CN109583117A - The determination method, apparatus and electronic equipment of power supply reliability - Google Patents
The determination method, apparatus and electronic equipment of power supply reliability Download PDFInfo
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- CN109583117A CN109583117A CN201811500323.1A CN201811500323A CN109583117A CN 109583117 A CN109583117 A CN 109583117A CN 201811500323 A CN201811500323 A CN 201811500323A CN 109583117 A CN109583117 A CN 109583117A
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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Abstract
The present invention provides the determination method, apparatus and electronic equipment of a kind of power supply reliability, comprising: obtains the component parameters of each electrical component on target power distribution network；The component parameters of each electrical component are input to the electricity distribution network model pre-established, so that electricity distribution network model determines fault element；Wherein, affiliated electricity distribution network model is established based on sequential Monte Carlo method；Electricity distribution network model is related to preset failure load meter；Based on fault element, the power supply reliability degree of target power distribution network is determined.The present invention can reduce the calculating time of reliability index, improve the assessment efficiency of distribution network reliability degree.
Description
Technical field
The present invention relates to technical field of electric power, more particularly, to the determination method, apparatus and electronics of a kind of power supply reliability
Equipment.
Background technique
With the rapid development of modern social economy, widely available, the user of high-tech product and advanced IT application equipment
The output value of every degree electricity increasingly rises, and unit power failure is measured increasing to economic loss caused by user and society.Therefore, user couple
The requirement of power supply reliability is also higher and higher, the research and application to power supply reliability, is to guarantee power supply quality, realize electric power work
The important means of industry modernization.And power distribution network be with the allo link of user, directly influence the power quality of user.Institute
It is the major criterion for measuring a power distribution network with the power supply reliability index of power distribution network.Currently, generalling use analytic method to distribution
The power supply reliability index of net carries out assessment calculating, but power distribution network a fairly large number of for electrical component, analytic method will consume
The expense long period is calculated, and causes the efficiency for calculating reliability index lower.
Summary of the invention
In view of this, the purpose of the present invention is to provide the determination method, apparatus and electronic equipment of a kind of power supply reliability,
The calculating time of reliability index can be reduced, the assessment efficiency of distribution network reliability degree is improved.
In a first aspect, the embodiment of the invention provides a kind of determination methods of power supply reliability, comprising: obtain target distribution
The component parameters of online each electrical component；The component parameters of each electrical component are input to the electricity distribution network model pre-established, with
Electricity distribution network model is set to determine fault element；Wherein, affiliated electricity distribution network model is established based on sequential Monte Carlo method；Power distribution network
Model is related to preset failure load meter；Based on fault element, the power supply reliability degree of target power distribution network is determined.
With reference to first aspect, the embodiment of the invention provides the first possible embodiments of first aspect, wherein on
State the establishment process of electricity distribution network model, comprising: obtain failure load meter；It wherein, include target power distribution network in failure load meter
The corresponding relationship of electrical component and load point；By sequential Monte Carlo method, power distribution network mould corresponding with failure load meter is established
Type.
The possible embodiment of with reference to first aspect the first, the embodiment of the invention provides second of first aspect
Possible embodiment, wherein the step of above-mentioned acquisition failure load meter, comprising: be based on breadth-first search, obtain mesh
Each electrical component on standard configuration power grid, and each load point being connected with each electrical component；According to electrical member each on target power distribution network
Part, and each load point being connected with each electrical component, determine failure load meter.
The possible embodiment of with reference to first aspect the first, the embodiment of the invention provides the third of first aspect
Possible embodiment, wherein above-mentioned to be based on fault element, the step of determining the power supply reliability degree of target power distribution network, packet
It includes: according to failure load meter, determining each load point being connected with fault element；Based on fault element, calculate and fault element phase
The power off time and power failure frequency of each load point even；According to the power off time for each load point being connected with fault element and power failure
Frequency determines the power supply reliability degree of target power distribution network.
