CN105023195B - Containing distributed photovoltaic evaluation method for distribution network reliability - Google Patents

Containing distributed photovoltaic evaluation method for distribution network reliability Download PDF

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CN105023195B
CN105023195B CN201510289086.9A CN201510289086A CN105023195B CN 105023195 B CN105023195 B CN 105023195B CN 201510289086 A CN201510289086 A CN 201510289086A CN 105023195 B CN105023195 B CN 105023195B
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power failure
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CN105023195A (en
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鞠非
袁晓冬
华明明
汪鹏程
吴国奇
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State Grid Corp of China SGCC
State Grid Jiangsu Electric Power Co Ltd
Changzhou Power Supply Co of Jiangsu Electric Power Co
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State Grid Corp of China SGCC
State Grid Jiangsu Electric Power Co Ltd
Changzhou Power Supply Co of Jiangsu Electric Power Co
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Priority to CN201510289086.9A priority patent/CN105023195B/en
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Abstract

The present invention relates to a kind of evaluation method for distribution network reliability Han distributed photovoltaic, the method AHP analytic process sets up the distribution network reliability model Han distributed photovoltaic；Utilize n the area reliability data that oneself collects, engineering statistics algorithm is used to calculate containing three layers of index in distributed photovoltaic distribution network reliability model, and engineering statistics algorithm result of calculation is added, and area total load value and total number of users are as BP train samples input value, and by fuzzy membership method, reliability index is marked as sample output valve, it is trained, it is thus achieved that the case library of three layers of index scoring；Utilize Satty rule, use relative weighting method, determine the weighted value between each layer index in reliability model；Three layers of index engineering calculation value according to realistic objective system carry out the reliable overall performane of goal systems and calculate.The method can be complete and comprehensive calculating pre-arranged power failure reliability and economic reliability index.

Description

Containing distributed photovoltaic evaluation method for distribution network reliability
Technical field
The present invention relates to the reliability assessment technical field of power distribution network, can containing distributed photovoltaic power distribution network particularly to one By property evaluation methodology.
Background technology
Widely available along with developing rapidly of modern social economy, high-tech product and advanced IT application equipment, user The output value often spending electricity rises day by day, and it is increasing to user and the social economic loss caused that unit stops delivery.Therefore, user Requirement to power system power supply reliability is more and more higher.Distribution Power System Reliability be one of Power System Reliability important Ingredient, comments the distribution network reliability containing distributed photovoltaic that there is no complete set in the research of distribution Power System Reliability at present Valency model, existing theory analysis algorithm can't calculate pre-arranged power failure reliability index well, and theory analysis algorithm is fitted For the Pre-Evaluation of electric network reliability index, and often can only calculate electric network fault power failure reliability index, it is impossible to calculate this Pre-power failure reliability index in the built reliability model of mesh.
Summary of the invention
The technical problem to be solved in the present invention is to provide a kind of complete and comprehensive and can calculate pre-arranged power failure reliability With economic reliability index containing distributed photovoltaic evaluation method for distribution network reliability.
One of technical scheme realizing the object of the invention is to provide a kind of evaluation method for distribution network reliability, analyzes with AHP Method sets up the distribution network reliability model Han distributed photovoltaic；Utilize n the area reliability data collected, use engineering statistics Algorithm calculates containing three layers of index in distributed photovoltaic distribution network reliability model, and engineering statistics algorithm result of calculation is added Area total load value and total number of users are as BP train samples input value, and by fuzzy membership method to reliability Index carries out marking as sample output valve, is trained, it is thus achieved that the case library of three layers of index scoring；Utilize Satty rule, adopt Use relative weighting method, determine the weighted value between each layer index in reliability model；Three layers of index according to realistic objective system Engineering calculation value carries out the reliable overall performane of goal systems and calculates.
