CN105069701A - Monte Carlo method based risk evaluation method for power transmission system - Google Patents
Monte Carlo method based risk evaluation method for power transmission system Download PDFInfo
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Abstract
The present invention provides a Monte Carlo method based risk evaluation method for a power transmission system. The risk evaluation method comprises the following steps of: reading data of each element in the power transmission system; calculating a normal tide of each element in the power transmission system; randomly extracting a fault event of each element in the power transmission system by adopting the Monte Carlo method to obtain a state of the power transmission system; forming a risk indicator according to the state of the power transmission system; judging whether the risk indicator reaches a convergence condition or not, and if so, performing the next step, or if not, returning the third step; and forming a reliability indicator of each element and a total risk indicator of the power transmission system. According to the Monte Carlo method based risk evaluation method for the power transmission system, a sampling method is used for selecting the state and the risk indicator is obtained by using a statistical method.
Description
Technical field
The present invention relates to a kind of transmission system methods of risk assessment based on Monte Carlo method.
Background technology
In transmission system operational process, it is the main cause destroying system safety operation that equipment is stopped transport, and the failure rate of power equipment often determines the probable value of malfunction.The failure rate of element is the important indicator characterizing this equipment operational reliability, is also one of required most basic parameter when carrying out risk assessment to transmission system.In the evaluation studies of risk, generally all adopt the method for traditional reliability statistics to determine the probability of malfunction of equipment.The determination of probability of equipment failure, needs to arrange power equipment operational reliability data for many years and statistics obtains.But, the failure rate of equipment is often difficult to determine because of the disappearance of statistical data, such as, in the reliability index statistics of the Chinese AC system transmission facility provided by China national power monitoring council's management of electric power dependability center, data and the cable data of 110kV electric pressure just lack to some extent., finding from the operational reliability data of actual electric network meanwhile, when carrying out operation risk assessment, for the indoor equipment such as bus, transformer of transformer station inside, adopting traditional equipment dependability data substantially to conform to on-the-spot ruuning situation; But for the failure rate of the outdoor elements such as overhead transmission line, but there is different with traditional reliability data, need the impact considering additional Ei environmental factor and some other factor.
After the failure rate determining each element in system, the malfunction of a selection system is needed to calculate.The main method of selecting system malfunction is Monte Carlo method and Monte Carlo method.Two kinds of approach application are when risk assessment, and the key distinction may be summarized to be: the method for Monte Carlo method sampling carries out condition selecting, obtains risk indicator by the method for statistics; And Monte Carlo rule utilizes the state enumerating choice of technology system, by the method calculation risk index of resolving.
Summary of the invention
The object of the present invention is to provide a kind of transmission system methods of risk assessment based on Monte Carlo method, fast and easy can realize transmission system risk assessment, carry out condition selecting by the method for sampling, obtain risk indicator by the method for statistics.
The technical scheme realizing above-mentioned purpose is: based on the transmission system methods of risk assessment of Monte Carlo method, comprise the following steps:
S1, reads in the data of each element in transmission system;
S2, calculates the Normal load flow of each element in transmission system;
S3, adopts Monte Carlo method to randomly draw the event of failure of each element in transmission system, obtains transmission system state;
S4, according to described transmission system state, forms risk indicator;
S5, judges whether risk indicator reaches the condition of convergence, if reach, then carries out step S6; If do not reach, then return step S3;
S6, forms the reliability index of each element and the overall risk index of transmission system.
The above-mentioned transmission system methods of risk assessment based on Monte Carlo method, in described step S3,
In transmission system, each element is simulated with being uniformly distributed [0,1], suppose that each element has and lost efficacy and work two states, and the failure state of each element is separate.Make S
irepresent the state of element i, Q
irepresent its failure probability, then one [0,1] interval equally distributed random number R is produced to element i
i, make:
Therefore there is the transmission system state s=(s of N number of element
1..., s
i..., s
n), when the quantity of sampling is enough large, the sampling frequency of system state s can be used as the unbiased esti-mator of its probability, that is:
In formula (2): M is sampling number, m (s) is the number of times occurring system state s in sampling.
