CN111950894A - Power system reliability assessment method based on improved Monte Carlo method - Google Patents
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Abstract
The invention provides a power system reliability evaluation method based on an improved Monte Carlo method, which classifies fault sets, theoretically completely considers all possible fault states of the system, divides the fault states into 2 subsets of sequencing faults and sampling faults, divides the sizes of the 2 subsets by changing a set value, and respectively selects an optimal method for consideration.
Description
Technical Field
The invention relates to the field of power system reliability evaluation, in particular to a power system reliability evaluation method based on an improved Monte Carlo method.
Background
The power system is an important infrastructure for providing a power source for industrial production and people's life to ensure that the national economy develops rapidly and people's life is carried out normally, along with the rapid development of industrial production and the continuous improvement of people's life, the reliability of the operation of the power system and the quality of the power system become the main requirements of new generations on the power system, the reliability of the power system mainly means that the power system can continuously transmit high-quality power to users under the condition of normal operation and ensure the comprehensive capability of the required power, the reliability of the power system is an important index for measuring the operation capability and the power supply reliability of the power system, the power system can be reduced in reliability due to various reasons in the actual operation process, meanwhile, the power failure accident of the power system occurs continuously in the present year, so that the national economy and people's life are seriously influenced, therefore, the evaluation on the reliability of the power system can effectively guide the planning and construction of the power system, improve the safe operation capacity of the power system and promote the rapid development of the power system in China.
At present, the basic methods for reliability evaluation of power systems mainly include probabilistic evaluation methods and deterministic evaluation methods. For the whole power system, the power system is a system with strong randomness, various factors influencing the reliability are random, a large error occurs in an evaluation result when a deterministic method is used, the whole power system cannot be evaluated scientifically, an analytic method and a Monte Carlo method which are probabilistic evaluation methods are basic methods for evaluating the reliability of the power system, the results of random states are evaluated according to the probability of the occurrence of the random states of the system, the analytic method has high calculation accuracy in the application process, but the number of analyzed states increases continuously along with the enlargement of the scale of the power system, and the Monte Carlo method is not suitable for the reliability evaluation of a large power system, the calculation accuracy of the Monte Carlo method does not change along with the scale of the power system in the actual application process, but the sampling of a zero fault state space cannot be avoided, a large number of sampling points fall in a fault-free area, so that the sampling efficiency is degraded when the system reliability is improved.
Disclosure of Invention
In order to solve the technical problem, the invention provides a fault set classification method, which divides each heavy fault state into 2 subsets to be considered respectively by selecting each heavy fault cutoff probability: dividing k fault states with the occurrence probability larger than the fault cutoff probability into a sequencing fault set, adopting improved fast rows to perform analysis and analysis, and obtaining the most accurate index through the least comparison times; k fault states with the occurrence probability smaller than the fault cutoff probability are classified into a sampling fault set, and Monte Carlo simulation analysis is carried out by adopting a self-optimizing layered uniform sampling method, so that the index estimation value can be efficiently obtained. The method can flexibly allocate the size of each fault set, optimally allocate the sampling times of each heavy fault state in the sampling process, avoid the waste of efficiency of sampling zero fault areas, and avoid the phenomenon of sampling degradation when the reliability of the system is improved.
The technical scheme adopted by the invention is as follows: a power system reliability assessment method based on an improved Monte Carlo method comprises the following steps:
step 1): dividing a state set omega formed by system elements into a sequencing fault set omegaFAnd sampling the fault set omegaM(ii) a Inputting system data;
step 2): selecting a system state by improving a quick sequencing algorithm; carrying out reliability evaluation on the system state; updating the reliability index;
step 3): judging whether the system fault state probability is less than the cut-off probability akIf not, returning to the step 2), and if so, executing the step 4);
step 4): performing Monte Carlo sampling analysis on the state in the pair by adopting a self-optimizing hierarchical uniform sampling method, and outputting an estimated value after sampling is finished when the expected precision is reached;
further, when the accumulated sum of the sorted fault occurrence probabilities reaches a set value, the sorting is stopped, and the occurrence probability of the last sorted fault state is selected as a cut-off probability akWill be ordered fault statusState subsumption ordering fault set omegaFAnalysis of omega by analytical methodFInfluence of the state of (1) on the reliability index;
further, the remaining system fault conditions not considered (i.e., the probability of occurrence of a fault is less than the cutoff probability a)k) Into the sampling fault set omegaMIn the method, a self-optimizing hierarchical uniform sampling method is adopted to carry out the omega alignmentMCarrying out Monte Carlo sampling analysis on the state in (1), finishing sampling and outputting an estimated value when the expected precision is reached;
wherein the Ω is ΩF+ΩMThe power system reliability index may be expressed as
Furthermore, x is an N-dimensional vector formed by N elements of the system, and f (x) is the influence generated by the fault state; p (x) is the probability of the fault condition occurring.
