CN106980918A - A kind of generating and transmitting system reliability evaluation system - Google Patents
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Abstract
The present invention discloses a kind of generating and transmitting system reliability evaluation system, module, reliability model of unit, which are built, including reliability index builds module, simulated sampling module, computing module and output module, the present invention uses component state duration sampling method, frequency in sampling depends on Evaluation accuracy, and it is unrelated with system scale, and dimension of its convergence rate also with problem is unrelated, the reliability assessment of large-scale electrical power system is particularly suitable for use in；And by merging identical systems state, considerably reduce the status number for needing to assess；It is estimated by the way that multiple failure is converted into substance failure, so as to accelerate the estimating velocity of each system mode, can thus greatly reduces the assessment time of whole system.
Description
Technical field
The invention belongs to power system simulation and calculating field, and in particular to a kind of generating and transmitting system reliability assessment system
System.
Background technology
Power system is a complexity, dynamic system, power system traditionally is divided into some subsystems, according to these
The function of subsystem assesses the reliability of each subsystem respectively, including：Electricity generation system, transmission system, Composite power system, match somebody with somebody
Electric system and power plant Main Electrical Connection in Transformer Substation reliability assessment.The functional characteristics of these subsystems be it is different, it is practical
Appraisal procedure and the reliability index of use are also different, and its degree of perfection has very big difference.Generating and transmitting system is also known as
Large power system.There is a problem in the practical engineering application of large power system abundant intensity reliability assessment, that is, calculate always
Complexity, into obstruction, it is widely popularized the major obstacle used for this.In order to solve this problem, scholars propose big in succession
The quick partitioning algorithm of Reliability evaluation, the parallel processing algorithm based on sequential Monte Carlo simulation, genetic algorithm are found
Contribute Reliability Index maximum system mode, Fault Pattern Recognition, profit are carried out to system mode using neutral net
Optimal load curtailment is carried out with neutral net to alleviate " the calculating calamity " of reliability assessment, carry out big power train using network flow programming
The methods such as system reliability assessment.
Although large power system adequacy evaluation by thirties years development oneself through achieving substantial amounts of achievement in research,
As the development of computer technology and other related disciplines, particularly power system are constantly to super-pressure, remote, Large Copacity side
To development, system scale is increasing, and the method for operation of system also becomes increasingly complex so that large power system does not have before being provided with
Some new features, this also requires that Approach for Bulk Power Systems Reliability Assessment will carry out corresponding analysis according to this development and change and grind simultaneously
Study carefully.At present, related research still suffers from sizable difficulty.
Generating and transmitting system Calculation of Reliability is typically using AC power flow analytic approach, DC power flow analytic approach or net stream cut set method
Deng method system.But, it is right when tidal current analysis method particularly AC power flow analytic approach is applied to generating and transmitting system Calculation of Reliability
" dimension calamity " problem occurs in large scale system.Its main cause is to need to carry out the state of each analysis accident exchange tide
Flow point is analysed, or even accident stability analysis.When overload, voltage out-of-limit occurs in system, optimal load curtailment calculating is still carried out.
And the calculating of electric power system alternating current trend is the Solve problems of one group of Nonlinear System of Equations, stability Calculation is then Nonlinear System of Equations
Optimization with the Solve problems of differential equation group, and load reduction, which is calculated, is related to a Large Scale Nonlinear planning（Optimization）Ask
Topic.For a medium scale system, in fact it could happen that accident state it is in a large number.If to each shape
If state will carry out tidal current analysis, stability analysis and load reduction calculating, its amount of calculation will be very big.If Shang Yaokao
Consider the influence of the influence, such as weather, load model of objective factor, then whole amount of calculation is up to the degree being difficult to.
The content of the invention
To overcome the weak point that prior art is present, the present invention provides one kind and reduced in the case where ensuring computational accuracy
The generating and transmitting system reliability evaluation system of computation complexity.To realize above-mentioned target, the technical solution adopted by the present invention is：
A kind of generating and transmitting system reliability evaluation system, including reliability index build module, reliability model of unit and build mould
Block, simulated sampling module, computing module and output module, the reliability index, which builds module, to be used to build assessment hair transmission of electricity system
The reliability index of system；The reliability model of unit, which builds module, to be used to build the component reliability mould for assessing generating and transmitting system
Type；The operation that the simulated sampling module is used for generating and transmitting system carries out simulated sampling, obtains system mode sequence；The meter
Calculating module is used to calculate the reliability index that the reliability index builds module construction；The output module is used to export described
The result of calculation of computing module；The reliability index builds module and is connected with reliability model of unit structure module, institute
State reliability model of unit structure module with the simulated sampling module to be connected, the simulated sampling module and the computing module
Connection, the computing module is connected with the output module.
