CN108376194B - Insulator pollution accumulation prediction method based on atmospheric environment parameters - Google Patents

Insulator pollution accumulation prediction method based on atmospheric environment parameters Download PDF

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CN108376194B
CN108376194B CN201810144520.8A CN201810144520A CN108376194B CN 108376194 B CN108376194 B CN 108376194B CN 201810144520 A CN201810144520 A CN 201810144520A CN 108376194 B CN108376194 B CN 108376194B
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张志劲
张东东
蒋兴良
舒立春
胡建林
胡琴
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Abstract

The invention provides an insulator contamination accumulation prediction method based on atmospheric environment parameters, which comprises the following steps: s1: collecting atmospheric environment parameters; s2: sequentially carrying out pretreatment and discretization on the particle size and the mass concentration of the atmospheric pollution particles in the atmospheric environment parameters to form a particle mass concentration-particle size discrete relation set; s4: acquiring mass concentration of atmospheric pollution particles in a particle mass concentration-particle size discrete relation set, calling insulator surface area pollution amount in an insulator pollution amount database in unit time, and calculating insulator surface pollution amount increment in each detection time period; s5: and superposing the insulator surface dirt accumulation increment in each detection time period to obtain the total insulator surface dirt accumulation amount in the continuous dirt accumulation time period. According to the method, the field insulator pollution degree measurement is carried out without organizing manpower, and the surface area pollution amount of the insulator is predicted only by conventional atmospheric environment parameter detection, so that the insulation pollution state outside the power transmission and distribution network is obtained.

Description

Insulator pollution accumulation prediction method based on atmospheric environment parameters
Technical Field
The invention relates to a prediction method of surface area pollution of an insulator, in particular to a dynamic prediction method of insulator pollution accumulation based on atmospheric environment parameters.
Background
The external insulation characteristic is one of the key technologies of the extra-high voltage direct current transmission project. In the construction of ultra-high voltage transmission, the span of a transmission corridor is continuously enlarged, so that an overhead line is difficult to pass through various polluted areas in complex environments. And the atmospheric pollutants in the dirty area subside on the surface of external insulation equipment to form the deposition, under the unfavorable meteorological condition that humidity is higher (like fog, dew, mao rain, snow melt), thereby the external insulation surface foul layer will obtain moist and have conductivity for foul layer surface conductance and leakage current under the operating voltage will greatly increased, thereby lead to insulating properties to reduce, even cause the surface flashover, cause the pollution flashover accident. According to statistics, large-area pollution flashover accidents are usually concentrated in economically developed and densely populated areas, almost occur every year, and pollution flashover peak occurs every 5 to 6 years, the damage of the pollution flashover peak is far greater than that of other kinds of power grid faults, and in the 80-90 years of the 20 th century, the pollution flashover accident frequency is 2 nd in the total frequency of the power grid accidents and is only second to the thunder damage, but the loss caused by the pollution flashover accident is ten times that of the thunder damage accident. Currently, in order to conveniently determine the level of a power grid polluted area, and carry out related work such as circuit external insulation design, circuit insulator cleaning and creepage distance adjustment, an electric power operation department usually uses manpower to carry out field insulator pollution degree measurement as a main means so as to determine the pollution state of a circuit. The method is complex to operate and needs to consume a large amount of manpower and material resources.
Therefore, a simple and feasible dynamic prediction method for insulator pollution accumulation, which saves manpower and material resources, is needed.
Disclosure of Invention
In view of the above, the present invention provides an insulator contamination accumulation prediction method based on atmospheric environmental parameters, which establishes a single-bit time insulator contamination accumulation database of a discrete relationship set of atmospheric environmental parameters by performing data fitting, discretization, simulation, and the like on the acquired atmospheric parameters, so as to conveniently call the mass concentration of atmospheric contamination particles in the particle mass concentration-particle diameter discrete relationship set and the unit time insulator surface contamination amount in the unit time insulator contamination accumulation database according to the acquired atmospheric parameters, and calculate the total insulator surface contamination accumulation amount for a continuous contamination accumulation time period. According to the method, manual work is not required to be organized to carry out field insulator pollution degree measurement, only conventional atmospheric environment parameter detection is required to predict the surface area pollution amount of the insulator, manpower and material resources are saved, meanwhile, dynamic prediction of pollution accumulation is achieved, and the insulating pollution state of the power transmission and distribution network is obtained.