The invention provides a power system reliability evaluation method based on an improved Monte Carlo method, which classifies fault sets, theoretically completely considers all possible fault states of a system, divides the fault states into 2 subsets of sequencing faults and sampling faults, divides the sizes of the 2 subsets by changing a set value, and respectively selects an optimal method for consideration, thereby effectively improving the evaluation efficiency.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a fault set classification algorithm flow diagram.
FIG. 2 is a flow chart of an improved fast sequencing algorithm.
Detailed Description
In order to make the objects, technical solutions and advantages of the present disclosure more apparent, example embodiments according to the present disclosure will be described in detail below with reference to the accompanying drawings. It is to be understood that the described embodiments are merely a subset of the embodiments of the present disclosure and not all embodiments of the present disclosure, with the understanding that the present disclosure is not limited to the example embodiments described herein. All other embodiments made by those skilled in the art without inventive efforts based on the embodiments of the present disclosure described in the present disclosure should fall within the scope of the present disclosure.
The technical scheme adopted by the invention is as follows: referring to fig. 1, fig. 1 shows a flowchart of a method for evaluating reliability of an electric power system based on an improved monte carlo method according to an embodiment of the present invention. The reliability evaluation method comprises the following steps:
step 1): dividing a state set omega formed by system elements into a sequencing fault set omegaFAnd sampling the fault set omegaM(ii) a Inputting system data;
step 2): selecting a system state by improving a quick sequencing algorithm; carrying out reliability evaluation on the system state; updating the reliability index;
step 3): judging whether the system fault state probability is less than the cut-off probability alphakIf not, returning to the step 2), and if so, executing the step 4);
step 4): performing Monte Carlo sampling analysis on the state in the pair by adopting a self-optimizing hierarchical uniform sampling method, and outputting an estimated value after sampling is finished when the expected precision is reached;
further, when the accumulated sum of the sorted fault occurrence probabilities reaches a set value, the sorting is stopped, and the occurrence probability of the last sorted fault state is selected as a cut-off probability akSorting the fault states into a sorted fault set omegaF, analyzing the influence of the state in the omega F on the reliability index by adopting an analytical method;
further, the remaining system fault conditions not considered (i.e., the probability of occurrence of a fault is less than the cutoff probability a)k) Into the sampling fault set omegaMIn the method, a self-optimizing hierarchical uniform sampling method is adopted to carry out the omega alignmentMCarrying out Monte Carlo sampling analysis on the state in (1), finishing sampling and outputting an estimated value when the expected precision is reached;
wherein the Ω is ΩF+ΩMThe power system reliability index may be expressed as
Furthermore, x is an N-dimensional vector formed by N elements of the system, and f (x) is the influence generated by the fault state; p (x) is the probability of the fault condition occurring.