It is preferred that, the reliability index includes cutting load probability P LC, cutting load frequency EFLC, cutting load duration
EDLC, average cutting load duration ADLC, cutting load desired value ELC, expected loss of energy EENS, system blackout index
BPII, system cut down electricity index BPECI and severity index S I.
It is preferred that, the reliability model of unit be two state models, two state include failure-free operation state and
Fault restoration state.
It is preferred that, the simulated sampling module is taken out using component state duration sampling method to generating and transmitting system
Sample.
It is preferred that, the component state duration sampling method merges identical system mode in sampling process.
It is preferred that, multiple failure is assessed and is converted into substance assessment of failure by the component state duration sampling method.
It is preferred that, the calculation formula of the reliability index is by the Monte Carlo using component state duration sampling method
Method is exported.
Compared with prior art, beneficial effects of the present invention are：
（1）What the present invention sampled is element state duration rather than element state, and the system considers Operation of Electric Systems
The timing of state, therefore can accurately calculate the reliability index in actual motion on timing, it is adaptable to stochastic production
Simulation is calculated the cost of production, while helping to instruct real system to plan and economic evaluation.
（2）The great advantage of the present invention is that convergence rate is unrelated with the dimension of problem, and this feature determines the system pair
The practicality of multidimensional, higher-dimension problem.In the reliability assessment of power system, compared with analytic method, system scale is bigger, this hair
Bright advantage is more obvious.
（3）The present invention considerably reduces the status number for needing to assess, so as to accelerate to comment by merging identical systems state
Estimate speed.
（4）The present invention is estimated by the way that multiple failure is converted into substance failure, greatly accelerates each system mode
Estimating velocity.
（5）The frequency in sampling of the present invention depends on Evaluation accuracy, and unrelated with system scale, is therefore particularly suitable for big rule
The reliability assessment of mould power system.
Brief description of the drawings
Fig. 1 is a kind of structural representation of generating and transmitting system reliability evaluation system of the invention.
Fig. 2 is that repairable elements of the present invention are run and stoppage in transit cyclic process schematic diagram.
Fig. 3 is repairable elements state space schematic diagram of the present invention.
Fig. 4 is component state duration sampling method principle schematic of the present invention.
Fig. 5 is IEEE-RTS79 system main wiring diagrams.
Embodiment
As shown in figure 1, a kind of generating and transmitting system reliability evaluation system, including reliability index structure module, element can
By property model construction module, simulated sampling module, computing module and output module, the reliability index build module with it is described
Reliability model of unit builds module connection, and the reliability model of unit builds module and is connected with the simulated sampling module,
The simulated sampling module is connected with the computing module, and the computing module is connected with the output module.Wherein：
Reliability index, which builds module, to be used to build the reliability index for assessing power system.Reliability index can be retouched quantitatively
State the reliability level of system.According to the difference of object, reliability index mainly includes system index and the class of load point index two.
Load point index describes the reliability level of single load point, such as power off time, power failure frequency, embodies the office of failure
Portion influences, and can simultaneously serve as the calculating basis of high one-level system adequacy evaluation.System index is then of overall importance, is described
Influence of the failure to system global reliability, system index includes basic index and export index, and export index is to referring to substantially
Mark is further processed what is obtained, the comparison that can be used between different system.The reliability index of the present embodiment is negative including cutting
Lotus probability P LC, cutting load frequency EFLC, cutting load duration EDLC, average cutting load duration ADLC, cutting load are expected
Value ELC, expected loss of energy EENS, system blackout index BPII, system cut down electricity index BPECI and severity index
SI.Reliability index formula using the Monte Carlo method of component state duration sampling method by being exported.Wherein：
（1）Cutting load probability（Probability of Load Curtailment, PLC）
Cutting load probability refers to that the system failure causes in the time scale shared by cutting load state in timing statisticses section.
（1）
Wherein S is the set of cutting load state, tiIt is cutting load state duration, T is total timing statisticses.
（2）Cutting load frequency（Expected of Frequency of Load Curtailment, EFLC）
Cutting load frequency refers to the number of times of cutting load event caused by the system failure in the unit interval.Unit for times/year.
（2）
Wherein NiIt is cutting load number of times, T is total timing statisticses.
