CN105117839A - Power system weaknesses identification method based on cascading failure - Google Patents

Power system weaknesses identification method based on cascading failure Download PDF

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CN105117839A
CN105117839A CN201510514677.1A CN201510514677A CN105117839A CN 105117839 A CN105117839 A CN 105117839A CN 201510514677 A CN201510514677 A CN 201510514677A CN 105117839 A CN105117839 A CN 105117839A
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cascading failure
represent
electricity
transmission line
load
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CN105117839B (en
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田春筝
周玉龙
王圆圆
王建学
王磊
杨红旗
毛玉宾
王世谦
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State Grid Corp of China SGCC
Xian Jiaotong University
Economic and Technological Research Institute of State Grid Henan Electric Power Co Ltd
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State Grid Corp of China SGCC
Xian Jiaotong University
Economic and Technological Research Institute of State Grid Henan Electric Power Co Ltd
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Abstract

The invention provides a power system weaknesses identification method based on a cascading failure. A cascading failure model is introduced into the state analysis of risk assessment. The influence of the cascading failure developed by an originating failure on a power grid is taken into account. The dynamic and cascading development law of a blackout incident is met. With the help of a cascading failure process, a weakness affecting the blackout incident is analyzed and identified. A key element in the blackout incident can be really screened out. An acquired weakness result is comprehensive, accurate and useful. According to the invention, the mature theory of risk assessment based on a Monte Carlo simulation method is effectively inherited; complex relationship derivation is not needed; failure enumerating is not needed; and especially for a large system, the advantages of the method provided by the invention are apparent.

