CN108828494A - Intelligent electric energy meter function calibration method based on genetic algorithm - Google Patents
Intelligent electric energy meter function calibration method based on genetic algorithm Download PDFInfo
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Abstract
The intelligent electric energy meter function calibration method based on genetic algorithm that the invention discloses a kind of, intelligent electric energy meter related power parameter when calibrating event and intelligent electric energy meter function are examined and determine is set according to actual needs first, the trigger condition table for obtaining event to be examined and determine, then obtains the value range of each power parameter according to trigger condition table；Then to adjust source parameter vector as individual chromosome, each tune source parameter vector is successively obtained using genetic algorithm, wherein the fitness value of individual corresponds to the event number to be examined and determine that tune source parameter vector is triggered for it；Finally according to adjusting source parameter vector to be configured the power parameter of intelligent electric energy meter, the calibrating to intelligent electric energy meter function is realized.The present invention can automatically generate the required tune source parameter vector of intelligent electric energy meter function calibrating, and the calibrating of all events to be examined and determine can be completed using the tune source parameter vector of negligible amounts, tester's workload can be reduced, the efficiency of intelligent electric energy meter function calibrating is improved.
Description
Technical field
The invention belongs to intelligent electric energy meter technical fields, more specifically, are related to a kind of intelligence based on genetic algorithm
Electric energy table function calibration method.
Background technique
Main tool of the electric energy meter as current electrical energy measurement and economic balance, it accurate whether, are directly related to country
With the economic interests of user.Domestic major electric energy meter manufacturer is based on production of intelligent electric energy meter at present, such electric energy meter
In process of production, unavoidably there is substandard product, while user is in use, it is also possible to electric energy meter occur and not conform to
The case where lattice.Accurately evaluating the whether qualified progress of electric energy meter is a very important aspect, therefore intelligent electric energy meter
Calibrating is that a very important link of field application is put into after it is produced.The project of electric energy meter Function detection includes
The tens remainder event such as defluidization, cutout, over-current and -load, under-voltage, decompression, power down.For three-phase electric energy meter, most of event needs again
Each phase event is measured respectively and closes phase event, therefore workload is in that three times or more increase.Manually calibration operation amount is too big item by item,
Scheme more appropriate at present is to complete to test by automatically testing platform.
Fig. 1 is the structure chart of intelligent electric energy meter automatically testing platform.As shown in Figure 1, mainly include PC machine, power source and by
It surveys object (electric energy meter).General work process is divided into 3 steps：
● adjust ginseng：PC machine carries out tune ginseng to electric energy meter, such as the threshold voltage of decompression triggering, recovery, current condition etc.；
● adjust source：PC machine adjusts power source, according to the testing process (formulating in software platform) formulated is realized, controls function
Rate source is to electric energy meter output voltage and electric current.If (ammeter is normal, and the parameter that can be stored according to the first step judges event
Generation whether, and keep a record)；
● reading data：(specific data are by surveying according to testing process and the in due course reading power meters record data of scheme for PC machine
Item is tried to determine), and compared with anticipatory data, provide test result.
Opposite manual testing, automatically testing platform can mitigate labor workload significantly, avoid mistake.But nonetheless,
Testing time required for the test of one three-phase electric energy meter is still that calibrating unit institute is insupportable.Testing time mainly disappears
Consumption is at two aspects：
First is that testing scheme is time-consuming：Current testing scheme needs tester to formulate one by one, contains nearly 100 for one
For the electric energy meter of item event, develops programs and need about 10 minute/* 100=1000 minutes, i.e., about 17 hours.
Second is that the testing time is long：The test of each event as mentioned before is divided into three steps：It adjusts ginseng, adjust source and reading data.
