CN115115109A - Physical asset wall building method and device and terminal equipment - Google Patents
Physical asset wall building method and device and terminal equipment Download PDFInfo
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Abstract
The application is suitable for the technical field of power grid equipment capital investment prediction, and provides a physical asset wall establishing method, a device and terminal equipment, wherein the physical asset wall establishing method comprises the following steps: acquiring retired equipment information and in-transit equipment information; clustering analysis is carried out on the retired equipment information to obtain that the retired service life of the retired equipment is prolonged by a significant year; selecting one year before and after the promotion of the significant year as a representative year, fitting and correcting the retirement rate of each year based on the retired equipment information in the representative year, and obtaining the actual retirement rate of each year of each type of equipment; and obtaining the quantity of the equipment retired in the future every year of the in-transit equipment through random simulation according to the actual annual retirement rate of each type of equipment and the information of the in-transit equipment. This application can reach the effect of peak clipping valley filling to the curve of future retirement quantity, makes the quantity of annual retirement equipment steady relatively to make the fund also steady relatively, be favorable to the reasonable fund distribution that carries on.
Description
Technical Field
The application belongs to the technical field of power grid equipment capital investment prediction, and particularly relates to a physical asset wall building method and device and terminal equipment.
Background
Along with the rapid development of economy, the physical asset scale of the power grid continuously rises, and the tasks of maintenance, overhaul and technical improvement of the power grid become severe day by day. How to scientifically plan the construction of the power grid, and reasonably and orderly performing asset transformation is the basis and guarantee of safe, stable, efficient and economic operation of the power grid.
The asset wall is an image description of intensive delivery conditions of assets in a historical time range, the law of the assets changing along with time is analyzed after the assets are arranged according to time sequence according to historical data, finally, the delivery time is taken as a horizontal axis, the asset scale is taken as a vertical axis, the represented delivery asset scale is in a wall shape, and the scale quantity of the delivery of the existing assets in different years in history is reflected.
In recent years, with the intensive research on the asset wall, it is unreasonable to shift the number of all the equipment by only depending on the average service life, so that the randomness of the retirement service life of the power grid equipment is ignored, and the huge technical improvement pressure of the historical peak period investment on the future is also ignored. These results in large fluctuation of the technical improvement scale in a certain period of time, and cause unreasonable fund distribution, which is not beneficial to the asset management of the power grid enterprise.
Disclosure of Invention
In order to overcome the problems in the related art, the embodiment of the application provides a physical asset wall establishing method and device and terminal equipment.
The application is realized by the following technical scheme:
in a first aspect, an embodiment of the present application provides a physical asset wall building method, including: acquiring retired equipment information and in-transit equipment information; performing cluster analysis on the decommissioned equipment information to obtain the decommissioned service life of the decommissioned equipment which is obviously prolonged; selecting one year from before and after the significant year of promotion as a representative year, fitting and correcting the retirement rate of each year based on the retired equipment information in the representative year, and obtaining the actual retirement rate of each year of each type of equipment; and obtaining the quantity of the equipment retired in the future every year of the in-transit equipment through random simulation according to the actual annual retirement rate of each type of equipment and the in-transit equipment information.
Based on the first aspect, in some possible implementations, the retired device information includes a year of operation, a year of retirement, a service life, and a reason for retirement of the retired device, where the reason for retirement includes technical improvement or major repair; the in-transit device information includes a commissioning year of the in-transit device and a commissioning quantity per year.
Based on the first aspect, in some possible implementation manners, the performing cluster analysis on the retired device information to obtain a significant year of the retired device's retired life includes: and performing multi-index clustering based on a fisher optimal segmentation method, and determining the exact age of the major influence caused by technical change, wherein the exact age is the retired service life of the retired equipment and is obviously prolonged.
