CN112232580B - Power supply interruption loss analysis method and device - Google Patents
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Abstract
The invention discloses a method and a device for analyzing power supply interruption loss, which comprises the following steps: acquiring average loss values respectively corresponding to a plurality of interruption durations of an industry to be analyzed; constructing an initial duration loss model according to the interruption duration and the average loss value; receiving actual loss values of the target object of the industry to be analyzed corresponding to the interruption durations respectively; adjusting the initial duration loss model according to the interruption duration and the actual loss value to generate a target duration loss model of the target object; receiving a predicted interrupt duration of the target object; and determining the loss risk value of the predicted interruption duration according to the target duration loss model. The method and the device solve the technical problems of high loss evaluation cost and low accuracy of an evaluation result in the prior art, and more accurately and effectively evaluate the risk of power supply interruption loss.
Description
Technical Field
The invention relates to the technical field of power data analysis, in particular to a power supply interruption loss analysis method and device.
Background
The aim of power supply enterprises is to provide safe, reliable and economical electric energy for users, but in the actual operation process of a power system, because the instantaneous change of the power demand and system faults in the power generation, transmission and distribution processes can influence the power supply capacity, power failure accidents are caused, and the loss is brought to national economy and people's life. On one hand, the scale of the power grid is continuously enlarged, and the system structure is gradually complicated; on the other hand, the dependence degree of modern industrial production and resident life on electric energy is higher and higher, the occurrence of power failure cannot be tolerated more and more, and the problem of power supply reliability of a power grid is more prominent.
The existing research on power supply reliability evaluation mainly focuses on system side indexes such as power supply interruption times and duration, but the actual severity of the influence of power supply interruption on different types of users is different, so that researchers begin to pay attention to a user power supply interruption loss evaluation method. Evaluating the power supply interruption loss of the user is the key for measuring the power supply reliability of the user, developing subsequent treatment service and ensuring the power supply reliability. At present, the economic loss evaluation caused by long-term power supply interruption of a user is still judged mainly according to a research result, and a statistical result of each power supply interruption loss provided by the user is used as a decision basis. And a researcher summarizes the load outage loss coefficients of different types of users in a typical power supply interruption duration period as a reference to evaluate the user loss, and the general basis is used for providing a reference for similar research.
However, the above solutions are all in the stage of analyzing the research data, no connection between the user loss and the interruption event characteristics is established, repeated research work needs to be performed according to different users to perform loss evaluation, the cost is high, the possibility of loss occurrence is not considered, it is difficult to accurately reflect the average condition of loss in a long time period, and the evaluation result has a large fluctuation deviation.
Disclosure of Invention
The invention provides a power supply interruption loss analysis method and device, and solves the technical problems of high loss evaluation cost and low accuracy of evaluation results in the prior art.
The invention provides a power supply interruption loss analysis method, which comprises the following steps:
acquiring average loss values respectively corresponding to a plurality of interruption durations in the industry to be analyzed;
constructing an initial duration loss model according to the interruption duration and the average loss value;
receiving actual loss values of the target object of the industry to be analyzed corresponding to the interruption durations respectively;
adjusting the initial duration loss model according to the interruption duration and the actual loss value to generate a target duration loss model of the target object;
receiving a predicted interrupt duration of the target object;
and determining the loss risk value of the predicted interruption duration according to the target duration loss model.
Optionally, the step of constructing an initial duration loss model according to the interruption duration and the average loss value includes:
and combining the interruption time length and the average loss values corresponding to the interruption time lengths respectively by adopting a curve fitting method to construct an initial time length loss model.
Optionally, the industry to be analyzed further includes a plurality of reference objects, and the step of adjusting the initial duration loss model according to the interruption duration and the actual loss value to generate a target duration loss model of the target object includes:
correcting the initial duration loss model according to the actual loss value to obtain a middle duration loss model of the target object and the multiple reference objects;
determining a plurality of loss distribution models of the interruption duration by adopting an intermediate duration loss model and a parameter estimation method of the target object and the plurality of reference objects;
adopting the central values of the loss distribution models of the interruption durations as target loss values corresponding to the interruption durations respectively;
and generating a target duration loss model of the target object according to the interruption duration and the target loss value.
