CN106897814A - Operation states of electric power system reliability evaluation system and application based on multiple factors - Google Patents
Operation states of electric power system reliability evaluation system and application based on multiple factors Download PDFInfo
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- CN106897814A CN106897814A CN201710030096.XA CN201710030096A CN106897814A CN 106897814 A CN106897814 A CN 106897814A CN 201710030096 A CN201710030096 A CN 201710030096A CN 106897814 A CN106897814 A CN 106897814A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
Abstract
The invention belongs to operation states of electric power system reliability assessment field, specifically a kind of operation states of electric power system reliability evaluation system and application based on multiple factors.The system includes Information Collecting ＆ Processing module, non-sequential Monte Carlo sample process module, the operation states of electric power system reliability assessment processing module of failure factor；The Information Collecting ＆ Processing module of the failure factor includes external environment condition Weather information harvester, power system device maloperation information collecting device, power system device ageing state apparatus for evaluating, power system device manufacturing defect rate statistic device；The present invention can comprehensively gather various parameter that may be impacted to the reliability service of power system, and send data to operation states of electric power system reliability assessment processing module, the influence that the generation of various randomness events may be caused to Operation of Electric Systems is substantially envisaged, with boundless technology application prospect and potential economic worth.
Description
Technical field
The invention belongs to operation states of electric power system reliability assessment field, specifically a kind of electric power based on multiple factors
System running state reliability evaluation system and application.
Background technology
Power system as social security basic activity, its ruuning situation is close with national life and social and economic activities
Cut is closed, and ensure that it is substantially to work about electric power to provide safe efficient, lasting, stabilization a power supply environment
Ask.The task of power system is to provide a user with electric energy continually, up-to-standard.Due to the equipment of power system, including
The primary equipments such as generator, transformer, transmission line of electricity, breaker and matched secondary device, can all occur different type
Failure so that influence power system normally operation and to user's normal power supply.Electric power system fault is to electric power enterprise, Yong Huhe
National economy some links can all cause different degrees of economic loss.With the quickening of social modernization's process, produce and raw
Work is increasing to the dependence of power supply, thus the loss that causes of having a power failure also increasingly increases, therefore has to Power System Reliability
Higher and higher requirement.The most basic function of power system is to provide electric energy, that is, continual fixation is provided to people
Up-to-standard electric energy.The main task of Operation of Electric Systems reliability is：The exactly accumulative force device for first having to do is being gone through
The data produced in history running and the data accumulated after reliability testing has been carried out to element, then with regard to these data
Further carry out the reliability of analysis element.
Whole power system network is made up of various electric network elements, thus power system operational reliability
State with each electric network element is closely bound up.Operation of the different conditions of these electric network elements to system has very big shadow
Ring.When the equipment to power system carries out fail-safe analysis, the reliability level of element and ambient weather environment, whether
The change whether generation maloperation, equipment occur aging, equipment these factors of manufacturing defect rate is relevant.Therefore, it can utilize
The reliability of the reliable sex expression Operation of Electric Systems of these elements.The present invention can comprehensively gather it is various may be to electricity
The parameter that the reliability service of Force system is impacted, and send data to operation states of electric power system reliability assessment treatment mould
Block, substantially envisages the influence that the generation of various randomness events may be caused to Operation of Electric Systems, with boundless
Technology application prospect and potential economic worth.