（3）The cutting load duration（Expected of Duration of Load Curtailment, EDLC）
The cutting load duration is the hourage that cutting load probability multiplies 1 year, represents the total time of system cutting load in 1 year.It is single
Position is hour/year.
（3）
（4）The average cutting load duration（Average Duration of Load Curtailment, ADLC）
The average cutting load duration refers to the average value of cutting load state duration in each cutting load event.Unit is small
When/time.
（4）
（5）Cutting load desired value（Expectation of Load Curtailment, ELC）
Cutting load desired value refers to the average value of the excision electricity of each cutting load event in system, and unit is megawatt/year.
（5）
Wherein S is the set of cutting load state, CiIt is cutting load amount, T is total timing statisticses.
（6）Expected loss of energy（Expectation of Energy Not Supply, EENS）
Expected loss of energy refers to the deficiency of total delivery in 1 year in system.Unit is megawatt hour/year.Because the index is
Energy indexes, are widely used in the fields such as overall merit, the systems organization of reliability and economy, therefore be reliability assessment
In one of core index.
（6）
Wherein S is the set of cutting load state, CiIt is cutting load amount, tiIt is cutting load state duration, T is presidential timing
Between.
（7）System blackout index（Bulk Power Interruption Index, BPII）
The cutting load average value and the relation of annual peak load of system blackout index reflection single accident, can be used for not homology
Comparison between system.
（7）
（8）System cuts down electricity index（Bulk Power Energy Curtailment Index, BPECI）
System cuts down electricity index and reflects the annual short of electricity amount of system and the relation of annual peak load, can be used between different system
Comparison, unit be megawatt hour/megawatt.
（8）
（9）Severity index, also referred to as system point（Severity index, SI）
（9）
System point can be understood as whole year and run on total system under peak load mode and have a power failure one minute, describe the system failure
The order of severity.International conference on large HV electric systems in 1983 is commented SI indexs the degree that user impacts according to system disturbance
Level：0 grade, SI<1, acceptable unreliable state；1 grade, 1≤SI<10, the unreliable state being had a significant impact to user；
2 grades, 10≤SI<100, there is the unreliable state having a strong impact on to user；3 grades, 100≤SI<1000, have very to user
The unreliable state having a strong impact on.
Reliability model of unit, which builds module, to be used to build the reliability model of unit for assessing power system.Component reliability
Model is based primarily upon Markov Chain, provides two state Markov switching models of each element.Element is power system
Least unit, the basis that appropriate element probabilistic model is reliability assessment is set up according to element feature and attribute.Element is main
It is divided into repairable elements and the major class of unrepairable element two.The main element of power system such as transformer, generator, circuit, electricity
Hold reactor etc., the overwhelming majority is all repairable elements, and repairable elements can be divided into available and unavailable two states, meter again
It is that down state then occurs at random caused by schedule ahead, forced outage to draw down state caused by stopping transport.Cause
In the case that this does not consider planned outage, power system component is divided into normal operating condition and forced outage state, normal operation
State is exactly failure-free operation state, i.e. forced outage state fault restoration state.Which system at a time belongs to
The state of kind is then random, so two state models of element can be set up, as shown in Figure 2.
It is assumed that the fault rate and repair rate of element are respectively λ, μ, then two state space graphs of element are as shown in Figure 3.
The operation that simulated sampling module is used for power system carries out simulated sampling, obtains system mode sequence.The present invention
Simulated sampling use component state duration sampling method.
Component state duration sampling method is a kind of sequential Monte Carlo method.It is assumed that element run time and malfunction
Lower repair time will obey certain probability distribution, exponential distribution be used generally in Model in Reliability Evaluation of Power Systems, then according to member
The fault rate and repair rate of part determine state and state duration of the element in preset time section.When in preset time section
After the state and state duration of all elements are determined, it is possible to obtain state and the duration of system, in a given system
Under system state, the state of each element is constant.
The step of component state duration sampling method, is divided into：
（1）The dry run time series of element is obtained according to the reliability model of unit；
（2）According to the fault rate λ and repair rate μ of element, when meeting the no-failure operation of exponential distribution using transform method acquisition
Between τ1With fault correction time τ2：
Wherein, fault rate λ is mean time between failures MTTF inverse, and repair rate μ is mean repair time MTTR
Inverse, γ1And γ2It is the uniform random number on [0,1].