Realize the object of the invention technical scheme two be to provide a kind of evaluation side Han distributed photovoltaic distribution network reliability Method, including following several steps:
1. the distribution network reliability evaluation model containing distributed photovoltaic is set up: use AHP method with containing distributed photovoltaic The reliability of power distribution network is overall performane, selects conventional reliability, economic reliability, equipment performance to stop as first class index, fault Electricity conventional reliability, pre-arranged power failure conventional reliability, the economic reliability of fault outage, pre-arranged power failure economic reliability, change Depressor performance, link performance are as two-level index, user's mean failure rate frequency of power cut, user's mean failure rate power off time, user Have a power failure average duration, fault power supply reliability, fault electricity deficiency index, fault outage average user number, user is average Pre-arranged frequency of power cut, user's average pre-arranged power off time, pre-arranged power failure average duration, pre-arranged are powered reliably Have a power failure economic number of times, user of rate, pre-arranged electricity deficiency index, pre-arranged power failure average user number, user's mean failure rate is average Power economic reliability, fault outage of fault outage economic time, fault outage average economic persistent period, fault averagely lacks and supplies Electricity, the user's average pre-arranged economic number of times of power failure, user's average pre-arranged power failure economic time, pre-arranged have a power failure average economical Persistent period, pre-arranged power economic reliability, pre-arranged have a power failure average lack delivery, line outage rate, transformator therefore Barrier outage rate, line outage average duration, transformer fault power failure average duration are three grades of indexs；Fingers at different levels It it is membership relation between mark；
2. the calculation expression of three grades of indexs in reliability evaluation model is determined: three grades of index calculating methods use engineering system Calculating method；
3. three grades of index standards of grading are set up: use fuzzy membership method to set up three grades of index standards of grading；
4. three grades of index scoring case libraries are set up: choose the reliability statistics parameter in n area, n ＞ 20, pass through construction calculation Method obtains the engineering calculation value of three grades of indexs, obtains score value by standards of grading；
5. three grades of indexs of goal systems calculate: statistics goal systems uses engineering statistics algorithm to calculate what three grades of indexs needed Data, are calculated three grades of desired values of goal systems by the expression formula in the table 1 that 2. step obtains；
6. three grades of indexs of goal systems are marked: according to three grades of index value of calculation of goal systems, area total load value, The total number of users in area, equipment sum, according to three grades of index scoring case libraries, three grades of index score values of output goal systems；
7. the weight between index in reliability evaluation model is determined: utilize 1～9 scaling laws of Satty to set up each layer and sentence Disconnected matrix, uses relative weighting method to determine the weight of each index of same layer；
8. goal systems reliability is evaluated: use AHP method, the most upwards calculate according to formula (1), obtain mesh Mark system reliability overall performane comprehensive grading value:
S ′ R = Σ i = 1 b S ′ i × W i - - - ( 1 ) ,
In formula: S ' R represents the scoring of arbitrary non-bottom index；S′iRepresent the scoring of lower floor's index i；WiRepresent lower floor's index The weight of i；B represents index S ' lower floor's index number of R；The most up calculate from basic unit's index scoring and Weight summation, Top S ' R value is overall performane comprehensive grading value；According to reliability overall performane score value, goal systems reliability is commented Valency.
Further, step 2. in, specifically three grades of index calculating methods use engineering statistics algorithms: join for a certain Electricity system set known parameters as: total number of users N, unit are family, and general assembly varying capacity S, unit are MVA, total line length L, unit For km, total transformator number of units T, unit are platform；Engineering statistics algorithm is used to calculate containing distributed photovoltaic distribution network reliability three grades Index needs the data of statistics to include: during distribution-free formula photovoltaic, fault outage number of times MF(MS), unit be time that fault is stopped each time Electricity time HFi(HSi), unit be h, fault outage number of users N each timeFi(NSi), unit be