CN117150808A - Method, system and equipment for evaluating toughness of power transmission line in strong convection weather - Google Patents
Method, system and equipment for evaluating toughness of power transmission line in strong convection weather Download PDFInfo
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Abstract
The application provides a method, a system and equipment for evaluating toughness of a power transmission line in strong convection weather, comprising the following steps: partitioning the power transmission line according to the geographic position of the line; determining the total fault probability of each partition based on the line running time, a pre-constructed tower fault probability model, real-time monitoring data and forecast data; determining the average fault repair time of each partition based on the line fault history data and the maintenance time; determining a toughness evaluation index based on the total fault probability of each partition and the average fault repair time of each partition in combination with the highest voltage level of the power transmission line; and evaluating the toughness of the power transmission line under strong convection weather based on the toughness evaluation index. The application realizes the toughness assessment of the power transmission line in strong convection weather, rapidly analyzes the weak area in the power transmission line, and provides basis for taking preventive measures or rapidly recovering the first-aid repair of the line.
Description
Technical Field
The application relates to the field of power transmission engineering, in particular to a method, a system and equipment for evaluating toughness of a power transmission line in strong convection weather.
Background
Toughness is the ability to reflect whether a power system can fail severely and quickly cope with a restoration of an operating state after failure under the influence of an extreme disaster. The high-toughness power grid has better disaster resistance and the capability of recovering operation after disaster under the disaster environment.
The strong convection weather brings great influence to the safe and stable operation of the power transmission line, and faults such as wire breakage, strand breakage, wind deflection discharge, tower inversion and the like occur. According to strong convection strong wind weather characteristics, the method for improving the wind speed of the power transmission line design to improve wind resistance is one of effective ways. However, the practical application has larger inapplicability, such as that the wind speed of the tornado can reach 100m/s, the occurrence time and the place randomness are strong, the influence range is relatively smaller (several meters to hundreds of meters), and if the design wind speed of the power transmission line is integrally lifted, the engineering cost is exponentially increased, and the cost cannot be measured. At present, the power grid is still in a passive coping state for strong convection strong wind weather.
Typhoons are also easy to cause short circuit, windage yaw or body damage faults of overhead lines, so that scholars at home and abroad introduce a concept of toughness to quantify the bearing capacity and emergency recovery capacity of the power system when the power system is used for coping with typhoon weather, and a plurality of power distribution network toughness assessment models are established under the action of typhoons so as to improve the capability of the overhead lines to cope with typhoon disasters. However, for strong convection strong wind weather, a comprehensive toughness evaluation method of the power transmission line has not been studied.
Disclosure of Invention
In order to solve the problem of strong convection strong wind weather, the application provides a method for evaluating the toughness of a power transmission line in strong convection weather, which comprises the following steps:
partitioning the power transmission line according to the geographic position of the line;
determining the total fault probability of each partition based on the line running time, a pre-constructed tower fault probability model, real-time monitoring data and forecast data;
determining the average fault repair time of each partition based on the line fault history data and the maintenance time;
determining a toughness evaluation index based on the total fault probability of each partition and the average fault repair time of each partition in combination with the highest voltage level of the power transmission line;
and evaluating the toughness of the power transmission line under strong convection weather based on the toughness evaluation index.
Optionally, the determining the total fault probability of each partition based on the line running time, the pre-constructed tower fault probability model, the real-time monitoring data and the forecast data includes:
obtaining the reference fault probability of each tower based on the line running time and a pre-constructed tower fault probability model;
analyzing the real-time monitoring data and the forecast data, determining a weighted coefficient sum of strong convection weather fault probabilities, and calculating fault probabilities of various elements;
determining an overhead line fault rate based on the reference fault probability and the strong convection weather fault probability weighting coefficient;
determining a total fault probability of each partition based on the fault probabilities of the various types of elements and the overhead line fault rate;
the tower fault probability model is established by utilizing Webull distribution and combining historical standing account data of the power transmission line;
the various types of elements include towers and various grades of wire.
Optionally, the fault rate of the overhead line is calculated according to the following formula:
wherein:is the fault rate of the overhead line; lambda (lambda) 0 (t) is a reference fault rate function; w is a strong convection weather fault probability weighting coefficient.
Optionally, the total fault probability of each partition is calculated according to the following formula:
wherein: lambda's' m For the total failure probability of partition m,is the fault rate of the overhead line; j is an element type number, wherein the wire number is 1, and the tower number is 2; />The number of the ith type of elements in the mth partition; />Is the i-th type element failure rate.