The third possible embodiment with reference to first aspect, the embodiment of the invention provides the 4th kind of first aspect
Possible embodiment, wherein the power off time and power failure frequency for each load point that above-mentioned basis is connected with fault element determine
The step of power supply reliability degree of target power distribution network, comprising: by the power off time for each load point being connected with fault element and
Power failure frequency is saved to predeterminable area, obtains load cell index table；Based on load cell index table, target power distribution network is determined
Power supply target value；According to power supply target value, the power supply reliability degree of above-mentioned target power distribution network is determined.
With reference to first aspect, the embodiment of the invention provides the 5th kind of possible embodiments of first aspect, wherein on
State the step of electricity distribution network model determines fault element, comprising: when calculating the no-failure operation of each electrical component of target power distribution network
Between, and determine the smallest electrical component of time between failures；Calculate the reparation of the smallest electrical component of time between failures
Time；According to the time between failures of each electrical component of target power distribution network and the smallest electrical component of time between failures
Repair time, determine fault element.
Second aspect, the embodiment of the present invention also provide a kind of determining device of power supply reliability, comprising: parameter obtains mould
Block, for obtaining the component parameters of each electrical component on target power distribution network；Input module, for joining the element of each electrical component
Number is input to the electricity distribution network model pre-established, so that electricity distribution network model determines fault element；Wherein, affiliated electricity distribution network model is
It is established based on sequential Monte Carlo method；Electricity distribution network model is related to preset failure load meter；Reliability determining module, is used for
Based on fault element, the power supply reliability degree of target power distribution network is determined.
In conjunction with second aspect, the embodiment of the invention provides the first possible embodiments of second aspect, wherein on
It states device to be also used to: obtaining failure load meter；It wherein, include the electrical component and load point of target power distribution network in failure load meter
Corresponding relationship；By sequential Monte Carlo method, electricity distribution network model corresponding with failure load meter is established.
The third aspect, the embodiment of the present invention also provide a kind of electronic equipment, including processor and memory；It is deposited on memory
Computer program is contained, computer program executes the 5th kind of possibility such as first aspect to first aspect when being run by processor
Any one of embodiment method.
Fourth aspect, the embodiment of the present invention also provide a kind of computer storage medium, for being stored as first aspect to
Computer software instructions used in any one of 5th kind of possible embodiment of one side method.
The embodiment of the present invention bring it is following the utility model has the advantages that
The determination method, apparatus and electronic equipment of a kind of power supply reliability provided in an embodiment of the present invention, first acquisition mesh
The component parameters of each electrical component on standard configuration power grid, and component parameters are input in the electricity distribution network model pre-established, with
Electricity distribution network model is set to determine fault element based on component parameters, wherein electricity distribution network model is established based on sequential Monte Carlo method
, the power supply reliability degree of target power distribution network is finally determined according to fault element.The embodiment of the present invention passes through sequential Meng Teka
Lip river method establishes electricity distribution network model, carries out analogue simulation to the operating condition of power distribution network, can determine fault element quickly, in turn
The time used in assessment distribution network reliability degree can be reduced, the assessment effect of distribution network reliability degree is improved
Rate.
Other features and advantages of the present invention will illustrate in the following description, also, partly become from specification
It obtains it is clear that understand through the implementation of the invention.The objectives and other advantages of the invention are in specification, claims
And specifically noted structure is achieved and obtained in attached drawing.
To enable the above objects, features and advantages of the present invention to be clearer and more comprehensible, preferred embodiment is cited below particularly, and cooperate
Appended attached drawing, is described in detail below.
Detailed description of the invention
It, below will be to specific in order to illustrate more clearly of the specific embodiment of the invention or technical solution in the prior art
Embodiment or attached drawing needed to be used in the description of the prior art be briefly described, it should be apparent that, it is described below
Attached drawing is some embodiments of the present invention, for those of ordinary skill in the art, before not making the creative labor
It puts, is also possible to obtain other drawings based on these drawings.
Fig. 1 is a kind of flow diagram of the determination method of power supply reliability provided in an embodiment of the present invention；
Fig. 2 is the flow chart of the determination method of another power supply reliability provided in an embodiment of the present invention；
Fig. 3 is a kind of structural schematic diagram of the determining device of power supply reliability provided in an embodiment of the present invention；
Fig. 4 is the structural schematic diagram of a kind of electronic equipment provided in an embodiment of the present invention.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with attached drawing to the present invention
Technical solution be clearly and completely described, it is clear that described embodiments are some of the embodiments of the present invention, rather than
Whole embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not making creative work premise
Under every other embodiment obtained, shall fall within the protection scope of the present invention.
