CN110298535A - A kind of power grid active O&M warning information generation method - Google Patents
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Abstract
The present invention relates to information technology fields, and in particular to a kind of power grid active O&M warning information generation method, comprising the following steps: A) obtain each element of regional power grid history operation/maintenance data, obtain regional power grid in each distribution historical load data；B the O&M vector V of element) is obtaineds；C load condition vector V) is obtainedP；D the historic state vector V of element) is establishedF, obtain element whole historic state vector VFSet, as historic state set F；E) periodical monitoring element and its place distribution, obtain the last state vector of elementIfThen issue warning information.Substantial effect of the invention is: by the step of handling history operation/maintenance data, generating the foundation that warning information generates, save artificial setting data threshold, improve the accuracy of warning information.
Description
Technical field
The present invention relates to information technology fields, and in particular to a kind of power grid active O&M warning information generation method.
Background technique
Power distribution station is the most basic power supply unit of county domain power grid, is the key that ensure that ring " comes to down, can use " to electric power
Section, is the infrastructure and important public utilities of county economy social development.The sound development of power distribution station is supplied concerning harmony
The building of electricity consumption relationship.However due to various reasons, power distribution station overall development level is lower, in construction retrofit and operation management
Experience is relied primarily in the process, lacks science decision.The power distribution network in some areas is very weak, radius of electricity supply length, conductor cross-section
It is small, distribution capacity is low per family, load peak-valley difference is big, the especially load boom periods such as spring and summer peak meeting " low-voltage " problem is prominent
Out.Existing area's operation maintenance personnel is in passive O&M, and to the monitoring deficiency of platform area key equipment route, monitoring rank is lower,
Just start O&M maintenance after platform area is out of joint, causes power distribution station reliability poor.Thus need to develop active O&M
Fault early warning method.
Such as Chinese patent CN105354614B, publication date on March 26th, 2019, a kind of electric network information fortune based on big data
Dimension active forewarning method system includes status early warning, threshold value early warning, becomes early warning, trending early warning, evaluation early warning fastly and be associated with early warning,
Status early warning, by being detected and being obtained to the information resources between grid nodes as a result, information resources state is divided into just
Normal state, lost contact state and unstable state three classes；If information resources are in lost contact state, alerted；If letter
Breath resource plays pendulum, and needs to carry out status early warning；Threshold value early warning passes through the numerical value of the information resources to grid nodes
It is compared with preset threshold value, if exceeding threshold value, carries out early warning or alarm；Lateral early warning is any grid nodes
The numerical value of information resources with and the numerical value of the arranged side by side similar node of the node be compared, is then carried out beyond certain threshold value in advance
It is alert；Longitudinal early warning is that the numerical value of the information resources of any grid nodes is compared with the historical data of the node itself, is exceeded
Certain threshold value then carries out early warning；Trending early warning continuously monitors the information resources of grid nodes, passes through grid nodes
Difference, the target rate of growth this four Index Establishments between threshold value of warning, early warning activation threshold value, index current value and threshold value of warning
Mathematical model judges current electric grid node operating status；Early warning is evaluated, real-time monitoring is carried out to the information resources of grid nodes,
And the mathematical model of grid nodes scoring is established, it is customized by the user the threshold of the numerical value of the information resources of setting grid nodes
Value realizes evaluation early warning；It is associated with early warning, data correlation rule mining algorithms are carried out to the data of each grid nodes, with Apriori
Based on algorithm, Boolean matrix is constructed, and by branch's screening and optimizing, at most to occupancy computing resource in Apriori algorithm
Binomial Frequent Set calculating task carries out beta pruning to improve efficiency of algorithm, analyzes the relevance between grid nodes by data, and
It is monitored.Although its alarm mode is more, its underutilization to regional power grid historical data cannot good combined area
The operation of domain power grid is practical, be easy to cause accidentally early warning.
Summary of the invention
It is carried out actively the technical problem to be solved by the present invention is lacking effective bond area power grid history data at present
The warning information generation method of O&M.Propose a kind of early warning more accurately electricity closer in conjunction with regional power grid operation data
Host moves O&M warning information generation method.
