CN106127347A - Consider the regional power grid accident load loss predictor method of voltage character of load - Google Patents
Consider the regional power grid accident load loss predictor method of voltage character of load Download PDFInfo
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Abstract
The invention discloses a kind of regional power grid accident load loss predictor method considering voltage character of load, including: load nature of electricity consumed and power device type according to user carry out load classification to area power grid；The related data of area electricity consumption user is carried out pretreatment, obtains carrying the circuit of single load type；The circuit carrying various single load type is analyzed, obtains the qualitative relationships of voltage landing degree and trouble duration and load loss degree；With voltage landing degree Δ U and trouble duration Δ T as variable, various model of fit are analyzed, choose the model of wherein R square value maximum as nonlinear fitting model, finally give with load loss Δ P as dependent variable, with voltage landing degree Δ U and the trouble duration Δ T nonlinear function as independent variable, predict the load loss of area power grid with this.This area's network load loss forecasting method is simple, can effectively predict network load damaed cordition in the case of different faults, possess bigger practical value.
Description
Technical field
The present invention relates to the technical field of power system accident afterload loss analysis, consider load electricity particularly to one
The regional power grid accident load loss predictor method of pressure characteristic.
Background technology
Electric energy is the energy economical and practical, easy to clean in current life.The day different moon new and social fast along with science and technology
Speed develops, and the power consumption needed for the whole world rises steadily, and especially manufactures more and more higher with the electrifing degree in production process,
Various emerging manufacture methods, emerging technology and the high-end devices that the change of the characteristic of power supply is the sensitiveest is put into manufacture in a large number
In, user has reached new height to the serious hope of the quality of power supply.Meanwhile, many new semiconductor devices put into and electric power electricity
Sub-device brings again the harm of the much quality of power supply to power system.Along with the continuous progress of society, generating and defeated, distribution body
The separation of system, the situation of the power industry marketization will gradually form, and electric energy is using will be by quality and quantity as a kind of special commodity
Determine the price.Therefore, solve power supply-distribution system to exist the problem of the quality of power supply, meets consumer to electricity and electric power most possibly
The demand of quality, it has also become the most highly important step.
After last century the eighties, with being used on a large scale and emerging use of the sensitive power electronic equipment of high-tech
The high speed of electricity facility updates, and the problem such as dynamic power quality more comes into one's own, the most notable, consequence ratio is more serious
One of them problem is exactly voltage dip, the most urgently proposes one and can effectively predict that each is by shadow when grid collapses
The method ringing the capacity of node excision load.
Summary of the invention
It is an object of the invention to the shortcoming overcoming prior art with not enough, it is provided that a kind of ground considering voltage character of load
District's power grid accident load loss predictor method, sets up negative by series of steps such as load classification, data screening, regression modelings
Lotus loss forecasting model, this model is for ensureing that power supply is stable, protect user's set, reducing the economic damage that fault is brought to user
Mistake, configuration relay protection, raising grid stability can provide vital with reference to foundation.
The purpose of the present invention is achieved through the following technical solutions:
A kind of regional power grid accident load loss predictor method considering voltage character of load, described method comprises following step
Rapid:
S1, load nature of electricity consumed and power device type according to user carry out load classification to area power grid；
S2, to area electricity consumption user related data carry out pretreatment, obtain carrying the circuit of single load type；
S3, the circuit carrying various single load type is analyzed, obtains voltage landing degree and time fault continues
Between with the qualitative relationships of load loss degree；
Various model of fit, as variable, are analyzed, choosing by S4, the degree Δ U and trouble duration Δ T that lands with voltage
Take the maximum model of wherein R square value as nonlinear fitting model, finally give with load loss Δ P as dependent variable, with electricity
Drop of pressure degree Δ U and trouble duration Δ T is the nonlinear function of independent variable.