The content of the invention
For accurate evaluation Power System Reliability, the invention provides a kind of Operation of Electric Systems based on multiple factors
State reliability evaluation system and application, concrete technical scheme are as follows：
A kind of operation states of electric power system reliability evaluation system based on multiple factors is included at the information gathering of failure factor
Reason module, non-sequential Monte Carlo sample process module, operation states of electric power system reliability assessment processing module；The failure
The Information Collecting ＆ Processing module of factor is used to gather causes the unreliable factor of power system abnormal running；The non-sequential illiteracy
Special Carlow sample process module is used to set sampling cycle-index under given required precision, to the electricity of all kinds of unreliable factors
Force system state carries out random sampling, and sets up the state matrix of system；At the operation states of electric power system reliability assessment
Reason module is used to calculate the unreliable influence degree grading index of network system under every kind of unreliable factor, to Operation of Electric Systems
The reliability of state is estimated；The Information Collecting ＆ Processing module of the failure factor includes that external environment condition Weather information gathers dress
Put, power system device maloperation information collecting device, power system device ageing state apparatus for evaluating, power system device system
Make ratio of defects statistic device；The external environment condition Weather information harvester, power system device maloperation information collecting device,
Power system device ageing state apparatus for evaluating, power system device manufacturing defect rate statistic device by collect it is unreliable because
Element input to the Information Collecting ＆ Processing module of failure factor is processed, after the Information Collecting ＆ Processing module of failure factor will be processed
Data input to non-sequential Monte Carlo sample process module processed, non-sequential Monte Carlo sample process module will locate
Data input after reason is to operation states of electric power system reliability assessment processing module.
Further, the external environment condition Weather information includes high temperature, ice and snow, typhoon, heavy rain, thunderbolt.
Further, the unreliable factor includes weather conditions, the electricity that external environment condition Weather information harvester is collected
Equipment misoperation factor, power system device ageing state assessment dress that Force system equipment misoperation information collecting device is collected
Put the ageing equipment factor that collects, the device fabrication ratio of defects that power system device manufacturing defect rate statistic device is collected because
Element.
A kind of application of the operation states of electric power system reliability evaluation system based on multiple factors is comprised the following steps：
（1）By the Information Collecting ＆ Processing module of unreliable factor data input to failure factor；
（2）Calculate the unreliable rate of power system device：By the Information Collecting ＆ Processing module collection of failure factor and process not
Responsible factor data, and i-th kind of unreliable factor is calculated in its unreliable influence degree etc. by setting up unreliable rate model
Level beWhen caused unreliable rate,By equationCalculate, wherein,For can not at it under i-th kind of factor
It is by influence degree gradeWhen equipment fault number of times；The failure total degree for being the equipment under i-th kind of unreliable factor；
The information of unreliable influence degree grade is obtained by counting；
（3）Unreliable rate information transfer to non-sequential Monte Carlo after by the Information Collecting ＆ Processing resume module of failure factor is taken out
Sample processing module；POWER SYSTEM STATE x is made up of the state of all power system device elements, and the state of each element uses one
It is individual to be uniformly distributed to represent in [0,1] interval；Each element has reliable and unreliable two states, and part failure rate is
Separate；I-th state of element is represented,Its unreliable rate is represented, then one is produced in [0,1] area to element a
Between equally distributed random number, make
；
Represent that then the state of this K equipment component together form by vector z with the K system mode of power equipment element
The state z=of whole power system（,…,,…,）；Sequential Monte Carlo sample process module to it is above-mentioned at random
By sexual factor random sampling, the system mode corresponded to after the m times sampling in L sampling of system can be designated as=（,…,,…,）（M=1,2 ..., L）；The state matrix of formation system：
；
Wherein, K is power equipment component population；
If P（Z）For the probability that power equipment element state Z occurs, and power system are constituted and owned by K power equipment element
The state of power equipment is stochastic variable independent of each other, now, P（）=P() ... P () ... P (）；
（4）Non- sequential Monte Carlo takes out that [sample processing module is by state matrix data transfer to operation states of electric power system reliability
Assessment processing module, calculates the unreliable influence degree grading index of network system under every kind of event, to Operation of Electric Systems shape
The reliability of state is estimated；The unreliable influence degree grading index of network system is by test function F（）Expression；
（5）In the operation reliability evaluation of power system, define probability that unreliable rate occurs for unreliable factor with it is unreliable
The product of influence degree grading index, the unreliability E of operation of power networks is expressed as the wind that all anticipation unreliability factors occur
Dangerous sum, its expression formula is as follows：
；
E is the unreliability index of operation of power networks, and z is power equipment element state, and Z is power equipment element state set, F
（Z）It is the unreliable influence degree grading index of network system, P（Z）For the probability that power equipment element state Z occurs.