Optionally, before partitioning the power transmission line according to the geographical location of the line, the method further includes: and numbering each power transmission line.
Optionally, the average fault repair time of each partition is calculated according to the following formula:
wherein t 'is' m The average fault repair time of the partition m is the partition number;is the fault rate of the overhead line; j is the element type number; />The number of the ith type of elements in the mth partition; />Failure rate for the i-th type of element; />Mean fault repair time for the line; />Mean time to fail-over for the i-th type of element.
Optionally, the toughness evaluation index is calculated according to the following formula:
wherein L is a toughness evaluation index of the power transmission line in strong convection weather; q (t) is the basic running state of the transmission line; t is t 0 The moment when strong convection occurs; t is t 3 N is the power transmission line partition set at the power transmission line state recovery time; p (P) m Loss of power for a partition load, V m Is the highest voltage level of the overhead transmission line area, t' m For the average failover time of partition m, λ' m Is the total failure probability of partition m.
Optionally, the evaluating the toughness of the power transmission line in strong convection weather based on the toughness evaluation index includes:
judging whether the toughness evaluation index is larger than a preset initial toughness evaluation index of a set multiple;
if the difference is larger than the preset value, the toughness of the transmission line is poor in strong convection weather, and disaster prevention measures are needed; otherwise, the toughness of the transmission line is stronger in strong convection weather, and disaster prevention measures are not needed;
the initial toughness evaluation index is determined based on the voltage level of the power transmission line, fault history data and maintenance time.
In still another aspect, the present application further provides a system for evaluating toughness of a power transmission line in strong convection weather, including:
the partitioning module is used for partitioning the power transmission line according to the geographic position of the line;
the probability calculation module is used for determining the total fault probability of each partition based on the line running time, a pre-constructed tower fault probability model, real-time monitoring data and forecast data;
the time calculation module is used for determining the average fault repair time of each partition based on the line fault historical data and the maintenance time;
the evaluation index calculation module is used for determining a toughness evaluation index based on the total fault probability of each partition and the average fault repair time of each partition in combination with the highest voltage level of the power transmission line;
and the evaluation module is used for evaluating the toughness of the power transmission line under strong convection weather based on the toughness evaluation index.
Optionally, the probability calculation module is specifically configured to:
obtaining the reference fault probability of each tower based on the line running time and a pre-constructed tower fault probability model;
analyzing the real-time monitoring data and the forecast data, determining a weighted coefficient sum of strong convection weather fault probabilities, and calculating fault probabilities of various elements;
determining an overhead line fault rate based on the reference fault probability and the strong convection weather fault probability weighting coefficient;
determining a total fault probability of each partition based on the fault probabilities of the various types of elements and the overhead line fault rate;
the tower fault probability model is established by utilizing Webull distribution and combining historical standing account data of the power transmission line;
the various types of elements include towers and various grades of wire.
Optionally, the probability calculation module calculates the failure rate of the overhead line by:
wherein:is the fault rate of the overhead line; lambda (lambda) 0 (t) is a reference fault rate function; w is a strong convection weather fault probability weighting coefficient.
Optionally, the probability calculation module calculates the total failure probability of each partition by:
wherein: lambda's' m For the total failure probability of partition m,is the fault rate of the overhead line; j is an element type number, wherein the wire number is 1, and the tower number is 2; />The number of the ith type of elements in the mth partition; />Is the i-th type element failure rate.
Optionally, the time calculation module calculates the average fault repair time of each partition by the following formula:
wherein t 'is' m The average fault repair time of the partition m is the partition number;is the fault rate of the overhead line; j is the element type number; />The number of the ith type of elements in the mth partition; />Failure rate for the i-th type of element; />Mean fault repair time for the line; />Mean time to fail-over for the i-th type of element.
Optionally, the evaluation index calculation module calculates the evaluation index by:
wherein L is a toughness evaluation index of the power transmission line in strong convection weather; q (t) is the basic running state of the transmission line; t is t 0 The moment when strong convection occurs; t is t 3 N is the power transmission line partition set at the power transmission line state recovery time; p (P) m Loss of power for a partition load, V m Is the highest voltage level of the overhead transmission line area, t' m For the average failover time of partition m, λ' m Is the total failure probability of partition m.