It adjusts ginseng and adjusts the time in source shorter, but after tune source, need to keep 60 seconds or so (inspection criterion requirement) before reading data
In addition, the current data reading system time is also longer, in minutes.Then restore power source to be kept for 60 seconds.Therefore each event
Test needs 3 minutes or so.According to test procedure, each event needs to test 10 times (guaranteeing 10 unloading data correctness),
Therefore the overall test time of an event needs 0.5 hour.100 need about 50 hours.
To sum up, the conventional detection for completing an electric energy meter needs about 8.5 working days, even if the round-the-clock work of detection platform
It is also required to 3 days or so.
Summary of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide a kind of intelligent electric energy meter function based on genetic algorithm
Energy calibration method automatically generates tune source parameter vector required when the calibrating of intelligent electric energy meter function, reduces tester's workload,
Improve the efficiency of intelligent electric energy meter function calibrating.
It for achieving the above object, include following the present invention is based on the intelligent electric energy meter function calibration method of genetic algorithm
Step：
S1：Setting intelligent electric energy meter is involved when calibrating event and intelligent electric energy meter function are examined and determine according to actual needs
Power parameter, obtain the trigger condition table D of event to be examined and determine, the element d in trigger condition table DijIndicate event i quilt to be examined and determine
The condition met needed for power parameter j when triggering, if event i to be examined and determine is triggered and does not need power parameter j and meet specific item
Part, then corresponding element dijFor sky, wherein i=0,1 ..., M-1, j=0,1 ..., N-1, M indicate event number to be examined and determine, and N is indicated
Power parameter quantity；
S2：For power parameter j, if it is phase parameter, then its value range C is enabledjFor [0,180], otherwise according to
Its value range is arranged in the trigger condition table D of calibrating event, and specific method is：Power parameter j phase is obtained from trigger condition table D
The corresponding trigger condition of event to be examined and determine is closed, the power parameter j critical value of trigger condition is obtained, remembers acquired critical value quantity
For Q, all critical values are arranged from big to small and obtain critical value sequenceThe then value range C of power parameter jj
ForWherein α > 1,0≤β < 1；
S3：Enable tune source parameter vector serial number k=0；
S4：Judge trigger condition table D whether be it is empty, if so, tune source parameter needed for the calibrating of intelligent electric energy meter function to
Amount, which obtains, to be completed, and is entered step S8, is otherwise entered step S5；
S5：The tune source parameter vector P [k] that serial number k is obtained using genetic algorithm will adjust source parameter in genetic algorithm
Vector is as individual chromosome, i.e. genetic algorithm individual X=[x1,x2,…,xN], wherein xjIndicate the value of power parameter j, it is right
Answering value range is Cj, individual fitness value corresponds to the event number to be examined and determine that tune source parameter vector is triggered for it；
S6：The set B for the event to be examined and determine for being adjusted source parameter vector P [k] to trigger is obtained according to current trigger condition table D
[k] data of event to be examined and determine will be deleted in event sets B [k] to be examined and determine from current trigger condition table D；
S7：Enable k=k+1, return step S4；
S8：The quantity for remembering the tune source parameter vector finally obtained is K, successively according to tune source parameter vector P [k] to intelligent electricity
The power parameter of energy table is configured, and wherein k=0,1 ..., K-1, are then returned to the nominal value of power parameter, according to intelligence
The output data of electric energy meter judges whether triggered event is consistent with the event in corresponding event sets B [k] to be examined and determine, such as
Fruit is consistent, then determines that the event calibrating in event sets B [k] to be examined and determine passes through, otherwise search inconsistent event, determine the thing
Part calibrating does not pass through.