Further, described step S1 specifically include following step by step:
S11, for target estimation area, according to the data with existing statistics industry kind that comprised of this area and every profession and trade institute
The typical power device used；
S12, use look-up table, obtain each typical case's power device to voltage-sensitive degree, and each power device is returned
Enter in the load classification being previously set.
Further, described load classification includes: 1) electric power, heating power, combustion gas and water production and supply industry；2) in data
The heart；3) hospital；4) construction industry；5) sophisticated manufacturing；6) transportation；7) communications industry；8) chemical industry；9) agriculture
Industry；10) the common electricity consumption of school's unit house；11) light industry manufacturing industry；12) metal smelt.
Further, described step S2 particularly as follows:
By arranging the data of electricity consumption user, exclude and comprise two kinds and the circuit of above load type, only retain and take
Circuit with single load type.
Further, described step S3 specifically comprise following step by step:
S31, the Voltage Drop situation of trouble point, duration of fault, transition impedance data when occurring according to accident, bring into
Load flow calculation network, when calculating fault generation, the Voltage Drop situation of each node line in electrical network, adds up every circuit often
Voltage Drop horizontal Δ U, fault drop-out time Δ T and the load loss Δ P of correspondence in secondary accident；
S32, find the circuit of voltage dip at least occurs in 5 accidents, and classify by failure date；
S33, reading data, in plot step S32, the Δ U-Δ P of every circuit and Δ T-Δ P scatterplot and matching are bent
Line chart, finds matching rule therein；
S34, it is chosen at the data that fit characteristic in step S33 is good, carries out regression analysis, obtain voltage landing degree Δ
The qualitative relationships of U and trouble duration Δ T and load loss Δ P.
Further, described step S4 specifically comprise following step by step:
S41, employing regression analysis instrument SPSS, carried out Δ U-Δ P, the relation of Δ T-Δ P under various nonlinear models
Analyze, and choose the maximum nonlinear model of R square value as object module；
Under the corresponding model that S42, employing step S41 are obtained, the parameter of Δ U and Δ T is as initial parameter, is input to non-
In linear regression analysis, use sequence quadratic programming method, finally give with Δ P as dependent variable, non-for independent variable with Δ T with Δ U
Linear functional relation, the load loss of area power grid when predicting that fault occurs with this.
Further, in described step S4, R square value is defined as follows:
R square value is the ratio that regression sum of square accounts for total sum of squares, and wherein the calculation expression of regression sum of square is:WhereinRepresent the value obtained according to regression forecasting；Represent the average of sample, be defined as:The calculation expression of total sum of squares is:
The present invention has such advantages as relative to prior art and effect:
The present invention has simple advantage, it is possible under conditions of the fault data of power supply enterprise's grasp is limited preferably
Simulate the loss of this area network load and voltage landing degree and the relation of trouble duration, thus effectively under prediction
Load loss amount when secondary accident occurs, and the increasing of data volume that the order of accuarcy that calculates of the method is grasped along with power supply enterprise
Add and improve constantly, it is possible to the accident afterload to electrical network loses and carries out prediction the most accurately.
Accompanying drawing explanation
Fig. 1 is the stream of the regional power grid accident load loss predictor method considering voltage character of load disclosed in the present invention
Journey block diagram；
Fig. 2 is the scatterplot of voltage landing degree Δ U and load loss amount Δ P；
Fig. 3 is the matched curve figure of voltage landing degree Δ U and load loss amount Δ P；
Fig. 4 is the scatterplot of trouble duration Δ T and load loss amount Δ P；
Fig. 5 is the matched curve figure of trouble duration Δ T and load loss amount Δ P.
Detailed description of the invention
For making the purpose of the present invention, technical scheme and advantage clearer, clear and definite, develop simultaneously embodiment pair referring to the drawings
The present invention further describes.Should be appreciated that specific embodiment described herein, and need not only in order to explain the present invention
In limiting the present invention.