Optionally, the step of modifying the initial duration loss model according to the actual loss value to obtain an intermediate duration loss model of the target object and the plurality of reference objects includes:
calculating a ratio of the actual loss value to the average loss value;
adjusting the initial duration loss model by adopting the average value of the ratio to generate first duration loss models corresponding to the target object and the plurality of reference objects respectively;
calculating a first loss value at a preset moment by adopting the first time length loss model;
and adjusting the ratio by adopting a binary search method, returning to the step of adjusting the initial time length loss model by adopting the average value of the ratio, and generating first time length loss models corresponding to the target object and the plurality of reference objects respectively until the difference value between the first loss value and the actual loss value is smaller than a preset threshold value.
Optionally, the step of determining the loss risk value of the predicted interruption duration according to the target duration loss model includes:
calculating a second loss value of the target duration loss model at the predicted interruption duration;
calculating the loss occurrence probability of the loss distribution model in the prediction interruption duration;
and obtaining the loss risk value of the predicted interruption duration by adopting the product of the second loss value and the loss occurrence probability.
The invention also provides a power supply interruption loss analysis device, which comprises:
the average loss value acquisition module is used for acquiring average loss values corresponding to a plurality of interruption durations of the industry to be analyzed;
the initial duration loss model building module is used for building an initial duration loss model according to the interruption duration and the average loss value;
the real-time loss value receiving module is used for receiving actual loss values of the target object of the industry to be analyzed corresponding to the interruption durations respectively;
a target duration loss model generation module, configured to adjust the initial duration loss model according to the interruption duration and the actual loss value, and generate a target duration loss model of the target object;
a predicted interrupt duration receiving module, configured to receive a predicted interrupt duration of the target object;
and the loss risk value determining module is used for determining the loss risk value of the predicted interruption duration according to the target duration loss model.
Optionally, the initial duration loss model building module includes:
and the construction submodule is used for constructing an initial duration loss model by combining the interruption duration and the average loss values corresponding to the interruption durations by adopting a curve fitting method.
Optionally, the industry to be analyzed further includes a plurality of reference objects, and the target duration loss model generation module includes:
the intermediate duration loss model building submodule is used for correcting the initial duration loss model according to the actual loss value to obtain intermediate duration loss models of the target object and the multiple reference objects;
a loss distribution model determination submodule configured to determine a plurality of loss distribution models of the interrupt duration by using an intermediate duration loss model and a parameter estimation method for the target object and the plurality of reference objects;
the target loss value determining submodule is used for adopting the central value of the loss distribution model of the plurality of interruption durations as the target loss values corresponding to the plurality of interruption durations respectively;
and the target duration loss model generation submodule is used for generating a target duration loss model of the target object according to the interruption duration and the target loss value.
Optionally, the intermediate duration loss model building submodule includes:
a ratio calculation unit for calculating a ratio of the actual loss value to the average loss value;
a first time length loss model generating unit, configured to adjust the initial time length loss model by using a mean value of the ratio, and generate first time length loss models corresponding to the target object and the multiple reference objects, respectively;
the first loss value calculating unit is used for calculating a first loss value at a preset moment by adopting the first time length loss model;
and a ratio adjusting unit, configured to adjust the ratio by using a binary search method, return to the step of adjusting the initial duration loss model by using the average value of the ratios, and generate first duration loss models corresponding to the target object and the multiple reference objects, respectively, until a difference between the first loss value and the actual loss value is smaller than a predetermined threshold.
Optionally, the loss risk value determination module includes:
the second loss value operator module is used for calculating a second loss value of the target duration loss model in the predicted interruption duration;
a loss occurrence probability calculation submodule for calculating a loss occurrence probability of the loss distribution model at the predicted interruption duration;
and the loss risk value determining submodule is used for determining the loss risk value of the predicted interruption duration by adopting the product of the second loss value and the loss occurrence probability.
According to the technical scheme, the invention has the following advantages:
in the embodiment of the invention, an initial duration loss model is constructed according to the interruption duration and the average loss value by acquiring the average loss value corresponding to a plurality of interruption durations of the industry to be analyzed; the method comprises the steps of receiving actual loss values corresponding to a plurality of interruption durations respectively in the industry to be analyzed, carrying out optimization adjustment on an initial duration loss model according to the actual loss values and the interruption durations to generate a target duration loss model of a target object, receiving predicted interruption durations of the target object, and determining a loss risk value of the predicted interruption durations according to the target duration loss model, so that the technical problems of high loss evaluation cost and low accuracy of evaluation results in the prior art are solved, and the risk of power supply interruption loss is evaluated more accurately and effectively.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without inventive labor.