Optionally, the evaluation module is specifically configured to:
judging whether the toughness evaluation index is larger than a preset initial toughness evaluation index of a set multiple;
if the difference is larger than the preset value, the toughness of the transmission line is poor in strong convection weather, and disaster prevention measures are needed; otherwise, the toughness of the transmission line is stronger in strong convection weather, and disaster prevention measures are not needed;
the initial toughness evaluation index is determined based on the voltage level of the power transmission line, fault history data and maintenance time.
In yet another aspect, the present application also provides a computer device, comprising: one or more processors;
the processor is used for storing one or more programs;
when the one or more programs are executed by the one or more processors, a method for evaluating toughness of a transmission line in strong convection weather is implemented as described above.
In yet another aspect, the present application further provides a computer readable storage medium, on which a computer program is stored, where the computer program is executed to implement a method for evaluating toughness of a power transmission line in strong convection weather as described above.
Compared with the prior art, the application has the beneficial effects that:
the application provides a method for evaluating toughness of a power transmission line in strong convection weather, which comprises the following steps: partitioning the power transmission line according to the geographic position of the line; determining the total fault probability of each partition based on the line running time, a pre-constructed tower fault probability model, real-time monitoring data and forecast data; determining the average fault repair time of each partition based on the line fault history data and the maintenance time; determining a toughness evaluation index based on the total fault probability of each partition and the average fault repair time of each partition in combination with the highest voltage level of the power transmission line; and evaluating the toughness of the power transmission line under strong convection weather based on the toughness evaluation index. The application realizes the toughness assessment of the power transmission line in strong convection weather, rapidly analyzes the weak area in the power transmission line, and provides basis for taking preventive measures or rapidly recovering the first-aid repair of the line.
Drawings
FIG. 1 is a flow chart of a method for evaluating toughness of a power transmission line in strong convection weather;
fig. 2 is a graph of the toughness of the transmission line of the present application.
Detailed Description
At present, toughness evaluation of a power system aims at a power distribution network system, economic loss caused by the power distribution system is taken as an evaluation parameter to determine the toughness of the power distribution system, and the toughness evaluation method of a power transmission line aims at a blank stage. In the power transmission line, the faults caused by severe disasters can cause serious consequences, but in extremely severe climates such as typhoons, tornadoes and the like, the severe climates are difficult to deal with by improving design standards, so that a comprehensive evaluation method, namely a toughness evaluation method, of the power transmission line in a disaster environment needs to be established by taking the safe operation of the power transmission line, the lowest fault degree and the fastest recovery after the disaster as multi-parameter evaluation targets.
Example 1: a method for evaluating toughness of a power transmission line in strong convection weather is shown in fig. 1:
s1: partitioning the power transmission line according to the geographic position of the line;
s2: determining the total fault probability of each partition based on the line running time, a pre-constructed tower fault probability model, real-time monitoring data and forecast data;
s3: determining the average fault repair time of each partition based on the line fault history data and the maintenance time;
s4: determining a toughness evaluation index based on the total fault probability of each partition and the average fault repair time of each partition in combination with the highest voltage level of the power transmission line;
s5: and evaluating the toughness of the power transmission line under strong convection weather based on the toughness evaluation index.
The present application will be described in detail below:
in S1, partitioning the power transmission line according to the geographical position of the line, specifically including:
according to the toughness evaluation index calculation method, each base tower and each grade of lead are combined, the power transmission line to be evaluated is divided into a plurality of blocks, and series connection is established among the blocks.
S2, determining the total fault probability of each partition based on line operation time, a pre-constructed tower fault probability model, real-time monitoring data and forecast data, wherein the method comprises the following steps:
obtaining the reference fault probability of each tower based on the line running time and a pre-constructed tower fault probability model;
analyzing the real-time monitoring data and the forecast data, and determining strong convection weather fault probability weighting coefficients and fault probabilities of various elements;
determining an overhead line fault rate based on the reference fault probability and the strong convection weather fault probability weighting coefficient;
determining a total fault probability of each partition based on the fault probabilities of the various types of elements and the overhead line fault rate;
the tower fault probability model is established by utilizing Webull distribution and combining historical standing account data of the power transmission line;
the various types of elements include towers and various grades of wire.