Embodiment
Referring to Fig. 1, Fig. 1 is the regional power grid accident load loss considering voltage character of load disclosed in the present embodiment
The process step figure of predictor method.The regional power grid accident load loss predictor method considering voltage character of load shown in Fig. 1,
Specifically include following steps:
S1, load nature of electricity consumed and power device type according to user carry out load classification to area power grid；
S2, to area electricity consumption user related data carry out pretreatment, obtain carrying the circuit of single load type；
S3, the circuit carrying various single load type is analyzed, obtains voltage landing degree and time fault continues
Between with the qualitative relationships of load loss degree；
Various model of fit, as variable, are analyzed, choosing by S4, the degree Δ U and trouble duration Δ T that lands with voltage
Take the maximum model of wherein R square value as nonlinear fitting model, finally give with load loss Δ P as dependent variable, with electricity
Drop of pressure degree Δ U and trouble duration Δ T is the nonlinear function of independent variable.
Wherein, in described step S4, R square value is defined as follows:
R square value is the ratio that regression sum of square accounts for total sum of squares, and wherein the calculation expression of regression sum of square is:WhereinRepresent the value obtained according to regression forecasting；Represent the average of sample, be defined as:The calculation expression of total sum of squares is:
In concrete application, area power grid is born by step S1, load nature of electricity consumed and power device type according to user
Lotus is classified, and comprises the steps of
S11, for objective area, the industry kind and the every profession and trade that are comprised according to related data statistics this area are used
Typical power device；
S12, use look-up table, obtain each typical case's power device to voltage-sensitive degree, and each power device is returned
Enter in 12 kinds of load classification that the present invention is summed up.Load classification is as shown in the table:
Table 1. load classification
| Numbering | Industry |
| 1 | Electric power, heating power, combustion gas and water production and supply industry |
| 2 | Data center |
| 3 | Hospital |
| 4 | Construction industry |
| 5 | Sophisticated manufacturing |
| 6 | Transportation |
| 7 | The communications industry |
| 8 | Chemical industry |
| 9 | Agricultural |
| 10 | The common electricity consumption of school's unit house |
| 11 | Light industry manufacturing industry |
| 12 | Metal smelt |
In concrete application, described step S2, particularly as follows: the related data of area electricity consumption user is carried out pretreatment, excludes
Comprise two kinds and the circuit of above load type, only retain the circuit carrying single load type.
The load classification and the line related number that arrange the corresponding somewhere obtained are as shown in table 2 below:
Table 2. all kinds of load line way
In concrete application, described step S3, the circuit carrying various single load type is analyzed, obtains voltage drop
The qualitative relationships of the degree that falls and trouble duration and load loss degree.According to step S2 statistics obtain as a result, it is possible to see
The number of lines comprised to school's unit house common electricity consumption type load is most, in order to ensure the accuracy of result, the present invention
Further the circuit comprising the type load is analyzed.Comprise the steps of
S31, the data such as the Voltage Drop situation of trouble point, duration of fault, transition impedance, band when occurring according to accident
Calculating network after the fashion, the Voltage Drop situation of each node line in electrical network when calculating fault generation.Add up every circuit to exist
Voltage Drop horizontal Δ U, fault drop-out time Δ T and the load loss Δ P of correspondence in fault every time；
S32, find the circuit of voltage dip at least occurs in 5 accidents, and classify by failure date；
S33, read data by MATLAB, the Δ U-Δ P of every circuit and Δ T-Δ P scatterplot in plot step S32
Figure and matched curve, find matching rule therein；
Processed by data, obtain the scatterplot of Δ U-Δ P and matched curve as shown in Figure 2 and Figure 3；And Δ T-Δ P's is scattered
Point diagram and matched curve are as shown in Figure 4, Figure 5.
S34, it is chosen at the data that fit characteristic in step S33 is good, carries out regression analysis, obtain voltage landing degree Δ
The qualitative relationships of U and trouble duration Δ T and load loss Δ P.