The present invention is based on the intelligent electric energy meter function calibration methods of genetic algorithm, and setting intelligence is electric according to actual needs first
Energy table related power parameter when calibrating event and intelligent electric energy meter function are examined and determine, obtains the triggering item of event to be examined and determine
Then part table obtains the value range of each power parameter according to trigger condition table；Then to adjust source parameter vector as individual
Chromosome successively obtains each tune source parameter vector using genetic algorithm, wherein the fitness value of individual corresponds to tune source ginseng for it
The event number to be examined and determine that number vector is triggered；Finally the power parameter of intelligent electric energy meter is set according to tune source parameter vector
It sets, realizes the calibrating to intelligent electric energy meter function.The present invention can automatically generate the required tune of intelligent electric energy meter function calibrating
Source parameter vector, and the calibrating of all events to be examined and determine can be completed using the tune source parameter vector of negligible amounts, it is possible to reduce it surveys
Person works' amount is tried, the efficiency of intelligent electric energy meter function calibrating is improved.
Detailed description of the invention
Fig. 1 is the structure chart of intelligent electric energy meter automatically testing platform；
Fig. 2 is the specific embodiment flow chart of the intelligent electric energy meter function calibration method the present invention is based on genetic algorithm.
Specific embodiment
A specific embodiment of the invention is described with reference to the accompanying drawing, preferably so as to those skilled in the art
Understand the present invention.Requiring particular attention is that in the following description, when known function and the detailed description of design perhaps
When can desalinate main contents of the invention, these descriptions will be ignored herein.
Embodiment
Fig. 2 is the specific embodiment flow chart of the intelligent electric energy meter function calibration method the present invention is based on genetic algorithm.
As shown in Fig. 2, the present invention is based on the specific steps of the intelligent electric energy meter function calibration method of genetic algorithm to include：
S201：Obtain the trigger condition table of event to be examined and determine：
Setting intelligent electric energy meter is related when calibrating event and intelligent electric energy meter function are examined and determine according to actual needs
Power parameter obtains the trigger condition table D of event to be examined and determine, the element d in trigger condition table DijIndicate that event i to be examined and determine is touched
The condition met needed for power parameter j when hair, if event i to be examined and determine is triggered and does not need power parameter j and meet specified conditions,
Then corresponding element dijFor sky, wherein i=0,1 ..., M-1, j=0,1 ..., N-1, M indicate event number to be examined and determine, and N indicates electricity
Source number of parameters.
Table 1 is the trigger condition table D example that three-phase intelligent electric-energy meter waits for calibrating event.
Table 1
Parameter in table 1 in every trigger condition is as follows：
A) defluidization event current trigger lower limit lccl (3%-10%), the current trigger upper limit lccu (0.5%-2%) voltage
It triggers lower limit lcvl (60%-90%), determine delay time lct (10s-90s)；
B) it stops event voltage triggered lower limit cfvl (60%-85%), current trigger upper limit cfcu (0.5%-5%), sentence
Determine delay time cft (10s-90s)；
C) overcurrent events current trigger lower limit occl (0.5-1.5Imax), determine delay time oct (10s-90s)；
D) overload event active power triggers lower limit olpl (0.5-1.5Imax), determine delay time olt (10s-90s)；
E) over-voltage events voltage triggered lower limit ovvl (110%-130%), judgement delay time ovt (10s-90s)；
F) under-voltage event voltage triggered upper limit uvvu (70%-90%), judgement delay time uvt (10s-90s)；
G) decompression event current trigger lower limit lvcl (0.5%-5%), voltage triggered upper limit lvvu (70%-90%), electricity
Pressure restores lower limit lvvrl (lvvu-90%) and determines delay time lvt (10s-90s)；
H) full decompression event voltmeter critical voltage u (60%), judgement delay time alvt (10s-90s)；
I) break phase event voltage triggered upper limit pfvu (70%-90%), current trigger upper limit pfcu (0.5%-5%), sentence
Determine delay time pft (10s-90s)；
J) reversed event active power triggering lower limit aprl (0.5%-5%) of active power, judgement delay time aprt
(10s-90s)；
K) reversed event active power triggering lower limit prl (0.5%-5%) of trend, judgement delay time prlt (10s-
90s)；
L) current imbalance event current imbalance rate ubcr (10%-90%), serious unbalance factor hubcr (20%-
90%), determine delay event (10s-90s)；
M) Voltage unbalance event Voltage unbalance rate ubvr (10%-90%), serious unbalance factor (20%-90%),
Determine delay time (10s-90s)；
N) " u " expression " critical voltage "；
O) " | | " indicates at least to meet 1 in several trigger conditions of " | | " mark or, exist i.e. in a line, there is no " |
| " mark trigger condition be must satisfy；
P) "/" expression does not need to meet specified conditions.
