query, after once certain data enters data warehouse, generally will be retained for a long time, namely count
According to typically there being substantial amounts of inquiry operation in warehouse, but amendment and deletion action are little, generally have only to regularly load, refresh.
And data generally comprise historical information, system have recorded from past a certain time point (as started to apply the time point of data warehouse) to
The information in each current stage, by these information, can make quantitative analysis to the operation course of system and future trend
And prediction.Analysis result is saved in data warehouse, if system needs to use these analytical data by big data processing module
Can be obtained by big data processing module.
Preferably, flush bonding processor 30 is provided with data access interface；Receiving data access at data access interface please
When asking, access database information, and backward reference result according to the process ID that data access request is corresponding.
The structural representation of flush bonding processor 30 is shown in Figure 4, and flush bonding processor 30 uses built-in Linux to grasp
Make system.Built-in Linux operating system provides the scheduling between the distribution of process (or thread) resource and process (or thread)
Switching, encapsulates hardware driving simultaneously, provides base layer support for application program.The requirement of intelligent measure harvester possesses abundant
Hardware resource, requires higher to complete machine operational efficiency, uses 32 real time operating systems can carry out more perfect to hardware resource
Ground management, it is possible to be more efficiently completed software function exploitation.Flush bonding processor 30 is additionally provided with Embedded Application scheduler module；Should
Embedded Application scheduler module includes data acquisition process, uplink communication process, show process etc..Intelligent measure harvester needs
Complete to measure at a high speed acquisition tasks, uplink communication task, display task dispatching, operation effect can be improved by multi-process operation
Rate, it is ensured that stable and reliable operation.
As shown in Figure 4, this flush bonding processor 30 also includes: Embedded Application process manager module, data base administration mould
Block, big data processing module, Embedded SQL ite3 data base.Concrete, Embedded Application process manager module be used for monitoring into
The duty of journey, thread and application module.Application process management module can be more efficient by the management of application processes
Ground monitoring each process, thread work state, timely respond to various event and corresponding subsequent treatment.
Database management module provides operation and maintenance to data base, and intelligent measure harvester needs to safeguard substantial amounts of
Data, use traditional document storage mode, are unfavorable for the management of data, are carried out mass data by database management module
Management can improve data storage efficiency, improves data access speed.
Big data processing module utilizes big data theory to extract the mass data in data base, change, analyze into
Row data mining forms data warehouse, and data content contains the whole service cycle, by data in the system whole service cycle
The trend of change is comprehensively analyzed and evaluates, and finally obtains closest to actual load model.
Embedded SQL ite3 data base is systems with data support, is all bases about data manipulation, and it has
Increase income, feature small and exquisite, efficient, take resource the lowest, be highly suitable for needing the embedded equipment of data base.
The application interface API of embedded database SQLite3 has been carried out again encapsulating by database management module, embedded
Database SQLite 3 uses c language development, possesses abundant interface function, if using embedded database SQLite3 completely
The interface function provided carries out database program developing, and on the one hand program code amount strengthens, on the other hand due to sometimes for many
Individual interface function combination be used together the function that just can complete to need in actual application, cause interface in-convenience in use.For this
The situation of kind, according to the functional requirement of database management module, is combined the api function of embedded database SQLite3, collects
Become, encapsulate, form the data base interface function being easy to use so that the api interface after encapsulation is more suitable for the present invention.It addition, it is logical
Cross database management module can be managed collectively from process, thread, the application module access request to data base.Data depositary management
The data of system are managed collectively by reason module as an independent process, relate to data in each process, thread
The operation accessed all carries out data access by a unified data access interface, and data access request is sent to by this interface
In database management module, database management module can correctly identify the process of request data after receiving data access request
(thread) ID, returns to corresponding process (thread) through database access operation by the result of data access, completes data and visits
The operation asked.
Preferably, shown in Figure 2, this device also includes: communication module 50, communication module and flush bonding processor 30 phase
Even；Communication module, for communicating with host computer, receives the control instruction of host computer transmission or by information on load and/or load
Model parameter is uploaded to host computer.Owing to part throttle characteristics on-line analysis is the highest to requirement of real-time, for the ease of safeguarding Intelligent testing
Amount acquisition terminal needs the function possessing remote upgrade and field upgrade, so intelligent measure acquisition terminal to use with main website
TCP/IP network communication, it is ensured that high speed data transfer can be carried out.