Table 3. Δ U regression analysis
As can be seen from the above table, the standardized regression coefficient of Δ U is 0.563.According to theory of regression analysis, standardized regression
Coefficient is the biggest, and the impact of this independent variable is the biggest, it can be deduced that conclusion, and Δ U and Δ P presents significant positive correlation.
In like manner, the relation that can obtain Δ T and Δ P is as shown in the table:
Table 4 Δ T regression analysis
According to table 4 it can be seen that Δ T and Δ P also presents significant positive correlation.
In concrete application, step S4, matching obtain load loss Δ P and voltage landing degree Δ U and trouble duration
The non-linear relation of Δ T, comprises the steps of
S41, use regression analysis instrument SPSS, the relation of Δ U under various nonlinear models and Δ T Yu Δ P is carried out point
Analysis, and choose the maximum nonlinear model of R square value as object module；
Respectively logarithmic model, conic model, power model, exponential model are carried out model total and parameter evaluation,
Obtain result as shown in the table:
The model of table 5. variable Δ U amounts to
The model of table 6. variable Δ T amounts to
As can be seen from the above table, the R square value of conic section is maximum, therefore conic model should be used to be fitted.
Under the corresponding model that S42, employing S41 are obtained, the parameter of Δ U and Δ T is as initial parameter, is input to non-linear
In regression analysis, use sequence quadratic programming method, finally give the nonlinear function of Δ P and Δ U and Δ T, predict with this
The load loss of area power grid when fault occurs
In sequence programming method, arranging step-length is 2, and iterations is set to 200, and iteration course is as follows:
Table 7. iteration result
Note: in " iterations " arranges, main iterations is on the left of arithmetic point, and secondary iterations is right at arithmetic point
Side.
Stop after iteration 15 times, obtain optimal solution, nonlinear regression can be obtained according to result in table
Expression formula, as follows:
Δ P=0.233 Δ U-0.428 Δ U2-4.272ΔT+46.41ΔT2+0.11
The most just obtain the relation of accident afterload loss Δ P and Δ U and Δ T in the circuit of the 10th type load type,
The load of remaining type equally obtains the relation being similar to according to step S3-S5.Finally, the relation of whole 12 kinds of load types
Add up and can be obtained by total expression formula.
In sum, the present invention provides a kind of regional power grid accident load loss side of estimating considering voltage character of load
Method, sets up load loss forecast model by series of steps such as load classification, data screening, regression modelings, this model pair
In economic loss, the configuration relay protection ensureing that power supply is stable, protecting user's set, reduction fault to bring to user, improve electricity
Net stability can provide vital with reference to foundation.The inventive method has simple advantage, it is possible in power supply enterprise
Preferably simulate under conditions of fault data that industry is grasped is limited the loss of this area network load and voltage landing degree and
The relation of trouble duration, thus effectively prediction next time accident occur time load loss amount, and the method calculate accurate
The increase of the data volume that degree is grasped along with power supply enterprise and improve constantly, it is possible to after the most accurately to the accident of electrical network
Load loss carries out prediction.
Above-described embodiment is the present invention preferably embodiment, but embodiments of the present invention are not by above-described embodiment
Limit, the change made under other any spirit without departing from the present invention and principle, modify, substitute, combine, simplify,
All should be the substitute mode of equivalence, within being included in protection scope of the present invention.
Claims (7)
1. the regional power grid accident load loss predictor method considering voltage character of load, it is characterised in that described method
Comprise the steps of
S1, load nature of electricity consumed and power device type according to user carry out load classification to area power grid；
S2, to area electricity consumption user related data carry out pretreatment, obtain carrying the circuit of single load type；
S3, the circuit carrying various single load type is analyzed, obtain voltage landing degree and trouble duration with
The qualitative relationships of load loss degree；
Various model of fit, as variable, are analyzed, choose it by S4, the degree Δ U and trouble duration Δ T that lands with voltage
The model of middle R square value maximum, as nonlinear fitting model, finally gives with load loss Δ P as dependent variable, with voltage drop
The degree that falls Δ U and trouble duration Δ T is the nonlinear function of independent variable.