In some possible implementations based on the first aspect, the selecting one year from before and after the significant year of promotion as a representative year, and fitting and correcting the annual retirement rate based on the retired device information in the representative year to obtain the actual annual retirement rate of each type of device includes: according to preset conditions, selecting one year from before and after the promotion significant year as a representative year, and recording as a first representative year and a second representative year; randomly extracting a plurality of sample devices from one class of retired devices of the first representative year and the second representative year respectively, and recording the sample devices as a first sample and a second sample; counting the retired life of each device in the first sample and the second sample, and respectively calculating the retired rate of the devices in the first sample and the second sample under different retired lives; and performing Weibull parameter fitting on the service life retirement rate of a certain class of retired equipment calculated in the first representative year and the second representative year, and correcting by using a fitted curve to obtain the actual annual retirement rate of the certain class of retired equipment.
Based on the first aspect, in some possible implementations, the preset condition includes: over 80% of the same type of equipment that is in operation in the current year has been decommissioned in the representative year; in the representative year, the number of devices put into operation in the current year is larger compared with other years; in the representative year, the distribution of the types of different retired years of use of the equipment put into operation in the year is greater than the rest of the year.
Based on the first aspect, in some possible implementations, the obtaining, by random simulation, the number of future annual retired devices of the in-transit device according to the retirement rate and the in-transit device information includes: if the commissioning year of a certain type of the in-service equipment is before the representative year, randomly simulating the decommissioning rate of the first representative year, otherwise, randomly simulating the decommissioning rate corrected by Weibull of the second representative year to obtain the decommissioning year of the certain type of the in-service equipment, sorting and summarizing all types of the in-service equipment, and obtaining the in-service equipment decommissioned in the next year.
Based on the first aspect, in some possible implementations, the sorting and summarizing all the categories of the on-board devices includes: repeatedly obtaining the retired years of a certain type of the in-service equipment, and averaging the retired years to eliminate randomness; and summarizing the quantity of the in-service equipment of the same type of the same voltage class retired in the same year in the future to obtain the quantity of the in-service equipment retired in the future every year.
The method for establishing the physical asset wall can achieve the effect of peak clipping and valley filling on the curve of the future retired quantity, so that the quantity of the retired equipment is relatively stable every year, the fund is relatively stable, and reasonable fund distribution is facilitated.
In a second aspect, an embodiment of the present application provides a physical asset wall building apparatus, including: the acquiring module is used for acquiring decommissioned equipment information and in-transit equipment information; the cluster analysis module is used for carrying out cluster analysis on the retired equipment information to obtain the retired service life of the retired equipment, which is obviously prolonged; the fitting module is used for fitting and correcting the retirement rate of each year from one year before and one year after the significant year of promotion as a representative year based on the retired equipment information in the representative year to obtain the actual retirement rate of each year of each type of equipment; and the random simulation module is used for obtaining the number of the retired equipment of the in-transit equipment every year in the future through random simulation according to the retirement rate and the in-transit equipment information.
In a third aspect, an embodiment of the present application provides a terminal device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor, when executing the computer program, implements the physical asset wall building method according to any one of the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium, where a computer program is stored, and when executed by a processor, the computer program implements the physical asset wall building method according to any one of the first aspect.
It is to be understood that, for the beneficial effects of the second aspect to the fourth aspect, reference may be made to the relevant description in the first aspect, and details are not described herein again.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the specification.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flowchart of a physical asset wall building method according to an embodiment of the present application;
fig. 2 is a schematic view illustrating a flow of adjusting the equipment life ratio in the physical asset wall building method according to an embodiment of the present application;
fig. 3 is a schematic flowchart of simulation of retirement number of equipment in a physical asset wall building method according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a physical asset wall building device provided in an embodiment of the present application;
fig. 5 is a schematic structural diagram of a terminal device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items and includes such combinations.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to" determining "or" in response to detecting ". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.
Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather mean "one or more but not all embodiments" unless specifically stated otherwise. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless expressly specified otherwise.