The invention provides an insulator contamination accumulation prediction method based on atmospheric environment parameters, which comprises the following steps:
s1: collecting atmospheric environment parameters, wherein the atmospheric environment parameters comprise the particle size and mass concentration of atmospheric pollution particles;
s2: pretreating the particle size and mass concentration of the atmospheric pollution particles in the atmospheric environment parameters to form a pollution particle mass fraction-particle size continuous function, and discretizing the continuous function to form a particle mass concentration-particle size discrete relation set;
s4: according to the collected atmospheric parameters, acquiring the mass concentration of atmospheric pollution particles in a particle mass concentration-particle diameter discrete relation set, calling the surface area pollution amount of the insulator in an insulator pollution amount database in unit time, and calculating the surface area pollution increment of the insulator in each detection time period;
s5: and superposing the insulator surface dirt accumulation increment in each detection time period to obtain the total insulator surface dirt accumulation amount in the continuous dirt accumulation time period.
Further, the atmospheric environment parameter further includes a wind speed of the atmospheric environment;
and comparing the collected real-time wind speed and the real-time particle size of the atmospheric pollution particles with an insulator accumulated pollution amount database in unit time to obtain the current surface area pollution amount of the insulator.
Further, in the step S4, the calculation formula of the insulator surface contamination accumulation increment in each detection period is
Figure BDA0001578459570000021
Wherein, cp0Is a reference mass concentration; c. Cpi(dp) The particle diameter in the i time period is dpThe mass concentration of the dirt particles is corresponding to the mass concentration of the dirt particles; viWind speed for the ith time period; t is tiIs the duration of the ith time period; rhom(Vi,dp) At the reference mass concentration, the wind speed is ViA particle diameter of dpIn the case of (3), the amount of dirt deposited per unit time on the surface of the insulator; dpMThe maximum value of the particle size of the atmospheric particulates in the ith time period; delta phimiThe insulator surface fouling increment is the i-th period.
Further, in step S5, the calculation formula of the total amount of accumulated dirt on the surface of the insulator during the continuous dirt accumulation period is:
Figure BDA0001578459570000031
wherein, N means dividing the continuous dirt accumulation time period into N detection time periods; h is the time sum of N detection time periods; phim(H) The final pollution amount generated by the atmospheric pollution particles on the surface of the insulator under the continuous pollution accumulation H time.
Further, the step S2 of preprocessing the particle size and mass concentration of the atmospheric pollution particles in the atmospheric environmental parameters to form a continuous function of mass fraction-particle size of the pollution particles includes:
setting the particle size in the air to be less than d in the ith (i is more than or equal to 1 and less than or equal to N) time periodpThe mass fraction of the filthy particles is lambdai(dp)：
Figure BDA0001578459570000032
Wherein d is0Is the reference particle size of the dirt particles; lambda [ alpha ]i(dp) In the i time period, the particle size in the air is less than dpThe mass fraction of the fouling particles; c. Ci(dp) In the i time period, the particle size in the air is less than dpThe mass concentration of the fouling particles; c. Ci(d0) In the i time period, the particle size in the air is less than d0The mass concentration of the fouling particles;
setting the relationship between the mass fraction and the particle size of the atmospheric pollution particles under the atmospheric environment pollution to satisfy Rosin-Rammer distribution:
Figure BDA0001578459570000033
wherein n is1Is a distribution characteristic index; n is2Is a distribution characteristic coefficient;
substituting the mass concentrations of the collected atmospheric pollution particles with different particle diameters in the ith time period into the formulas (3) and (4), and calculating to obtain n1And n2A value of (d); n is to be1And n2Substituting the value of (a) into the formula (4) to obtain a continuous function of mass fraction-particle size of the atmospheric pollution particles in the ith time period;
further, the discretizing of the mass fraction-particle size continuous function of the contaminant particles in the step S2 includes discretizing the particle size dpChanging the formula (4) into the formula (3) according to the fixed variable at equal intervals to obtain a particle mass concentration-particle size dispersion relation set;
the calculation formula of the particle mass concentration in the particle mass concentration-particle size dispersion relation set is as follows:
Figure BDA0001578459570000041
wherein, Δ dpAs a fixed variable of the size of the discretized foulant particle, cpi(dp) The particle diameter in the i time period is dpThe mass concentration of the dirt particles is corresponding to the mass concentration of the dirt particles;
and 4, calling the corresponding mass concentration of the atmospheric pollution particles in the formula (5) in the particle mass concentration-particle diameter discrete relation set according to the actually collected mass concentration of the pollution particles with the particle diameter smaller than the reference particle diameter in each detection time period and the actually collected particle diameter of the atmospheric pollution particles.