（3）According to the non-failure operation time of element and fault correction time, given simulation total period T is simulated
Interior running status duration time sequence；
（4）The running status duration time sequence of comprehensive all elements, merges identical systems state, obtains the status switch of system
And the duration, in each system mode, each element state is constant；
（5）The status switch of system is estimated one by one, cutting load amount is calculated.
The Sampling schematic diagram of component state duration sampling method is as shown in figure 4, first pass through to 3 elements（A,
B and C）Operation and malfunction continuous-time analog, then obtain in system mode and state duration, figure to cover half
11 system modes are simulated altogether in pseudotime section.When being estimated one by one to the status switch of system, if in state
Fault element is identical, and the cutting load amount calculated is identical, and contribution and the state to reliability index
Duration it is relevant, therefore the method that can be added by the system mode duration merges two states.Here
Same fault element should be included：
（1）Generator is either connected to the different hairs of rated capacity on same bus, fault rate, repair rate all same in itself
Motor；
（2）Either two ends connect bus identical line parameter circuit value, rated capacity, fault rate, repair rate all same to circuit in itself
Multi-loop line；
（3）Transformer is in itself or transformer parameter, no-load voltage ratio, rated capacity, fault rate, the parallel pressure change of repair rate all same
Device.
Wrapped in the system mode sequence that can be seen that sampling generation from the Sampling of component state duration sampling method
, can be by merging identical systems state, using storage system status and condition evaluation results containing many identical systems states
Method needs the system mode number of assessment to reduce.8 not homologys are only included in 11 system modes simulated in such as Fig. 4
System state, state 10 can directly read the condition evaluation results of state 6, it is not necessary to recalculate, state 11 and state
7 is identical with state 1, it is not necessary to recalculates.It is using effect of the method for identical systems state to reduction amount of calculation is merged
It will be apparent that therefore using memory technology, merge identical systems state and condition evaluation results, can greatly reduce needs and comment
The status number estimated, reduces amount of calculation, but cost is to need to take substantial amounts of internal memory, here it is the thought of " trading space for time ".
Only reducing needs the system mode number assessed to be inadequate, in order to further reduce amount of calculation, it is necessary to accelerate each
The speed that system mode is assessed.
Given system state is estimated, most time-consuming situation occurs from that multiple element is out of service to cause trend meter
Calculate the situation of convergence difficulties.Normal load flow is calculated and the speed of substance assessment of failure is comparatively faster, if it is possible to will be multiple
Assessment of failure is converted to substance assessment of failure, it is possible to significantly speed up the estimating velocity of each state.Can be with from Sampling
Find out, the difference of adjacent two state is the state change of single element in system mode sequence（Element fault or element are repaiied
It is multiple）, the two kinds of situations now occurred are：
（1）Latter state is that a certain element fault is superimposed on the basis of previous state, and latter state can be converted to previous
Substance assessment of failure is carried out on the basis of state.
（2）Latter state is that a certain element fault reparation is superimposed on the basis of previous state, then the failure of latter state
Tuple is reduced, and assesses difficulty reduction.Now, in fact it could happen that two kinds of situations：
（a）Latter state is probably the state above occurred in evaluation process, directly can be merged by equal state,
This condition evaluation results is obtained from existing storage result.
（b）Latter state is only re-started and is it could also be possible that emerging state, can not now accelerate estimating velocity
System state estimation, but still the sub- status switch of a certain continuous substance failure formation can be assumed to be to be estimated, generation
Valency is to assess a multiple failure to be converted into multiple substance assessment of failures, but total calculating time has still been reduced.It is former from sampling
Multiple failure can be assessed and be converted to substance assessment of failure by reason analysis, principle, can significantly speed up the assessment of each state
State 4 is triple failures in speed, such as Fig. 4（Element ABC failures）, can be in state 3（Element AB failures）Base
Plinth enterprising units C substances failure is estimated；State 5 is emerging double malfunction（Element AC failures）,
It can be assumed to enter units A substance failures on the basis of original state 1, then enter units C substances failure to carry out
Assess, can essentially quickly assume state 2（Element A failures）On the basis of enter units C substances failure to carry out
Assess.
Computing module is used to calculate reliability index, i.e., according to the dry run result of simulated sampling module, substitutes into above-mentioned
Formula（1）~（9）, it is possible to calculate the value of each reliability index.
Output module is used for output reliability index result of calculation.
Embodiment：
IEEE-RTS79 systems are the very important example of field of power, main wiring diagram as shown in figure 5, including 24
Bus, 71 elements, wherein containing 33 circuits, 32 generators, 5 transformers and 1 reactor, total installed capacity holds
Measure 3405MW, peak load 2850MW.
