CN111047467B - Heuristic generation method and system of expected fault set of power grid forest fire disasters - Google Patents
Heuristic generation method and system of expected fault set of power grid forest fire disasters Download PDFInfo
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Abstract
The invention discloses a method and a system for generating an expected failure set of a heuristic power grid mountain fire disaster, wherein the method comprises the following steps: inverting and calculating an affected important line set according to the power grid mountain fire density prediction result; individually encoding all affected important lines; the codes of all affected important lines together form a fault combination X; repeating T times by adopting a random sampling mode aiming at all affected important lines to generate T fault combinations to form a fault combination group; calculating a grid stability margin P for each fault combination in a fault combination group i The method comprises the steps of carrying out a first treatment on the surface of the Calculating a current minimum stability margin P for each fault combination i best And a minimum stability margin G in T fault combinations best The method comprises the steps of carrying out a first treatment on the surface of the And calculating and generating the next batch of T fault combinations, incorporating the fault combinations lower than the power grid stability margin threshold into an expected fault set, and repeating Y times to obtain a final heuristic power grid mountain fire disaster expected fault set. The method can quickly obtain the power grid mass-sending expected fault set under the mountain fire disaster.
Description
Technical Field
The invention relates to the technical field of power grid protection, in particular to a method and a system for generating an expected failure set of a heuristic power grid mountain fire disaster.
Background
In recent years, with the change of fire custom for industry and agriculture, the Chinese forest fire disasters have a steep rise trend, and the number of forest fire hotspots exceeds 8 ten thousand in one year according to satellite monitoring hotspot data display. When the mountain fire occurs, the generated smoke particles and high-temperature ionization act to cause the air insulation of the power transmission line to be reduced, so that the mountain fire tripping accident of the power transmission line occurs. Because the mountain fire points are wide in multiple surfaces, a plurality of lines can trip and power failure at the same time in severe cases, and an important threat is formed to the safe operation of the power grid.
Currently, the power grid fault risk analysis is mainly focused on the aspects of power grid cascading failure characteristics and risk analysis, and the research on the power grid mass-sending fault condition is less. The power grid mass-sending faults have dimension disaster problems when a fault set is generated by adopting an enumeration method because the calculated amount grows exponentially along with the increase of the fault dimension.
Therefore, the method and the system for generating the expected fault set of the power grid mountain fire disaster can be used for heuristically searching and generating the expected fault set of the power grid mountain fire disaster, effectively reducing the scale of the fault set, overcoming the dimension problem and providing a theoretical basis for efficiently developing the risk analysis of the power grid mountain fire disaster.
Disclosure of Invention
The invention provides a heuristic generation method and system of an expected fault set of a power grid forest fire disaster, which are used for solving the technical problem that the fault set is difficult to comprehensively generate when the power grid mass-sending faults are researched in the prior art.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
a heuristic generation method of an expected failure set of a power grid forest fire disaster comprises the following steps:
s1: inverting and calculating an affected important line set according to the power grid mountain fire density prediction result;
s2: individually encoding all affected important lines; the codes of all affected important lines together form a fault combination X, x= [ X ] 1 ,x 2 ,…,x n ]The method comprises the steps of carrying out a first treatment on the surface of the Wherein x is j The code of the j-th line is that n is the number of affected important lines obtained by inversion;
s3: repeating S2 for T times by adopting a random sampling mode aiming at all affected important lines to generate T fault combinations to form a fault combination group;
s4: calculating a grid stability margin P for each fault combination in a fault combination group i ，i＝1,2,…,T；
S5: calculating a current minimum stability margin P for each fault combination i best And a minimum stability margin G in T fault combinations best ；
S6: the following formula is adopted to calculate and generate the next batch of T fault combinations:
x i ＝x i +v i
in the formula, v i Migration speed for the ith fault combination; rand () is [0,1]Random numbers of (a); c 1 And c 2 Is a heuristic parameter;
s7: setting a power grid stability margin threshold U, wherein fault combinations lower than the power grid stability margin threshold are included in an expected fault set, and fault combinations higher than the power grid stability margin threshold are ignored;
s8: setting and repeatedly calculating the batch number Y, and repeating the steps S4 to S7 for Y times to obtain a final heuristic power grid mountain fire disaster expected failure set.
Preferably, a random sampling manner is adopted for all affected important lines, and the method comprises the following steps:
the random numbers between the affected important line assignments [0,1] are sampled, and the line with the value range of [0,0.5] of the random numbers is not included in the fault combination, and the line with the value range of (0.5, 1) of the random numbers is included in the fault combination.