Considering that the occurrence probability of most low-weight faults of the power system is obviously greater than the occurrence probability of high-weight faults, if the faults are sequenced in all states from low-weight to high-weight, the efficiency is wasted, only the events with higher probability in the multiple faults need to be sequenced in a layering way, and if the sum P of the k-weight fault probabilities can be solved in advancekWhen the k-fold system fault states are sorted in the step 2) of the rapid sorting technology, when the sum of the cumulative probabilities of the sorted fault states is close, the k-fold system fault state sorting is cut off, so that the sorting faults can be concentrated and the heavy system fault states with relatively high occurrence probability are included, and the step 3) of sorting all the system fault states in the original rapid sorting technology is not needed, thereby saving a large number of comparison times and calculation amount. Therefore, please refer to fig. 2, which is a specific flowchart of the improved fast sequencing algorithm adopted in step 2). The step 2) comprises the following steps:
step 1): inputting system data, obtaining the relative failure rate theta of the element, and redefining the element serial number according to the theta from the major path to the minor path;
step 2): let k be 1 and m be 1, calculate the sum of k order fault state probabilities PkSetting λ k, where λ k is cumulativeA fault probability parameter, which is a positive number less than 1 that is arbitrarily set, such as 0.8;
step 3): computing the sum of k order failure state probabilities PkSetting λk；
Step 4): sequencing the first m fault states with higher probability in the k faults by a quick sequencing method;
step 5): accumulating the probability of the fault state and judging whether it is greater than lambdakPkIf not, returning to the step 4), and if yes, executing the step 6);
step 6): judging whether multiple faults are considered or not, if not, returning to the step 3), and if so, executing the step 7);
step 7): analyzing the fault state consequence and outputting a reliability index;
the quick sequencing algorithm considers that the occurrence probability of most of low-weight faults of the power system is obviously greater than that of high-weight faults, if all fault states from low-weight faults to high-weight faults are sequenced, efficiency is wasted, and only events with higher probability in the multiple faults need to be sequenced in a layering mode.
In summary, the invention provides a power system reliability evaluation method based on an improved monte carlo method, which classifies fault sets, theoretically considers all possible fault states of the system completely, divides the fault states into 2 subsets of sequencing faults and sampling faults, divides the sizes of the 2 subsets by changing set values, and selects an optimal method for consideration respectively, thereby effectively improving evaluation efficiency;
while the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present disclosure as defined by the following claims. It is therefore intended that the present embodiments be considered in all respects as illustrative and not restrictive, reference being made to the appended claims rather than to the foregoing description to indicate the scope of the patent as claimed.
Claims (3)
1. A power system reliability assessment method based on an improved monte carlo method, the method comprising:
step 1): dividing a state set omega formed by system elements into a sequencing fault set omegaFAnd sampling the fault set omegaM(ii) a Inputting system data;
step 2): selecting a system state by improving a quick sequencing algorithm; carrying out reliability evaluation on the system state; updating the reliability index;
step 3): judging whether the system fault state probability is smaller than a cut-off probability alpha k, if not, returning to the step 2), and if so, executing the step 4);
step 4): and (3) carrying out Monte Carlo sampling analysis on the state in the pair by adopting a self-optimizing hierarchical uniform sampling method, and outputting an estimated value after sampling is finished when the expected precision is reached.
2. A power system reliability assessment method as claimed in claim 1, said step 2) comprising:
when the cumulative sum of the sorted fault occurrence probabilities reaches a set value, stopping sorting, and selecting the sorted last fault state occurrence probability as a cut-off probability alphakSorting the fault states into a sorted fault set omegaFAnalysis of omega by analytical methodFThe influence of the state in (1) on the reliability index.
3. The method of claim 1, wherein the remaining system failure states not considered (i.e., the failure occurrence probability is less than the cut-off probability α)k) Into the sampling fault set omegaMIn the method, a self-optimizing hierarchical uniform sampling method is adopted to carry out the omega alignmentMCarrying out Monte Carlo sampling analysis on the state in (1), finishing sampling and outputting an estimated value when the expected precision is reached;
wherein the Ω is ΩF+ΩMThe power system reliability index may be expressed as
Furthermore, x is an N-dimensional vector formed by N elements of the system, and f (x) is the influence generated by the fault state; p (x) is the probability of the fault condition occurring.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017016021A1 (en) * | 2015-07-28 | 2017-02-02 | 天津大学 | State enumeration reliability evaluation method based on influence increment and device therefor |
| CN108681815A (en) * | 2018-05-11 | 2018-10-19 | 贵州电网有限责任公司 | A kind of operation reliability evaluation method based on quicksort and matrix in block form |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017016021A1 (en) * | 2015-07-28 | 2017-02-02 | 天津大学 | State enumeration reliability evaluation method based on influence increment and device therefor |
| CN108681815A (en) * | 2018-05-11 | 2018-10-19 | 贵州电网有限责任公司 | A kind of operation reliability evaluation method based on quicksort and matrix in block form |
Non-Patent Citations (1)
| Title |
|---|
| 黄江宁 等: "基于故障集分类的电力系统可靠性评估方法", 《中国电机工程学报》, vol. 33, no. 16, pages 112 - 121 * |
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