The specific content of S2 is as follows:
the overhead line failure rate may be determined from a baseline failure rate function and a strong convection weather failure probability weighting coefficient. The quasi-fault rate function is determined by the line service time and is modeled by utilizing Weibull distribution. In extreme weather environments such as strong wind, ice coating and the like, the overhead line fault rate is increased sharply, the fault probability weighting coefficient is utilized to improve the fault occurrence probability, and in the application process, the strong convection weather category experienced by the power transmission line is determined by utilizing wind speed and temperature analysis according to the online monitoring data and the related meteorological data, so that the probability weighting coefficient is determined.
Wherein:is the fault rate of the overhead line; lambda (lambda) 0 (t) calculating by using historical fault data ledgers of the areas where the power transmission lines are located as a reference fault rate function; w is a strong convection weather fault probability weighting coefficient.
Wherein: lambda's' m For the total failure probability of partition m,is the fault rate of the overhead line; j is the element type number; />The number of the ith type of elements in the mth partition; />Is the i-th type element failure rate.
Determining an average fault repair time for each partition based on each line fault history data and the maintenance time in S3, including:
and determining the average fault time of various faults according to the historical data of the faults of each line and the maintenance time, and calculating the fault rate of the overhead line and the average fault repair time of the line of the power transmission line in the area according to the following formula.
Wherein t 'is' m The average fault repair time of the partition m is the partition number;is the fault rate of the overhead line; j is an element type number, wherein the wire number is 1, and the tower number is 2; />The number of the ith type of elements in the mth partition; />Failure rate for the i-th type of element; />Mean fault repair time for the line; />Mean time to fail-over for the i-th type of element.
And S4, determining a toughness evaluation index based on the total fault probability of each partition and the average fault repair time of each partition in combination with the highest voltage level of the power transmission line, wherein the toughness evaluation index specifically comprises the following steps:
according to the method, the load loss of the power transmission line when a disaster occurs is used as a power transmission line toughness evaluation index, and the larger the index is, the larger the load damage of the power transmission line is, and the lower the toughness of the power transmission line is. The calculation formula of the toughness evaluation index is as follows:
wherein L is a toughness evaluation index of the power transmission line in strong convection weather; q (t) is the basic running state of the transmission line; t is t 0 The moment when strong convection occurs; t is t 3 N is the power transmission line partition set at the power transmission line state recovery time; p (P) m Loss of power for a partition load, V m Is the highest voltage level of the overhead transmission line area, t' m For the average failover time of partition m, λ' m The total failure probability of the partition m is given by m, which is the partition number.
And the vulnerable repair indexes are adopted to realize the quantification of the toughness of the power transmission line and the evaluation of the toughness of the power transmission line. In FIG. 2, a conceptual curve of toughness is shown, Q (t) is the basic operating state of the transmission line, t 0 Time t is the moment of strong convection 0 -t 1 In the period, t is that the power transmission line fails to timely cope with 1 -t 2 The period is to cut down load or stop running after the line fails, t 2 Is a circuit repair phase.
And S5, evaluating the toughness of the power transmission line in strong convection weather based on the toughness evaluation index, wherein the method specifically comprises the following steps:
judging whether the toughness evaluation index is larger than a preset initial toughness evaluation index of a set multiple;
if the difference is larger than the preset value, the toughness of the transmission line is poor in strong convection weather, and disaster prevention measures are needed; otherwise, the toughness of the transmission line is stronger in strong convection weather, and disaster prevention measures are not needed;
the initial toughness evaluation index is determined based on the voltage level of the power transmission line, fault history data and maintenance time.
The determination of the initial toughness evaluation index specifically includes:
and calculating an initial toughness evaluation value in the power transmission line partition by using the data such as the power transmission line voltage level, the fault history data information, the fault type, the maintenance time and the like.
The whole process of evaluating the toughness of the power transmission line under strong convection weather by the toughness evaluation index is as follows:
firstly, calculating an initial toughness evaluation value in a power transmission line subarea by using information such as a power transmission line voltage grade, fault history data and the like, a fault type (damage degree caused by a fault is relatively small when no strong convection weather exists), maintenance time and the like.
When strong convection weather comes, the basic information of the strong convection weather is determined according to the meteorological information, the damage and the rush repair difficulty and time caused by the basic information are calculated, the toughness index under the strong convection weather is calculated, when the toughness index under the strong convection reaches the set multiple of the initial toughness evaluation, the set multiple is 1.5 times, and the line is required to carry out corresponding disaster prevention measures such as inspection, maintenance and the like.