family, each time fault outage load Capacity PFi(PSi), unit be MW h and dress varying capacity SFi(SSi), unit be MVA, circuit, transformer fault number of times be respectively MFL、MFT, ignore switch, circuit breaker failure situation, MFL+MFT=MF, circuit, transformator are stopped transport and total time are respectively HFL、HFT,During containing distributed photovoltaic, power failure load all, power failure loaded portion outer in isolated island scope are at isolated island model In enclosing and power failure load all fault outage number of times M in the range of isolated islandFa、MFbAnd MFc(MFa+MFb+MFc=MF；MFaCorresponding HFi、NFi、PFi、SFiIt is worth constant；MFcCorresponding HFi、NFi、PFi、SFiValue is 0；MFbCorresponding HFiIt is worth constant, NFi、PFi、SFiBecome N′Fi、P′Fi、S′Fi)；Three grades of index engineering statistics algorithm expression formulas of distribution network reliability containing distributed photovoltaic are as follows:
User mean failure rate frequency of power cut AFTC ': AFTC ′ = Σ i = 1 M F a N F i + Σ i = 1 M F b N F i ′ N ,
User mean failure rate power off time AIHC-F ': A I H C - F ′ = Σ i = 1 M F a H F i × N F i + Σ i = 1 M F b H F i × N F i ′ N ,
Fault outage average duration MID-F ': M I D - F ′ = Σ i = 1 M F a H F i × N F i + Σ i = 1 M F b H F i × N F i ′ Σ i = 1 M F a N F i + Σ i = 1 M F b N F i ′ ,
Fault power supply reliability RS-F ': R S - F ′ = 1 - A I H C - F ′ 8760 ,
Fault electricity deficiency index ENS-F ': E N S - F ′ = Σ i = 1 M F a P F i × H F i + Σ i = 1 M F b P F i ′ × H Fi ,
Fault outage average user number MIC-F ':
User average pre-arranged frequency of power cut ASTC:
User average pre-arranged power off time AIHC-S:
Pre-arranged power failure average duration MID-S:
Pre-arranged power supply reliability RS-S: R S - S = 1 - A I H C - S 8760 ,
Pre-arranged electricity deficiency index ENS-S:
Pre-arranged power failure average user number MIC-S:
User's mean failure rate economic number of times AFETC ' of power failure:
User mean failure rate power failure economic time AIEHC-F ':
The average economic persistent period MID-F ' of fault outage:
Fault is powered economic reliability ERS-F:
Fault outage averagely lacks delivery AENT-F ':
User's average pre-arranged economic number of times ASETC of power failure:
User average pre-arranged power failure economic time AIEHC-S:
The pre-arranged average economic persistent period MIED-S of power failure:
Pre-arranged is powered economic reliability ERS-S:
Pre-arranged has a power failure and averagely lacks delivery AENT-S:
Line outage rate RIFI-L: R I F I - L = M F L L × 100 ,
Transformer fault outage rate RTFI-T:
Line outage average duration MDLOI-L:
Transformer fault power failure average duration MDTOI-T:
Further, 3. step, uses fuzzy membership method to set up the process of three grades of index standards of grading specifically: First determine typical case's scoring point, then three grades of desired values in a certain scope are quantified as typical case's scoring point, gradually form each three Level index standards of grading.
Further, the most specifically, the training sample of BP neutral net is constituted step by with lower part: three grades of index works Journey value of calculation number of users total with area total load value and area constitutes the input value of BP neural network sample, uses fuzzy membership side The result that reliability index is marked by method, as the output valve of training sample, provides form: sample input value；Sample exports Value；
(1) BP neutral net number:
For conventional reliability, economic reliability and equipment dependability, it is respectively adopted different BP network；I.e. constitute three classes BP Neutral net；
(2) the BP neutral net number of plies:
BP neutral net employing 3-tier architecture: input layer+intermediate layer+output layer；
(3) each node layer number:
Three class BP neutral nets each node layer number such as table 2,
Table 2 three class BP neutral net each node layer number
BP neural network type Input layer is counted number Hidden layer node number Output layer node number
Conventional reliability 14 14 12
Economic reliability 12 12 10
Equipment performance 5 5 4
Conventional reliability BP network sample input value: the total number of users in corresponding three grades of indexs+area total load value+area； Sample output valve: the fuzzy membership method score value of three grades of corresponding indexs；
Economic reliability BP network sample input value: the total number of users in corresponding three grades of indexs+area total load value+area； Sample output valve: the fuzzy membership method score value of three grades of corresponding indexs；
Equipment performance BP network sample input value: three grades of corresponding indexs+equipment sum；Sample output valve: corresponding three The fuzzy membership method score value of level index；
(4) excitation function Sigmoid f (x)=1/ (1+e-x).
Further, step 4. in, three grades of index score values are in [0,100] is interval.