With the rapid development of economy, the physical asset scale of the power grid continuously rises, and the tasks of maintenance, overhaul and technical improvement of the power grid become severe day by day. How to scientifically plan the construction of the power grid and reasonably and orderly perform asset transformation is the basis and guarantee of safe, stable, efficient and economic operation of the power grid. The method develops the research on the real asset management of the power grid, constructs a stable asset wall model, and has important practical significance for improving the asset management level of the power grid enterprise.
The asset wall is an image description of intensive delivery conditions of assets in a historical time range, the law of the assets changing along with time is analyzed after the assets are arranged according to time sequence according to historical data, finally, the delivery time is taken as a horizontal axis, the asset scale is taken as a vertical axis, the represented delivery asset scale is in a wall shape, and the scale quantity of the delivery of the existing assets in different years in history is reflected.
By using the asset wall and combining the translation years, the future technical improvement condition of the existing asset part can be predicted. And establishing an asset wall through accumulated statistics of historical commissioning assets, translating the single assets according to the retirement years of the assets to obtain a future technical improvement asset wall, and predicting the investment scale and the total investment scale of the selected unit equipment.
However, in recent years, with the intensive research on the asset wall, it is unreasonable to shift the number of all the devices only by the average service life, so that the randomness of the retirement service life of the power grid devices is ignored, and the huge technical improvement pressure of the historical peak period investment on the future is also ignored. These results in large fluctuation of the technical improvement scale in a certain period of time, and cause unreasonable fund distribution, which is not beneficial to the asset management of the power grid enterprise. Therefore, the construction of a proper quantity prediction method has important significance for the establishment of the asset wall.
Based on the problems, the application provides a physical asset wall building method. The physical asset wall building method of the present application is described in detail below with reference to fig. 1.
Fig. 1 is a schematic flow chart of a physical asset wall building method according to an embodiment of the present application, and with reference to fig. 1, the physical asset wall building method is described in detail as follows:
in step 101, retired device information and in-transit device information are obtained.
Illustratively, the retired device information includes the year of operation, the year of retirement, the age of service, and the reason for retirement of the retired device, wherein the reason for retirement includes a technical improvement or major repair; the in-transit device information includes the year of commissioning of the in-transit device and the number of commissions per year.
In some embodiments, obtaining retired device information and in-transit device information comprises: according to the ERP data of the power grid company, relevant information of the retired equipment is derived, wherein the relevant information comprises the operation year of the retired equipment, the retired year of the retired equipment, the service life and the retired reason (technical improvement/overhaul); from the records, the year of commissioning of the operated equipment and the number of commissions per year are also derived.
In step 102, the decommissioned equipment information is subjected to cluster analysis, and the decommissioned service life of the decommissioned equipment is improved by a significant year.
Exemplarily, performing cluster analysis on the retired device information to obtain a significant year of retired life improvement of the retired device includes: and performing multi-index clustering based on a Fisher optimal segmentation method, and determining the exact age of the major influence caused by technical change, wherein the exact age is the retired service life of the retired equipment and is obviously prolonged.
In some embodiments, based on Fisher's optimal segmentation, the interval years (e.g., 2000 years) in which the decommissioning age of the equipment is improved most significantly are found, and the decommissioning life of the decommissioned equipment can be divided into before 2000 years and after 2000 years. The method comprises the following specific steps:
firstly, defining a section diameter:
wherein x is G Is the mean vector of the retired life of the retired equipment; x is the number of (a) The retirement life of the a-th retired device; let the retired equipment included in a class have a retirement lifetime of { x i ,x i+1 ,...,x j G ═ i, i + 1.., j }, D (i, j) denotes a class of diameters, i and j are the beginning and end of a selected number of years in the year.
Define the classification loss function:
wherein, L [ B (n, k)]Is a classification loss function; t represents the variable of the summation, from 1 up to the kth class; k is the number of classes, i is the quantile 1 ═ i 1 <i 2 <...<i k <n＝i k+1 -1
Solving a classification loss function
Wherein b (n, k) represents a division of n retired lifetimes into k classes; j is a variable representing a value from 2 to n in the first formula and a value from k to n in the second formula.