Further, step S4 is preceded by:
s3: in the atmospheric environment with different wind speeds and different pollution particle diameters, simulation calculation is carried out on the deposition of the pollution particles on the surface of the insulator, and a database of the volume pollution of the insulator in unit time is built;
and S4, comparing the acquired real-time wind speed and the real-time particle size of the atmospheric pollution particles with the insulator pollution amount database in unit time to obtain the current surface area pollution amount of the insulator.
Further, in step S3, the simulation calculation of deposition of dirty particles on the surface of the insulator in the atmospheric environment with different wind speeds and different particle sizes of the dirty particles includes:
using Comsol multi-physical field finite element software at preset wind speed ViParticle size d of dirt particlespSimulating the steady-state distribution of an electrostatic field and a flow field around the insulator in the atmospheric environment;
simulating and calculating the motion and deposition process of the dirt particles under the comprehensive action of an electric field and a flow field by using a particle tracking module of Comsol multi-physical-field finite element software to obtain a preset particle size d in unit timepWind speed ViCorresponding insulator surface area pollution amount rhom(Vi,dp) Established to a preset wind speed ViParticle diameter dpAnd a corresponding insulator deposition amount database per unit time.
The invention has the beneficial effects that: the invention establishes a single-bit time insulator dirt accumulation database of a discrete relation set of atmospheric environmental parameters by carrying out data fitting, discretization, simulation and other processing on the acquired atmospheric parameters, thereby conveniently calling the mass concentration of atmospheric dirt particles in a particle mass concentration-particle diameter discrete relation set and the insulator surface dirt amount in unit time in the insulator dirt accumulation database according to the acquired atmospheric parameters and calculating the total insulator surface dirt amount in a continuous dirt accumulation time period. According to the method, manual work is not required to be organized to carry out field insulator pollution degree measurement, only conventional atmospheric environment parameter detection is required to predict the surface area pollution amount of the insulator, manpower and material resources are saved, meanwhile, dynamic prediction of pollution accumulation is achieved, and the insulating pollution state of the power transmission and distribution network is obtained.
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The invention is further described below with reference to the following figures and examples:
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
As shown in fig. 1, the method for predicting insulator contamination deposition based on atmospheric environmental parameters provided by the invention comprises the following steps:
s1: collecting atmospheric environment parameters, wherein the atmospheric environment parameters comprise the particle size and mass concentration of atmospheric pollution particles.
TSP, PM10, and PM2.5 are three common standard atmospheric foul particles, the standards and methods for collection are mature.
Wherein TSP is an abbreviation of English Total Suspended Particulate, namely Total Suspended Particulate, which is air pollution particles with the particle size of less than 100 mu m;
PM in PM10 and PM2.5 is an abbreviation for Particulate matter in english.
Wherein, PM10 is atmospheric pollution particulate matter with particle size less than 10 μm; PM2.5 is atmospheric pollution particles with the particle size of less than 2.5 mu m.
Therefore, in the embodiment, the continuous pollutant accumulation time period is divided into N detection time periods, and the mass concentrations of the three kinds of atmospheric pollutant particulate matters, namely TSP, PM10 and PM2.5, in the ith detection time period are collected.