Currently, the assessment for generalling use the power supply reliability index that analytic method carries out power distribution network calculates.Analytic method needs first
The detailed topology information and device parameter for obtaining power distribution network, the power failure for then analyzing each element one by one according to topological relation influence
Range finally adds up and obtains total power supply reliability index.But difficulty in computation and calculating time can be with the increases of number of elements
Into exponential increase, be not suitable for the complicated operating status of assessment, such as multimode element, failure-frequency and to the real-time of new energy
Monitoring simulation.Based on this, a kind of the determination method, apparatus and electronic equipment of power supply reliability provided in an embodiment of the present invention can
To reduce the calculating time of reliability index, the assessment efficiency of distribution network reliability degree is improved.
For convenient for understanding the present embodiment, first really to a kind of power supply reliability disclosed in the embodiment of the present invention
The method of determining describes in detail, a kind of flow diagram of the determination method of power supply reliability shown in Figure 1, this method packet
Include following steps:
Step S102 obtains the component parameters of each electrical component on target power distribution network.
Wherein, component parameters include element failure rate and element repair time.For the ease of obtaining the member of each electrical component
Each electrical component can be associated with preservation to predeterminable area by part parameter with the component parameters of each electrical component.It further, can be with
Component parameters table is formed, for saving the component parameters of each electrical component and each electrical component.
The component parameters of each electrical component are input to the electricity distribution network model pre-established by step S104, so that power distribution network
Model determines fault element.
In view of the dynamic timeinvariance and uncertainty of power distribution network, the operating status and shape according to electrical component are needed
Step response establish power distribution network time-varying model namely aforementioned electricity distribution network model it is related to preset failure load meter.Therefore it needs
Failure load meter is obtained, to establish electricity distribution network model according to failure load meter.Wherein, electricity distribution network model is based on sequential Meng Teka
What Lip river method was established.Monte Carlo method is a kind of computer simulation algorithm, it may be convenient to uncertain factor in processing system
It influences, for being applied in the distribution network system of service condition complexity.Sequential Monte Carlo method in Monte carlo algorithm can be with
The total element fault of distribution network system, the state migration procedure of operation and timing variations factor are emulated to the shadow of distribution network system
It rings, therefore analog simulation is carried out to target power distribution network using sequential Monte Carlo method.
Because in practical power distribution network when the operating parameter of each electrical component in a certain range the moment variation, and run ginseng
Several change procedures has certain randomness and time variation, and the operating status of power distribution network is by the operating parameter of these electrical components
It determines, the change procedure of each operation of electric element parameter of distribution network system can be emulated using sequential Monte Carlo method, thus
Determine the fault element in target power distribution network.
Step S106 is based on fault element, determines the power supply reliability degree of target power distribution network.
After obtaining fault element, load point corresponding with the fault element can be obtained by failure load meter, then
The reliability index value of load point corresponding with the fault element is calculated, and then can determine the power supply of target power distribution network
Reliability index value, and the power supply reliability index value based on target power distribution network comments the power supply reliability of target power distribution network
Estimate.
A kind of determination method of power supply reliability provided in an embodiment of the present invention, first each electricity on acquisition target power distribution network
The component parameters of gas element, and component parameters are input in the electricity distribution network model pre-established, so that electricity distribution network model is based on
Component parameters determine fault element, wherein electricity distribution network model is established based on sequential Monte Carlo method, finally according to failure member
Part determines the power supply reliability degree of target power distribution network.The embodiment of the present invention establishes power distribution network mould by sequential Monte Carlo method
Type carries out analogue simulation to the operating condition of power distribution network, can determine fault element quickly, and then can reduce assessment distribution
Time used in net power supply reliability degree improves the assessment efficiency of distribution network reliability degree.
For the ease of understanding above-described embodiment, the embodiment of the invention also provides another power supply reliabilities really
Determine method, the flow chart of the determination method of another power supply reliability shown in Figure 2, method includes the following steps:
Step S202 initializes system data, and obtains the component parameters of each electrical component on target power distribution network.