As shown in table 1, table 1 gives the trigger condition that calibrating event is waited in three-phase intelligent electric-energy meter part, and each column represent
One power parameter (each phase voltage, electric current and phase), every a line represent an event to be examined and determine, which gives current to be checked
Determine the trigger condition (can be determined by the power supply vector that length is 9) of event.By taking the first row as an example, when A phase voltage is greater than defluidization thing
Part voltage triggered lower limit lcvl, A phase current is less than one of current trigger upper limit lccu and BC phase current and is greater than current trigger lower limit
Lccl, then it is assumed that A phase defluidization event occurs, and electric energy meter should have respective record, otherwise it is assumed that this function of electric energy meter is abnormal.
S202：Power parameter value range is set：
For power parameter j, if it is phase parameter, then its value range C is enabledjFor [0,180], otherwise basis is wait examine and determine
Its value range is arranged in the trigger condition table D of event, and specific method is：From trigger condition table D obtain power parameter j correlation to
The corresponding trigger condition of calibrating event obtains the power parameter j critical value of trigger condition, remembers that acquired critical value quantity is Q,
All critical values are arranged from big to small and obtain critical value sequenceThe then value range C of power parameter jjForWherein α > 1,0≤β < 1.
In order to make tune source parameter vector triggering thing more as far as possible corresponding to chromosome in subsequent genetic algorithm as far as possible
Part, improves the iteration efficiency of genetic algorithm, in the present embodiment to the value range of the power parameter of non-phase parameter carried out into
One-step optimization makes power parameter between all critical values, takes greater than critical value maximum value, less than between critical value minimum value
Value, the i.e. value range of power parameter j are a set, i.e.,
S203：Enable tune source parameter vector serial number k=0.
S204：Judge whether trigger condition table D is empty, if so, intelligent electric energy meter function examines and determine required tune source parameter
Vector, which obtains, to be completed, and is entered step S208, is otherwise entered step S205；
S205：Tune source parameter vector is obtained using genetic algorithm：
The tune source parameter vector P [k] that serial number k is obtained using genetic algorithm will adjust source parameter vector in genetic algorithm
As individual chromosome, i.e. genetic algorithm individual X=[x1,x2,…,xN], wherein xjIndicate that the value of power parameter j, correspondence take
Value range is Cj, individual fitness value corresponds to the event number to be examined and determine that tune source parameter vector is triggered for it, it is clear that is touched
The event number to be examined and determine of hair is more, and the individual is more excellent.
Genetic algorithm is a kind of algorithms most in use, and basic process is：First each individual in population initialize
To initial population, the fitness value of each individual in population is calculated, generates next-generation population by selection, intersection, variation, if
Reach iteration termination condition, then selects optimum individual as final optimum individual from current population, otherwise continue under generation
Generation population.
S206：Update trigger condition table：
The set B for the event to be examined and determine for being adjusted source parameter vector P [k] to trigger is obtained according to current trigger condition table D
[k] data of event to be examined and determine will be deleted in event sets B [k] to be examined and determine from current trigger condition table D.
S207：Enable k=k+1, return step S204.
S208：The calibrating of intelligent electric energy meter function：
The quantity for remembering the tune source parameter vector finally obtained is K, successively according to tune source parameter vector P [k] to intelligent electric energy
The power parameter of table is configured, wherein k=0,1 ..., K-1, is then returned to the nominal value of power parameter, according to intelligent electricity
The output data of energy table judges whether triggered event is consistent with the event in corresponding event sets B [k] to be examined and determine, if
Unanimously, then determine that the event calibrating in event sets B [k] to be examined and determine passes through, otherwise search inconsistent event, determine the event
Calibrating does not pass through.