S2: pretreating the particle size and mass concentration of the atmospheric pollution particles in the atmospheric environment parameters to form a pollution particle mass fraction-particle size continuous function, and discretizing the continuous function to form a particle mass concentration-particle size discrete relation set;
s4: according to the collected atmospheric parameters, acquiring the mass concentration of atmospheric pollution particles in a particle mass concentration-particle diameter discrete relation set, calling the surface area pollution amount of the insulator in an insulator pollution amount database in unit time, and calculating the surface area pollution increment of the insulator in each detection time period;
s5: the method includes the steps that insulator surface accumulated dirt increments in all detection time periods are superposed to obtain insulator surface total accumulated dirt amount in a continuous dirt accumulation time period, collected atmospheric parameters are subjected to data fitting, discretization, simulation and the like, a single-bit time insulator accumulated dirt amount database of a discrete relation set of atmospheric environmental parameters is established, accordingly, the mass concentration of atmospheric dirt particles in a particle mass concentration-particle diameter discrete relation set and the unit time insulator surface area dirt amount in the unit time insulator accumulated dirt amount database are called conveniently according to the collected atmospheric parameters, and the insulator surface total accumulated dirt amount in the continuous dirt accumulation time period is calculated. According to the method, manual work is not required to be organized to carry out field insulator pollution degree measurement, only conventional atmospheric environment parameter detection is required to predict the surface area pollution amount of the insulator, manpower and material resources are saved, meanwhile, dynamic prediction of pollution accumulation is achieved, and the insulating pollution state of the power transmission and distribution network is obtained.
In this embodiment, in the step S4, the calculation formula of the increment of the surface contamination accumulation of the insulator in each detection time period is
Figure BDA0001578459570000061
Wherein, cp0Taking 15mg/m as reference mass concentration3；cpi(dp) The particle diameter in the i time period is dpThe mass concentration of the dirt particles is corresponding to the mass concentration of the dirt particles; viWind speed for the ith time period; t is tiIs the duration of the ith time period; rhom(Vi,dp) At the reference mass concentration, the wind speed is ViA particle diameter of dpIn the case of (3), the amount of dirt deposited per unit time on the surface of the insulator; dpMThe maximum value of the particle size of the atmospheric particulates in the ith time period; delta phimiThe insulator surface fouling increment is the i-th period.
In step S5, the formula for calculating the total amount of accumulated dirt on the surface of the insulator in the continuous dirt accumulation period is:
Figure BDA0001578459570000062
wherein, N means dividing the continuous dirt accumulation time period into N detection time periods; h is the time sum of N detection time periods; phim(H) The final pollution amount generated by the atmospheric pollution particles on the surface of the insulator under the continuous pollution accumulation H time.
In this embodiment, the step S2 of preprocessing the particle size and mass concentration of the atmospheric pollution particles in the atmospheric environment parameter to form a continuous function of mass fraction-particle size of the pollution particles includes:
setting the time period of i (i is more than or equal to 1 and less than or equal to N) in airMedium particle diameter less than dpThe mass fraction of the filthy particles is lambdai(dp)：
Figure BDA0001578459570000071
Wherein d is0Is the standard grain diameter of the dirt particles, and the unit is mum; in this embodiment d0Taking 100 mu m; lambda [ alpha ]i(dp) In the i time period, the particle size in the air is less than dpThe mass fraction of the fouling particles; c. Ci(dp) In the i time period, the particle size in the air is less than dpThe mass concentration of the fouling particles; c. Ci(d0) In the i time period, the particle size in the air is less than d0The mass concentration of the filth particles.
In this embodiment, ci(d0) I.e. ci(100) The mass concentration of TSP in the i-th period.
Setting the relationship between the mass fraction and the particle size of the atmospheric pollution particles under the atmospheric environment pollution to satisfy Rosin-Rammer distribution:
Figure BDA0001578459570000072
wherein n is1Is a distribution characteristic index; n is2Are distribution characteristic coefficients.
Combining equations (3) and (4), obtaining three data points for equation (4) based on the mass concentrations of TSP, PM10, PM2.5 atmospheric pollutant particulate matter in the i-th time period:
Figure BDA0001578459570000073
Figure BDA0001578459570000074
Figure BDA0001578459570000075
wherein, Ci(100)、Ci(10)、Ci(2.5) the mass concentrations of TSP, PM10 and PM2.5 atmospheric pollution particles in the ith time period are respectively, and the unit is mg/m3。
Calculating the formulas (6), (7) and (8) to obtain n1And n2A value of (d); n is to be1And n2Substituting the value of (a) into the formula (4) to obtain a continuous function of mass fraction-particle size of the atmospheric pollution particles in the ith time period;
the discretization of the mass fraction-particle size continuous function of the dirt particles in the step S2 includes the step of discretizing the particle size dpChanging the formula (4) into the formula (3) according to the fixed variable at equal intervals to obtain a particle mass concentration-particle size dispersion relation set;
the calculation formula of the particle mass concentration in the particle mass concentration-particle size dispersion relation set is as follows:
Figure BDA0001578459570000082
wherein, Δ dpAs a fixed variable of the size of the discretized foulant particle, cpi(dp) The particle diameter in the i time period is dpThe mass concentration of the dirt particles corresponds to.