Further, the step（3）InIt is a stochastic variable, z is a random vector.
Beneficial effects of the present invention are：
1st, collection is multiple may cause the factor of power system device failure, not only allow for that power system component event may be caused
The internal factor of barrier, it is also contemplated that the influence of this kind of external enchancement factor to component reliability such as weather, can obtain by unit
The reliability of the Operation of Electric Systems under part internal factor and external factor collective effect, be easy to network operation personnel can and
When ready process Operation of Electric Systems hidden danger that may be present；
2nd, using non-sequential Monte Carlo simulation, it is only necessary to the unreliable probability of element as sampling process input data,
And the method can apply to the hydrology and the isoparametric state sampling of weather.Also, this method is not limited to year as base
The simulation of plinth, can also be conveniently used with carries out random time section（Week, the moon, season or year）Simulation；
3rd, can be very good to be adapted in the assessment of Operation of Electric Systems security risk using non-sequential Monte Carlo simulation, this
The foundation of individual method be system mode be all element states combination, and each element state can appear in by element
The shape probability of state is sampled to determine；
4th, the speed of sampling can be accelerated using non-sequential Monte Carlo simulation.
Brief description of the drawings
Fig. 1 is a kind of structural representation of the operation states of electric power system reliability evaluation system based on multiple factors of the present invention
Figure.
Specific embodiment
In order to be better understood from the present invention, with reference to specific embodiment, the invention will be further described：
A kind of operation states of electric power system reliability evaluation system based on multiple factors is included at the information gathering of failure factor
Reason module, non-sequential Monte Carlo sample process module, operation states of electric power system reliability assessment processing module；The failure
The Information Collecting ＆ Processing module of factor is used to gather causes the unreliable factor of power system abnormal running；The non-sequential illiteracy
Special Carlow sample process module is used to set sampling cycle-index under given required precision, to the electricity of all kinds of unreliable factors
Force system state carries out random sampling, and sets up the state matrix of system；At the operation states of electric power system reliability assessment
Reason module is used to calculate the unreliable influence degree grading index of network system under every kind of unreliable factor, to Operation of Electric Systems
The reliability of state is estimated；The Information Collecting ＆ Processing module of the failure factor includes that external environment condition Weather information gathers dress
Put, power system device maloperation information collecting device, power system device ageing state apparatus for evaluating, power system device system
Make ratio of defects statistic device；The external environment condition Weather information harvester, power system device maloperation information collecting device,
Power system device ageing state apparatus for evaluating, power system device manufacturing defect rate statistic device by collect it is unreliable because
Element input to the Information Collecting ＆ Processing module of failure factor is processed, after the Information Collecting ＆ Processing module of failure factor will be processed
Data input to non-sequential Monte Carlo sample process module processed, non-sequential Monte Carlo sample process module will locate
Data input after reason is to operation states of electric power system reliability assessment processing module.
Further, the external environment condition Weather information includes high temperature, ice and snow, typhoon, heavy rain, thunderbolt.
Further, the unreliable factor includes weather conditions, the electricity that external environment condition Weather information harvester is collected
Equipment misoperation factor, power system device ageing state assessment dress that Force system equipment misoperation information collecting device is collected
Put the ageing equipment factor that collects, the device fabrication ratio of defects that power system device manufacturing defect rate statistic device is collected because
Element.