Preferably, the grid stability margin P for each fault combination i I=1, 2, …, T; the method adopts the following calculation mode to calculate:
wherein T is the number of fault combinations in the expected fault set;
a static grid stability margin for the ith group of faults;
transient grid stability margin for the ith group of faults; />
And (3) a dynamic power grid stability margin for the ith group of faults.
Preferably, c 1 And c 2 The value of (2).
The invention also provides a computer system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any of the methods described above when executing the computer program.
The invention also provides a computer storage medium having stored thereon a computer program which when executed by a processor performs the steps of any of the methods described above.
The invention has the following beneficial effects:
the heuristic generation method and system of the power grid forest fire disaster forecast fault set can heuristically and rapidly obtain the power grid mass-sending forecast fault set under the forest fire disaster, and the fault set considers important power grid fault combinations for influencing importance, so that the line omission probability of the important forest fire disaster is effectively reduced; the principle is clear, the operation is convenient, the method has an important guiding function on the high-efficiency analysis of the power grid risk under the large-scale mountain fire disaster, and the practical value is high.
In addition to the objects, features and advantages described above, the present invention has other objects, features and advantages. The invention will be described in further detail with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention. In the drawings:
fig. 1 is a flow chart of a method for generating an expected failure set of a grid forest fire disaster according to a heuristic method in a preferred embodiment 1 of the present invention;
fig. 2 is a schematic diagram of a mountain fire density prediction result according to the preferred embodiment 2 of the present invention.
Detailed Description
Embodiments of the invention are described in detail below with reference to the attached drawings, but the invention can be implemented in a number of different ways, which are defined and covered by the claims.
Example 1:
referring to fig. 1, the method for generating the expected failure set of the power grid forest fire disaster according to the embodiment includes the following steps:
s1: and inverting and calculating an affected important line set according to the power grid mountain fire density prediction result.
S2: individually encoding all affected important lines; the codes of all affected important lines together form a fault combination X, x= [ X ] 1 ,x 2 ,…,x n ]The method comprises the steps of carrying out a first treatment on the surface of the Wherein x is j For the coding of the j-th line, n is the number of affected important lines obtained by inversion.
S3: repeating S2 for T times by adopting a random sampling mode aiming at all affected important lines to generate T fault combinations to form a fault combination group; the following steps are preferably adopted for all affected important lines by adopting a random sampling mode:
the random numbers between the affected important line assignments [0,1] are sampled, and the line with the value range of [0,0.5] of the random numbers is not included in the fault combination, and the line with the value range of (0.5, 1) of the random numbers is included in the fault combination.
S4: calculating a grid stability margin P for each fault combination in a fault combination group i I=1, 2, …, T; preferably calculated as follows:
wherein T is the number of fault combinations in the expected fault set;
a static grid stability margin for the ith group of faults;
transient grid stability margin for the ith group of faults; />
And (3) a dynamic power grid stability margin for the ith group of faults.
S5: calculating a current minimum stability margin for each fault combination
Minimum stability margin G in T fault combinations best ；
S6: the following formula is adopted to calculate and generate the next batch of T fault combinations:
x i ＝x i +v i
in the formula, v i Migration speed for the ith fault combination; rand () is [0,1]Random numbers of (a); c 1 And c 2 Is a heuristic parameter, c 1 And c 2 Is usually given a value of 2.
S7: and setting a power grid stability margin threshold U, wherein fault combinations lower than the power grid stability margin threshold are included in an expected fault set, and fault combinations higher than the power grid stability margin threshold are considered to have small influence on the power grid and can be ignored.
S8: setting and repeatedly calculating the batch number Y, and repeating the steps S4 to S7 for Y times to obtain a final heuristic power grid mountain fire disaster expected failure set.
Through the steps, the power grid mass-sending expected fault set under the mountain fire disaster can be obtained heuristically and rapidly, the fault set mainly considers the important power grid fault combination, and the line omission probability of the important mountain fire disaster is effectively reduced; the principle is clear, the operation is convenient, the method has an important guiding function on the high-efficiency analysis of the power grid risk under the large-scale mountain fire disaster, and the practical value is high.
Example 2:
the method for generating the expected fault set of the heuristic power grid mountain fire disaster of the embodiment comprises the following steps:
s1: and obtaining a mountain fire density prediction result according to a mountain fire density prediction module proposed by a disaster prevention and reduction national key laboratory of the power grid power transmission and transformation equipment (see figure 2). Inversion calculates the affected set of important lines as: {500kV line 1, 500kV line 5, 500kV line 8, 220kV line 9};
s2 to S7 of example 1 were performed; grid stability margin threshold u=0.7 in S7;
s8: setting repeated calculation batch number Y, and repeating the steps S4 to S7 for Y times to obtain a final heuristic power grid mountain fire disaster expected failure set, wherein the final heuristic power grid mountain fire disaster expected failure set is as follows: { [500kV line 1, 500kV line 5], [500kV line 5, 500kV line 8], [500kV line 1, 500kV line 5, 500kV line 8] }. The 220kV line 9 was found to have less impact on the grid and was negligible in generating the expected fault set.