The regional power grid accident load loss predictor method of consideration voltage character of load the most according to claim 1, it is special
Levy and be, described step S1 specifically include following step by step:
S11, for target estimation area, used according to the data with existing statistics industry kind that comprised of this area and every profession and trade
Typical power device；
S12, use look-up table, obtain each typical case's power device to voltage-sensitive degree, and each power device is included into thing
In the load classification first set.
The regional power grid accident load loss predictor method of consideration voltage character of load the most according to claim 2, it is special
Levying and be, described load classification includes: 1) electric power, heating power, combustion gas and water production and supply industry；2) data center；3) hospital；4)
Construction industry；5) sophisticated manufacturing；6) transportation；7) communications industry；8) chemical industry；9) agricultural；10) school's unit
The common electricity consumption of house；11) light industry manufacturing industry；12) metal smelt.
The regional power grid accident load loss predictor method of consideration voltage character of load the most according to claim 1, it is special
Levy and be, described step S2 particularly as follows:
By arranging the data of electricity consumption user, exclude and comprise two kinds and the circuit of above load type, only retain and carry list
The circuit of one load type.
The regional power grid accident load loss predictor method of consideration voltage character of load the most according to claim 1, it is special
Levy and be, described step S3 specifically comprise following step by step:
S31, the Voltage Drop situation of trouble point, duration of fault, transition impedance data when occurring according to accident, carry after the fashion
Calculating network, when calculating fault generation, the Voltage Drop situation of each node line in electrical network, adds up every circuit in each thing
Voltage Drop horizontal Δ U, fault drop-out time Δ T and the load loss Δ P of correspondence in therefore；
S32, find the circuit of voltage dip at least occurs in 5 accidents, and classify by failure date；
S33, read data, the Δ U-Δ P of every circuit and Δ T-Δ P scatterplot and matched curve figure in plot step S32,
Find matching rule therein；
S34, be chosen at the data that fit characteristic in step S33 is good, carry out regression analysis, obtain voltage landing degree Δ U and
The qualitative relationships of trouble duration Δ T and load loss Δ P.
The regional power grid accident load loss predictor method of consideration voltage character of load the most according to claim 1, it is special
Levy and be, described step S4 specifically comprise following step by step:
S41, employing regression analysis instrument SPSS, be analyzed Δ U-Δ P, the relation of Δ T-Δ P under various nonlinear models,
And choose the maximum nonlinear model of R square value as object module；
Under the corresponding model that S42, employing step S41 are obtained, the parameter of Δ U and Δ T is as initial parameter, is input to non-linear
In regression analysis, use sequence quadratic programming method, finally give with Δ P as dependent variable, non-linear for independent variable with Δ T with Δ U
Functional relationship, the load loss of area power grid when predicting that fault occurs with this.
The regional power grid accident load loss predictor method of consideration voltage character of load the most according to claim 1, it is special
Levying and be, in described step S4, R square value is defined as follows:
Described R square value is the ratio that regression sum of square accounts for total sum of squares, and wherein the calculation expression of regression sum of square is:WhereinRepresent the value obtained according to regression forecasting；Represent the average of sample, be defined as:The calculation expression of total sum of squares is:
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110705801A (en) * | 2019-10-10 | 2020-01-17 | 国网山东省电力公司泰安供电公司 | Power grid accident economic loss estimation method and system based on fault loss electric quantity |
| CN111245097A (en) * | 2020-02-21 | 2020-06-05 | 国网山东省电力公司宁阳县供电公司 | Intelligent power grid management and control system and method |
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| CN110705801A (en) * | 2019-10-10 | 2020-01-17 | 国网山东省电力公司泰安供电公司 | Power grid accident economic loss estimation method and system based on fault loss electric quantity |
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Application publication date: 20161116 |