Wherein, component parameters include element failure rate λ and element repair time T, in addition, the emulation time limit should be also obtained,
So that electricity distribution network model is based on the emulation time limit and is emulated.Further, repair time mainly acquires electrical component with user
Repair rate μ, i.e.,
Step S204, the load path of traversal search target power distribution network.
Specifically, be based on breadth-first search, obtain target power distribution network on each electrical component, and with each electrical member
The connected each load point of part, then according to electrical component each on target power distribution network, and each load being connected with each electrical component
Point determines failure load meter.In one embodiment, can be by power supply, breadth-first search time be utilized
Power distribution network framework is gone through, load point each in power distribution network is associated with all electrical components for influencing its function of supplying power, forms event
Hinder load meter.Wherein, when load point is connected with electrical component, i.e., it is believed that the electrical component has influence to load point.
Step S206, random sampling fault simulation.
Before carrying out random sampling fault simulation, failure load meter should be first obtained, because in failure load meter including mesh
The electrical component of standard configuration power grid and the corresponding relationship of load point, it is possible to by sequential Monte Carlo method, establish negative with failure
The corresponding electricity distribution network model of lotus table.
After electricity distribution network model is established, emulation mould can be carried out to target power distribution network according to said elements parameter and the emulation time limit
It is quasi-, to obtain load reliability index.
Step S208 counts load reliability index.
Assuming that distribution network system is in the stable work phase, the working curve of electrical component is to obey exponential distribution, i.e.,
The average continuous working period TTF (Time to Failure, time between failures) of electrical component and mean repair time
TTR (Time to Repair, repair time) obeys quantum condition entropy.
Random number is generated first with computer first, the TTF of each electrical component of target power distribution network is calculated, to all electricity
The TTF of gas element is ranked up, and determines the smallest electrical component of time between failures, is drawn off as this simulation
Fault element.Then it recycles computer to generate new random number, calculates repairing for the smallest electrical component of time between failures
The multiple time.According to the time between failures of each electrical component of target power distribution network and the smallest electrical member of time between failures
It the repair time of part, determines fault element, specifically, generating new random number using computer again, calculates fault element
TTF, and TTR and new TTF are added to original TTF.TTF rearrangement to all electrical components, it is minimum to take out TTF value
Electrical component as fault element.
For the above process, each electrical component is calculated first and is repaired in the moment t probability f (t) to break down and in moment t
The probability g (t) completed again calculates f (t) and g (t) by formula as follows:
Above-mentioned formula is then based on to obtain:
Wherein, F (t) indicates that the fault moment of electrical component is less than the probability of t, and it is small that G (t) indicates that electrical component repairs the moment
In the probability of t.
Then F (t) and G (t) are obtained to converting:
Wherein, F ' (t) indicates that the time between failures of electrical component are the probability of t, and G ' (t) indicates repairing for electrical component
The probability that the multiple time is t.As can be seen that F ' (t) and G ' (t) is the number in section [0,1], it therefore, can be by generating position
The mode of random number between [0,1], the in turn time between failures of sampling device and repair time, formula of sampling
Are as follows:
In formula, δ1And δ2It is equally distributed random number between [0,1].Using the above method, TTF and TTR is replaced respectively
Sampling, to acquire the time between failures TTF and repair time TTR of element.To which also available element state becomes
Change cyclic process.
After determining fault element by above-mentioned cyclic process, it is connected according to failure load meter, determination with fault element
Each load point, it is assumed that fault element is initial fault, calculates power off time and the power failure of each load point being connected with fault element
Frequency, and power off time and power failure frequency are saved in load cell index table, each load is counted according to load cell index table
The reliability index of point, wherein reliability index includes above-mentioned power off time and power failure frequency.
Step S210 calculates target distribution network system reliability index.
According to the power off time and power failure frequency of each load point being connected with fault element, the power supply of target power distribution network is determined
Reliability standard, that is, determining the reliability index of target distribution network system according to the reliability index of each load point.Based on institute
Load cell index table is stated, determines the power supply target value of the target power distribution network, then, according to the power supply target value, to institute
The power supply reliability degree for stating target power distribution network is determined.Wherein, it is mainly born according to fault simulation and all of indicator-specific statistics
The average value of the reliability index of lotus, to calculate the reliability index of system.