Example 3:
the present embodiment provides a computer system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any of the embodiments described above when executing the computer program.
The present embodiment provides a computer storage medium having a computer program stored thereon, which when executed by a processor performs the steps of any of the embodiments described above.
In summary, according to the invention, by combining random sampling with power grid stability margin calculation and screening, a power grid mass-sending expected fault set under mountain fire disasters can be obtained heuristically and rapidly, the fault set is mainly considered to influence important power grid fault combinations, the scale of the fault set is effectively reduced, the dimension problem is overcome, and the line omission probability of the important mountain fire disasters is effectively reduced; the principle is clear, the operation is convenient, the method has an important guiding function on the high-efficiency analysis of the power grid risk under the large-scale mountain fire disaster, and the practical value is high.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A method for generating an expected failure set of a heuristic power grid mountain fire disaster is characterized by comprising the following steps:
s1: inverting and calculating an affected important line set according to the power grid mountain fire density prediction result;
s2: individually encoding all affected important lines; the codes of all affected important lines together form a fault combination X, x= [ X ] 1 ,x 2 ,…,x n ]The method comprises the steps of carrying out a first treatment on the surface of the Wherein x is j The code of the j-th line is that n is the number of affected important lines obtained by inversion;
s3: repeating S2 for T times by adopting a random sampling mode aiming at all affected important lines to generate T fault combinations to form a fault combination group;
s4: calculating a grid stability margin P for each fault combination in a fault combination group i ，i＝1,2,…,T；
S5: calculating a current minimum stability margin P for each fault combination i best And minimum stability in T fault combinationsMargin G best ；
S6: the following formula is adopted to calculate and generate the next batch of T fault combinations:
v i ＝v i +c 1 ×rand()×(P i best -x i )+c 2 ×rand()×(G best -x i )
x i ＝x i +v i
in the formula, v i Migration speed for the ith fault combination; rand () is [0,1]Random numbers of (a); c 1 And c 2 Is a heuristic parameter;
s7: setting a power grid stability margin threshold U, wherein fault combinations lower than the power grid stability margin threshold are included in an expected fault set, and fault combinations higher than the power grid stability margin threshold are ignored;
s8: setting and repeatedly calculating the batch number Y, and repeating the steps S4 to S7 for Y times to obtain a final heuristic power grid mountain fire disaster expected failure set.
2. The method for generating the expected failure set of the heuristic power grid mountain fire disaster according to claim 1, wherein the method adopts a random sampling mode for all affected important lines, and comprises the following steps:
the random numbers between the affected important line assignments [0,1] are sampled, and the line with the value range of [0,0.5] of the random numbers is not included in the fault combination, and the line with the value range of (0.5, 1) of the random numbers is included in the fault combination.
3. The method for generating a set of expected faults of a grid forest fire disaster according to claim 1, wherein the grid stability margin P of each fault combination i I=1, 2, …, T; the method adopts the following calculation mode to calculate:
wherein T is the number of fault combinations in the expected fault set；
A static grid stability margin for the ith group of faults; />
Transient grid stability margin for the ith group of faults; />
And (3) a dynamic power grid stability margin for the ith group of faults.
4. The method for generating a set of expected faults in a power grid forest fire disaster as claimed in claim 1, wherein c 1 And c 2 The value of (2).
5. A computer system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method of any of the preceding claims 1 to 3 when the computer program is executed.
6. A computer storage medium having stored thereon a computer program, characterized in that the program, when executed by a processor, realizes the steps in the method of any of the preceding claims 1 to 3.
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| CN109118105A (en) * | 2018-08-28 | 2019-01-01 | 国网湖南省电力有限公司 | The risk analysis method and system of power grid mass-sending failure under mountain fire disaster |
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| CN101425686A (en) * | 2008-12-11 | 2009-05-06 | 国网电力科学研究院 | Electrical power system on-line safety and stability evaluation forecast failure collection adaptive selection method |
| CN109118105A (en) * | 2018-08-28 | 2019-01-01 | 国网湖南省电力有限公司 | The risk analysis method and system of power grid mass-sending failure under mountain fire disaster |
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