Description

A kind of power system weak link identification method based on cascading failure
Technical field
The present invention relates to a kind of discrimination method, be specifically related to a kind of power system weak link identification method based on cascading failure.
Background technology
A lot of large-scale blackout is there occurs in recent years in world wide, as 2003 North America " 8.14 " have a power failure on a large scale, 2011 the U.S. " 9.8 " have a power failure on a large scale, India in 2012 has a power failure on a large scale, cause great economic loss and social influence, cause the extensive concern of various countries to electric power netting safe running problem.Show researching and analysing of accident, large-scale blackout is caused by cascading failure mostly.Along with adding of the interconnected on a large scale of China's electrical network and Large Copacity power supply; electrical network start fault cause trend to shift on a large scale and cause cascading failure possibility increase; operation of power networks potential risk increases; bring certain challenge to the programming dispatching of electrical network and safe and reliable operation, the weak link making identification affect cascading failure generation seems very necessary.
Weak link identification method at present based on venture analysis is mainly divided into two classes, and a class is analytical method, and a class is simulation.All there are some defects in these two class methods, effectively can not carry out identification to the weak link affecting large-scale blackout.These defects are mainly reflected in:
(1) simulation and analytical method are only assessed the fault that starts, only to consider to start the impact of fault, and do not consider the chain expansion process of accident because the fault that starts causes, evaluation process is static, and the large-scale blackout of current extensive concern is dynamic, chain, the weak link affecting fault spread in electrical network only just can embody in cascading failure process, and classic method easily causes the imperfect and inaccurate of assessment result;
(2) analytical method, as Sensitivity Analysis Method and reliability tracing etc., mathematical analysis expression formula derivation all based on complexity draws the contribution of each element to system risk, computation process is more loaded down with trivial details, and there is instability problem in the method result under the Monte-carlo Simulation Method of current widespread use, so assessment scene can only be generated by enumerating fault, which increase the workload of bulk power grid weak link identification.
Summary of the invention
In order to overcome above-mentioned the deficiencies in the prior art, the invention provides a kind of power system weak link identification method based on cascading failure, consider start fault and cascading failure to the impact of electric power netting safe running, completed the identification of power system weak link by risk participation factors.
In order to realize foregoing invention object, the present invention takes following technical scheme:
The invention provides a kind of power system weak link identification method based on cascading failure, described discrimination method comprises the following steps:
Step 1: obtain basic technical data, run bound data and reliability data;
Step 2: generate N number of scene to be assessed;
Step 3: scene to be assessed is assessed;
Step 4: by the risk participation factors Identification of Power System weak link of each branch road.
In step 1, described basic technical data comprises node data, transmission line of electricity data, transformer data, load data and alternator data;
Described operation bound data comprises generator output upper lower limit value and Branch Power Flow upper lower limit value;
Described reliability data comprises generator forced outage rate, transmission line of electricity forced outage rate and transformer forced outage rate.
Described node data comprises node reference voltage;
Transmission line of electricity data comprise transmission line of electricity impedance and transmission line of electricity admittance;
Transformer data comprise transformer impedance, transformer admittance and transformer voltage ratio;
Load data comprises load active power and reactive load power;
Alternator data comprises that generator is current exerts oneself.
In step 2, adopt Monte Carlo simulation approach to generate N number of scene to be assessed, specifically comprise the following steps:
Step 2-1: for element j, to extract between (0,1) and to obey equally distributed random number U j;
Step 2-2: the running status S determining element j j, have:
S j = 1 1 ≥ U j ≥ FOR j 0 FOR j > U j ≥ 0
Wherein, FOR jrepresent the forced outage rate of element j; S jwhen=1, show that element j normally runs; S jwhen=0, show that element j exits because of fault;
Step 2-3: the running status S determining electric system, has:
S={S 1,S 2,…,S j,…,S n}
Wherein, n represents component population in electric system, j=1,2 ..., n;
Step 2-4: repeat step 2-1 to 2-3, the running status of N number of electric system can be obtained, as scene to be assessed.
Described element comprises generator, transmission line of electricity and transformer in electric system.
In described step 3, adopt cascading failure model to assess successively N number of scene to be assessed, specifically comprise the following steps:
Step 3-1: arranging cascading failure exponent number is 0;
Step 3-2: the meritorious of adjustment generator is exerted oneself and the active power of load, and records the cutting load amount of each load bus;
Step 3-3: DC power flow calculating is carried out to current scene, the effective power flow result of each transmission line of electricity in record electricity system;
