CN113567721B - Power failure statistics method for intelligent ammeter - Google Patents
Power failure statistics method for intelligent ammeter Download PDFInfo
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- CN113567721B CN113567721B CN202110878090.4A CN202110878090A CN113567721B CN 113567721 B CN113567721 B CN 113567721B CN 202110878090 A CN202110878090 A CN 202110878090A CN 113567721 B CN113567721 B CN 113567721B
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- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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- G01R11/02—Constructional details
- G01R11/25—Arrangements for indicating or signalling faults
Abstract
The invention relates to a power failure statistical method of an intelligent ammeter, which comprises the following steps of 1, storing the power-down time of the intelligent ammeter closest to the current statistical moment in an electric power acquisition system; step 2, searching power-down and power-up records corresponding to the conditions that the power-up time is more than or equal to the statistical starting time and the power-down time is less than or equal to the statistical ending time in the power acquisition system; step 3, eliminating the time which does not belong to the statistical time period from the power-down record and the power-up record searched in the step 2; and 4, searching records that the state of the intelligent ammeter at the current statistical moment is in a power-off state and the power-off time of the intelligent ammeter is before the statistical end time, setting the recorded power-off end time as the statistical end time, and calculating the power-off time of the searched records in the statistical time period to obtain the power-off time of each intelligent ammeter. According to the method, the power failure condition in the cross-statistics time period can be counted, the statistics process is simplified, and the data difference value can be reduced to the minimum.
Description
Technical Field
The invention relates to the field of intelligent electric meters, in particular to a power failure statistics method of an intelligent electric meter.
Background
Today, the smart electric meter is promoted vigorously, the domestic smart electric meter market is saturated gradually, the solution of the system is unified by the national power grid company to make standardized design, the problem of integration is solved, and the service requirement is met through unified standard requirements on power equipment and a power system. However, in the vast overseas market, the electric power informatization countries and markets with different grades are faced, communication basic equipment is not perfected in China, most of power grid construction is more backward than China, the communication basic environment is much backward than China, and especially in underdeveloped countries, the situation is worse.
Under the conditions that the power grid is not constructed enough and the communication environment can not meet the power information transmission, the information of power supply and power failure of a user is difficult to master in real time, the real-time power failure and power supply information of a region can not be mastered in real time, an electric company is expected to acquire the monthly power supply condition of the region through analyzing the power on and off events (the single power failure time, the power on time, the power off time, the total power failure time of an ammeter, the total power failure time, the regional average power failure time and the like need to be calculated), but because the information network is not smooth, the information collection is delayed, and the statistical information is difficult to guarantee accuracy and effectiveness. Moreover, the event that the ammeter pushes up, the power-on event and the power-off event are independent, and the power-on event and the power-off event in the time period need to be analyzed, but the event causes more data loss, so that the calculation of the total power failure time is inaccurate, the power-on event and the power-off event which do not occur in the time period can be lost, or the condition that the power-on event and the power-off event do not occur yet can not be accurately calculated. If each statistic is done for all events, a lot of computation space and speed is wasted, resulting in inefficiency.
According to the analysis of the time of occurrence and the statistical time of the power-down and power-up events, there are six situations, as shown in fig. 1, in which four situations of power-down and power-up can be matched:
(1) the power-down time is in the statistical time period, and the power-up time is in the statistical time period;
(2) the power-down time is within the statistical time period, and the power-up time is outside the statistical time period;
(3) the power-down time is outside the statistical time period, and the power-up time is within the statistical time period;
(4) the power-down time is outside the statistical time period, and the power-up time is outside the statistical time period;
in addition to the above four pairing methods, there are two other pairing methods, namely, after power-down, there are no power-up events until the statistical time, which is also a conventional case, and there are two methods as follows:
(5) the power-down time is outside the statistical time period, and the power-up time is absent;
(6) the power-down time is within the statistical time period, and the power-up time is absent;
the existing scheme comprises the following steps:
existing scheme 1: only for the event in the statistical time period, the three cases (3), (4) and (5) are lost, and the disadvantage of this scheme is that: the shorter the statistical period (e.g., daily) the higher the error rate, the longer the statistical period (e.g., monthly) the lower the error rate, since power outages of more than one month will typically not occur, but many more than one day.
Existing scheme 2: on the basis of scheme 1, reducing the error rate generally increases the statistical range by taking more data than a part of the time, and three cases (3), (4) and (5) are intended to be covered, which effectively reduces the error, but cannot be completely, and the more taken data cannot necessarily be covered entirely. The disadvantage of this solution is therefore: although the error of the scheme 1 is effectively reduced, the calculation resource of the program is consumed, the calculation range is enlarged, more data will be processed, invalid data is required to be filtered in algorithm, and therefore the complexity of the power failure time calculation algorithm is high.