The determination method, apparatus and electronic equipment of a kind of power supply reliability provided in an embodiment of the present invention, first acquisition mesh
The component parameters of each electrical component on standard configuration power grid, and component parameters are input in the electricity distribution network model pre-established, with
Electricity distribution network model is set to determine fault element based on component parameters, wherein electricity distribution network model is established based on sequential Monte Carlo method
, the power supply reliability degree of target power distribution network is finally determined according to fault element.The embodiment of the present invention passes through sequential Meng Teka
Lip river method establishes electricity distribution network model, carries out analogue simulation to the operating condition of power distribution network, can determine fault element quickly, in turn
The time used in assessment distribution network reliability degree can be reduced, the assessment effect of distribution network reliability degree is improved
Rate.
Further, the embodiment of the present invention includes LP (Load path, load path), FS (Fault simulation,
Fault simulation), (System index calculation, system refer to by IS (Index statistics, indicator-specific statistics) and SIC
Mark calculates).
Wherein, LP, by confirming the influence path of each load point, forms event for confirming all elements for influencing each load
Hinder load meter.Specifically, power grid architecture is traversed using breadth-first search by power supply, it will be each negative in power grid
Lotus point associates with all electrical components for influencing its function of supplying power, forms failure load meter.
Simulation of the FS for electrical component failure in power distribution network.Specifically, being built using sequential Monte Carlo method to power distribution network
Varying model (that is, aforementioned electricity distribution network model) immediately carries out analogue simulation to the operating condition of distribution system, obtains failure member
Part.
IS is used to count the reliability index of electrical component and load.
SIC is used to calculate the reliability index of distribution network system.Specifically, mainly according to fault simulation and indicator-specific statistics
As a result, the average value of the reliability index of all loads is found out, to calculate the reliability index of system.
In conclusion the embodiment of the present invention establishes time-varying model to power distribution network using sequential Monte Carlo method, to distribution
The operating condition of net system carries out analogue simulation, while dexterously applying breadth first search method traversal power distribution network and forming event
Hinder load meter, causes the load having a power failure to quickly locate failure, improve computational efficiency；While reliability index statistics
Load cell index table is formed, the time of reliability index statistics is reduced, improves whole efficiency.
For the determination method for the power supply reliability that previous embodiment provides, the embodiment of the invention also provides a kind of power supplies
The determining device of reliability, a kind of structural schematic diagram of the determining device of power supply reliability shown in Figure 3, the device include
Following part:
Parameter acquisition module 302, for obtaining the component parameters of each electrical component on target power distribution network.
Input module 304, for the component parameters of each electrical component to be input to the electricity distribution network model pre-established, so that
Electricity distribution network model determines fault element；Wherein, affiliated electricity distribution network model is established based on sequential Monte Carlo method.
Reliability determining module 306 determines the power supply reliability degree of target power distribution network for being based on fault element.
The determination method, apparatus and electronic equipment of a kind of power supply reliability provided in an embodiment of the present invention, pass through ginseng first
Number obtains the component parameters for each electrical component that module obtains on target power distribution network, and is input to component parameters by input module
In the electricity distribution network model pre-established, so that electricity distribution network model determines fault element based on component parameters, wherein electricity distribution network model
It is to be established based on sequential Monte Carlo method, final reliability determining module determines the power supply of target power distribution network according to fault element
Reliability standard.The embodiment of the present invention establishes electricity distribution network model by sequential Monte Carlo method, to the operating condition of power distribution network into
Row analogue simulation can quickly determine fault element, so can reduce assessment distribution network reliability degree used in when
Between, improve the assessment efficiency of distribution network reliability degree.
Further, above-mentioned apparatus is also used to obtain failure load meter, and passes through sequential Monte Carlo method, foundation and failure
The corresponding electricity distribution network model of load meter.Wherein, pair of the electrical component in failure load meter including target power distribution network and load point
It should be related to.
The technical effect and preceding method embodiment phase of device provided by the embodiment of the present invention, realization principle and generation
Together, to briefly describe, Installation practice part does not refer to place, can refer to corresponding contents in preceding method embodiment.