Step 3-4: if there is transmission line of electricity effective power flow overload, then add up each transmission line of electricity Overflow RateHT, the transmission line of electricity finding Overflow RateHT maximum is also excised, and cascading failure exponent number adds 1 simultaneously, after upgrading Load flow calculation data, performs step 3-5; If there is no transmission line of electricity effective power flow overload, then perform step 3-6;
Step 3-5: judge whether cascading failure exponent number reaches the maximal value of setting, if then perform step 3-6, otherwise is back to step 3-2;
Step 3-6: the cutting load amount of each load bus under the fault of cumulative cascading failure every rank, can obtain total cutting load amount of load bus to the cutting load amount summation of each load bus.
In described step 3-2, if P grepresent meritorious the exerting oneself of generator g, P drepresent the active power of load d, specifically have:
Step 3-2-1: after cascading failure occurs, if Σ is P g> Σ P d, then reduce the meritorious of all generators in electric system and exert oneself, until Σ P g≤ Σ P dor certain generator reaches minimum technology and exerts oneself; If Σ is P g< Σ P d, then increase the meritorious of all generators in electric system and exert oneself, until Σ P g>=Σ P dor certain generated power is exerted oneself and is reached ratings;
Step 3-2-2: if still there is Σ P g> Σ P d, then machine operation is cut, until meet Σ P according to current ascending the carrying out of exerting oneself of generator g=Σ P d;
Step 3-2-3: if still there is Σ P g< Σ P d, then cutting load operation is carried out according to load active power is ascending, until meet Σ P g=Σ P d.
Described step 4 specifically comprises the following steps:
Step 4-1: the probability of happening calculating each cascading failure, has:
P ( C i ) = p ( C i 1 ) &Pi; k = 1 M s i k
Wherein, P (C i) represent the probability of happening of i-th cascading failure; P (C i1) represent the 1st rank fault in i-th cascading failure, namely start probability of malfunction; M represents total exponent number of each cascading failure; s ikrepresent the fault correction factor of kth rank fault in i-th cascading failure, it is expressed as:
s i k = F k &Sigma; m &Element; O k F m
Wherein, F krepresent the transmission line of electricity Overflow RateHT that kth rank cascading failure is cut, F mrepresent kth rank fault overload branch road Overflow RateHT in i-th cascading failure, o krepresent the overload branch road collection of kth rank fault in i-th cascading failure;
Step 4-2: the risk participation value calculating each branch road, has:
R b = &Sigma; b &Element; o i P ( C i ) &times; L i
Wherein, o irepresent i-th cut branch road collection of cascading failure, R brepresent the risk participation value of branch road b, L irepresent the cutting load amount of i-th cascading failure;
Step 4-3: the risk indicator calculating electric system, has:
R = &Sigma; i P ( C i ) &times; L i
Wherein, R represents the risk indicator of electric system;
Step 4-4: the risk participation factors calculating each branch road, has:
I b=R b/R
Wherein, I brepresent the risk participation factors of branch road b;
Step 4-5: sort to the risk participation factors of each branch road, risk participation factors is larger, shows that this branch road is larger to widening one's influence of cascading failure, belongs to the weak link of electric system.
Compared with prior art, beneficial effect of the present invention is:
Cascading failure model is incorporated in the state analysis of risk assessment by the present invention, consider the fault progression that starts and become impact on electrical network after cascading failure, suit the rule of development that large-scale blackout is dynamic, chain, the weak link of large-scale blackout can be affected by means of cascading failure process analysis procedure analysis identification, really filter out the element played a crucial role in large-scale blackout, the weak link result drawn more comprehensively accurately, have more reference value;
Compared with the analytical methods such as Sensitivity Analysis Method, reliability back tracking method, the maturation that the present invention effectively inherits based on Monte Carlo Analogue Method risk assessment is theoretical, without the need to carrying out the derivation of complex relationship formula, also need not carry out enumerating of fault, especially, when system is larger, advantage of the present invention will be more obvious.
Accompanying drawing explanation
Fig. 1 is the power system weak link identification method process flow diagram based on cascading failure in the embodiment of the present invention;
Fig. 2 assesses scene process flow diagram to be assessed in the embodiment of the present invention.
Embodiment
Below in conjunction with accompanying drawing, the present invention is described in further detail.
The invention provides a kind of power system weak link identification method based on cascading failure, as Fig. 1, described discrimination method comprises the following steps:
Step 1: obtain basic technical data, run bound data and reliability data;
Step 2: generate N number of scene to be assessed;
Step 3: scene to be assessed is assessed;
Step 4: by the risk participation factors Identification of Power System weak link of each branch road.
In step 1, described basic technical data comprises node data, transmission line of electricity data, transformer data, load data and alternator data;
Described operation bound data comprises generator output upper lower limit value and Branch Power Flow upper lower limit value;
Described reliability data comprises generator forced outage rate, transmission line of electricity forced outage rate and transformer forced outage rate.