In order to solve the above technical problems, the technical solution used in the present invention are as follows: a kind of power grid active O&M warning information
Generation method, comprising the following steps: A) the history operation/maintenance data that obtains each element of regional power grid, it obtains and each matches in regional power grid
The historical load data of net；B) each element history operation/maintenance data is handled, obtains the O&M vector V of elements；C) to element
The historical load data of place distribution is handled, and load condition vector V is obtainedP；D the historic state vector V of element) is establishedF,
It obtains element and operates normally the whole historic state vector V occurred in historyFSet, as historic state set F；E) the period
Property monitoring element and its place distribution load, with method identical with step B-D obtain element last state vectorIfThen issue warning information.By handling history operation/maintenance data, the foundation that warning information generates is generated, is saved
The step of artificial setting data threshold, in conjunction with history operation/maintenance data, it can be improved the accuracy of warning information.
Preferably, the history operation/maintenance data of the element includes the state quantity data and numerical quantities data of element, step B
In, obtain the O&M vector V of elementsMethod the following steps are included: B1) the numerical quantities data of each element are divided into numerical value area
Between；B2) using numerical intervals as state name, state quantity data is converted by each component values amount data；B3) state quantity data is torn open
It is divided into Boolean quantity data, Boolean quantity data is indicated with vector, as O&M vector Vs.By dividing numerical intervals, number is highlighted
The feature of value establishes Boolean quantity data, facilitates comparison.
Preferably, obtaining load condition vector V in step CPMethod the following steps are included: C1) obtain regional power grid
The horizontal P of main loads of electricity consumption day i of interior each distributionM, a, i, i ∈ H, a ∈ A, A are to include in regional power grid with net collective；
C2 electricity consumption day main loads horizontal data) is divided into numerical intervals, using numerical intervals as state name, by main loads horizontal data
PM, a, iIt is converted into state quantity data；C3 state quantity data) is split as Boolean quantity data, Boolean quantity data are indicated with vector,
As load condition vector VP.By being compared using section by load demarcation interval, feature can be extracted from load data,
Early warning is carried out in conjunction with load, can be improved the accuracy of early warning.
Preferably, numerical quantities data are divided the method for numerical intervals the following steps are included: B11 in step B1) it obtains
Whole numerical quantities data of history operation/maintenance data, are arranged successively by numerical values recited, are denoted as set Ki under field；B12 set) is found
Minimum value k in KiminWith maximum value kmax, by subregion starting point ksTax initial value is kmin, partition end keTax initial value is kmax, investigate
Value km=ks+ n × Δ k, Δ k are the step-length manually set, and n is positive integer, and n initial value is 1；B13) n is constantly from adding 1, if it exists completely
The investigation value k of the following condition of footm:
Wherein, function N (x, y) indicates set Ki, and data value is in the data amount check of numerical intervals (x, y), then by (2km-ks)
As interval division point and division point set Km is added, by (2km-ks) value be assigned to ks, continue that n is enabled constantly to add 1 certainly, until
km> kmax；B14) by kminAnd kmaxSet Km is added and, as division points, numerical quantities data are divided into number using the value in Km
It is worth section.The distribution of usage history data itself carries out interval division, can be improved the conjugation with historical data, compared to people
Work demarcation interval, reduces cost of labor, avoids subjective factor, improves early warning accuracy.
Preferably, converting the method for state quantity data the following steps are included: B21 for numerical quantities data in step B2)
Numerical quantities data are divided into several sections, [nm(1), nm(2)], [nm(2), nm(3)]...[nm(k-1), nm(k))], wherein nm(1)With
nm(k)The respectively beginning and end of numerical intervals, nm(2)~nm(k-1)It, will for the intermediate division points of numerical intervalsRespectively as the state name of corresponding numerical intervals；B22) if history is transported
Dimension value amount data N, falls into section [nm(d), nm(d+1)], d ∈ [1, k-1], then by state nameAs field
Value completes numerical quantities data and is converted into state quantity data.