Defining a classification objective function
Wherein n is the number of ordered samples, k is the number of classes, P (n, k) is a fraction that minimizes the classification loss function L [ B (n, k) ], and i is the quantile.
Solving the optimal segmentation:
according to a recurrence formula:
determining an optimal segmentation number k:
and taking the corresponding k value at the inflection point of the e [ P (n, k) ] -k curve as the most classified number. Finally, the classification is determined to be 2 types, and the year 2000 is the year of remarkably improving the equipment quality.
In step 103, a year is selected from before and after the significant year is promoted as a representative year, and the annual retirement rate is fitted and corrected based on the retired equipment information in the representative year, so as to obtain the actual annual retirement rate of each type of equipment.
Illustratively, selecting one year before and after the significant year is promoted as a representative year, fitting and correcting the retired rate of each year based on the retired equipment information in the representative year to obtain the actual retired rate of each year of each type of equipment, including: according to preset conditions, selecting one year from before and after the promotion significant year as representative years, and recording as a first representative year and a second representative year; randomly extracting a plurality of sample devices from a certain class of retired devices of a first representative year and a second representative year respectively, and recording the sample devices as a first sample and a second sample; counting the retired life of each device in the first sample and the second sample, and respectively calculating the retired rate of the devices in the first sample and the second sample under different retired lives; the actual annual retirement rate of a certain class of retired equipment is obtained by performing Weibull parameter fitting on the service life retirement rates of the certain class of retired equipment calculated in the first representative year and the second representative year and correcting by using a fitted curve.
Wherein the preset conditions include: in a representative year, more than 80% of the same type of equipment put into service in the current year has already been retired; in a representative year, the number of devices put into operation in the current year is large compared with other years; in a representative year, the distribution of the types of different retired years of use of equipment commissioned in the year is greater than the rest of the year.
In some embodiments, referring to fig. 2, fig. 2 illustrates an equipment life scaling procedure comprising: analyzing the condition of the decommissioned equipment, selecting a representative year around 2000 (taking A year and B year as examples, A <2000, B >2000) according to the following conditions:
(1) most of the same type of equipment put into operation in the same year has been retired.
(2) The number of devices put into operation in the same year is large compared with other years.
(3) The distribution range of the retired service life of the equipment put into operation in the current year is relatively large, and the equipment is universal.
Taking X equipment as an example, finding out A, B years for the X equipment, randomly sampling 1000 equipment from A year, and marking as a sample M; 1000 devices were randomly sampled from year B and denoted as sample N. And counting the retired service lives of the devices in the M and N samples, and respectively calculating the retired rates of the devices in the M and N samples under each retired service life. The calculation results are shown in table 1 and table 2, where table 1 shows the ex-service rate of the X device M sample, and table 2 shows the ex-service rate of the X device N sample.
TABLE 1X equipment M sample retirement Rate
| Age of retirement | 1 | 2 | ... | ... | ... | K-1 | K |
| Retirement rate | p 1 | p 2 | ... | ... | ... | p K-1 | p K |
TABLE 2 decommissioning rate of X device N samples
| Age of retirement | 1 | 2 | ... | ... | ... | D-1 | D |
| Retirement rate | q 1 | q 2 | ... | ... | ... | q D-1 | q D |
Wherein theoretically D > K.
In some embodiments, performing a weibull parameter fit on each life retirement rate of the X device samples M, N comprises:
(ii) Weibull distribution Density function and distribution function
Where γ is a positional parameter, η is a proportional parameter, and β is a shape parameter. Since decommissioning of the equipment may also occur the first year of use, γ is 0. The three parameters of the Weibull distribution are degenerated into two parameters.