Fig. 1 is a flowchart illustrating steps of a method for analyzing a loss due to power interruption according to an embodiment of the present invention;
FIG. 2 is a flow chart illustrating steps of a method for analyzing loss due to interruption of power supply according to an alternative embodiment of the present invention;
FIG. 3 is a functional diagram of an initial duration loss model in an alternative embodiment of the invention;
FIG. 4 is a functional schematic of an intermediate duration loss model in an alternative embodiment of the invention;
FIG. 5 is a schematic diagram of a loss distribution model determination process in an alternative embodiment of the invention;
fig. 6 is a block diagram of a power interruption loss analysis apparatus according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a power supply interruption loss analysis method and device, which are used for solving the technical problems of higher loss evaluation cost and lower accuracy of evaluation results in the prior art.
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a flowchart illustrating a method for analyzing a loss due to power interruption according to an embodiment of the present invention.
The invention provides a power supply interruption loss analysis method, which comprises the following steps:
in the specific implementation, because the loss caused by power supply interruption of a certain industry is relatively similar under the condition of big data, in the process of analyzing the power supply interruption loss of the industry to be analyzed, average loss values respectively corresponding to a plurality of interruption durations of the industry to be analyzed can be obtained, so that the general power supply interruption loss condition of the industry to be analyzed is known, and an initial duration loss model is conveniently constructed subsequently.
The interruption time period may be set to 0 minute, 20 minutes, 1 hour, 4 hours, and 8 hours, or may be set by a person skilled in the art according to practical situations, and the embodiment of the present invention is not limited thereto.
102, constructing an initial duration loss model according to the interruption duration and the average loss value;
in the embodiment of the invention, the average loss value generally increases in a step-like manner along with the increase of the interruption time, and in order to further determine the regular relationship between the interruption time and the average loss value of the industry to be analyzed, an initial time loss model can be constructed according to the interruption time and the average loss value.
In particular implementations, the initial duration loss model may represent the loss of interruption of an ideal object in the industry under analysis as a function of the duration of the interruption.
103, receiving actual loss values of the target object of the industry to be analyzed corresponding to the interruption durations respectively;
104, adjusting the initial duration loss model according to the interruption duration and the actual loss value to generate a target duration loss model of the target object;
in order to obtain the change situation of the interruption loss of the target object in the industry to be analyzed along with the interruption time, the initial time loss model needs to be further optimized and adjusted.
In a specific implementation, an actual loss value of a target object in an interruption time may be different from an average loss value, so that the initial time loss model may be adjusted according to the interruption time and the actual loss value by receiving actual loss values corresponding to a plurality of interruption times of the industry to be analyzed, so as to generate a target object target time loss model.
and 106, determining a loss risk value of the predicted interruption duration according to the target duration loss model.
In specific implementation, in order to prevent loss increase of a target object caused by unknown power supply interruption, the predicted interruption time of the target object can be input into the target time loss model, so that the loss risk of the predicted interruption time can be determined and used as a basis for evaluating the power supply reliability of the region, and meanwhile, reference can be provided for the necessity of a user for subsequently installing treatment equipment such as a standby power supply.
In the embodiment of the invention, an initial duration loss model is constructed according to the interruption duration and the average loss value by acquiring the average loss value corresponding to a plurality of interruption durations of the industry to be analyzed; the method comprises the steps of receiving actual loss values corresponding to a plurality of interruption durations respectively in the industry to be analyzed, carrying out optimization adjustment on an initial duration loss model according to the actual loss values and the interruption durations to generate a target duration loss model of a target object, receiving predicted interruption durations of the target object, and determining a loss risk value of the predicted interruption durations according to the target duration loss model, so that the technical problems of high loss evaluation cost and low accuracy of evaluation results in the prior art are solved, and the risk of power supply interruption loss is evaluated more accurately and effectively.
Referring to fig. 2, fig. 2 is a flowchart illustrating steps of a power outage loss analysis method according to an alternative embodiment of the present invention, including:
in order to facilitate the analysis of the power supply interruption loss of a plurality of industries required by a user, average loss values corresponding to the distribution of a plurality of industries to be analyzed in a plurality of interruption time periods can be obtained simultaneously.