Further, step 7. specifically comprise the following steps that (1) index number less than 3 time, its weight is the most true by expert Fixed；Index number equals to or more than 3, will compare two-by-two with layer index, obtains using 1～9 scales of Saaty to represent each finger The judgment matrix of mark relative importance；
(2) coincident indicator CR of judgment matrix, the test and judge matrix degree of consistency are calculated
(3) as CR ＜ 0.10, it is judged that matrix consistency inspection is qualified, Maximum characteristic root and the correspondence of judgment matrix is calculated Characteristic vector, the characteristic vector after normalized is weight w of each index；If consistency check is defective, again adjust Whole determine Partial Elements in judgment matrix until its consistent sexual satisfaction requirement.
Further, step 7. in, (2) calculate judgment matrix coincident indicator CR, test and judge matrix concordance Degree specifically comprise the following steps that 1) calculate coincident indicator CI:
C I = λ m a x - a a - 1 ,
In formula: λmaxRepresent the Maximum characteristic root value of judgment matrix；A represents index number；
2) Aver-age Random Consistency Index RI is determined:
The Aver-age Random Consistency Index value be given by Saaty searches corresponding RI, such as table 3,
The Aver-age Random Consistency Index value that table 3 Saaty is given
a 1 2 3 4 5 6 7 8 9
RI 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45
3) consistency ration CR is calculated:
Further, step 8. in, the reliability quality such as table 4 that reliability overall performane score value is corresponding:
The reliability level that table 4 reliability overall performane score value is corresponding
Score value 100～90 90～80 80～70 70～60 ＜ 60
Reliability quality Excellent Good In Pass Difference
The present invention has positive effect: the evaluation method for distribution network reliability containing distributed photovoltaic of (1) present invention is to list The integrity problem of one carries out Comprehensive Evaluation, only introduces calculating individual failure reliability index compared to existing method, this Bright can comprehensive each reliability index of inductive statistics.Although major part basic unit index has the most in reliability index standard Clear and definite definition, but also do not have the people, according to these indexs, electric network reliability is carried out overall merit, the reliability set up herein Model may be used for the reliability evaluation containing distributed photovoltaic power distribution network.
(2) present invention containing distributed photovoltaic evaluation method for distribution network reliability, the index of each side carried out again detailed district Divide and tissue, thus the most excellent by present invention understands which three grades of indicator deviation, which three grades of index, in the future can be to deviation portion The index divided carries out emphasis improvement.Institute of the present invention established model is the most complete and comprehensive, distribution network reliability Comprehensive Appraisal Study with Engineer applied has feasibility and reference significance.
(3) the employing engineering statistics algorithm containing distributed photovoltaic evaluation method for distribution network reliability of the present invention calculates containing distribution Formula photovoltaic distribution network reliability three grades bid, the literature research in terms of reliability index calculating typically uses theory analysis algorithm, But theory analysis algorithm is applicable to the Pre-Evaluation of electric network reliability index, and often can only calculate electric network fault power failure reliability and refer to Mark, it is impossible to calculate the pre-power failure reliability index in the built reliability model of this project.Engineering statistics algorithm is by statistics electrical network Actual power failure data calculate reliability index value, have that calculating is simple, practicality is wide, result is accurate, can calculate pre-arranged The advantages such as power failure reliability and economic reliability index, it is adaptable to containing distributed photovoltaic distribution network reliability overall merit.
Accompanying drawing explanation
Fig. 1 is the flow chart containing distributed photovoltaic evaluation method for distribution network reliability of the present invention.
Fig. 2 is the distribution network reliability evaluation model figure containing distributed photovoltaic.