② two-parameter fitting of Weibull distribution
According to (r), we can transform the distribution function to obtain:
taking M as an example, 1000 data are arranged according to the length of the retired lifetime, and a total of 1000 data are defined as a sample with the serial number i in the M samples and the retired lifetime length of the ith sample. With substituting equation (1):
wherein, F (t) (i) ) For the median rank, the calculation formula is:
(1) obtaining after carrying out structure conversion:
order to
(2) Can be expressed as:
Y＝βx+βlnη (3)
let β ═ B and β ln η ═ a, use 1000 sets of observations (t) (i) ,F(t (i) ) Least squares fit to equation (3):
to obtain
After reduction, the estimated value of beta and eta can be obtained.
(iii) correcting the retirement rate of each year according to the Weibull function
Taking M samples as an example, bringing the retirement years from 1 to K into the Weibull density function respectively to obtain f (t). As shown in tables 3 and 4, wherein table 3 shows the ex-device M sample retirement rate and table 4 shows the X-device N sample retirement rate.
TABLE 3X equipment M sample retirement Rate
TABLE 4X equipment N sample retirement Rate
| Age of retirement | 1 | 2 | ... | ... | ... | D-1 | D |
| Retirement rate | q 1 | q 2 | ... | ... | ... | q D-1 | q D |
In step 104, the number of the equipment retired in the future every year of the in-transit equipment is obtained through random simulation according to the actual annual retirement rate of each type of equipment and the in-transit equipment information.
Illustratively, the quantity of the equipment retired in the future of the running equipment every year is obtained through random simulation according to the retirement rate and the information of the running equipment, and comprises the following steps: if the commissioning year of a certain type of in-service equipment is before the representative year, the decommissioning rate of the first representative year is used for carrying out random simulation, otherwise, the decommissioning rate corrected by Weibull of the second representative year is used for carrying out random simulation, the decommissioning year of the certain type of in-service equipment is obtained, all types of in-service equipment are sorted and summarized, and the in-service equipment decommissioned in each year in the future is obtained.
Wherein, the equipment of transporting in all kinds of arrangement and gathering includes: repeatedly obtaining the retired years of a certain class of in-service equipment, and averaging the retired years to eliminate randomness; and summarizing the quantity of the in-service equipment of the same type with the same voltage class retired in the same year in the future to obtain the quantity of the in-service equipment retired in the future every year.
In some embodiments, after obtaining the weibull-corrected lifetime retirement tables and the data of the running devices, each running device is simulated by an improved monte carlo random simulation method (the flow is shown in fig. 3), so as to obtain retired years of each device, and the data results are sorted to obtain the number of retired services in the future years; because the random rows of the monte carlo method are large, in order to avoid obvious errors caused by large randomness, simulation is carried out for multiple times, and then the average value is taken to eliminate the randomness.
Specifically, the improved monte carlo stochastic simulation process comprises the following steps:
(1) and inputting the retired service life and the corresponding proportion of the equipment with the modified Weibull distribution. Considering that the time interval of the dispersion of the input years of the operating equipment is larger, and the improvement of a power grid system and the technical improvement are accompanied, the condition of dividing the retired service life of the existing retired equipment into two or more service lives and the corresponding proportion is analyzed;
(2) stochastic simulations were performed using a modified monte carlo model:
1. determining individual devices
Devices put into year i, j being the jth device put into year i, e.g.
Representing the 12 th plant launched in 2008.
2. Performing cyclic judgment on the equipment
Taking a random number r, r belongs to [0,1 ]]. If the equipment
In<2000, then r enters the first row of the table to loop; i.e. i>T, r enters the second loop in the table.
Let the current year be the t-th year, the j-th equipment invested in the i-th year:
if t-i is less than or equal to x 1 ：
If 0<r≤p x1 If x is out of service year of the equipment 1 ；
If it is not
1,2,3,4, k-1, the decommissioning year of the device, x m+1 。
If x m <t-i≤x m+1 :
Taking a residual life set:
T＝{x (1) ,x (1) ,...,x (k-1-m) |x m+1 ≥t-i,m＝1,2,3,4,...,k-1}
(first lifetime x satisfying the condition is taken m+1 ＝x (1) ，x k ＝x (k-1-m) ) And weighting the life set according to the following method:
if it is used
The retirement year x of the equipment is x (1) ；
If it is used
1,2, k-1-m, the decommissioning year of the device is x (1+l) 。
(r) if t-i>x k The equipment is retired in the same year.