A kind of application of the operation states of electric power system reliability evaluation system based on multiple factors is comprised the following steps：
（1）Weather data, the power system device maloperation information gathering that external environment condition Weather information harvester is collected
Ageing equipment data that equipment misoperation data that device is collected, power system device ageing state apparatus for evaluating are collected,
The device fabrication ratio of defects data input that power system device manufacturing defect rate statistic device is collected to failure factor information
Acquisition processing module；
（2）Calculate the unreliable rate of power system device：By the Information Collecting ＆ Processing module collection of failure factor and process not
Responsible factor data, and i-th kind of unreliable factor is calculated in its unreliable influence degree etc. by setting up unreliable rate model
Level beWhen caused unreliable rate,By equationCalculate, wherein, it is in its unreliable shadow under i-th kind of factor
Ring the number of times of equipment fault when intensity grade is；The failure total degree for being the equipment under i-th kind of unreliable factor；No
The information of effected reliably intensity grade is obtained by relevant departments' statistics；
（3）By the unreliable rate after the Information Collecting ＆ Processing resume module of failure factorInformation transfer is to non-sequential Meng Teka
Lip river sample process module；POWER SYSTEM STATE x is made up of the state of all power system device elements, the state of each element
It is uniformly distributed to represent in [0,1] interval with one；Each element has reliable and unreliable two states, and component failure
Rate is separate.I-th state of element is represented, its unreliable rate is represented, then one is produced in [0,1] area to element a
Between equally distributed random number, make
；
Represent that then the state of this K equipment component together form by vector z with the K system mode of power equipment element
The state z=of whole power system（,…,,…,）；It is a stochastic variable, z is a random vector, non-sequential illiteracy
Special Carlow sample process module corresponds to the m times sampling to above-mentioned random unreliability factors random sampling in L sampling of system
System mode afterwards can be designated as=（,…,,…,）（m=1,2,…,L）；The state matrix of formation system：
；
Wherein, K is component population；
If P（Z）For the probability that power equipment element state Z occurs, and power system are constituted and owned by K power equipment element
The state of power equipment is stochastic variable independent of each other, now, P（）=P() ... P () ... P (）；
（4）Non- sequential Monte Carlo sample process module comments state matrix data transfer to operation states of electric power system reliability
Estimate processing module, the unreliable influence degree grading index of network system under every kind of event is calculated, to operation states of electric power system
Reliability be estimated；The unreliable influence degree grading index of network system is by test function F（）Expression；
（5）In the operation reliability evaluation of power system, define probability that unreliable rate occurs for unreliable factor with it is unreliable
The product of influence degree grading index, therefore, the unreliability E of operation of power networks is expressed as all anticipation unreliability factors to be occurred
Risk sum, its expression formula is as follows：
；
E is the unreliability index of operation of power networks, and z is power equipment element state, and Z is power equipment element state set, F
（Z）It is the unreliable influence degree grading index of network system, P（Z）For the probability that power equipment element state Z occurs.
The present invention is not limited to above-described specific embodiment, the foregoing is only preferable case study on implementation of the invention
, it is not intended to limit the invention, all any modifications made within the spirit and principles in the present invention, equivalent and change
Enter, should be included within the scope of the present invention.
Claims (5)
1. a kind of operation states of electric power system reliability evaluation system based on multiple factors, it is characterised in that：Including failure because
The Information Collecting ＆ Processing module of element, non-sequential Monte Carlo sample process module, at operation states of electric power system reliability assessment
Reason module；The Information Collecting ＆ Processing module of the failure factor be used for gather cause power system abnormal running it is unreliable because
Element；The non-sequential Monte Carlo sample process module is used to set sampling cycle-index under given required precision, to each
The POWER SYSTEM STATE of class unreliable factor carries out random sampling, and sets up the state matrix of system；The Operation of Electric Systems
The unreliable influence degree grade that state reliability assessment processing module is used to calculate network system under every kind of unreliable factor refers to
Mark, the reliability to operation states of electric power system is estimated；The Information Collecting ＆ Processing module of the failure factor includes outside
Ambient weather information collecting device, power system device maloperation information collecting device, the assessment of power system device ageing state
Device, power system device manufacturing defect rate statistic device；The external environment condition Weather information harvester, power system device
Maloperation information collecting device, power system device ageing state apparatus for evaluating, power system device manufacturing defect rate statistics dress
Put the unreliable factor that will be collected and be input into the Information Collecting ＆ Processing module of failure factor and processed, the information of failure factor
Acquisition processing module is processed the data input after treatment to non-sequential Monte Carlo sample process module, and non-sequential illiteracy is special
Carlow sample process module is by the data input after treatment to operation states of electric power system reliability assessment processing module.