Detailed description of the invention
(embodiment 1)
Seeing Fig. 1, the general thought containing distributed photovoltaic evaluation method for distribution network reliability of the present embodiment is to analyze with AHP Method sets up the distribution network reliability model Han distributed photovoltaic.Utilize n the area reliability data collected, use engineering statistics Algorithm calculates containing the three layers of index (index calculating method of improvement) in distributed photovoltaic distribution network reliability model, and by engineering Statistic algorithm result of calculation as BP train samples input value, and uses mould plus area total load value and total number of users Stick with paste subordination method to mark reliability index as sample output valve, be trained, it is thus achieved that the case of three layers of index scoring Example storehouse.Utilize Satty rule, use relative weighting method, determine the weighted value between each layer index in reliability model.According to reality Three layers of index engineering calculation value of border goal systems carry out the reliable overall performane of goal systems and calculate.Specifically include following several step Rapid:
1. the distribution network reliability evaluation model containing distributed photovoltaic is set up: the distribution network reliability containing distributed photovoltaic is commented Valency model is as in figure 2 it is shown, evaluation model construction method is as follows: use reliable with the power distribution network containing distributed photovoltaic of AHP method Property be overall performane, select conventional reliability, economic reliability, equipment performance as first class index, fault outage conventional reliability, Pre-arranged power failure conventional reliability, the economic reliability of fault outage, pre-arranged power failure economic reliability, transformer performance, circuit Performance is as two-level index, when user's mean failure rate frequency of power cut, user's mean failure rate power off time, user have a power failure the most persistently Between, fault power supply reliability, fault electricity deficiency index, fault outage average user number, user's average pre-arranged frequency of power cut, User's average pre-arranged power off time, pre-arranged power failure average duration, pre-arranged power supply reliability, pre-arranged electricity deficiency Index, pre-arranged power failure average user number, user's mean failure rate have a power failure economic number of times, user's mean failure rate power failure economic time, The fault outage average economic persistent period, fault is powered, and economic reliability, fault outage averagely lack delivery, user pacifies the most in advance Row's economic number of times of power failure, user's average pre-arranged power failure economic time, pre-arranged power failure average economic persistent period, pre-arranged supply The economic reliability of electricity, pre-arranged have a power failure and averagely lack delivery, line outage rate, transformer fault outage rate, line fault Power failure average duration, transformer fault power failure average duration are three grades of indexs.It it is membership relation between indexs at different levels.
2. the calculation expression of three grades of indexs in reliability evaluation model is determined: three grades of index calculating methods use engineering system Calculating method.Engineering statistics algorithm example: known parameters is set as total number of users N (family), general assembly varying capacity for a certain distribution system S (MVA), total line length L (km), total transformator number of units T (platform).Engineering statistics algorithm is used to calculate the distribution Han distributed photovoltaic Three grades of indexs of net reliability need the data of statistics to include (in units of 1 year): during distribution-free formula photovoltaic, fault (pre-arranged) Frequency of power cut MF(MS) (secondary), each time fault (pre-arranged) power off time HFi(HSi) (h), fault (pre-arranged) has a power failure each time Number of users NFi(NSi) (family), each time fault (pre-arranged) power failure load capacity PFi(PSi) (MW h) and dress varying capacity SFi (SSi) (MVA), circuit, transformer fault number of times are respectively MFL、MFT(ignore switch, circuit breaker failure situation, MFL+MFT=MF), Circuit, transformator are stopped transport and total time are respectively HFL、During containing distributed photovoltaic, have a power failure negative Lotus all, power failure loaded portion outer in isolated island scope stop with power failure load all faults in the range of isolated island in the range of isolated island Electricity number of times MFa、MFbAnd MFc(MFa+MFb+MFc=MF。MFaCorresponding HFi、NFi、PFi、SFiIt is worth constant；MFcCorresponding HFi、NFi、PFi、 SFiValue is 0；MFbCorresponding HFiIt is worth constant, NFi、PFi、SFiBecome N 'Fi、P′Fi、S′Fi).Power distribution network containing distributed photovoltaic is reliable Three grades of index engineering statistics algorithm expression formulas of property are as shown in table 1:
Table 1 three grades of index engineering statistics algorithm expression formulas of distribution network reliability containing distributed photovoltaic
That is: user's mean failure rate frequency of power cut AFTC ': AFTC ′ = Σ i = 1 M F a N F i + Σ i = 1 M F b N F i ′ N ,
User mean failure rate power off time AIHC-F ': A I H C - F ′ = Σ i = 1 M F a H F i × N F i + Σ i = 1 M F b H F i × N F i ′ N ,