The equipment is a kind of electronic equipment, specifically, the electronic equipment includes processor and storage device；On storage device
It is stored with computer program, computer program executes any one institute of embodiment as described above when being run by the processor
The method stated.
Fig. 4 is the structural schematic diagram of a kind of electronic equipment provided in an embodiment of the present invention, which includes: place
Device 40 is managed, memory 41, bus 42 and communication interface 43, the processor 40, communication interface 43 and memory 41 pass through bus
42 connections；Processor 40 is for executing the executable module stored in memory 41, such as computer program.
Wherein, memory 41 may include high-speed random access memory (RAM, Random Access Memory),
It may further include non-labile memory (non-volatile memory), for example, at least a magnetic disk storage.By extremely
A few communication interface 43 (can be wired or wireless) is realized logical between the system network element and at least one other network element
Letter connection, can be used internet, wide area network, local network, Metropolitan Area Network (MAN) etc..
Bus 42 can be isa bus, pci bus or eisa bus etc..The bus can be divided into address bus, data
Bus, control bus etc..Only to be indicated with a four-headed arrow convenient for indicating, in Fig. 4, it is not intended that an only bus or
A type of bus.
Wherein, memory 41 is for storing program, and the processor 40 executes the journey after receiving and executing instruction
Sequence, method performed by the device that the stream process that aforementioned any embodiment of the embodiment of the present invention discloses defines can be applied to handle
In device 40, or realized by processor 40.
Processor 40 may be a kind of IC chip, the processing capacity with signal.During realization, above-mentioned side
Each step of method can be completed by the integrated logic circuit of the hardware in processor 40 or the instruction of software form.
Above-mentioned processor 40 can be general processor, including central processing unit (Central Processing
Unit, abbreviation CPU), network processing unit (Network Processor, abbreviation NP) etc.；It can also be digital signal processor
(Digital Signal Processing, abbreviation DSP), specific integrated circuit (Application Specific
Integrated Circuit, abbreviation ASIC), ready-made programmable gate array (Field-Programmable Gate Array,
Abbreviation FPGA) either other programmable logic device, discrete gate or transistor logic, discrete hardware components.It can be real
Now or execute the embodiment of the present invention in disclosed each method, step and logic diagram.General processor can be micro process
Device or the processor are also possible to any conventional processor etc..The step of method in conjunction with disclosed in the embodiment of the present invention, can
Execute completion to be embodied directly in hardware decoding processor, or in decoding processor hardware and software module combination execute
It completes.Software module can be located at random access memory, flash memory, read-only memory, programmable read only memory or electrically-erasable
In the storage medium of this fields such as programmable storage, register maturation.The storage medium is located at memory 41, and processor 40 is read
Information in access to memory 41, in conjunction with the step of its hardware completion above method.
The determination method, apparatus of power supply reliability provided by the embodiment of the present invention and the computer program of electronic equipment produce
Product, the computer readable storage medium including storing the executable non-volatile program code of processor are computer-readable to deposit
It is stored with computer program on storage media, it is as described in the examples that previous methods are executed when which is run by processor
Method, specific implementation can be found in embodiment of the method, and details are not described herein.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description
Specific work process, can be with reference to the corresponding process in previous embodiment, and details are not described herein.
The computer program product of readable storage medium storing program for executing provided by the embodiment of the present invention, including storing program code
Computer readable storage medium, the instruction that said program code includes can be used for executing previous methods side as described in the examples
Method, specific implementation can be found in embodiment of the method, and details are not described herein.
It, can be with if the function is realized in the form of SFU software functional unit and when sold or used as an independent product
It is stored in a computer readable storage medium.Based on this understanding, technical solution of the present invention is substantially in other words
The part of the part that contributes to existing technology or the technical solution can be embodied in the form of software products, the meter
Calculation machine software product is stored in a storage medium, including some instructions are used so that a computer equipment (can be a
People's computer, server or network equipment etc.) it performs all or part of the steps of the method described in the various embodiments of the present invention.
And storage medium above-mentioned includes: that USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), arbitrary access are deposited
The various media that can store program code such as reservoir (RAM, Random Access Memory), magnetic or disk.