The above-mentioned transmission system methods of risk assessment based on Monte Carlo method, wherein, in described step S5, the described condition of convergence refers to enough sampling precisions, if risk indicator reaches enough sampling precisions, then carries out step S6; If risk indicator does not reach enough sampling precisions, then return step S3.
Transmission system methods of risk assessment based on Monte Carlo method of the present invention, beneficial effect is compared with prior art: first will carry out state sampling to equipment various in system, and the state of system is sampled and determined from equipment probability distribution function.The probability distribution of the various variablees required when giving element state sampling, sampling process can realize with the pseudorandom number generator of normal distribution by means of being uniformly distributed.To each systematic sample state, all there is the state probability values corresponding with it and consequence value, after the sample that have accumulated enough numbers, the result that each venture analysis obtains is added up and obtained final risk indicator.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of the transmission system methods of risk assessment based on Monte Carlo method of the present invention.
Embodiment
In order to make those skilled in the art can understand technical scheme of the present invention better, below in conjunction with accompanying drawing, its embodiment is described in detail:
Embodiments of the invention: refer to Fig. 1, based on the transmission system methods of risk assessment of Monte Carlo method, comprise the following steps:
S1, reads in the data of each element in transmission system;
S2, calculates the Normal load flow of each element in transmission system;
S3, adopts Monte Carlo method to randomly draw the event of failure of each element in transmission system, obtains transmission system state; In step S3,
In transmission system, each element is simulated with being uniformly distributed [0,1], suppose that each element has and lost efficacy and work two states, and the failure state of each element is separate.Make S
irepresent the state of element i, Q
irepresent its failure probability, then one [0,1] interval equally distributed random number R is produced to element i
i, make:
Therefore there is the transmission system state s=(s of N number of element
1..., s
i..., s
n), when the quantity of sampling is enough large, the sampling frequency of system state s can be used as the unbiased esti-mator of its probability, that is:
In formula (2): M is sampling number, m (s) is the number of times occurring system state s in sampling;
S4, according to described transmission system state, forms risk indicator;
S5, judges whether risk indicator reaches the condition of convergence, if reach, then carries out step S6; If do not reach, then return step S3;
S6, forms the reliability index of each element and the overall risk index of transmission system.
In step S5, the condition of convergence refers to enough sampling precisions, if risk indicator reaches enough sampling precisions, then carries out step S6; If risk indicator does not reach enough sampling precisions, then return step S3.
Transmission system methods of risk assessment based on Monte Carlo method of the present invention is according to being, a system state is the combination of all element states, and each element state can carry out sampling and determines by appearing at element this shape probability of state, the method, due to the contradiction between computing time and computational accuracy, adopts cut-off variance to ensure precision usually.
Transmission system methods of risk assessment based on Monte Carlo method of the present invention, first will carry out state sampling to equipment various in system, and the state of system is sampled and determined from equipment probability distribution function.The probability distribution of the various variablees required when giving element state sampling, sampling process can realize with the pseudorandom number generator of normal distribution by means of being uniformly distributed.To each systematic sample state, all there is the state probability values corresponding with it and consequence value, after the sample that have accumulated enough numbers, the result that each venture analysis obtains is added up and obtained final risk indicator.
Those of ordinary skill in the art will be appreciated that, above embodiment is only used to the present invention is described, and be not used as limitation of the invention, as long as in spirit of the present invention, all will drop in Claims scope of the present invention the change of the above embodiment, modification.
Claims (3)
1., based on the transmission system methods of risk assessment of Monte Carlo method, it is characterized in that, comprise the following steps:
S1, reads in the data of each element in transmission system;
S2, calculates the Normal load flow of each element in transmission system;
S3, adopts Monte Carlo method to randomly draw the event of failure of each element in transmission system, obtains transmission system state;
S4, according to described transmission system state, forms risk indicator;
S5, judges whether risk indicator reaches the condition of convergence, if reach, then carries out step S6; If do not reach, then return step S3;
S6, forms the reliability index of each element and the overall risk index of transmission system.