In this example, d is 1 μm. ltoreq.p≤100μm，ΔdpTaking 1 μm, the collection of particle mass concentration-particle size discrete relation is:
{cpi(dp)|cpi(dp)≈ci(d0)[λ(dp)-λ(dp-Δdp)]，1μm≤dp≤100μm，dp∈N，Δdp＝1μm}(9)
specifically, the calculation formula of each element in the particle mass concentration-particle size dispersion relation set is as follows:
Figure BDA0001578459570000081
in this example, the particle diameter d was obtainedpAnd (3) a particle mass concentration-particle diameter discrete relation set with the value range of 1-100 mu m is used for insulator pollution accumulation prediction and calling, namely, the corresponding atmospheric pollution particle mass concentration in the (10) formula in the particle mass concentration-particle diameter discrete relation set is called according to the actually collected mass concentration of pollution particles with the particle diameter smaller than the reference particle diameter in the air in each detection time period and the particle diameter of the atmospheric pollution particles to be called in the step 4.
In the embodiment, when the atmospheric parameters are collected, the mass concentration of the atmospheric pollution particles with a certain determined particle size is collected, the operation is relatively difficult, but the collection of the mass concentrations of all the atmospheric pollution particles with the particle sizes smaller than or equal to a certain determined particle size value is a conventional mature operation mode, the operation is simple, and the collected parameters are accurate and reliable. As in this embodiment, the mass concentrations of TSP, PM10, and PM2.5 collected are mass concentrations of atmospheric contaminant particulate matter having a particle size less than or equal to a certain determined particle size value, which are commonly used in meteorological parameter collection. The method for solving the mass concentrations of the atmospheric pollution particulate matters with various particle sizes by collecting the mass concentrations of the TSP, the PM10 and the PM2.5 is simple and easy to implement, and has general popularization.
The quality concentration of all the atmospheric pollution particles of which the collected particle diameters are less than or equal to a certain determined particle diameter value is converted into the quality concentration of the atmospheric pollution particles of which the particle diameters are a certain determined value through discretization treatment, so that the collection operation of atmospheric environment parameters is simplified, the quality concentration corresponding to the particle diameters of the atmospheric pollution particles is solved, the surface pollution increment of the insulator is calculated, and the parameters which are simple to operate and collected are accurate and reliable.
In the embodiment, manual work is not required to be organized to carry out field insulator pollution degree measurement, only the mass concentration of all the atmospheric pollution particles with the particle size smaller than or equal to a certain particle size value is required to be subjected to conventional detection, and the mass concentration of the atmospheric pollution particles corresponding to the determined particle size value for calculating the insulator surface pollution increment in each detection time period can be obtained by performing pretreatment and discretization on the mass concentration of the detected atmospheric pollution particles and the corresponding particle size, so that the manual work, the material resources and the simplicity and the practicability are saved.
The step S4 is preceded by:
s3: and (3) carrying out simulation calculation on the deposition of the polluted particles on the surface of the insulator under the atmospheric environment with different wind speeds and different particle sizes of the polluted particles, and constructing a database of the volume pollution of the insulator in unit time.
And S4, comparing the acquired real-time wind speed and the real-time particle size of the atmospheric pollution particles with the insulator pollution amount database in unit time to obtain the current surface area pollution amount of the insulator.
In the step S3, the simulation calculation of deposition of the dirty particles on the surface of the insulator in the atmospheric environment with different wind speeds and different sizes of the dirty particles includes:
using Comsol multi-physical field finite element software at preset wind speed ViParticle size d of dirt particlespAnd simulating the steady distribution of the electrostatic field and the flow field around the insulator in the atmospheric environment.