For example, the loss analysis required for residential, commercial, industrial, etc. types in the event of a power outage can be represented in the form of table 1 below:
TABLE 1
In a specific implementation, the average loss value of each object type can be collected through a data research and statistical method.
Alternatively, the above step 102 may be replaced by the following step 202:
The curve fitting method is commonly called as a pull curve, and is a method for substituting the existing data into a mathematical expression through a mathematical method. A data processing method for approximately describing or comparing a functional relationship between coordinates represented by a set of discrete points of a plane by using a continuous curve.
In an example of the present invention, a function relationship between the average loss values of the industry to be analyzed in the multiple interruption durations cannot be obtained, and at this time, a curve fitting method is required to be used in combination with the interruption durations and the average loss values corresponding to the multiple interruption durations, so as to construct an initial duration loss model.
Taking the industrial object type in table 1 above as an example, an initial duration loss model as shown in fig. 3 is established, where the dotted line is the corresponding loss value at each time point, and the solid line is the initial duration loss model of the industrial object type.
Alternatively, the initial duration loss model may be represented in a functional form, and taking the initial duration loss model shown in fig. 3 as an example, the functional form may be represented as follows:
Y＝-110.21x 4 +2261x 3 -16201x 2 +56598x+24509
wherein Y is a loss value and x is an interruption time length.
the specific implementation process of step 203 is similar to that of step 103, and is not described herein again.
in an alternative embodiment of the present invention, said step 204 may comprise the following sub-steps 2041-2044:
substep 2041, correcting the initial duration loss model according to the actual loss value to obtain a middle duration loss model of the target object and the multiple reference objects;
optionally, since the initial duration loss model is obtained by combining the average loss value of the industry to be analyzed with the interruption duration, the obtained initial duration loss model cannot accurately predict the loss value of the target object in the interruption duration. Therefore, after receiving actual loss values of the target object corresponding to the plurality of interruption durations respectively, further optimization and modification of the initial duration loss model according to the actual loss values are required to obtain an intermediate duration loss model.
Similarly, the same operation is performed on the plurality of reference objects to obtain corresponding intermediate duration loss models.
Further, the sub-step 2041 may include the following sub-steps S1-S4:
substep S1, calculating a ratio of the actual loss value to the average loss value;
step S2, adjusting the initial duration loss model by adopting the mean value of the ratio to generate first duration loss models respectively corresponding to the target object and the plurality of reference objects;
in another example of the present invention, after determining the initial duration loss model, in order to modify the initial duration loss model, a ratio of an actual loss value to the average loss value may be calculated; and in order to improve the accuracy of optimization adjustment, the average value of the ratio is obtained, and the initial duration loss model is adjusted by the average value to generate a first duration loss model.
In a specific implementation, the initial duration loss model is generally expressed by using a function, and taking the function expressed by the initial duration loss model shown in fig. 3 as an example, the first duration loss model obtained by multiplying the average value by the initial duration loss model may be as shown in fig. 4, where the function is expressed as:
y＝-85.229x 4 +1748.4x 3 -12528x 2 +43767x+18953
wherein the mean value is 0.7733, y is the first temporal loss value, the dotted line is the corresponding loss value at each time point, and the solid line is the first temporal loss model of the target object.
Similarly, for the process of constructing the first time-length loss model of the multiple reference objects, reference may be made to the above process of constructing the first time-length loss model of the target object, which is not described herein again.
A substep S3, calculating a first loss value at a preset moment by adopting the first time-length loss model;
and S4, adjusting the ratio by adopting a binary search method, returning to the step of adjusting the initial time length loss model by adopting the mean value of the ratio, and generating first time length loss models corresponding to the target object and the plurality of reference objects respectively until the difference value between the first loss value and the actual loss value is smaller than a preset threshold value.
The binary search method refers to binary search (also called binary search), and also called binary-exponential search (half-integer search) and logarithmic search (logarithmic search), and is a search algorithm for finding a specific element in an ordered array. The searching process starts from the middle element of the array, and if the middle element is exactly the element to be searched, the searching process is ended; if a particular element is larger or smaller than the middle element, then the search is performed in the half of the array that is larger or smaller than the middle element and the comparison is started from the middle element as was done at the beginning. If the array is empty at some step, the delegate cannot be found. Each comparison of this search algorithm reduces the search range by half.