Preferably, shown in Figure 2, also include: touch screen 60, touch screen 60 is connected with flush bonding processor 30；Touch
Screen is for showing corresponding information on load according to the instruction of user's input.
Preferably, this device also includes: keypad 70, and keypad is connected with flush bonding processor 30；Keypad is used for connecing
Receive the operational order of user's input.
The intelligent measure harvester of a kind of part throttle characteristics on-line analysis that the embodiment of the present invention provides, can online at a high speed
Gather analogue signal, close the border the signal according to collecting and determine online information on load online, the most permissible by flush bonding processor
Online information on load is processed, and determines load model parameters, without the process by host computer.It is determined by bearing
The composition of lotus node each moment various electrical equipment, and the part throttle characteristics parameter of true various power load equipment, and then can be
Line determines load model parameters, and power load equipment i.e. can carry out statistical analysis, the symbol of real-time exhibition power load equipment
Conjunction state.The data that intelligent measure harvester can be collected by big data processing module carry out initial processing, from different
Data are analyzed by dimension, provide big data support for load management department, provide reference proposition for spatial load forecasting decision-making.Logical
Data in data base are extracted, change, are processed to form data warehouse by the technology that excessive data process, and data content is contained
The whole service cycle, and then the data analysis rationalized can be carried out, finally give close to actual load model.Pass through data
Database management module is managed improving data storage efficiency to mass data, improves data access speed.
The intelligent measure harvester of a kind of part throttle characteristics on-line analysis that the embodiment of the present invention provides, by data acquisition,
The functions such as data process, load Analysis, load modeling, load parameter correction are integrated among a station terminal, except facilitating user
Outside safeguarding and using, additionally it is possible to the percentage ratio that various for load collection point power load equipment account for total amount is presented to use in real time
Family, facilitates user's monitoring to line load.
Device embodiment described above is only schematically, and the wherein said unit illustrated as separating component can
To be or to may not be physically separate, the parts shown as unit can be or may not be physics list
Unit, i.e. may be located at a place, or can also be distributed on multiple NE.Can be selected it according to the actual needs
In some or all of module realize the purpose of the present embodiment scheme.Those of ordinary skill in the art are not paying creativeness
Work in the case of, be i.e. appreciated that and implement.
Through the above description of the embodiments, those skilled in the art it can be understood that to each embodiment can
The mode adding required general hardware platform by software realizes, naturally it is also possible to pass through hardware.Based on such understanding, on
State the part that prior art contributes by technical scheme the most in other words to embody with the form of software product, should
Computer software product can store in a computer-readable storage medium, such as ROM/RAM, magnetic disc, CD etc., including some fingers
Make with so that a computer equipment (can be personal computer, server, or the network equipment etc.) performs each and implements
The method described in some part of example or embodiment.
The aforementioned description to the specific illustrative embodiment of the present invention illustrates that and the purpose of illustration.These describe
It is not wishing to limit the invention to disclosed precise forms, and it will be apparent that according to above-mentioned teaching, can much change
And change.The purpose selected exemplary embodiment and describe is to explain that the certain principles of the present invention and reality thereof should
With so that those skilled in the art be capable of and utilize the present invention various different exemplary and
Various different selections and change.The scope of the present invention is intended to be limited by claims and equivalents thereof.
Claims (9)
1. the intelligent measure harvester of a part throttle characteristics on-line analysis, it is characterised in that including: analog-digital converter, numeral
Signal processing circuit and flush bonding processor；The outfan of described analog-digital converter and the input of described digital signal processing circuit
End is connected, and the outfan of described digital signal processing circuit is connected with described flush bonding processor；
Described analog-digital converter is used for gathering analog sampling signal, and described analog sampling signal is converted to digital sampled signal,
And by the transmission of described digital sampled signal to described digital signal processing circuit；
Described digital signal processing circuit is for determining online information on load according to described digital sampled signal, described at specific electric load
Information includes: one or more in magnitude of voltage, current value, mains frequency, active power, reactive power, merit angle；
Described flush bonding processor is used for determining load model parameters according to described online information on load, and according to described load mould
Shape parameter carries out Load Characteristic Analysis.
Device the most according to claim 1, it is characterised in that also include: memorizer；
Described memorizer is connected with described flush bonding processor, is used for storing database information, and described database information includes institute
That states in digital sampled signal, described online information on load and described load model parameters is one or more.