In this embodiment, the wind speed ViPresetting to be 1-5 m/s, and the interval is 0.2 m/s; particle diameter dpIt is preset to 1-50 μm with 1 μm intervals.
Simulating and calculating the motion and deposition process of the dirt particles under the comprehensive action of an electric field and a flow field by using a particle tracking module of Comsol multi-physical-field finite element software to obtain a preset particle size d in unit timepWind speed ViCorresponding insulator surface area pollution amount rhom(Vi,dp) Established to a preset wind speed ViParticle diameter dp(wind velocity V)iTaking 1-5 m/s with the interval of 0.2 m/s; particle diameter dp1-100 μm at an interval of 1 μm) for insulator contamination prediction, i.e., step S4.
The following is further exemplified:
in the insulator deposition amount database per unit time, the wind speed V of one atmospheric environmentiAnd a particle size d of atmospheric pollution particlespCorresponding to the surface pollution amount rho of an insulatorm(Vi,dp)
Real-time wind speed V of the collected detection time periodiAnd real-time particle size d of atmospheric pollution particlespComparing with the insulator accumulated dirt amount database in unit time to find the same wind speed ViParticle size d of atmospheric pollution particlespAnd acquiring the corresponding surface area pollution amount of the current insulator.
The following examples further illustrate:
when the collected real-time wind speed is 3m/s and the real-time particle size of the atmospheric pollution particles is 55 microns, the collected real-time wind speed is brought into a (3m/s, 55 microns) insulator pollution amount database in unit time for comparison, and if the wind speed is the same as that of the insulator pollution amount database in unit time and the particle size of the atmospheric pollution particles is the same as that of the insulator pollution amount database in unit time, the insulator surface area pollution amount rho corresponding to the (3m/s, 55 microns) in unit time can be obtained from the insulator pollution amount database in unit timem(3,55)。
In this embodiment, since the wind speed and the particle diameter in the insulator deposition amount per unit time database are discrete values, the input (V) may occuri,dp) The wind speed and particle size in the database cannot be matched. When inputting (V)i,dp) (V) input when calling the insulator deposition amount per unit time databasei,dp) When the wind speed and the particle size in the database cannot be corresponded, searching the sum (V) in the databasei,dp) The nearest four points of the unit time pollution amount database is approximated by a linear interpolation method to obtain (V)i,dp) The corresponding amount of accumulated dirt per unit time.
The following examples further illustrate:
when the collected real-time wind speed is 3.5m/s and the real-time particle size of the atmospheric pollution particles is 55.4 microns, the collected real-time wind speed is brought into a (3.5m/s, 55.4 microns) unit time pollution amount database for comparison, and no corresponding wind speed and particle size data of the atmospheric pollution particles exist. At this time, 4 points closest to (3.5m/s, 55.4 μm), i.e., (3m/s, 55 μm), (3m/s, 56 μm), (4m/s, 55 μm), (4m/s, 56 μm) in the data were searched. The 4 points are brought into a unit time dirt accumulation database for comparison, and the unit time insulator surface area dirt amount rho corresponding to the four points is obtainedm(3,55)，ρm(3,56)，ρm(4,55)，ρm(4,56). Rho is obtained by adopting a linear interpolation method for the surface area pollution of the four insulators in unit timem(3.5, 55.4) calculated as follows:
Figure BDA0001578459570000111
in this embodiment, once the insulator deposition and contamination amount database in unit time is established, in each detection time period, the real-time wind speed and the real-time particle size of the atmospheric contamination particles acquired in each detection time period can be compared with the insulator deposition and contamination amount database in unit time to directly acquire the corresponding insulator deposition and contamination amount in unit time, and the insulator deposition and contamination amount database in unit time does not need to be repeatedly established in each detection time period, so that the calculation accuracy is ensured, and the calculation process is simplified.
When the insulator pollution amount of the atmospheric environmental parameters is actually predicted, the insulator pollution amount of the current detection time period is directly obtained by comparing the detected wind speed and the particle size of the atmospheric pollution particles with an insulator pollution amount database in unit time, field insulator pollution degree measurement is carried out without organizing manpower, and the insulator surface area pollution amount is predicted only by conventional atmospheric environmental parameter detection, so that the manpower and material resources are saved, the dynamic prediction of the pollution accumulation is realized, and the insulating pollution state outside the power transmission and distribution network is obtained.