In the face of strong convection bad weather such as typhoons and tornadoes, the electric power transmission line is difficult to completely protect through structural design, and the electric power transmission line is required to be maintained in the running process in order to reduce the influence of the strong convection weather on the line. The application provides a method for evaluating the toughness of a power transmission line in strong convection weather, which realizes the toughness evaluation of the power transmission line in strong convection weather, rapidly analyzes a weak area in the power transmission line and provides a basis for taking preventive measures or rapidly recovering the first-aid repair of the line.
According to the method, the influence of different strong convection weather categories on the fault probability of the power transmission line is considered, the influence of the characteristics and the operation time length of the power transmission line on the fault probability is considered by utilizing the fault probability of the power transmission line, the toughness of the power transmission line is measured by utilizing the electric quantity loss according to the voltage grade of the power transmission line and the time required for rush repair, and the accurate evaluation of the power transmission line under all parameters is realized.
Example 2
Taking a certain power transmission line area as an example, the power transmission lines comprise 2 500kV power transmission lines, 4 220kV power transmission lines and 6 110kV power transmission lines, and each line tower has 20 bases.
Step 1, numbering each power transmission line, wherein the 500kV line number is A1, the A2, the 220kV line number is B1-4, the 110kV line is C1-6, and the C519 number represents the 19 th foundation tower of the 110kV No. 5 line. And partitioning the power transmission line according to the geographic position of the line to obtain a certain partition of A101-A105, B104-B110, B411-B415, C307-C311 and C514-C520.
Step 2, building a pole tower fault probability model by utilizing historical standing account data of the power transmission line and utilizing Webull distribution, and combining line operation time to obtain reference fault probabilities of all pole towers, wherein the reference fault probabilities are 8% of A1 line damage probability, the damage probability of the A104 pole tower is 3% due to repair records, and the damage probabilities of B1, B4, C3 and C5 lines are 10%,8%,8% and 9% respectively.
And 3, identifying strong convection weather suffered by the line according to real-time monitoring data and weather forecast to obtain a maximum wind speed which can be achieved when each area suffers certain strong convection weather, determining a fault probability weighting coefficient, and calculating fault probability of each tower and each guide line.
And 4, determining the average fault time of various faults according to the fault historical data and the maintenance time of each line, and calculating the fault rate of the overhead line and the average fault repair time of the line of the power transmission line in the area according to the following formula.
Wherein lambda' m For the total failure probability of partition m,is the fault rate of the overhead line; j is the element type number; />The number of the ith type of elements in the mth partition; />For the failure rate of the ith type of element, t' m The average fault repair time for partition m; />Mean fault repair time for the line; />For the mean time to fail-over for the i-th type of element,
and 5, repeating the step 3 and the step 4, and solving the fault rate of the overhead line and the average fault repair time of the line of each partition power transmission line. Finally, calculating the toughness evaluation index of the power transmission line in the area according to the following formula;
wherein L is toughness evaluation index of power transmission line in strong convection weatherMarking; q (t) is the basic running state of the transmission line; t is t 0 The moment when strong convection occurs; t is t 3 N is the power transmission line partition set at the power transmission line state recovery time; p (P) m Loss of power for a partition load, V m Is the highest voltage level of the overhead transmission line area, t' m For the average failover time of partition m, λ' m Is the total failure probability of partition m.
A method for evaluating toughness of a power transmission line in strong convection weather comprises the following steps:
and establishing a pole tower fault probability model by using the Webull distribution, wherein the pole tower fault probability model can be used for calculating a reference fault rate function. Based on characteristics of the power transmission line body, such as voltage class, power transmission line operation time, environment where the power transmission line is located and the like, a fault probability model of different elements in different areas of different power transmission line areas is established. When the power transmission line is in operation, the probability of failure is given out more accurate analysis and prediction of fragile links aiming at the power transmission line at different positions, so that the early warning capability of disaster risk is improved, and the elements comprise a wire and a pole tower;
the monitoring data and the meteorological forecast are utilized to quickly reflect the types of strong convection weather encountered by the line, and the power transmission line fault probability weighting coefficient is set according to the types of severe weather, so that the damage probability of extreme weather with different degrees to the line is more accurately reflected;
establishing a power transmission line partition set, evaluating the occurrence probability of faults of the power transmission line in each region, and the time and electric quantity loss required by repairing and recovering after the occurrence probability, and giving the total fault probability of the faults of the line in different partition ranges;
judging the occurrence time of extreme weather based on the monitoring data according to the total fault probability of the power transmission line faults, and determining the toughness evaluation index in the power transmission line area by utilizing the whole time scale integration from the occurrence of the extreme weather to the repair period.