Fault outage average duration MID-F ': M I D - F ′ = Σ i = 1 M F a H F i × N F i + Σ i = 1 M F b H F i × N F i ′ Σ i = 1 M F a N F i + Σ i = 1 M F b N F i ′ ,
Fault power supply reliability RS-F ': R S - F ′ = 1 - A I H C - F ′ 8760 ,
Fault electricity deficiency index ENS-F ': E N S - F ′ = Σ i = 1 M F a P F i × H F i + Σ i = 1 M F b P F i ′ × H F i ,
Fault outage average user number MIC-F ':
User average pre-arranged frequency of power cut ASTC:
User average pre-arranged power off time AIHC-S:
Pre-arranged power failure average duration MID-S:
Pre-arranged power supply reliability RS-S: R S - S = 1 - A I H C - S 8760 ,
Pre-arranged electricity deficiency index ENS-S:
Pre-arranged power failure average user number MIC-S:
User's mean failure rate economic number of times AFETC ' of power failure:
User mean failure rate power failure economic time AIEHC-F ':
The average economic persistent period MID-F ' of fault outage:
Fault is powered economic reliability ERS-F:
Fault outage averagely lacks delivery AENT-F ':
User's average pre-arranged economic number of times ASETC of power failure:
User average pre-arranged power failure economic time AIEHC-S:
The pre-arranged average economic persistent period MIED-S of power failure:
Pre-arranged is powered economic reliability ERS-S:
Pre-arranged has a power failure and averagely lacks delivery AENT-S:
Line outage rate RIFI-L: R I F I - L = M F L L × 100 ,
Transformer fault outage rate RTFI-T:
Line outage average duration MDLOI-L:
Transformer fault power failure average duration MDTOI-T:
3. three grades of index standards of grading are set up: use fuzzy membership method to set up three grades of index standards of grading.The most true Then three grades of desired values in a certain scope are quantified as typical case's scoring point, gradually form each three grades of indexs by fixed typical case's scoring point Standards of grading.
4. three grades of index scoring case libraries are set up: choose the reliability statistics parameter in n (n ＞ 20) individual area, pass through engineering Algorithm obtains the engineering calculation value of three grades of indexs, obtains score value by standards of grading.Three grades of index score values are in [0,100] district In.
The training sample of BP neutral net is constituted by with lower part: three grades of index engineering calculation values and area total load value and The total number of users in area constitutes the input value of BP neural network sample, marks reliability index by fuzzy membership method Result, as the output valve of training sample, provides form: sample input value；Sample output valve.
(1) BP neutral net number:
For conventional reliability, economic reliability and equipment dependability, it is respectively adopted different BP network.I.e. constitute three classes BP Neutral net.
(2) the BP neutral net number of plies:
BP neutral net employing 3-tier architecture: input layer+intermediate layer+output layer.
(3) each node layer number:
Three class BP neutral nets each node layer number such as table 2.
Table 2 three class BP neutral net each node layer number
BP neural network type Input layer is counted number Hidden layer node number Output layer node number
Conventional reliability 14 14 12
Economic reliability 12 12 10
Equipment performance 5 5 4
Conventional reliability BP network sample input value: three grades of indexs+area total load value+area corresponding in Fig. 1 is always used Amount；Sample output valve: the fuzzy membership method score value of three grades of indexs corresponding in Fig. 1.
Economic reliability BP network sample input value: three grades of indexs+area total load value+area corresponding in Fig. 1 is always used Amount；Sample output valve: the fuzzy membership method score value of three grades of indexs corresponding in Fig. 1.
Equipment performance BP network sample input value: three grades of indexs corresponding in Fig. 1+equipment sum；Sample output valve: Fig. 1 The fuzzy membership method score value of three grades of indexs of middle correspondence.
(4) excitation function Sigmoid f (x)=1/ (1+e-x).
5. three grades of indexs of goal systems calculate: statistics goal systems uses engineering statistics algorithm to calculate what three grades of indexs needed Data, are calculated three grades of desired values of goal systems by the expression formula in the table 1 that 2. step obtains.
6. three grades of indexs of goal systems are marked: according to three grades of index value of calculation of goal systems, area total load value, The total number of users in area, equipment sum, according to three grades of index scoring case libraries, three grades of index score values of output goal systems.
7. the weight between index in reliability evaluation model is determined: utilize 1～9 scaling laws of Satty to set up each layer and sentence Disconnected matrix, uses relative weighting method to determine the weight of each index of same layer, specifically comprises the following steps that
(1), when index number is less than 3, its weight is directly determined by expert；Index number equals to or more than 3, will refer to layer Mark compares two-by-two, obtains the judgment matrix using 1～9 scales of Saaty to represent each index relative importance.
(2) calculating coincident indicator CR of judgment matrix, the test and judge matrix degree of consistency, step is as follows:
1) coincident indicator CI is calculated:
C I = λ m a x - a a - 1
In formula: λmaxRepresent the Maximum characteristic root value of judgment matrix；A represents index number.