Finally, the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all of them should be covered in the claims of the present invention.

Claims (7)

1. An insulator contamination accumulation prediction method based on atmospheric environment parameters is characterized by comprising the following steps: the method comprises the following steps:
s1: collecting atmospheric environment parameters, wherein the atmospheric environment parameters comprise the particle size and mass concentration of atmospheric pollution particles;
s2: pretreating the particle size and mass concentration of the atmospheric pollution particles in the atmospheric environment parameters to form a pollution particle mass fraction-particle size continuous function, and discretizing the continuous function to form a particle mass concentration-particle size discrete relation set; the calculation formula of the particle mass concentration in the particle mass concentration-particle size dispersion relation set is as follows:
Figure FDA0003218304460000011
wherein, Δ dpAs a fixed variable of the size of the discretized foulant particle, cpi(dp) The particle diameter in the i time period is dpThe mass concentration of the dirt particles is corresponding to the mass concentration of the dirt particles; c. Ci(d0) In the i time period, the particle size in the air is less than d0The mass concentration of the fouling particles;
s4: according to the collected atmospheric parameters, acquiring the mass concentration of atmospheric pollution particles in a particle mass concentration-particle diameter discrete relation set, calling the surface area pollution amount of the insulator in an insulator pollution amount database in unit time, and calculating the surface area pollution increment of the insulator in each detection time period; the calculation formula of the insulator surface pollution increment in each detection time period is
Figure FDA0003218304460000012
Wherein, cp0Is a reference mass concentration; c. Cpi(dp) The particle diameter in the i time period is dpThe mass concentration of the dirt particles is corresponding to the mass concentration of the dirt particles; viWind speed for the ith time period; t is tiIs the duration of the ith time period; rhom(Vi,dp) At the reference mass concentration, the wind speed is ViA particle diameter of dpIn the case of (2), unit time of the surface of the insulatorThe amount of accumulated dirt; dpMThe maximum value of the particle size of the atmospheric particulates in the ith time period; delta phimiThe increment of the surface contamination of the insulator in the ith time period;
s5: and superposing the insulator surface dirt accumulation increment in each detection time period to obtain the total insulator surface dirt accumulation amount in the continuous dirt accumulation time period.
2. The insulator contamination accumulation prediction method based on the atmospheric environmental parameter as recited in claim 1, wherein: the atmospheric environment parameters further comprise the wind speed of the atmospheric environment;
and comparing the collected real-time wind speed and the real-time particle size of the atmospheric pollution particles with an insulator accumulated pollution amount database in unit time to obtain the current surface area pollution amount of the insulator.
3. The insulator contamination accumulation prediction method based on the atmospheric environmental parameter as recited in claim 1, wherein: in step S5, the formula for calculating the total amount of accumulated dirt on the surface of the insulator in the continuous dirt accumulation period is:
Figure FDA0003218304460000021
wherein, N means dividing the continuous dirt accumulation time period into N detection time periods; h is the time sum of N detection time periods; phim(H) The final pollution amount generated by the atmospheric pollution particles on the surface of the insulator under the continuous pollution accumulation H time.