2. the transmission system methods of risk assessment based on Monte Carlo method according to claim 1, is characterized in that, in described step S3,
In transmission system, each element is simulated with being uniformly distributed [0,1], suppose that each element has and lost efficacy and work two states, and the failure state of each element is separate.Make S
irepresent the state of element i, Q
irepresent its failure probability, then one [0,1] interval equally distributed random number R is produced to element i
i, make:
Therefore there is the transmission system state s=(s of N number of element
1..., s
i..., s
n), when the quantity of sampling is enough large, the sampling frequency of system state s can be used as the unbiased esti-mator of its probability, that is:
In formula (2): M is sampling number, m (s) is the number of times occurring system state s in sampling.
3. the transmission system methods of risk assessment based on Monte Carlo method according to claim 1, is characterized in that, in described step S5, the described condition of convergence refers to enough sampling precisions, if risk indicator reaches enough sampling precisions, then carries out step S6; If risk indicator does not reach enough sampling precisions, then return step S3.
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Cited By (7)
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| CN106485392A (en) * | 2016-07-29 | 2017-03-08 | 国家电网公司 | Reliability of Interconnected Generating System appraisal procedure |
| CN107634519A (en) * | 2017-10-11 | 2018-01-26 | 湘潭大学 | A kind of power network line segmentation differentiation planing method for considering risk |
| CN108734567A (en) * | 2018-04-03 | 2018-11-02 | 杭州连银科技有限公司 | A kind of asset management system and its appraisal procedure based on big data artificial intelligence air control |
| CN109149559A (en) * | 2018-08-06 | 2019-01-04 | 中国电力科学研究院有限公司 | A kind of Demand-side interconnection reliability estimation method and system |
| CN110728415A (en) * | 2018-07-16 | 2020-01-24 | 苏州市三敏环境工程有限公司 | Motor evaluation system based on Monte Carlo method |
| CN111651889A (en) * | 2020-06-04 | 2020-09-11 | 重庆大学 | High-risk event screening method, device, equipment and storage medium for power transmission system |
| CN111680410A (en) * | 2020-05-29 | 2020-09-18 | 武汉天富海科技发展有限公司 | Ship IPS risk assessment method based on hybrid non-sequential Monte Carlo improvement method |
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2015
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| 吕立召: "非序贯蒙特卡洛改进法在电网运行方式风险评估中的应用", 《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》 * |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106485392A (en) * | 2016-07-29 | 2017-03-08 | 国家电网公司 | Reliability of Interconnected Generating System appraisal procedure |
| CN107634519A (en) * | 2017-10-11 | 2018-01-26 | 湘潭大学 | A kind of power network line segmentation differentiation planing method for considering risk |
| CN107634519B (en) * | 2017-10-11 | 2021-03-30 | 湘潭大学 | Power grid line section differentiation planning method considering risks |
| CN108734567A (en) * | 2018-04-03 | 2018-11-02 | 杭州连银科技有限公司 | A kind of asset management system and its appraisal procedure based on big data artificial intelligence air control |
| CN110728415A (en) * | 2018-07-16 | 2020-01-24 | 苏州市三敏环境工程有限公司 | Motor evaluation system based on Monte Carlo method |
| CN109149559A (en) * | 2018-08-06 | 2019-01-04 | 中国电力科学研究院有限公司 | A kind of Demand-side interconnection reliability estimation method and system |
| CN111680410A (en) * | 2020-05-29 | 2020-09-18 | 武汉天富海科技发展有限公司 | Ship IPS risk assessment method based on hybrid non-sequential Monte Carlo improvement method |
| CN111651889A (en) * | 2020-06-04 | 2020-09-11 | 重庆大学 | High-risk event screening method, device, equipment and storage medium for power transmission system |
| CN111651889B (en) * | 2020-06-04 | 2024-04-26 | 重庆大学 | High-risk event screening method, device, equipment and storage medium for power transmission system |
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