3. And randomly simulating all the devices to obtain the future equipment retired technical improvement quantity distribution.
4. And repeatedly carrying out a plurality of random simulation experiments, eliminating the randomness of the number r taken by each device, calculating the average value of the retired technical improvement quantity of the device in each year in the future, and drawing an asset wall quantity graph.
In some embodiments, different types of equipment of different voltage classes are simulated, the results are sorted and collected, the number of the same type of equipment of the same voltage class retired in the same year is collected, the number of the retired equipment in the future every year is obtained, and the number scale of the retired equipment of different types under each voltage class is constructed.
The method for establishing the physical asset wall can achieve the effect of peak clipping and valley filling on the curve of the future retired quantity, so that the quantity of the retired equipment is relatively stable every year, the fund is relatively stable, and reasonable fund distribution is facilitated.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Fig. 4 shows a block diagram of the physical asset wall building apparatus provided in the embodiment of the present application, which corresponds to the physical asset wall building method described in the foregoing embodiment, and for convenience of description, only the parts related to the embodiment of the present application are shown.
Referring to fig. 4, the physical asset wall building apparatus in the embodiment of the present application may include an obtaining module 201, a cluster analysis module 202, a fitting module 203, and a stochastic simulation module 204.
The acquiring module 201 is configured to acquire retired device information and in-transit device information; the cluster analysis module 202 is used for performing cluster analysis on the retired equipment information to obtain a significant year of retired service life improvement of the retired equipment; the fitting module 203 is used for fitting and correcting the retirement rate of each year based on the retired equipment information in the representative year by selecting one year from before and after the promotion of the significant year as the representative year to obtain the actual retirement rate of each year of each type of equipment; and the random simulation module 204 is configured to obtain the number of the retired devices of the in-transit device every year in the future through random simulation according to the retirement rate and the in-transit device information.
In some embodiments, the obtaining module 201 may specifically be configured to: acquiring retired equipment information and in-transit equipment information, comprising: the retired equipment information comprises the operation year, retired year, service life and retired reason of the retired equipment, wherein the retired reason comprises technical improvement or major repair; the in-transit device information includes the year of commissioning of the in-transit device and the number of commissions per year.
In some embodiments, the cluster analysis module 202 may be specifically configured to: and performing multi-index clustering based on a fisher optimal segmentation method, and determining the exact age of the major influence caused by the technical change, wherein the exact age is the retired service life of the retired equipment and is obviously prolonged.
In some embodiments, fitting module 203 may be specifically configured to: according to preset conditions, selecting one year from before and after the promotion significant year as representative years, and recording as a first representative year and a second representative year;
randomly extracting a plurality of sample devices from a certain class of retired devices of a first representative year and a second representative year respectively, and recording the sample devices as a first sample and a second sample; counting the retired life of each device in the first sample and the second sample, and respectively calculating the retired rate of the devices in the first sample and the second sample under different retired life; the actual annual retirement rate of a certain class of retired equipment is obtained by performing Weibull parameter fitting on the service life retirement rates of the certain class of retired equipment calculated in the first representative year and the second representative year and correcting by using a fitted curve.
Wherein the preset conditions include: in a representative year, more than 80% of the same type of equipment put into service in the current year has already been retired; in a representative year, the number of devices put into operation in the current year is large compared with other years; in a representative year, the distribution of the types of different retired years of use of equipment commissioned in the year is greater than the rest of the year.