Described node data comprises node reference voltage;
Transmission line of electricity data comprise transmission line of electricity impedance and transmission line of electricity admittance;
Transformer data comprise transformer impedance, transformer admittance and transformer voltage ratio;
Load data comprises load active power and reactive load power;
Alternator data comprises that generator is current exerts oneself.
In step 2, adopt Monte Carlo simulation approach to generate N number of scene to be assessed, specifically comprise the following steps:
Step 2-1: for element j, to extract between (0,1) and to obey equally distributed random number U j;
Step 2-2: the running status S determining element j j, have:
S j = 1 1 &GreaterEqual; U j &GreaterEqual; FOR j 0 FOR j > U j &GreaterEqual; 0
Wherein, FOR jrepresent the forced outage rate of element j; S jwhen=1, show that element j normally runs; S jwhen=0, show that element j exits because of fault;
Step 2-3: the running status S determining electric system, has:
S={S 1,S 2,…,S j,…,S n}
Wherein, n represents component population in electric system, j=1,2 ..., n;
Step 2-4: repeat step 2-1 to 2-3, the running status of N number of electric system can be obtained, as scene to be assessed.
Described element comprises generator, transmission line of electricity and transformer in electric system.
As Fig. 2, in described step 3, adopt cascading failure model to assess successively N number of scene to be assessed, specifically comprise the following steps:
Step 3-1: arranging cascading failure exponent number is 0;
Step 3-2: the meritorious of adjustment generator is exerted oneself and the active power of load, and records the cutting load amount of each load bus;
Step 3-3: DC power flow calculating is carried out to current scene, the effective power flow result of each transmission line of electricity in record electricity system;
Step 3-4: if there is transmission line of electricity effective power flow overload, then add up each transmission line of electricity Overflow RateHT, the transmission line of electricity finding Overflow RateHT maximum is also excised, and cascading failure exponent number adds 1 simultaneously, after upgrading Load flow calculation data, performs step 3-5; If there is no transmission line of electricity effective power flow overload, then perform step 3-6;
Step 3-5: judge whether cascading failure exponent number reaches the maximal value of setting, if then perform step 3-6, otherwise is back to step 3-2;
Step 3-6: the cutting load amount of each load bus under the fault of cumulative cascading failure every rank, can obtain total cutting load amount of load bus to the cutting load amount summation of each load bus.
In described step 3-2, if P grepresent meritorious the exerting oneself of generator g, P drepresent the active power of load d, specifically have:
Step 3-2-1: after cascading failure occurs, if Σ is P g> Σ P d, then reduce the meritorious of all generators in electric system and exert oneself, until Σ P g≤ Σ P dor certain generator reaches minimum technology and exerts oneself; If Σ is P g< Σ P d, then increase the meritorious of all generators in electric system and exert oneself, until Σ P g>=Σ P dor certain generated power is exerted oneself and is reached ratings;
Step 3-2-2: if still there is Σ P g> Σ P d, then machine operation is cut, until meet Σ P according to current ascending the carrying out of exerting oneself of generator g=Σ P d;
Step 3-2-3: if still there is Σ P g< Σ P d, then cutting load operation is carried out according to load active power is ascending, until meet Σ P g=Σ P d.
Described step 4 specifically comprises the following steps:
Step 4-1: the probability of happening calculating each cascading failure, has:
P ( C i ) = p ( C i 1 ) &Pi; k = 1 M s i k
Wherein, P (C i) represent the probability of happening of i-th cascading failure; P (C i1) represent the 1st rank fault in i-th cascading failure, namely start probability of malfunction; M represents total exponent number of each cascading failure; s ikrepresent the fault correction factor of kth rank fault in i-th cascading failure, it is expressed as:
s i k = F k &Sigma; m &Element; O k F m
Wherein, F krepresent the transmission line of electricity Overflow RateHT that kth rank cascading failure is cut, F mrepresent kth rank fault overload branch road Overflow RateHT in i-th cascading failure, o krepresent the overload branch road collection of kth rank fault in i-th cascading failure;
Step 4-2: the risk participation value calculating each branch road, has:
R b = &Sigma; b &Element; o i P ( C i ) &times; L i
Wherein, o irepresent i-th cut branch road collection of cascading failure, R brepresent the risk participation value of branch road b, L irepresent the cutting load amount of i-th cascading failure;
Step 4-3: the risk indicator calculating electric system, has:
R = &Sigma; i P ( C i ) &times; L i
Wherein, R represents the risk indicator of electric system;
Step 4-4: the risk participation factors calculating each branch road, has:
I b=R b/R
Wherein, I brepresent the risk participation factors of branch road b;
Step 4-5: sort to the risk participation factors of each branch road, risk participation factors is larger, shows that this branch road is larger to widening one's influence of cascading failure, belongs to the weak link of electric system.
Finally should be noted that: above embodiment is only in order to illustrate that technical scheme of the present invention is not intended to limit; those of ordinary skill in the field still can modify to the specific embodiment of the present invention with reference to above-described embodiment or equivalent replacement; these do not depart from any amendment of spirit and scope of the invention or equivalent replacement, are all applying within the claims of the present invention awaited the reply.