In summary, the statistical error rate of scheme 1 is higher, and the statistical information is incomplete; the scheme 2 improves the statistical error rate compared with the scheme 1, but does not completely solve the problem, and has poorer performance in statistics; in both schemes 1 and 2, there are a large number of calculations in statistics, the pressure is more concentrated, and there is a performance bottleneck. There is therefore a need for further improvements over existing solutions.
Disclosure of Invention
The invention aims to solve the technical problem of providing a power failure statistics method of an intelligent ammeter with smaller calculation complexity and more accurate calculation aiming at the prior art.
The technical scheme adopted for solving the technical problems is as follows: a power failure statistical method of an intelligent ammeter is characterized in that: the method comprises the following steps:
step 1, storing the power-down time of the intelligent ammeter closest to the current statistical moment in the power acquisition system, and storing the power-up time in the power acquisition system if a power-up event occurs between the power-down time and the current statistical moment;
step 2, setting a statistical start time and a statistical end time in a statistical time period, and searching power-down and power-up records corresponding to the conditions that the power-up time is more than or equal to the statistical start time and the power-down time is less than or equal to the statistical end time in a power acquisition system;
step 3, eliminating the time which does not belong to the statistical time period from the power-down record and the power-up record searched in the step 2;
step 4, searching records that the state of the intelligent ammeter at the current statistical moment is in a power failure state and the power-down time of the intelligent ammeter is before the statistical end time, setting the power-down end time of the records as the statistical end time, and dividing the statistical start time into two parts:
1. setting the power-down time of the intelligent ammeter meeting the condition as the statistical starting time if the power-down time is less than or equal to the statistical starting time;
2. the power-down time is more than the statistical starting time, and the power-down time of the intelligent ammeter meeting the condition is kept unchanged;
and 5, counting the power failure time recorded in the counted time period, so as to obtain the power failure time of each intelligent ammeter.
As an improvement, a buffer space is opened up in the power acquisition system, and the power-down time and the power-up time of the intelligent ammeter are stored in the buffer space.
In order to prevent data loss and influence the calculation accuracy, the power acquisition system in step 1 updates the occurrence time and the power failure state of the power down event to a storage space and synchronously updates the occurrence time and the power failure state to a database of the acquisition system each time the power down event is received.
In order to avoid abnormal situations, the acquisition system judges whether the power-on time exists in the buffer space when the power-on time is received each time, if yes, the sequence of the power-on time and the power-on time is judged, and if the power-on time and the power-on time accord with the pairing situation, the step 2 is shifted to.
Specifically, when the power-on time is more than the power-off time, the matching situation is met; otherwise, when the power-on time is less than the power-off time, the pairing situation is not met.
In this scheme, smart electric meter is according to down electric time, power up time and statistics time quantum analysis and has six kinds of records:
the records of the power-down time and the power-up time according with the pairing condition comprise four types:
(1) the power-down time is in the statistical time period, and the power-up time is in the statistical time period;
(2) the power-down time is within the statistical time period, and the power-up time is outside the statistical time period;
(3) the power-down time is outside the statistical time period, and the power-up time is within the statistical time period;
(4) the power-down time is outside the statistical time period, and the power-up time is outside the statistical time period;
the power-down time and the power-up time do not meet the pairing condition, namely: that is, the record that no power-on event is generated until the current statistical moment after the smart meter is powered down includes two kinds:
(5) the power-down time is outside the statistical time period, and the power-up time is absent;
(6) the power-down time is within the statistical time period, and the power-up time is absent.
Preferably, the removing method in the step 3 is as follows:
when the power-down time is less than the statistical start time, setting the power-down time of the intelligent ammeter meeting the condition as the statistical start time;
and when the power-on time is more than the statistical end time, setting the power-on time of the intelligent ammeter meeting the condition as the statistical end time.
Further, the intelligent ammeter is in communication connection with the power acquisition system and is used for acquiring the power failure time of the intelligent ammeter by the power acquisition system.
Specifically, the intelligent ammeter is in communication connection with the power acquisition system in a wireless mode.
Preferably, the power acquisition system is a master station.