Preferably, in step C1, the main loads horizontal data P of electricity consumption day iM, iCalculation method the following steps are included:
C11 the hourly average load for) counting electricity consumption day i, is denoted as GH, h ∈ [0,23]；C12 it) since 0, using Δ P as step-length, delimit N number of negative
Lotus section, n-th load setting cover the G of electricity consumption day iH, h ∈ [0,23]Maximum value；C13) by GH, h ∈ [0,23]It is put into where it
Load setting adjusts Δ P, makesWherein NpExpression is placed at least one GH, h ∈ [0,23]Load setting sum；
C14 it) obtains and is placed into GH, h ∈ [0,23]The minimum load setting of quantity, the master with the median of the load setting, as electricity consumption day i
Want load level data PM, iIt participates in calculating.
Preferably, including by the method that state quantity data is split as Boolean quantity data are as follows: obtain the complete of state quantity data
Quantity of state field is split as multiple fields using state value as field name, by field name and quantity of state number by portion's state value
According to the identical field set of value, remaining splits field zero setting, and completion status amount data are split as Boolean quantity data.
Preferably, in step B12, the setting method of step delta k includes are as follows: the two of numerical quantities data in set of computations Ki
Two differences, the difference that rejecting is zero carry out the operation that takes absolute value to remaining difference, using minimum value therein as step delta k, ginseng
With calculating.
Substantial effect of the invention is: by handling history operation/maintenance data, generate that warning information generates according to
According to, artificial the step of setting data threshold is saved, operating process is simplified, is more bonded with regional power grid history data,
Improve the accuracy of warning information.
Detailed description of the invention
Fig. 1 is one warning information generation method flow diagram of embodiment.
Specific embodiment
Below by specific embodiment, and in conjunction with attached drawing, a specific embodiment of the invention is further described in detail.
Embodiment one:
A kind of power grid active O&M warning information generation method, as shown in Figure 1, the present embodiment the following steps are included:
A the history operation/maintenance data for) obtaining each element of regional power grid, obtains the historical load data of each distribution in regional power grid,
The history operation/maintenance data of element includes the state quantity data and numerical quantities data of element.
B) each element history operation/maintenance data is handled, obtains the O&M vector V of elements；Specifically includes the following steps:
B1 the numerical quantities data of each element) are divided into numerical intervals；B2) using numerical intervals as state name, by each component values amount data
It is converted into state quantity data；B3 state quantity data) is split as Boolean quantity data, Boolean quantity data are indicated with vector, as
O&M vector Vs.The method that state quantity data is split as Boolean quantity data are as follows: whole state values of state quantity data are obtained,
Quantity of state field is split as multiple fields using state value as field name, field name is identical with state quantity data value
Field set, remaining splits field zero setting, and completion status amount data are split as Boolean quantity data.Numerical quantities data are divided into numerical value
The method in section is the following steps are included: B11) obtain field under history operation/maintenance data whole numerical quantities data, by numerical values recited
It is arranged successively, is denoted as set Ki；B12 the minimum value k in set Ki) is foundminWith maximum value kmax, by subregion starting point ksAssign initial value
For kmin, partition end keTax initial value is kmax, investigation value km=ks+ n × Δ k, Δ k are the step-length manually set, set of computations Ki
The difference two-by-two of middle numerical quantities data, the difference that rejecting is zero carry out the operation that takes absolute value to remaining difference, by minimum therein
It is positive integer that value, which is used as step delta k, n, and n initial value is 1；B13) n meets the investigation value km of following condition constantly from adding 1 if it exists:
Wherein, function N (x, y) indicates set Ki, and data value is in the data amount check of numerical intervals (x, y), then by (2km-ks)
As interval division point and division point set Km is added, by (2km-ks) value be assigned to ks, continue that n is enabled constantly to add 1 certainly, until
km> kmax；B14) by kminAnd kmaxSet Km is added and, as division points, numerical quantities data are divided into number using the value in Km
It is worth section.The distribution of usage history data itself carries out interval division, can be improved the conjugation with historical data, compared to people
Work demarcation interval, reduces cost of labor, avoids subjective factor, improves early warning accuracy.It converts numerical quantities data to
The method of state quantity data is the following steps are included: B21) numerical quantities data are divided into several sections, [nm(1), nm(2)],
[nM (2),nm(3)]...[nm(k-1), nm(k)], wherein nm(1)And nm(k)The respectively beginning and end of numerical intervals, nm(2)~nm(k-1)
It, will for the intermediate division points of numerical intervalsRespectively as corresponding numerical value
The state name in section；B22) if history O&M numerical quantities data N, falls into section [nm(d), nm(d+1)], d ∈ [1, k-1], then by shape
State nameAs field value, completes numerical quantities data and be converted into state quantity data.