2) Aver-age Random Consistency Index RI is determined:
The Aver-age Random Consistency Index value be given by Saaty searches corresponding RI, such as table 3,
The Aver-age Random Consistency Index value that table 3 Saaty is given
a 1 2 3 4 5 6 7 8 9
RI 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45
3) consistency ration CR is calculated:
(3) as CR ＜ 0.10, it is judged that matrix consistency inspection is qualified, Maximum characteristic root and the correspondence of judgment matrix is calculated Characteristic vector, the characteristic vector after normalized is weight w of each index；If consistency check is defective, again adjust Whole determine Partial Elements in judgment matrix until its consistent sexual satisfaction requirement.
8. goal systems reliability is evaluated: use AHP method, the most upwards calculate according to formula (1), obtain mesh Mark system reliability overall performane comprehensive grading value:
S ′ R = Σ i = 1 b S ′ i × W i - - - ( 1 ) ,
In formula: S ' R represents the scoring of arbitrary non-bottom index；S′iRepresent the scoring of lower floor's index i；WiRepresent lower floor's index The weight of i；B represents index S ' lower floor's index number of R；The most up calculate from basic unit's index scoring and Weight summation, Top S ' R value is overall performane comprehensive grading value.
According to reliability overall performane score value, goal systems reliability is evaluated.
The reliability quality such as table 4 that reliability overall performane score value is corresponding:
The reliability level that table 4 reliability overall performane score value is corresponding
Score value 100～90 90～80 80～70 70～60 ＜ 60
Reliability quality Excellent Good In Pass Difference
Obviously, above-described embodiment is only for clearly demonstrating example of the present invention, and not to the present invention The restriction of embodiment.For those of ordinary skill in the field, can also be made it on the basis of the above description The change of its multi-form or variation.Here without also cannot all of embodiment be given exhaustive.And these belong to this What bright spirit was extended out obviously changes or changes among still in protection scope of the present invention.

Claims (1)

1. an evaluation method for distribution network reliability Han distributed photovoltaic, it is characterised in that include following several step:
1. the distribution network reliability evaluation model containing distributed photovoltaic is set up: use AHP method with the distribution containing distributed photovoltaic The reliability of net is overall performane, selects conventional reliability, economic reliability, equipment performance as first class index, and fault outage is normal Rule reliability, pre-arranged power failure conventional reliability, the economic reliability of fault outage, pre-arranged power failure economic reliability, transformator Performance, link performance have a power failure as two-level index, user's mean failure rate frequency of power cut, user's mean failure rate power off time, user Average duration, fault power supply reliability, fault electricity deficiency index, fault outage average user number, user pacify the most in advance Row's frequency of power cut, user's average pre-arranged power off time, pre-arranged have a power failure average duration, pre-arranged power supply reliability, pre- Electricity deficiency index, pre-arranged power failure average user number, the user's mean failure rate economic number of times of power failure, user's mean failure rate is arranged to stop Electricity economic time, fault outage average economic persistent period, fault power economic reliability, fault outage averagely lack delivery, User's average pre-arranged economic number of times of power failure, user's average pre-arranged power failure economic time, pre-arranged have a power failure average economical lasting Time, pre-arranged power economic reliability, pre-arranged have a power failure average lack delivery, line outage rate, transformer fault stop Electricity rate, line outage average duration, transformer fault power failure average duration are three grades of indexs；Indexs at different levels it Between be membership relation；
2. the calculation expression of three grades of indexs in reliability evaluation model is determined: three grades of index calculating methods use engineering statistics to calculate Method；
3. three grades of index standards of grading are set up: use fuzzy membership method to set up three grades of index standards of grading；
4. three grades of index scoring case libraries are set up: choose the reliability statistics parameter in n area, n > 20, obtained by Engineering Algorithm Obtain the engineering calculation value of three grades of indexs, obtain score value by standards of grading；
5. three grades of indexs of goal systems calculate: statistics goal systems uses engineering statistics algorithm to calculate the number that three grades of indexs need According to, three grades of desired values of goal systems are calculated by the expression formula in the table 1 that 2. step obtains；
6. three grades of indexs of goal systems are marked: according to three grades of index value of calculation of goal systems, area total load value, area Total number of users, equipment sum, according to three grades of index scoring case libraries, three grades of index score values of output goal systems；
7. the weight between index in reliability evaluation model is determined: utilize 1 ~ 9 scaling law of Satty to set up each layer and judge square Battle array, uses relative weighting method to determine the weight of each index of same layer；
8. goal systems reliability is evaluated: use AHP method, the most upwards calculate according to formula (1), obtain target system System reliability overall performane comprehensive grading value:
(1),
In formula: S ' R represents the scoring of arbitrary non-bottom index；Represent the scoring of lower floor's index i；Represent lower floor's index i Weight；B represents index S ' lower floor's index number of R；The most up calculate from basic unit's index scoring and Weight summation, the highest Layer S ' R value is overall performane comprehensive grading value；According to reliability overall performane score value, goal systems reliability is evaluated.