Device the most according to claim 2, it is characterised in that described flush bonding processor is provided with data access interface；
When described data access interface receives data access request, according to the process ID that described data access request is corresponding
Access described database information, and backward reference result.
Device the most according to claim 2, it is characterised in that described flush bonding processor is additionally operable to believe described data base
Breath carries out data pick-up；The mapping being set up the association between variety classes database information and inter-system data by Data Integration is closed
System, forms data warehouse；And data warehouse is carried out data integration, form cube metadata information.
Device the most according to claim 1, it is characterised in that described flush bonding processor specifically for: determine online receipts
The described online information on load of collection, arranged by offline user investigation and analysis simultaneously obtain various typical outlets the electricity consumption of confession
Load equipment ratio, according to described online information on load and power load equipment ratio-dependent load bus each moment various electricity consumption
The composition of equipment；Determine the part throttle characteristics parameter of various power load equipment according to dynamic analog test or representative value, utilize quiet
State load equivalence method calculates constant-impedance, constant current, the ratio of invariable power during static load is constituted, and then determines load mould online
Shape parameter.
Device the most according to claim 5, it is characterised in that described set according to described online information on load and power load
The composition of standby ratio-dependent load bus each moment various electrical equipment, including:
Off-line carries out user's sampling survey, each load type transformer station chooses some typical 10kV or 6kV outlets and bears
Lotus characteristic survey, analysis and arrangement obtains the electrical equipment of 10kV or the 6kV outlet of each load type and constitutes situation: include that electricity consumption sets
Standby type i and each electrical equipment proportion ρi；Described load type includes: industrial load type, Commercial Load type, resident
Load type or agricultural load type；
The voltage V of online acquisition 110kV/35kV every 10kV outlet circuit jj, electric current Ij, power factor PFj, calculate to obtain and be somebody's turn to do
Circuit 10kV side outlet power Pj=VjIjPFj；
Jth sampling survey 10kV or 6kV in the i-th type load including industry class, commercial, resident's class, agriculture is gone out
Line institute electricity supply and use equipment constitutes situation, popularization and application to other 10kV or 6kV outlets, and statistics draws this period all kinds of electrical equipment
General power, divided by the general power of this period whole load bus, all kinds of electricity consumption of this period whole 220kV transformer station can be obtained
Ratio k of equipment ii:If this transformer station a total of n bar 10kV or 6kV outlet.
7. according to the arbitrary described device of claim 1-6, it is characterised in that also include: communication module, described communication module with
Described flush bonding processor is connected；
Described communication module for communicating with host computer, receive control instruction that host computer sends or by information on load and/
Or load model parameters is uploaded to host computer.
8. according to the arbitrary described device of claim 1-6, it is characterised in that also including: touch screen, described touch screen is with described
Flush bonding processor is connected；
Described touch screen is for showing corresponding information on load according to the instruction of user's input.
9. according to the arbitrary described device of claim 1-6, it is characterised in that also including: keypad, described keypad is with described
Flush bonding processor is connected；
Described keypad is for receiving the operational order of user's input.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610447063.0A CN106154082A (en) | 2016-06-20 | 2016-06-20 | A kind of intelligent measure harvester of part throttle characteristics on-line analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610447063.0A CN106154082A (en) | 2016-06-20 | 2016-06-20 | A kind of intelligent measure harvester of part throttle characteristics on-line analysis |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106154082A true CN106154082A (en) | 2016-11-23 |
Family
ID=57353547
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610447063.0A Pending CN106154082A (en) | 2016-06-20 | 2016-06-20 | A kind of intelligent measure harvester of part throttle characteristics on-line analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106154082A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110531150A (en) * | 2019-09-10 | 2019-12-03 | 浙江蓝迪电力科技有限公司 | A kind of Road test system and method |
| CN113050486A (en) * | 2021-03-12 | 2021-06-29 | 南京工程学院 | Electric power system edge calculation and data distribution device based on industrial personal computer |