4. The insulator contamination accumulation prediction method based on the atmospheric environmental parameter as recited in claim 1, wherein: in the step S2, the pretreatment of the particle size and the mass concentration of the atmospheric pollution particles in the atmospheric environmental parameters to form a continuous function of the mass fraction-particle size of the pollution particles includes:
setting the particle size in the air to be less than d in the ith (i is more than or equal to 1 and less than or equal to N) time periodpThe mass fraction of the filthy particles is lambdai(dp)：
Figure FDA0003218304460000022
Wherein d is0Is the reference particle size of the dirt particles; lambda [ alpha ]i(dp) In the i time period, the particle size in the air is less than dpThe mass fraction of the fouling particles; c. Ci(dp) In the i time period, the particle size in the air is less than dpThe mass concentration of the fouling particles; c. Ci(d0) In the i time period, the particle size in the air is less than d0The mass concentration of the fouling particles;
setting the relationship between the mass fraction and the particle size of the atmospheric pollution particles under the atmospheric environment pollution to satisfy Rosin-Rammer distribution:
Figure FDA0003218304460000023
wherein n is1Is a distribution characteristic index; n is2Is a distribution characteristic coefficient;
substituting the mass concentrations of the collected atmospheric pollution particles with different particle diameters in the ith time period into the formulas (3) and (4), and calculating to obtain n1And n2A value of (d); n is to be1And n2Substituting the value of (a) into the formula (4) to obtain a continuous function of mass fraction-particle size of the atmospheric pollution particles in the ith time period;
5. the insulator contamination accumulation prediction method based on the atmospheric environmental parameter as recited in claim 4, wherein: the discretization of the mass fraction-particle size continuous function of the dirt particles in the step S2 includes the step of discretizing the particle size dpChanging the formula (4) into the formula (3) according to the fixed variable at equal intervals to obtain a particle mass concentration-particle size dispersion relation set;
and 4, calling the corresponding mass concentration of the atmospheric pollution particles in the formula (5) in the particle mass concentration-particle diameter discrete relation set according to the actually collected mass concentration of the pollution particles with the particle diameter smaller than the reference particle diameter in each detection time period and the actually collected particle diameter of the atmospheric pollution particles.
6. The insulator contamination accumulation prediction method based on the atmospheric environmental parameter as recited in claim 2, wherein: the step S4 is preceded by:
s3: in the atmospheric environment with different wind speeds and different pollution particle diameters, simulation calculation is carried out on the deposition of the pollution particles on the surface of the insulator, and a database of the volume pollution of the insulator in unit time is built;
and S4, comparing the acquired real-time wind speed and the real-time particle size of the atmospheric pollution particles with the insulator pollution amount database in unit time to obtain the current surface area pollution amount of the insulator.
7. The insulator contamination accumulation prediction method based on the atmospheric environmental parameter as recited in claim 6, wherein: in the step S3, the simulation calculation of deposition of the dirty particles on the surface of the insulator in the atmospheric environment with different wind speeds and different sizes of the dirty particles includes:
using Comsol multi-physical field finite element software at preset wind speed ViParticle size d of dirt particlespSimulating the steady-state distribution of an electrostatic field and a flow field around the insulator in the atmospheric environment;
simulating and calculating the motion and deposition process of the dirt particles under the comprehensive action of an electric field and a flow field by using a particle tracking module of Comsol multi-physical-field finite element software to obtain a preset particle size d in unit timepWind speed ViCorresponding insulator surface area pollution amount rhom(Vi,dp) Established to a preset wind speed ViParticle diameter dpAnd a corresponding insulator deposition amount database per unit time.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2008123805A (en) * 2006-11-10 2008-05-29 Chugoku Electric Power Co Inc:The Insulator pollution area prediction system, method, and program
CN105067043A (en) * 2015-08-28 2015-11-18 国家电网公司 Power transmission and transformation equipment accumulated dirt growth rate prediction apparatus
CN105160419A (en) * 2015-08-06 2015-12-16 国家电网公司 Insulator equivalent salt density prediction model introducing air quality index

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9384560B2 (en) * 2014-10-27 2016-07-05 King Fahd University Of Petroleum And Minerals Contamination level estimation method for high voltage insulators

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2008123805A (en) * 2006-11-10 2008-05-29 Chugoku Electric Power Co Inc:The Insulator pollution area prediction system, method, and program
CN105160419A (en) * 2015-08-06 2015-12-16 国家电网公司 Insulator equivalent salt density prediction model introducing air quality index
CN105067043A (en) * 2015-08-28 2015-11-18 国家电网公司 Power transmission and transformation equipment accumulated dirt growth rate prediction apparatus

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
低风速下瓷三伞绝缘子积污特性数值模拟研究;吕玉坤等;《华北电力大学学报》;20150930;第43卷(第5期);第46-50页 *
王黎明等.考虑气象、几何参数、大气污染物的绝缘子表面污秽度预测方法.《高电压技术》.2016,第42卷(第3期), *
考虑气象、几何参数、大气污染物的绝缘子表面污秽度预测方法;王黎明等;《高电压技术》;20160331;第42卷(第3期);第876-884页 *

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