Using the system simulation IEEE-RTS79 system running states of the present invention, simulated time is 1,000,000 hours, simulation
It the results are shown in Table 1.
The IEEE-RTS79 system running state analog results of table 1
As shown in Table 1, under the simulated time of 1,000,000 hours, a total of 55783 states, failure tuple is from 0 weight（No
Failure）To 9 weights, wherein the probability of 1 weight failure and 2 weight failures is very high, 67.3% is amounted to, and multiple failure（Three
Weight and more than）Probability be 19.4%, also account for considerable proportion.Increase the general of multiple failure with parts number in theory
Rate will also continue to increase, therefore, when carrying out reliability assessment to RTS79 systems, except conventional N-1 and N-2 event
Barrier, multiple failure also answers emphasis to consider, it is ensured that the correctness of result.
Based on said system state simulation result, the maximum failure tuple considered in reliability assessment is set to 10 weights, commented
Estimate result as shown in table 2.
The IEEE-RTS79 Reliability evaluation results of table 2
Note：Analytic method is R.Billinton result of calculation.
From table 2 it can be seen that the result of calculation of reliability index is consistent with R.Billinton result, it is of the invention
Algorithm is correct.Comparatively, R.Billinton result of calculation is less than normal, because what R.Billinton was used
Analytic method has used Contingency screening technology, and generator failure highest considers 5 weights, and line fault highest considers 3 weights, neglects
The influence of high heavy failure is omited.Also from side illustration, the influence of high heavy failure can not at will be ignored for this, even small probability thing
Part, but because consequence is serious so may have larger contribution to reliability index, it is therefore desirable to reference to system mode analog result
Determine failure highest tuple, it is ensured that the credibility of reliability assessment result.
Claims (7)
1. a kind of generating and transmitting system reliability evaluation system, it is characterised in that build module, element including reliability index reliable
Property model construction module, simulated sampling module, computing module and output module, the reliability index, which builds module, to be used to build
Assess the reliability index of generating and transmitting system；The reliability model of unit, which builds module, to be used to build assessment generating and transmitting system
Reliability model of unit；The operation that the simulated sampling module is used for generating and transmitting system carries out simulated sampling, obtains system shape
State sequence；The computing module is used to calculate the reliability index that the reliability index builds module construction；The output mould
Block is used for the result of calculation for exporting the computing module；The reliability index builds module and the reliability model of unit structure
Block connection is modeled, the reliability model of unit builds module and is connected with the simulated sampling module, the simulated sampling module
It is connected with the computing module, the computing module is connected with the output module.
2. a kind of generating and transmitting system reliability evaluation system according to claim 1, it is characterised in that the reliability refers to
Mark include cutting load probability P LC, cutting load frequency EFLC, cutting load duration EDLC, be averaged cutting load duration ADLC,
Cutting load desired value ELC, expected loss of energy EENS, system blackout index BPII, system cut down electricity index BPECI and tight
Severe index S I.
3. a kind of generating and transmitting system reliability evaluation system according to claim 1, it is characterised in that the element is reliable
Property model be two state models, two state include failure-free operation state and fault restoration state.
4. a kind of generating and transmitting system reliability evaluation system according to claim 1, it is characterised in that the simulated sampling
Module is sampled using component state duration sampling method to generating and transmitting system.
5. a kind of generating and transmitting system reliability evaluation system according to claim 4, it is characterised in that the element state
Duration sampling merges identical system mode in sampling process.
6. a kind of generating and transmitting system reliability evaluation system according to claim 4, it is characterised in that the element state
Multiple failure is assessed and is converted into substance assessment of failure by duration sampling.
7. a kind of generating and transmitting system reliability evaluation system according to claim 1, it is characterised in that the reliability refers to
Target calculation formula using the Monte Carlo method of component state duration sampling method by being exported.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106992513A (en) * | 2017-02-16 | 2017-07-28 | 广西电网有限责任公司电力科学研究院 | A kind of Method for Reliability Evaluation of Composite Generation-Transmission System |
| CN108122070A (en) * | 2017-12-12 | 2018-06-05 | 国家电网公司 | The definite method and apparatus of distribution network reliability |
| CN109494754A (en) * | 2019-01-08 | 2019-03-19 | 国网湖南省电力有限公司 | Consider the urgent cutting load method of power grid of user time fairness |
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