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CN106713233B (en) * 2015-11-13 2020-04-14 国网智能电网研究院 Network security state judging and protecting method
CN106845711A (en) * 2017-01-22 2017-06-13 南方电网科学研究院有限责任公司 The processing method and processing unit of power supply reliability data
CN106972481B (en) * 2017-02-28 2019-07-05 国网江苏省电力公司常州供电公司 The safety quantitative estimation method of scale electrically-charging equipment access active power distribution network
CN108288122B (en) * 2018-01-12 2021-10-12 南方电网科学研究院有限责任公司 Assessment method and device of multi-region interconnection system
CN110348652A (en) * 2018-04-03 2019-10-18 普华讯光（北京）科技有限公司 The quantitative estimation method of switchgear house operation health degree
CN109636232A (en) * 2018-12-26 2019-04-16 天津大学 A kind of distribution key element recognition methods based on user's sensing reliability
CN111339215A (en) * 2019-05-31 2020-06-26 北京东方融信达软件技术有限公司 Structured data set quality evaluation model generation method, evaluation method and device
CN110264068A (en) * 2019-06-18 2019-09-20 国网北京市电力公司 The treating method and apparatus of electric power data
CN110503305B (en) * 2019-07-25 2022-02-01 西安理工大学 Transformer performance evaluation method
CN110490471B (en) * 2019-08-23 2023-07-11 广西电网有限责任公司电力科学研究院 Transformation method for power distribution network power supply reliability differentiation
CN110570118A (en) * 2019-09-06 2019-12-13 云南电网有限责任公司电力科学研究院 Power distribution network fault management scheme evaluation method and evaluation device
CN111582626A (en) * 2020-03-17 2020-08-25 上海博英信息科技有限公司 Power grid planning adaptability method based on big data
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CN113112136A (en) * 2021-03-31 2021-07-13 国网经济技术研究院有限公司 Comprehensive evaluation method and system for reliability of power distribution network
CN113361941B (en) * 2021-06-18 2023-11-21 国网江苏省电力有限公司信息通信分公司 Reliability evaluation method and system for power communication network
CN114091947A (en) * 2021-11-29 2022-02-25 深圳供电局有限公司 User regional characteristic evaluation method and system

Family Cites Families (8)

* Cited by examiner, † Cited by third party
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CN102222908B (en) * 2011-06-09 2014-02-05 重庆大学 Distribution network reliability estimation method considering prearranged stoppage
CN102542347A (en) * 2011-12-28 2012-07-04 东南大学 Method for comprehensively evaluating electric energy quality
CN102611101B (en) * 2012-03-08 2014-01-15 国家电网公司 Method for evaluating operational safety of interconnected power grid
CN103473715A (en) * 2013-09-09 2013-12-25 国家电网公司 Method for evaluating reliability of power distribution network provided with distributed photovoltaic system
CN104008302B (en) * 2014-06-09 2017-01-18 上海电力学院 Power distribution network reliability evaluation method based on combinational weighting and fuzzy scoring
CN104318374A (en) * 2014-10-21 2015-01-28 国网重庆市电力公司电力科学研究院 Method for assessing reliability of medium voltage distribution network for calculating upstream power restoration operation time
CN104376504B (en) * 2014-11-06 2017-10-27 国家电网公司 A kind of distribution system probabilistic reliability appraisal procedure based on analytic method
CN104636988A (en) * 2015-02-11 2015-05-20 国家电网公司 Active power distribution network assessment method

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