Compared with the prior art, the invention has the advantages that: the method has the advantages that the latest outage information is recorded, the single outage situation is calculated after each event is received, the follow-up information gathering of the statistics time period is facilitated, therefore, the calculation pressure is shared by calculating the outage time of each intelligent ammeter in real time, the calculation complexity is reduced, in addition, the outage situation in the statistics time period can be counted, the statistics process is simplified, the data difference value can be reduced to the minimum, the real outage situation can be reflected according to the result in the statistics time period, and the method is more suitable for use.
Drawings
Fig. 1 is a schematic diagram of a relationship between a power-down time, a power-up time and a statistical time period of an existing smart meter;
fig. 2 is a flowchart of a power outage statistics method of the intelligent ammeter according to an embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the embodiments of the drawings.
As shown in fig. 1, six records are recorded by the smart meter according to analysis of the power-down time, the power-up time and the statistical time period:
the records of the power-down time and the power-up time according with the pairing condition comprise four types:
(1) the power-down time is in the statistical time period, and the power-up time is in the statistical time period;
(2) the power-down time is within the statistical time period, and the power-up time is outside the statistical time period;
(3) the power-down time is outside the statistical time period, and the power-up time is within the statistical time period;
(4) the power-down time is outside the statistical time period, and the power-up time is outside the statistical time period;
the power-down time and the power-up time do not meet the pairing condition, namely: that is, the record that no power-on event is generated until the current statistical moment after the smart meter is powered down includes two kinds:
(5) the power-down time is outside the statistical time period, and the power-up time is absent;
(6) the power-down time is within the statistical time period, and the power-up time is absent.
In order to accurately count records satisfying the above 6 situations in the same statistics time period, as shown in fig. 2, the power outage statistical method of the smart meter in this embodiment includes the following steps:
step 1, storing the power-down time of the intelligent ammeter closest to the current statistical moment in the power acquisition system, and storing the power-up time in the power acquisition system if a power-up event occurs between the power-down time and the current statistical moment;
step 2, setting a statistical start time and a statistical end time in a statistical time period, and searching power-down and power-up records corresponding to the conditions that the power-up time is more than or equal to the statistical start time and the power-down time is less than or equal to the statistical end time in a power acquisition system;
step 3, eliminating the time which does not belong to the statistical time period from the power-down record and the power-up record searched in the step 2;
the specific rejecting method comprises the following steps:
when the power-down time is less than the statistical start time, setting the power-down time of the intelligent ammeter meeting the condition as the statistical start time;
when the power-on time is more than the statistical end time, setting the power-on time of the intelligent ammeter meeting the condition as the statistical end time;
step 4, searching records that the state of the intelligent ammeter at the current statistical moment is in a power failure state and the power-down time of the intelligent ammeter is before the statistical end time, setting the power-down end time of the records as the statistical end time, and dividing the statistical start time into two parts:
1. setting the power-down time of the intelligent ammeter meeting the condition as the statistical starting time if the power-down time is less than or equal to the statistical starting time;
2. the power-down time is more than the statistical starting time, and the power-down time of the intelligent ammeter meeting the condition is kept unchanged;
and 5, counting the power failure time recorded in the counted time period, so as to obtain the power failure time of each intelligent ammeter.
In this embodiment, in order to facilitate data storage, a buffer space is opened up in the power acquisition system, and the power-down time and the power-up time of the smart meter are stored in the buffer space. When the power acquisition system receives a power-down event, updating the occurrence time and the power failure state of the power-down event into a storage space and synchronously updating the occurrence time and the power failure state into a database of the acquisition system; and when the acquisition system receives the power-on time each time, judging whether the power-on time exists in the buffer space, if yes, judging the sequence of the power-on time and the power-on time, and if the sequence meets the pairing condition, switching to the step 2. When the power-on time is more than the power-off time, the pairing situation is met; otherwise, when the power-on time is less than the power-off time, the pairing situation is not met.
In addition, the intelligent ammeter is in communication connection with the power acquisition system and is used for acquiring the power failure time of the intelligent ammeter by the power acquisition system. In this embodiment, the smart meter is connected with the power collection system in a wireless manner. Preferably, the power acquisition system is a master station.
The four conditions (1), (2), (3) and (4) in fig. 1 can be searched through the method in the step 2, but only the power-on time and the power-off time of the (1) th type are within the statistical time period, and the difference between the power-on time and the power-off time can be used as the power-off time within the statistical time period without any operation in the condition; for the three cases (2), (3) and (4), removing the time which does not belong to the statistical time period according to the method in the step 3, and setting the power-on time as the statistical end time for the case (2); aiming at the condition (3), setting the power-down time as the statistical starting time; aiming at the condition (4), the power-down time is set as the statistics start time and the power-up time is set as the statistics end time; and taking the difference value between the changed power-on time and the changed power-off time as the power-off time in the statistical time period.