Technical solution in order to better illustrate the present invention carries out implementation procedure of the invention using a specific example
It is described in detail.Table 2 is the trigger condition table D of event to be examined and determine in the present embodiment.
Table 2
As shown in table 2, intelligent electric energy meter is three-phase electric energy meter in the present embodiment, i.e., power parameter quantity is 9, thing to be examined and determine
Number of packages amount is 32.When data are -1 in table 2, illustrate corresponding event to be examined and determine be triggered do not need corresponding power parameter meet it is specific
Condition, other data are the critical value of default, can be reset before testing by user.With the 1st event to be examined and determine, " A phase is lost
It is illustrated for stream ", wherein the 1st column " UA">70%, which represents A phase voltage, has to be larger than 0.7 times of standard voltage value, the 4th column " UA”
<0.5%, which represents electric current, is necessarily less than 0.005 times of standard current value.
Next the value range of setting power parameter.With power parameter UAFor, according to the column of table 2 the 1st it can be seen that UA's
Critical value has 6：1.2,0.9,0.78,0.7,0.6,0.3.Parameter alpha=1.1, β=0.5 is set in the present embodiment, therefore it takes
Value range is Cj=[1.32,0.15].Then further be optimized for value range [1.32,1.1,0.84,0.74,0.65,
0.45,0.15].The value range of other 8 genes is obtained using same procedure.
Source parameter vector will be adjusted as individual chromosome, it is clear that the length of genetic algorithm individual is 9, is obtained using genetic algorithm
Each tune source parameter vector is taken, detailed process is as follows：
The first step：Genetic algorithm generates the tune source parameter vector of serial number 0, is denoted as P [0], searches in table 2 and currently adjusted
The event to be examined and determine of source parameter vector P [0] triggering, remembers that its collection is combined into B [0], specific as follows：
P [0]=[0.65,1.32,0.65,1.32,1.32,1.32,180,180,180]
B [0]=[18,7,29,28,30,6,17,20,31,15,10,13,8]
Then it the data of event to be examined and determine will be deleted in event sets B [0] to be examined and determine from table 2.
Second step：Based on updated table 2, genetic algorithm generates tune source parameter vector P [1], looks into table 2 in the updated
The event to be examined and determine for currently source parameter vector being adjusted to trigger is looked for, remembers that its collection is combined into B [1], it is specific as follows：
P [1]=[1.32,0.74,1.32,0.0025,0.0025,1.32,0,0,0]
B [1]=[14,11,12,0,24,1,16,4,3]
Then it the data of event to be examined and determine will be deleted in event sets B [1] to be examined and determine from updated table 2.
It repeats the above steps, obtains final intelligent electric energy meter function verification test scheme.Table 3 is that the present embodiment obtains
Intelligent electric energy meter function verification test scheme.Table 4 is each tune source parameter in intelligent electric energy meter function verification test scheme in table 3
The corresponding event to be examined and determine of vector.
Table 3
Table 4
As shown in Table 3 and Table 4, the number of source parameter vector is adjusted in the present embodiment needed for the calibrating of three-phase intelligent electric-energy meter function
Amount is 6, that is, the function calibrating for dividing 6 setting power parameters that 32 events to be examined and determine can be completed adjusts source to keep 60 according to each
Second, each event examines and determine 10 calculating, needs in total：6 60 seconds/time of tune source * tune source * 10 times=60 minutes.According to background skill
Description in art it is found that the overall test time of event needs 0.5 hour in the prior art, then in the present embodiment 32 to
Calibrating event is total to need 16 hours.It can be seen that automatically generating intelligent electric energy meter function verification test scheme using the present invention, and should
Testing scheme is reasonable, can effectively reduce tester's workload, improves the efficiency of intelligent electric energy meter function calibrating.