In some embodiments, the stochastic simulation module 204 may be specifically configured to: obtaining the quantity of equipment retired in the future of the equipment in transit every year through random simulation according to the retirement rate and the information of the equipment in transit, comprising the following steps: if the commissioning year of a certain type of in-service equipment is before the representative year, the decommissioning rate of the first representative year is used for carrying out random simulation, otherwise, the decommissioning rate corrected by Weibull of the second representative year is used for carrying out random simulation, the decommissioning year of the certain type of in-service equipment is obtained, all types of in-service equipment are sorted and summarized, and the in-service equipment decommissioned in each year in the future is obtained.
Wherein, the equipment of transporting in all kinds of arrangement and gathering includes: repeatedly obtaining the retired years of a certain class of in-service equipment, and averaging the retired years to eliminate randomness; and summarizing the quantity of the in-service equipment of the same type with the same voltage class retired in the same year in the future to obtain the quantity of the in-service equipment retired in the future every year.
It should be noted that, for the information interaction, execution process, and other contents between the above-mentioned devices/units, the specific functions and technical effects thereof are based on the same concept as those of the embodiment of the method of the present application, and specific reference may be made to the part of the embodiment of the method, which is not described herein again.
It should be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional units and modules is only used for illustration, and in practical applications, the above function distribution may be performed by different functional units and modules as needed, that is, the internal structure of the apparatus may be divided into different functional units or modules to perform all or part of the above described functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
An embodiment of the present application further provides a terminal device, and referring to fig. 5, the terminal device 300 may include: at least one processor 310, a memory 320, and a computer program stored in the memory 320 and executable on the at least one processor 310, the processor 310 implementing the steps of any of the various method embodiments described above when executing the computer program, such as the steps 101 to 104 in the embodiment shown in fig. 1. Alternatively, the processor 310, when executing the computer program, implements the functions of the modules/units in the above-described device embodiments, such as the functions of the modules 201 to 204 shown in fig. 4.
Illustratively, the computer program may be divided into one or more modules/units, which are stored in the memory 320 and executed by the processor 310 to accomplish the present application. The one or more modules/units may be a series of computer program segments capable of performing specific functions, which are used to describe the execution of the computer program in the terminal device 300.
Those skilled in the art will appreciate that fig. 5 is merely an example of a terminal device and is not limiting and may include more or fewer components than shown, or some components may be combined, or different components such as input output devices, network access devices, buses, etc.
The Processor 310 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 320 may be an internal storage unit of the terminal device, or may be an external storage device of the terminal device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. The memory 320 is used for storing the computer programs and other programs and data required by the terminal device. The memory 320 may also be used to temporarily store data that has been output or is to be output.
The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.
The method for establishing the physical asset wall provided by the embodiment of the application can be applied to terminal equipment such as a computer, a tablet computer, a notebook computer, a netbook, a Personal Digital Assistant (PDA), a mobile phone and the like, and the embodiment of the application does not limit the specific type of the terminal equipment at all.
The embodiment of the application also provides a computer-readable storage medium, which stores a computer program, and the computer program, when executed by a processor, implements the steps in the embodiments of the physical asset wall building method.
The embodiment of the application provides a computer program product, and when the computer program product runs on a mobile terminal, the steps in each embodiment of the physical asset wall building method can be realized when the mobile terminal is executed.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium and can implement the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing apparatus/terminal apparatus, a recording medium, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other ways. For example, the above-described apparatus/network device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. A physical asset wall building method is characterized by comprising the following steps:
acquiring retired equipment information and in-transit equipment information;
performing cluster analysis on the decommissioned equipment information to obtain the decommissioned service life of the decommissioned equipment, which is obviously prolonged;
selecting one year from before and after the significant year of promotion as a representative year, fitting and correcting the retirement rate of each year based on the retired equipment information in the representative year, and obtaining the actual retirement rate of each year of each type of equipment;
and obtaining the quantity of the equipment decommissioned every year in the future of the equipment in transit through random simulation according to the actual annual decommissioning rate of each type of equipment and the information of the equipment in transit.