In the above-mentioned optimization adjustment process of the initial time-length loss model, the accuracy of the obtained first time-length loss model is limited, possibly due to the fact that the difference between the average loss value and the actual loss value is too large. Therefore, in order to further improve the accuracy of the first time-length loss model, the first time-length loss model may be used to calculate a first loss value at a predetermined time, then the ratio is adjusted by using a binary search method, and then the first loss value at the predetermined time is recalculated until the difference between the first loss value and the actual loss value is smaller than a predetermined threshold.
The predetermined time is an interruption duration corresponding to the actual loss value, and the predetermined threshold may be 0 or 1%, which is not limited in this embodiment of the present invention.
Substep 2042, determining a loss distribution model of the plurality of interruption durations by using an intermediate duration loss model and a parameter estimation method of the target object and the plurality of reference objects;
referring to fig. 5, fig. 5 shows a schematic diagram of the determination process of the loss distribution model.
In a specific implementation, firstly, selecting an interruption time, after acquiring intermediate time loss models of a plurality of reference objects and an intermediate time loss model of the target object, determining a loss distribution model of the interruption time by using a parameter estimation method, which can be expressed by the following functional form:
where e is a natural constant and max (f (y)) refers to the loss maximum.
Substep 2043, using the central value of the loss distribution model of the plurality of interruption durations as the target loss value corresponding to each of the plurality of interruption durations;
and a substep 2044 of generating a target duration loss model of the target object according to the interruption duration and the target loss value.
In the embodiment of the present invention, after the loss distribution model is obtained, to further optimize the first time-length loss model, a central value of the loss distribution model of a plurality of interruption time lengths, that is, an average value of a loss maximum value and a loss minimum value, is selected as a target loss value corresponding to each of the plurality of interruption time lengths. And generating a target duration loss model of the target object by adopting the target loss value and the interruption duration
In a specific implementation, taking the function representation of the first time length loss model as an example, the function representation of the target time length loss model is as follows:
y*＝-78.709x 4 +1660.1x 3 -12726x 2 +50254x+21689
in the embodiment of the present invention, the specific implementation process of step 205 is similar to that of step 105, and is not described herein again.
And step 206, determining the loss risk value of the predicted interruption duration according to the target duration loss model.
In one example of the present invention, the step 206 may include the following sub-steps 2061-2063:
a substep 2061 of calculating a second loss value of the target duration loss model at the predicted interruption duration;
a substep 2062 of calculating a loss occurrence probability of the loss distribution model at the predicted interruption duration;
substep 2063, obtaining the loss risk value of the predicted interruption duration by using the product of the second loss value and the loss occurrence probability.
In a specific implementation, after the target duration loss model is obtained, in order to predict and evaluate the loss condition of the target object in any interruption duration, a loss risk value of the predicted interruption duration needs to be solved according to the target duration loss model. Obtaining a loss severity value of the target object under the predicted interruption duration through a second loss value of the target duration loss model in the predicted interruption duration; calculating the loss occurrence probability under the prediction interruption duration through the loss distribution model; and finally, determining the product of the second loss value and the loss occurrence probability, and determining the loss risk value of the target user in predicting the interruption duration.
Taking the predicted interruption duration faced by the target user as 5 hours as an example, the loss risk loss value lossR is:
lossR＝y*(5)·f(y*(5))
wherein y (5) =11.31, f (y (5)) =0.889, and the loss risk of the predicted interrupt duration event of the user is 10.06 ten thousand yuan.
In the embodiment of the invention, an initial duration loss model is constructed by adopting a curve fitting method according to a plurality of interruption durations and corresponding average loss values by acquiring the average loss values corresponding to the plurality of interruption durations in the industry to be analyzed; receiving actual loss values corresponding to the industry to be analyzed in the multiple interruption durations respectively, optimally adjusting the initial duration loss model according to the ratio of the actual loss values to the average loss value, generating a first duration loss model, adjusting the average value of the ratio by using a binary search method, revising the first duration loss model again, generating an intermediate duration loss model of a target object and multiple reference objects, determining multiple loss distribution models of the interruption durations by using a parameter estimation method based on the intermediate duration loss model, taking the median of the multiple loss distribution models as a target loss value, combining the interruption durations to generate the target duration loss model of the target object, receiving the predicted interruption durations of the target object, determining the loss risk value of the predicted interruption durations according to the product of the target duration loss model and the loss distribution models, so as to solve the technical problems that the loss evaluation cost is high and the evaluation result accuracy is low in the prior art, and more accurately and effectively evaluate the risk of power supply interruption loss.