Claims (8)

1. based on a power system weak link identification method for cascading failure, it is characterized in that: described discrimination method comprises the following steps:
Step 1: obtain basic technical data, run bound data and reliability data;
Step 2: generate N number of scene to be assessed;
Step 3: scene to be assessed is assessed;
Step 4: by the risk participation factors Identification of Power System weak link of each branch road.
2. the power system weak link identification method based on cascading failure according to claim 1, is characterized in that: in step 1, and described basic technical data comprises node data, transmission line of electricity data, transformer data, load data and alternator data;
Described operation bound data comprises generator output upper lower limit value and Branch Power Flow upper lower limit value;
Described reliability data comprises generator forced outage rate, transmission line of electricity forced outage rate and transformer forced outage rate.
3. the power system weak link identification method based on cascading failure according to claim 2, is characterized in that: described node data comprises node reference voltage;
Transmission line of electricity data comprise transmission line of electricity impedance and transmission line of electricity admittance;
Transformer data comprise transformer impedance, transformer admittance and transformer voltage ratio;
Load data comprises load active power and reactive load power;
Alternator data comprises that generator is current exerts oneself.
4. the power system weak link identification method based on cascading failure according to claim 1, is characterized in that: in step 2, adopts Monte Carlo simulation approach to generate N number of scene to be assessed, specifically comprises the following steps:
Step 2-1: for element j, to extract between (0,1) and to obey equally distributed random number U j;
Step 2-2: the running status S determining element j j, have:
S j = 1 1 &GreaterEqual; U j &GreaterEqual; FOR j 0 FOR j > U j &GreaterEqual; 0
Wherein, FOR jrepresent the forced outage rate of element j; S jwhen=1, show that element j normally runs; S jwhen=0, show that element j exits because of fault;
Step 2-3: the running status S determining electric system, has:
S={S 1,S 2,…,S j,…,S n}
Wherein, n represents component population in electric system, j=1,2 ..., n;
Step 2-4: repeat step 2-1 to 2-3, the running status of N number of electric system can be obtained, as scene to be assessed.
5. the power system weak link identification method based on cascading failure according to claim 4, is characterized in that: described element comprises generator, transmission line of electricity and transformer in electric system.
6. the power system weak link identification method based on cascading failure according to claim 4, is characterized in that: in described step 3, adopts cascading failure model to assess successively N number of scene to be assessed, specifically comprises the following steps:
Step 3-1: arranging cascading failure exponent number is 0;
Step 3-2: the meritorious of adjustment generator is exerted oneself and the active power of load, and records the cutting load amount of each load bus;
Step 3-3: DC power flow calculating is carried out to current scene, the effective power flow result of each transmission line of electricity in record electricity system;
Step 3-4: if there is transmission line of electricity effective power flow overload, then add up each transmission line of electricity Overflow RateHT, the transmission line of electricity finding Overflow RateHT maximum is also excised, and cascading failure exponent number adds 1 simultaneously, after upgrading Load flow calculation data, performs step 3-5; If there is no transmission line of electricity effective power flow overload, then perform step 3-6;
Step 3-5: judge whether cascading failure exponent number reaches the maximal value of setting, if then perform step 3-6, otherwise is back to step 3-2;
Step 3-6: the cutting load amount of each load bus under the fault of cumulative cascading failure every rank, can obtain total cutting load amount of load bus to the cutting load amount summation of each load bus.
7. the power system weak link identification method based on cascading failure according to claim 6, is characterized in that: in described step 3-2, if P grepresent meritorious the exerting oneself of generator g, P drepresent the active power of load d, specifically have:
Step 3-2-1: after cascading failure occurs, if Σ is P g> Σ P d, then reduce the meritorious of all generators in electric system and exert oneself, until Σ P g≤ Σ P dor certain generator reaches minimum technology and exerts oneself; If Σ is P g< Σ P d, then increase the meritorious of all generators in electric system and exert oneself, until Σ P g>=Σ P dor certain generated power is exerted oneself and is reached ratings;
Step 3-2-2: if still there is Σ P g> Σ P d, then machine operation is cut, until meet Σ P according to current ascending the carrying out of exerting oneself of generator g=Σ P d;
Step 3-2-3: if still there is Σ P g< Σ P d, then cutting load operation is carried out according to load active power is ascending, until meet Σ P g=Σ P d.
8. the power system weak link identification method based on cascading failure according to claim 1, is characterized in that: described step 4 specifically comprises the following steps:
Step 4-1: the probability of happening calculating each cascading failure, has:
P ( C i ) = p ( C i 1 ) &Pi; k = 1 M s i k
Wherein, P (C i) represent the probability of happening of i-th cascading failure; P (C i1) represent the 1st rank fault in i-th cascading failure, namely start probability of malfunction; M represents total exponent number of each cascading failure; s ikrepresent the fault correction factor of kth rank fault in i-th cascading failure, it is expressed as:
s i k = F k &Sigma; m &Element; O k F m
Wherein, F krepresent the transmission line of electricity Overflow RateHT that kth rank cascading failure is cut, F mrepresent kth rank fault overload branch road Overflow RateHT in i-th cascading failure, o krepresent the overload branch road collection of kth rank fault in i-th cascading failure;
Step 4-2: the risk participation value calculating each branch road, has:
R b = &Sigma; b &Element; o i P ( C i ) &times; L i
Wherein, o irepresent i-th cut branch road collection of cascading failure, R brepresent the risk participation value of branch road b, L irepresent the cutting load amount of i-th cascading failure;
Step 4-3: the risk indicator calculating electric system, has:
R = &Sigma; i P ( C i ) &times; L i
Wherein, R represents the risk indicator of electric system;
Step 4-4: the risk participation factors calculating each branch road, has:
I b=R b/R
Wherein, I brepresent the risk participation factors of branch road b;
Step 4-5: sort to the risk participation factors of each branch road, risk participation factors is larger, shows that this branch road is larger to widening one's influence of cascading failure, belongs to the weak link of electric system.
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Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105719062A (en) * 2016-01-15 2016-06-29 西安交通大学 Method for assessing risks and weak links of power grid, with double fault probability characteristics considered
CN105741016A (en) * 2016-01-22 2016-07-06 中国电力科学研究院 Static reliability probability index acquiring method for medium-term power grid planning
CN106845852A (en) * 2017-02-07 2017-06-13 国网河南省电力公司 Multi-infeed DC receiving end AC system Voltage Stability Evaluation fault set forming method
CN107069705A (en) * 2017-02-16 2017-08-18 广西电网有限责任公司电力科学研究院 A kind of electric network element cascading failure analogy method
CN107516911A (en) * 2017-10-11 2017-12-26 中国南方电网有限责任公司 The discrimination method in AC-DC hybrid power grid cascading failure fragility source
CN107909276A (en) * 2017-11-20 2018-04-13 广东电网有限责任公司电力调度控制中心 A kind of vulnerability assessment method of power information physics emerging system
CN108767848A (en) * 2018-05-31 2018-11-06 西南交通大学 A kind of electric system vulnerable line identifying and cascading failure prevention method
CN110969355A (en) * 2019-12-03 2020-04-07 重庆大学 Screening method and device of incremental risk event and computer readable medium
CN111049129A (en) * 2019-12-11 2020-04-21 国网浙江常山县供电有限公司 Two-stage evaluation method for weak operation link of power distribution network
CN113162034A (en) * 2021-04-20 2021-07-23 西南交通大学 Method for calculating power supply capacity of weak power grid of electrified railway