2. The physical asset wall building method according to claim 1, wherein the decommissioned device information includes a year of operation, a year of decommissioning, a service life, and a reason for decommissioning of the decommissioned device, the reasons for decommissioning including technical modification or major repair;
the in-transit device information includes a commissioning year of the in-transit device and a commissioning quantity per year.
3. The method for building the physical asset wall according to claim 1, wherein the step of performing cluster analysis on the decommissioned equipment information to obtain a significant year of life improvement of the decommissioned equipment comprises:
and performing multi-index clustering based on a fisher optimal segmentation method, and determining the exact age of the major influence caused by technical change, wherein the exact age is the retired service life of the retired equipment and is obviously prolonged.
4. The method for building a physical asset wall according to claim 1, wherein the step of fitting and correcting the annual retirement rate based on the retired equipment information in the representative year by selecting one year from before and after the significant year of the promotion as the representative year to obtain the actual annual retirement rate of each type of equipment comprises:
according to preset conditions, selecting one year from before and after the significant year of the promotion as a representative year, and recording the representative year as a first representative year and a second representative year;
randomly extracting a plurality of sample devices from one class of retired devices of the first representative year and the second representative year respectively, and recording the sample devices as a first sample and a second sample;
counting the retired life of each device in the first sample and the second sample, and respectively calculating the retired rates of the devices in the first sample and the second sample under different retired lives;
and performing Weibull parameter fitting on the service life retirement rate of a certain class of retired equipment calculated in the first representative year and the second representative year, and correcting by using a fitted curve to obtain the actual annual retirement rate of the certain class of retired equipment.
5. The physical asset wall building method according to claim 4, wherein the preset conditions include:
over 80% of the same type of equipment that is in operation in the current year has been decommissioned in the representative year;
in the representative year, the number of devices put into operation in the current year is larger compared with other years;
in the representative year, the distribution of the types of different retired years of use of the equipment put into operation in the year is greater than the rest of the year.
6. The method for building the physical asset wall according to claim 4, wherein the obtaining the number of the equipment retired in the future every year of the equipment in transit through stochastic simulation according to the retirement rate and the information of the equipment in transit comprises:
if the commissioning year of a certain type of the in-service equipment is before the representative year, randomly simulating the decommissioning rate of the first representative year, otherwise, randomly simulating the decommissioning rate corrected by Weibull of the second representative year to obtain the decommissioning year of the certain type of the in-service equipment, sorting and summarizing all types of the in-service equipment, and obtaining the in-service equipment decommissioned in the next year.
7. The physical asset wall building method according to claim 6, wherein said collating and summarizing all the categories of said on-board devices comprises:
repeatedly obtaining the retired years of a certain type of the in-service equipment, and averaging the retired years to eliminate randomness;
and summarizing the quantity of the in-service equipment of the same type of the same voltage class retired in the same year in the future to obtain the quantity of the in-service equipment retired in the future every year.
8. A physical asset wall building device, comprising:
the acquisition module is used for acquiring decommissioned equipment information and in-transit equipment information;
the cluster analysis module is used for carrying out cluster analysis on the retired equipment information to obtain the retired service life of the retired equipment, which is obviously prolonged;
the fitting module is used for fitting and correcting the retirement rate of each year from one year before and one year after the significant year of promotion as a representative year based on the retired equipment information in the representative year to obtain the actual retirement rate of each year of each type of equipment;
and the random simulation module is used for obtaining the number of the retired equipment of the in-transit equipment every year in the future through random simulation according to the retirement rate and the in-transit equipment information.
9. A terminal device comprising a memory and a processor, the memory having stored therein a computer program operable on the processor, wherein the processor implements the method of any one of claims 1 to 7 when the computer program is invoked and executed.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 7.
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| CN202210734973.2A CN115115109A (en) | 2022-06-27 | 2022-06-27 | Physical asset wall building method and device and terminal equipment |
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| CN202210734973.2A CN115115109A (en) | 2022-06-27 | 2022-06-27 | Physical asset wall building method and device and terminal equipment |
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