C) historical load data of distribution where element is handled, obtains load condition vector VP.Specifically include with
Lower step: C1) obtain regional power grid in each distribution electricity consumption day i the horizontal P of main loadsM, a, i, i ∈ H, a ∈ A, A are region
Include in power grid matches net collective；C2 electricity consumption day main loads horizontal data) is divided into numerical intervals, using numerical intervals as state
Name, by main loads horizontal data PM, a, iIt is converted into state quantity data；C3 state quantity data) is split as Boolean quantity data, it will
Boolean quantity data are indicated with vector, as load condition vector VP.The main loads horizontal data P of electricity consumption day iM, iCalculating side
Method is the following steps are included: C11) statistics electricity consumption day i hourly average load, be denoted as GH, h ∈ [0,23]；C12) since 0, it is with Δ P
Step-length, delimit N number of load setting, and n-th load setting covers the G of electricity consumption day iH, h ∈ [0,23]Maximum value；C13) will
GH, h ∈ [0,23]The load setting being put into where it adjusts Δ P, makesWherein NpExpression is placed at least one
GH, h ∈ [0,23]Load setting sum；C14 it) obtains and is placed into GH, h ∈ [0,23]The minimum load setting of quantity, with the loading zone
Between median, the main loads horizontal data P as electricity consumption day iM, iIt participates in calculating.
D the historic state vector V of element) is establishedF, obtain element operate normally in history whole historic states for occurring to
Measure VFSet, as historic state set F.
E) periodical monitoring element and its load of place distribution, obtain element most in method identical with step B-D
New state vectorIfThen issue warning information.By handling history operation/maintenance data, warning information is generated
The foundation of generation saves artificial the step of setting data threshold, in conjunction with history operation/maintenance data, can be improved warning information
Accuracy.
Above-mentioned embodiment is only a preferred solution of the present invention, not the present invention is made in any form
Limitation, there are also other variations and modifications on the premise of not exceeding the technical scheme recorded in the claims.
Claims (8)
1. a kind of power grid active O&M warning information generation method, which is characterized in that
The following steps are included:
A the history operation/maintenance data for) obtaining each element of regional power grid, obtains the historical load data of each distribution in regional power grid；
B) each element history operation/maintenance data is handled, obtains the O&M vector V of elements；
C) historical load data of distribution where element is handled, obtains load condition vector Vp；
D the historic state vector V of element) is establishedF, obtain element and operate normally the whole historic state vector V occurred in historyF
Set, as historic state set F；
E) periodical monitoring element and its load of place distribution, the newest shape of element is obtained in method identical with step B-D
State vectorIfThen issue warning information.