Referring to fig. 6, fig. 6 shows a power interruption loss analysis apparatus according to an embodiment of the present invention, including:
an average loss value obtaining module 601, configured to obtain average loss values corresponding to multiple interruption durations of an industry to be analyzed;
an initial duration loss model building module 602, configured to build an initial duration loss model according to the interruption duration and the average loss value;
a real-time loss value receiving module 603, configured to receive actual loss values corresponding to a plurality of interruption durations of a target object of the industry to be analyzed;
a target duration loss model generating module 604, configured to adjust the initial duration loss model according to the interruption duration and the actual loss value, and generate a target duration loss model of the target object;
a predicted interrupt duration receiving module 605, configured to receive the predicted interrupt duration of the target object;
a loss risk value determining module 606, configured to determine a loss risk value of the predicted interruption duration according to the target duration loss model.
Optionally, the initial duration loss model building module 602 includes:
and the construction submodule is used for combining the interruption duration and the average loss values corresponding to the interruption durations respectively by adopting a curve fitting method to construct an initial duration loss model.
Optionally, the industry to be analyzed further includes a plurality of reference objects, and the target duration loss model generating module 604 includes:
the intermediate duration loss model building submodule is used for correcting the initial duration loss model according to the actual loss value to obtain intermediate duration loss models of the target object and the multiple reference objects;
a loss distribution model determination submodule configured to determine a plurality of loss distribution models of the interrupt duration by using an intermediate duration loss model and a parameter estimation method for the target object and the plurality of reference objects;
the target loss value determining submodule is used for adopting the central value of the loss distribution model of the plurality of interruption durations as the target loss values corresponding to the plurality of interruption durations respectively;
and the target duration loss model generation submodule is used for generating a target duration loss model of the target object according to the interruption duration and the target loss value.
Optionally, the intermediate duration loss model building submodule includes:
a ratio calculation unit for calculating a ratio of the actual loss value to the average loss value;
a first time length loss model generating unit, configured to adjust the initial time length loss model by using a mean value of the ratio, and generate first time length loss models corresponding to the target object and the multiple reference objects, respectively;
the first loss value calculating unit is used for calculating a first loss value at a preset moment by adopting the first time length loss model;
and a ratio adjusting unit, configured to adjust the ratio by using a binary search method, return to the step of adjusting the initial duration loss model by using the mean value of the ratio, and generate first duration loss models corresponding to the target object and the multiple reference objects, respectively, until a difference between the first loss value and the actual loss value is smaller than a predetermined threshold.
Optionally, the loss risk value determination module 606 includes:
a second loss value operator module, configured to calculate a second loss value of the target duration loss model in the predicted interruption duration;
a loss occurrence probability calculation sub-module, configured to calculate a loss occurrence probability of the loss distribution model in the predicted interruption duration;
and the loss risk value determining submodule is used for determining the loss risk value of the predicted interruption duration by adopting the product of the second loss value and the loss occurrence probability.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. 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 position, or may be distributed on multiple 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.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention 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; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (6)
1. A method for analyzing a loss due to interruption of power supply, comprising:
acquiring average loss values respectively corresponding to a plurality of interruption durations of an industry to be analyzed;
constructing an initial duration loss model according to the interruption duration and the average loss value;
receiving actual loss values of the target object of the industry to be analyzed corresponding to the interruption durations respectively;
adjusting the initial duration loss model according to the interruption duration and the actual loss value to generate a target duration loss model of the target object;
receiving a predicted interrupt duration of the target object;
determining a loss risk value of the predicted interruption duration according to the target duration loss model;
the industry to be analyzed comprises a plurality of reference objects;
the step of adjusting the initial duration loss model according to the interruption duration and the actual loss value to generate a target duration loss model of the target object includes:
correcting the initial duration loss model according to the actual loss value to obtain a middle duration loss model of the target object and the multiple reference objects;
determining a plurality of loss distribution models of the interruption duration by adopting an intermediate duration loss model and a parameter estimation method of the target object and the plurality of reference objects;
adopting the central value of the loss distribution model of the plurality of interruption durations as the target loss value corresponding to each of the plurality of interruption durations;
generating a target duration loss model of the target object according to the interruption duration and the target loss value;
the step of modifying the initial duration loss model according to the actual loss value to obtain an intermediate duration loss model of the target object and the plurality of reference objects includes:
calculating a ratio of the actual loss value to the average loss value;
adjusting the initial duration loss model by adopting the average value of the ratio to generate first duration loss models corresponding to the target object and the plurality of reference objects respectively;
calculating a first loss value at a preset moment by adopting the first time length loss model;
and adjusting the ratio by adopting a binary search method, returning to the step of adjusting the initial time length loss model by adopting the mean value of the ratio, and generating first time length loss models respectively corresponding to the target object and the plurality of reference objects until the difference value between the first loss value and the actual loss value is smaller than a preset threshold value.