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102063651A (en) * 2010-11-10 2011-05-18 中国电力科学研究院 Urban power grid risk evaluation system based on on-line data acquisition
CN102737286A (en) * 2012-04-23 2012-10-17 中国电力科学研究院 Online risk analysis system and method for regional power grid
CN103246806A (en) * 2013-04-25 2013-08-14 浙江大学 Operation risk evaluation method comprising wind- power plant electric system

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102063651A (en) * 2010-11-10 2011-05-18 中国电力科学研究院 Urban power grid risk evaluation system based on on-line data acquisition
CN102737286A (en) * 2012-04-23 2012-10-17 中国电力科学研究院 Online risk analysis system and method for regional power grid
CN103246806A (en) * 2013-04-25 2013-08-14 浙江大学 Operation risk evaluation method comprising wind- power plant electric system

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
段玉波等: "基于蒙特卡罗模拟法在变电站风险评估中的研究", 《科学技术与工程》 *

Cited By (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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CN105719062B (en) * 2016-01-15 2019-08-16 西安交通大学 A kind of power grid risk considering double probability of malfunction characteristic and weak link appraisal procedure
CN105741016A (en) * 2016-01-22 2016-07-06 中国电力科学研究院 Static reliability probability index acquiring method for medium-term power grid planning
CN106845852B (en) * 2017-02-07 2021-01-29 国网河南省电力公司 Voltage stability evaluation fault set forming method for multi-direct current feed-in receiving end alternating current system
CN106845852A (en) * 2017-02-07 2017-06-13 国网河南省电力公司 Multi-infeed DC receiving end AC system Voltage Stability Evaluation fault set forming method
CN107069705A (en) * 2017-02-16 2017-08-18 广西电网有限责任公司电力科学研究院 A kind of electric network element cascading failure analogy method
CN107516911A (en) * 2017-10-11 2017-12-26 中国南方电网有限责任公司 The discrimination method in AC-DC hybrid power grid cascading failure fragility source
CN107909276A (en) * 2017-11-20 2018-04-13 广东电网有限责任公司电力调度控制中心 A kind of vulnerability assessment method of power information physics emerging system
CN108767848A (en) * 2018-05-31 2018-11-06 西南交通大学 A kind of electric system vulnerable line identifying and cascading failure prevention method
CN110969355A (en) * 2019-12-03 2020-04-07 重庆大学 Screening method and device of incremental risk event and computer readable medium
CN110969355B (en) * 2019-12-03 2023-06-09 重庆大学 Method, device and computer readable medium for screening increment risk event
CN111049129A (en) * 2019-12-11 2020-04-21 国网浙江常山县供电有限公司 Two-stage evaluation method for weak operation link of power distribution network
CN113162034A (en) * 2021-04-20 2021-07-23 西南交通大学 Method for calculating power supply capacity of weak power grid of electrified railway
CN113162034B (en) * 2021-04-20 2023-05-05 西南交通大学 Method for calculating power supply capacity of weak power grid containing electrified railway

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