2. a kind of operation states of electric power system reliability evaluation system based on multiple factors according to claim 1, its
It is characterised by：The external environment condition Weather information includes high temperature, ice and snow, typhoon, heavy rain, thunderbolt.
3. a kind of operation states of electric power system reliability evaluation system based on multiple factors according to claim 1, its
It is characterised by：The unreliable factor includes weather conditions, the power system that external environment condition Weather information harvester is collected
Equipment misoperation factor, the collection of power system device ageing state apparatus for evaluating that equipment misoperation information collecting device is collected
To ageing equipment factor, the device fabrication ratio of defects factor that collects of power system device manufacturing defect rate statistic device.
4. a kind of application of the operation states of electric power system reliability evaluation system based on multiple factors, it is characterised in that：Including
Following steps：
（1）By the Information Collecting ＆ Processing module of unreliable factor data input to failure factor；
（2）Calculate the unreliable rate of power system device：By the Information Collecting ＆ Processing module collection of failure factor and process not
Responsible factor data, and i-th kind of unreliable factor is calculated in its unreliable influence degree etc. by setting up unreliable rate model
Level beWhen caused unreliable rate,By equationCalculate, wherein,For unreliable at its under i-th kind of factor
Influence degree grade isWhen equipment fault number of times；The failure total degree for being the equipment under i-th kind of unreliable factor；
The information of unreliable influence degree grade is obtained by counting；
（3）By the unreliable rate after the Information Collecting ＆ Processing resume module of failure factorInformation transfer is to non-sequential Monte Carlo
Sample process module；POWER SYSTEM STATE x is made up of the state of all power system device elements, and the state of each element is used
One is uniformly distributed to represent in [0,1] interval；Each element has reliable and unreliable two states, and part failure rate
It is separate；I-th state of element is represented,Its unreliable rate is represented, then one is produced in [0,1] to element a
Interval equally distributed random number, make
；
Represent that then the state of this K equipment component together form by vector z with the K system mode of power equipment element
The state z=of whole power system（,…,,…,）；Sequential Monte Carlo sample process module to it is above-mentioned at random
By sexual factor random sampling, the system mode corresponded to after the m times sampling in L sampling of system can be designated as=（,…,,…,）（M=1,2 ..., L）；The state matrix of formation system：
；
Wherein, K is power equipment component population；
If P（Z）For the probability that power equipment element state Z occurs, and power system are constituted and owned by K power equipment element
The state of power equipment is stochastic variable independent of each other, now, P（）=P() ... P () ... P (）；
（4）Non- sequential Monte Carlo takes out that [sample processing module is by state matrix data transfer to operation states of electric power system reliability
Assessment processing module, calculates the unreliable influence degree grading index of network system under every kind of event, to Operation of Electric Systems shape
The reliability of state is estimated；The unreliable influence degree grading index of network system is by test function F（）Expression；
（5）In the operation reliability evaluation of power system, define probability that unreliable rate occurs for unreliable factor with it is unreliable
The product of influence degree grading index, the unreliability E of operation of power networks is expressed as the wind that all anticipation unreliability factors occur
Dangerous sum, its expression formula is as follows：
E is the unreliability index of operation of power networks, and z is power equipment element state, and Z is power equipment element state set, F
（Z）It is the unreliable influence degree grading index of network system, P（Z）For the probability that power equipment element state Z occurs.
5. a kind of operation states of electric power system reliability evaluation system based on multiple factors according to claim 4
Using, it is characterised in that：The step（3）InIt is a stochastic variable, z is a random vector.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107863771A (en) * | 2017-10-12 | 2018-03-30 | 浙江大学 | Multimode power system redundancy optimization method based on sequence optimization and Monte Carlo |
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2017
- 2017-01-17 CN CN201710030096.XA patent/CN106897814A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107863771A (en) * | 2017-10-12 | 2018-03-30 | 浙江大学 | Multimode power system redundancy optimization method based on sequence optimization and Monte Carlo |
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Application publication date: 20170627 |
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