| RU2807982C1 (en) * | 2023-09-05 | 2023-11-21 | Федеральное государственное бюджетное образовательное учреждение высшего образования "Московский авиационный институт (национальный исследовательский университет)" | Electric field strength vector meter for aircraft lightning protection system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101777765A (en) * | 2010-01-27 | 2010-07-14 | 中国电力科学研究院 | On-line load simulation method of power system |
| CN102169646A (en) * | 2011-04-13 | 2011-08-31 | 深圳市双合电气股份有限公司 | Dynamic data-based online load modeling system |
| CN203101540U (en) * | 2012-12-07 | 2013-07-31 | 上海市电力公司 | Portable load characteristic analyzer |
| CN103580284A (en) * | 2013-10-31 | 2014-02-12 | 广州瑞信电力科技有限公司 | Low-voltage integrated reading system |
| US20150309092A1 (en) * | 2012-11-16 | 2015-10-29 | Tianjin University | Current Pattern Matching Method for Non-Intrusive Power Load Monitoring and Disaggregation |
-
2016
- 2016-06-20 CN CN201610447063.0A patent/CN106154082A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101777765A (en) * | 2010-01-27 | 2010-07-14 | 中国电力科学研究院 | On-line load simulation method of power system |
| CN102169646A (en) * | 2011-04-13 | 2011-08-31 | 深圳市双合电气股份有限公司 | Dynamic data-based online load modeling system |
| US20150309092A1 (en) * | 2012-11-16 | 2015-10-29 | Tianjin University | Current Pattern Matching Method for Non-Intrusive Power Load Monitoring and Disaggregation |
| CN203101540U (en) * | 2012-12-07 | 2013-07-31 | 上海市电力公司 | Portable load characteristic analyzer |
| CN103580284A (en) * | 2013-10-31 | 2014-02-12 | 广州瑞信电力科技有限公司 | Low-voltage integrated reading system |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110531150A (en) * | 2019-09-10 | 2019-12-03 | 浙江蓝迪电力科技有限公司 | A kind of Road test system and method |
| CN113050486A (en) * | 2021-03-12 | 2021-06-29 | 南京工程学院 | Electric power system edge calculation and data distribution device based on industrial personal computer |
| CN113050486B (en) * | 2021-03-12 | 2022-06-17 | 南京工程学院 | Electric power system edge calculation and data distribution device based on industrial personal computer |
| RU2807982C1 (en) * | 2023-09-05 | 2023-11-21 | Федеральное государственное бюджетное образовательное учреждение высшего образования "Московский авиационный институт (национальный исследовательский университет)" | Electric field strength vector meter for aircraft lightning protection system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Pawar et al. | An IoT based Intelligent Smart Energy Management System with accurate forecasting and load strategy for renewable generation | |
| US20220115867A1 (en) | Advanced power distribution platform | |
| CN107357856B (en) | Method for realizing data integration and data service based on power grid panoramic service model | |
| CN103366312B (en) | A kind of intelligent transformer substation cloud system | |
| JP5616330B2 (en) | Method and system for managing a power grid | |
| CN105337575B (en) | Photovoltaic plant status predication and method for diagnosing faults and system | |
| CN112700032A (en) | Fault prediction system and method for low-voltage direct-current power distribution and utilization system | |
| CN102982489A (en) | Power customer online grouping method based on mass measurement data | |
| CN110019098A (en) | Electrical energy measurement big data analysis system based on Hadoop frame | |
| CN109038678A (en) | Garden distributed energy intelligence managing and control system based on big data | |
| CN107741577A (en) | A kind of Source of Gateway Meter degree of accuracy on-line monitoring and analysis method and system | |
| CN111091240A (en) | Public institution electric power energy efficiency monitoring system and service method | |
| CN103632031B (en) | A kind of rural area based on load curve decomposition load type load modeling method | |
| CN103514571A (en) | Load curve decomposition based load modeling method for commercial load and resident load | |
| CN111398859B (en) | User low-voltage cause big data analysis method and system | |
| CN104201780A (en) | Load data collecting, transmitting and analyzing device used for rural power distribution area | |
| Nan et al. | Centralized automatic meter reading system based on GPRS technology | |
| CN115759708A (en) | Line loss analysis method and system considering power space-time distribution characteristics | |
| Ju et al. | The use of edge computing-based internet of things big data in the design of power intelligent management and control platform | |
| CN106154082A (en) | A kind of intelligent measure harvester of part throttle characteristics on-line analysis | |
| CN111177278A (en) | Grid user short-term load prediction real-time processing tool | |
| Patil et al. | GRID TIE solar power plant data acquisition system using internet of things | |
| El Khaouat et al. | Big data based management for smart grids | |
| CN109149637A (en) | Open monitoring management grid-connected system and its monitoring management method | |
| CN111857015B (en) | Power transmission and transformation cloud intelligent controller |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20161123 |
|
| RJ01 | Rejection of invention patent application after publication |