2. The method of claim 1, wherein the step of constructing an initial duration loss model based on the outage duration and the average loss value comprises:
and constructing an initial duration loss model by combining the interruption duration and the average loss values corresponding to the interruption durations by adopting a curve fitting method.
3. The method of claim 1, wherein said step of determining a loss risk value for said predicted outage duration based on said target duration loss model comprises:
calculating a second loss value of the target duration loss model at the predicted interruption duration;
calculating the loss occurrence probability of the loss distribution model in the prediction interruption duration;
and obtaining the loss risk value of the predicted interruption duration by adopting the product of the second loss value and the loss occurrence probability.
4. A power interruption loss analysis apparatus, comprising:
the average loss value acquisition module is used for acquiring average loss values corresponding to a plurality of interruption durations of the industry to be analyzed;
the initial duration loss model building module is used for building an initial duration loss model according to the interruption duration and the average loss value;
the real-time loss value receiving module is used for receiving actual loss values of the target object of the industry to be analyzed corresponding to the interruption durations respectively;
a target duration loss model generation module, configured to adjust the initial duration loss model according to the interruption duration and the actual loss value, and generate a target duration loss model of the target object;
a predicted interrupt duration receiving module, configured to receive the predicted interrupt duration of the target object;
a loss risk value determination module, configured to determine a loss risk value of the predicted interruption duration according to the target duration loss model;
the industry to be analyzed further comprises a plurality of reference objects;
the target duration loss model generation module comprises:
the intermediate duration loss model building submodule is used for correcting the initial duration loss model according to the actual loss value to obtain intermediate duration loss models of the target object and the multiple reference objects;
a loss distribution model determination sub-module, configured to determine a plurality of loss distribution models for the interruption duration by using a parameter estimation method and a loss model for an intermediate duration between the target object and the plurality of reference objects;
the target loss value determining submodule is used for adopting the central value of the loss distribution model of the plurality of interruption durations as the target loss values corresponding to the plurality of interruption durations respectively;
a target duration loss model generation submodule, configured to generate a target duration loss model of the target object according to the interruption duration and the target loss value;
the intermediate duration loss model construction submodule comprises:
a ratio calculation unit for calculating a ratio of the actual loss value to the average loss value;
a first time length loss model generating unit, configured to adjust the initial time length loss model by using a mean value of the ratio, and generate first time length loss models corresponding to the target object and the multiple reference objects, respectively;
the first loss value calculating unit is used for calculating a first loss value at a preset moment by adopting the first time length loss model;
and a ratio adjusting unit, configured to adjust the ratio by using a binary search method, return to the step of adjusting the initial duration loss model by using the mean value of the ratio, and generate first duration loss models corresponding to the target object and the multiple reference objects, respectively, until a difference between the first loss value and the actual loss value is smaller than a predetermined threshold.
5. The apparatus of claim 4, wherein the initial duration loss model building module comprises:
and the construction submodule is used for combining the interruption duration and the average loss values corresponding to the interruption durations respectively by adopting a curve fitting method to construct an initial duration loss model.
6. The apparatus of claim 4, wherein the loss risk value determination module comprises:
a second loss value operator module, configured to calculate a second loss value of the target duration loss model in the predicted interruption duration;
a loss occurrence probability calculation sub-module, configured to calculate a loss occurrence probability of the loss distribution model in the predicted interruption duration;
and the loss risk value determining submodule is used for determining the loss risk value of the predicted interruption duration by adopting the product of the second loss value and the loss occurrence probability.
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