Although the illustrative specific embodiment of the present invention is described above, in order to the technology of the art
Personnel understand the present invention, it should be apparent that the present invention is not limited to the range of specific embodiment, to the common skill of the art
For art personnel, if various change the attached claims limit and determine the spirit and scope of the present invention in, these
Variation is it will be apparent that all utilize the innovation and creation of present inventive concept in the column of protection.
Claims (2)
1. a kind of intelligent electric energy meter function calibration method based on genetic algorithm, which is characterized in that include the following steps：
S1：Setting intelligent electric energy meter related electricity when calibrating event and intelligent electric energy meter function are examined and determine according to actual needs
Source parameter obtains the trigger condition table D of event to be examined and determine, the element d in trigger condition table DijIndicate that event i to be examined and determine is triggered
When power parameter j needed for the condition that meets, if event i to be examined and determine is triggered and does not need power parameter j and meet specified conditions,
Corresponding element dijFor sky, wherein i=0,1 ..., M-1, j=0,1 ..., N-1, M indicate event number to be examined and determine, and N indicates power supply
Number of parameters；
S2：For power parameter j, if it is phase parameter, then its value range C is enabledjFor [0,180], otherwise according to thing to be examined and determine
Its value range is arranged in the trigger condition table D of part, and specific method is：It is to be checked that power parameter j correlation is obtained from trigger condition table D
Determine the corresponding trigger condition of event, obtain the power parameter j critical value of trigger condition, remembers that acquired critical value quantity is Q, it will
All critical values arrange obtain critical value sequence from big to smallThe then value range C of the power parameter jj
ForWherein α > 1,0≤β < 1；
S3：Enable tune source parameter vector serial number k=0；
S4：Judge whether trigger condition table D is empty, if so, tune source parameter vector needed for the calibrating of intelligent electric energy meter function obtains
It takes into, enters step S8, otherwise enter step S5；
S5：The tune source parameter vector P [k] that serial number k is obtained using genetic algorithm will adjust source parameter vector in genetic algorithm
As individual chromosome, i.e. genetic algorithm individual X=[x1,x2,…,xN], wherein xjIndicate that the value of power parameter j, correspondence take
Value range is Cj, individual fitness value corresponds to the event number to be examined and determine that tune source parameter vector is triggered for it；
S6：The set P [k] for the event to be examined and determine for being adjusted source parameter vector P [k] to trigger is obtained according to current trigger condition table D,
It the data of event to be examined and determine will be deleted in event sets B [k] to be examined and determine from current trigger condition table D；
S7：Enable k=k+1, return step S4；
S8：The quantity for remembering the tune source parameter vector finally obtained is K, successively according to tune source parameter vector P [k] to intelligent electric energy meter
Power parameter be configured, wherein k=0,1 ..., K-1, are then returned to the nominal value of power parameter, according to intelligent electric energy
The output data of table judges whether triggered event is consistent with the event in corresponding event sets B [k] to be examined and determine, if one
It causes, then determines that the event calibrating in event sets B [k] to be examined and determine passes through, otherwise search inconsistent event, determine that the event is examined
It is fixed not pass through.
2. intelligent electric energy meter function calibration method according to claim 1, which is characterized in that non-phase in the step S3
The value range C of the power parameter of parameterjTo gather, i.e.,
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| 杨霖: "电能表自动化检定***设计", 《中国优秀硕士学位论文全文数据库 工程科技II辑》 * |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112230180A (en) * | 2020-09-27 | 2021-01-15 | 青岛鼎信通讯股份有限公司 | Signal source phase modulation method of electric energy meter calibrating device based on FPGA |
| CN113552528A (en) * | 2021-06-29 | 2021-10-26 | 国网上海市电力公司 | Transformer substation bus unbalance rate abnormity analysis method based on improved genetic algorithm |
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