2. a kind of power grid active O&M warning information generation method according to claim 1, which is characterized in that
The history operation/maintenance data of the element includes the state quantity data and numerical quantities data of element, in step B, obtains element
O&M vector VsMethod the following steps are included:
B1 the numerical quantities data of each element) are divided into numerical intervals；
B2) using numerical intervals as state name, state quantity data is converted by each component values amount data；
B3 state quantity data) is split as Boolean quantity data, Boolean quantity data are indicated with vector, as O&M vector Vs。
3. a kind of power grid active O&M warning information generation method according to claim 2, which is characterized in that
In step C, load condition vector V is obtainedPMethod the following steps are included:
C1 the horizontal P of main loads of electricity consumption day i of each distribution in regional power grid) is obtainedM, a, i, i ∈ H, a ∈ A, A are region electricity
Include in net matches net collective；
C2 electricity consumption day main loads horizontal data) is divided into numerical intervals, using numerical intervals as state name, by main loads level
Data PM, a, iIt is converted into state quantity data；
C3 state quantity data) is split as Boolean quantity data, Boolean quantity data are indicated with vector, as load condition vector Vp。
4. a kind of power grid active O&M warning information generation method according to claim 2 or 3, which is characterized in that
In step B1 by numerical quantities data divide numerical intervals method the following steps are included:
B11 the whole numerical quantities data for) obtaining history operation/maintenance data under field, are arranged successively by numerical values recited, are denoted as set Ki；
B12 the minimum value k in set Ki) is foundminWith maximum value kmax, by subregion starting point ksTax initial value is kmin, partition end ks
Tax initial value is kmax, investigation value km=ks+ n × Δ k, Δ k are the step-length manually set, and n is positive integer, and n initial value is 1；
B13) n meets the investigation value k of following condition constantly from adding 1 if it existsm:
Wherein, function N (x, y) indicates set Ki, and data value is in the data amount check of numerical intervals (x, y), then by (2km-ks) make
For interval division point and division point set Km is added, by (2km-ks) value be assigned to ks, continue to enable n constantly from adding 1, until km
> kmax；
B14) by kminAnd kmaxSet Km is added and, as division points, numerical quantities data are divided into numerical value area using the value in Km
Between.
5. a kind of power grid active O&M warning information generation method according to claim 2 or 3, which is characterized in that
In step B2, by numerical quantities data be converted into state quantity data method the following steps are included:
B21 numerical quantities data) are divided into several sections, [nm(1), nm(2)], [nm(2), nm(3)]...[nm(k-1), nm(k)],
Middle nm(1)And nm(k)The respectively beginning and end of numerical intervals, nm(2)~nm(k-1)It, will for the intermediate division points of numerical intervalsRespectively as the state name of corresponding numerical intervals；
B22) if history O&M numerical quantities data N, falls into section [nm(d), nm(d+1)], d ∈ [1, k-1], then by state nameAs field value, completes numerical quantities data and be converted into state quantity data.
6. a kind of power grid active O&M warning information generation method according to claim 3, which is characterized in that
In step C1, the main loads horizontal data P of electricity consumption day iM, iCalculation method the following steps are included:
C11 the hourly average load for) counting electricity consumption day i, is denoted as GH, h ∈ [0,23]；
C12) since 0, using Δ P as step-length, N number of load setting delimited, n-th load setting covers electricity consumption day i's
GH, h ∈ [0,23]Maximum value；
C13) by GH, h ∈ [0,23]The load setting being put into where it adjusts Δ P, makesWherein NpExpression is placed at least
One GH, h ∈ [0,23]Load setting sum；
C14 it) obtains and is placed into GH, h ∈ [0,23]The minimum load setting of quantity, with the median of the load setting, as electricity consumption day i
Main loads horizontal data PM, iIt participates in calculating.
7. a kind of power grid active O&M warning information generation method according to claim 2 or 3, which is characterized in that
The method that state quantity data is split as Boolean quantity data are as follows: whole state values of state quantity data are obtained, with state
Quantity of state field is split as multiple fields for field name by value, and field name field identical with state quantity data value is set
Position, remaining splits field zero setting, and completion status amount data are split as Boolean quantity data.
8. a kind of power grid active O&M warning information generation method according to claim 4, which is characterized in that
In step B12, the setting method of step delta k includes are as follows: the difference two-by-two of numerical quantities data in set of computations Ki is rejected and is
Zero difference carries out the operation that takes absolute value to remaining difference, using minimum value therein as step delta k, participates in calculating.
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| CN115048591A (en) * | 2022-06-17 | 2022-09-13 | 四川高融软科信息技术有限公司 | Power distribution network holographic data visualization intelligent display analysis system based on artificial intelligence |
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| CN115048591B (en) * | 2022-06-17 | 2023-09-29 | 河北新大长远电力科技股份有限公司 | Visual intelligent display analysis system of distribution network holographic data based on artificial intelligence |
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