Finally, it should be noted that embodiment described above, only a specific embodiment of the invention, to illustrate the present invention
Technical solution, rather than its limitations, scope of protection of the present invention is not limited thereto, although with reference to the foregoing embodiments to this hair
It is bright to be described in detail, those skilled in the art should understand that: anyone skilled in the art
In the technical scope disclosed by the present invention, it can still modify to technical solution documented by previous embodiment or can be light
It is readily conceivable that variation or equivalent replacement of some of the technical features；And these modifications, variation or replacement, do not make
The essence of corresponding technical solution is detached from the spirit and scope of technical solution of the embodiment of the present invention, should all cover in protection of the invention
Within the scope of.Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. a kind of determination method of power supply reliability characterized by comprising
Obtain the component parameters of each electrical component on target power distribution network；
The component parameters of each electrical component are input to the electricity distribution network model pre-established, so that the electricity distribution network model is true
Determine fault element；Wherein, the electricity distribution network model is established based on sequential Monte Carlo method；The electricity distribution network model and default
Failure load meter it is related；
Based on the fault element, the power supply reliability degree of the target power distribution network is determined.
2. the method according to claim 1, wherein the establishment process of electricity distribution network model, comprising:
Obtain failure load meter；It wherein, include the electrical component and load point of the target power distribution network in the failure load meter
Corresponding relationship；
By sequential Monte Carlo method, electricity distribution network model corresponding with the failure load meter is established.
3. according to the method described in claim 2, it is characterized in that, the step of obtaining failure load meter, comprising:
Based on breadth-first search, obtain each electrical component on the target power distribution network, and with it is each described electrical
The connected each load point of element；
According to the electrical component each on the target power distribution network, and each load point being connected with each electrical component, really
Determine failure load meter.
4. according to the method described in claim 2, it is characterized in that, determining the target power distribution network based on the fault element
Power supply reliability degree the step of, comprising:
According to the failure load meter, each load point being connected with the fault element is determined；
Based on the fault element, the power off time and power failure frequency of each load point being connected with the fault element are calculated；
According to the power off time and power failure frequency of each load point being connected with the fault element, the power supply of target power distribution network is determined
Reliability standard.
5. according to the method described in claim 4, it is characterized in that, being stopped according to each load point being connected with the fault element
Electric time and power failure frequency, the step of determining the power supply reliability degree of the target power distribution network, comprising:
The power off time for each load point being connected with the fault element and power failure frequency are saved to predeterminable area, load is obtained
Element index table；
Based on the load cell index table, the power supply target value of the target power distribution network is determined；
According to the power supply target value, the power supply reliability degree of the target power distribution network is determined.
6. the method according to claim 1, wherein electricity distribution network model determines the step of fault element, comprising:
The time between failures of each electrical component of target power distribution network are calculated, and determine the time between failures most
Small electrical component；
Calculate the repair time of the smallest electrical component of the time between failures；
It is the smallest according to the time between failures of each electrical component of target power distribution network and the time between failures
The repair time of electrical component, determine fault element.
7. a kind of determining device of power supply reliability characterized by comprising
Parameter acquisition module, for obtaining the component parameters of each electrical component on target power distribution network；
Input module, for the component parameters of each electrical component to be input to the electricity distribution network model pre-established, so that institute
It states electricity distribution network model and determines fault element；Wherein, the electricity distribution network model is established based on sequential Monte Carlo method；It is described to match
Electric network model is related to preset failure load meter；
Reliability determining module determines the power supply reliability degree of the target power distribution network for being based on the fault element.
8. device according to claim 7, which is characterized in that described device is also used to:
Obtain failure load meter；It wherein, include the electrical component and load point of the target power distribution network in the failure load meter
Corresponding relationship；
By sequential Monte Carlo method, electricity distribution network model corresponding with the failure load meter is established.
9. a kind of electronic equipment, which is characterized in that including processor and memory；
Computer program is stored on the memory, the computer program executes such as right when being run by the processor
It is required that 1 to 6 described in any item methods.
10. a kind of computer storage medium, which is characterized in that for being stored as used in any one of claim 1 to 6 the method
Computer software instructions.
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