The two cases (5) and (6) in fig. 1 can be retrieved through the method in the step 4, and for the (5) th case, the power-down time is set as the statistics start time, and the power-down end time is set as the statistics end time; aiming at the condition (6), the power-on time is kept unchanged, and the power-on ending time is set as the statistical ending time; and taking the difference value between the power-down ending time and the power-down time as the power-off time in the statistical time period.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that it will be apparent to those skilled in the art that several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the scope of the invention.
Claims (10)
1. A power failure statistical method of an intelligent ammeter is characterized in that: the method comprises the following steps:
step 1, storing the power-down time of the intelligent ammeter closest to the current statistical moment in the power acquisition system, and storing the power-up time in the power acquisition system if a power-up event occurs between the power-down time and the current statistical moment;
step 2, setting a statistical start time and a statistical end time in a statistical time period, and searching power-down and power-up records corresponding to the conditions that the power-up time is more than or equal to the statistical start time and the power-down time is less than or equal to the statistical end time in a power acquisition system;
step 3, eliminating the time which does not belong to the statistical time period from the power-down record and the power-up record searched in the step 2;
step 4, searching records that the state of the intelligent ammeter at the current statistical moment is in a power failure state and the power-down time of the intelligent ammeter is before the statistical end time, setting the power-down end time of the records as the statistical end time, and dividing the statistical start time into two parts:
1. setting the power-down time of the intelligent ammeter meeting the condition as the statistical starting time if the power-down time is less than or equal to the statistical starting time;
2. the power-down time is more than the statistical starting time, and the power-down time of the intelligent ammeter meeting the condition is kept unchanged;
and 5, counting the power failure time recorded in the counted time period, so as to obtain the power failure time of each intelligent ammeter.
2. The power outage statistical method for the intelligent ammeter according to claim 1, wherein: and opening up a buffer space in the power acquisition system, and storing the power-down time and the power-up time of the intelligent ammeter in the buffer space.
3. The power outage statistical method for the intelligent ammeter according to claim 2, wherein: and (2) when the power acquisition system receives the power-down event, updating the occurrence time and the power failure state of the power-down event into a storage space each time, and synchronously updating the occurrence time and the power failure state into a database of the acquisition system.
4. The power outage statistical method for the intelligent ammeter according to claim 2, wherein: and when the acquisition system receives the power-on time each time, judging whether the power-on time exists in the buffer space, if so, judging the sequence of the power-on time and the power-on time, and if the sequence meets the pairing condition, switching to the step 2.
5. The power outage statistical method for the intelligent ammeter according to claim 4, wherein: when the power-on time is more than the power-off time, the pairing situation is met; otherwise, when the power-on time is less than the power-off time, the pairing situation is not met.
6. The power outage statistical method for the intelligent ammeter according to claim 1, wherein: the intelligent ammeter can analyze according to the power-down time, the power-up time and the statistical time period and has six records:
the records of the power-down time and the power-up time according with the pairing condition comprise four types:
(2) the power-down time is in the statistical time period, and the power-up time is in the statistical time period;
(2) the power-down time is within the statistical time period, and the power-up time is outside the statistical time period;
(7) the power-down time is outside the statistical time period, and the power-up time is within the statistical time period;
(8) the power-down time is outside the statistical time period, and the power-up time is outside the statistical time period;
the power-down time and the power-up time do not meet the pairing condition, namely: that is, the record that no power-on event is generated until the current statistical moment after the smart meter is powered down includes two kinds:
(9) the power-down time is outside the statistical time period, and the power-up time is absent;
(6) the power-down time is within the statistical time period, and the power-up time is absent.
7. The power outage statistical method for the intelligent ammeter according to claim 1, wherein: the rejecting method in the step 3 is as follows:
when the power-down time is less than the statistical start time, setting the power-down time of the intelligent ammeter meeting the condition as the statistical start time;
and when the power-on time is more than the statistical end time, setting the power-on time of the intelligent ammeter meeting the condition as the statistical end time.
8. The power outage statistical method for the intelligent ammeter according to claim 1, wherein: the intelligent ammeter is in communication connection with the power acquisition system and is used for acquiring the power failure time of the intelligent ammeter by the power acquisition system.
9. The power outage statistical method for the intelligent ammeter according to claim 8, wherein: the intelligent ammeter is in communication connection with the power acquisition system in a wireless mode.
10. The power outage statistical method for the smart meter according to any one of claims 1 to 9, wherein: the electric power acquisition system is a master station.
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