Example 3
The application also provides a system for evaluating the toughness of the power transmission line in strong convection weather based on the same inventive concept, which comprises:
the partitioning module is used for partitioning the power transmission line according to the geographic position of the line;
the probability calculation module is used for determining the total fault probability of each partition based on the line running time, a pre-constructed tower fault probability model, real-time monitoring data and forecast data;
the time calculation module is used for determining the average fault repair time of each partition based on the line fault historical data and the maintenance time;
the evaluation index calculation module is used for determining a toughness evaluation index based on the total fault probability of each partition and the average fault repair time of each partition in combination with the highest voltage level of the power transmission line;
and the evaluation module is used for evaluating the toughness of the power transmission line under strong convection weather based on the toughness evaluation index.
Optionally, the probability calculation module is specifically configured to:
obtaining the reference fault probability of each tower based on the line running time and a pre-constructed tower fault probability model;
analyzing the real-time monitoring data and the forecast data, determining a weighted coefficient sum of strong convection weather fault probabilities, and calculating fault probabilities of various elements;
determining an overhead line fault rate based on the reference fault probability and the strong convection weather fault probability weighting coefficient;
determining a total fault probability of each partition based on the fault probabilities of the various types of elements and the overhead line fault rate;
the tower fault probability model is established by utilizing Webull distribution and combining historical standing account data of the power transmission line;
the various types of elements include towers and various grades of wire.
Optionally, the probability calculation module calculates the failure rate of the overhead line by:
wherein:is the fault rate of the overhead line; lambda (lambda) 0 (t) is a reference fault rate function; w is a strong convection weather fault probability weighting coefficient.
Optionally, the probability calculation module calculates the total failure probability of each partition by:
wherein: lambda's' m For the total failure probability of partition m,is the fault rate of the overhead line; j is an element type number, wherein the wire number is 1, and the tower number is 2; />The number of the ith type of elements in the mth partition; />Is the i-th type element failure rate.
Optionally, the time calculation module calculates the average fault repair time of each partition by the following formula:
wherein t 'is' m The average fault repair time of the partition m is the partition number;is the fault rate of the overhead line; j is an element type number, wherein the wire number is 1, and the tower number is 2; />The number of the ith type of elements in the mth partition; />Failure rate for the i-th type of element; />Mean fault repair time for the line; />Mean time to fail-over for the i-th type of element.
Optionally, the evaluation index calculation module calculates the evaluation index by:
wherein L is a toughness evaluation index of the power transmission line in strong convection weather; q (t) is the basic running state of the transmission line; t is t 0 The moment when strong convection occurs; t is t 3 N is the power transmission line partition set at the power transmission line state recovery time; p (P) m Loss of power for a partition load, V m Is the highest voltage level of the overhead transmission line area, t' m For the average failover time of partition m, λ' m Is the total failure probability of partition m.
Optionally, the evaluation module is specifically configured to:
judging whether the toughness evaluation index is larger than a preset initial toughness evaluation index of a set multiple;
if the difference is larger than the preset value, the toughness of the transmission line is poor in strong convection weather, and disaster prevention measures are needed; otherwise, the toughness of the transmission line is stronger in strong convection weather, and disaster prevention measures are not needed;
the initial toughness evaluation index is determined based on the voltage level of the power transmission line, fault history data and maintenance time.
Example 4
Based on the same inventive concept, the application also provides a computer device comprising a processor and a memory for storing a computer program comprising program instructions, the processor for executing the program instructions stored by the computer storage medium. The processor may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processor, digital signal processor (Digital Signal Processor, DSP), application specific integrated circuit (Application SpecificIntegrated Circuit, ASIC), off-the-shelf Programmable gate array (FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc., which are the computational core and control core of the terminal adapted to implement one or more instructions, in particular to load and execute one or more instructions in a computer storage medium to implement the corresponding method flow or corresponding functions, to implement the steps of a method for evaluating toughness of a transmission line in heavy convective weather in the above embodiments.
Example 5:
based on the same inventive concept, the present application also provides a storage medium, in particular, a computer readable storage medium (Memory), which is a Memory device in a computer device, for storing programs and data. It is understood that the computer readable storage medium herein may include both built-in storage media in a computer device and extended storage media supported by the computer device. The computer-readable storage medium provides a storage space storing an operating system of the terminal. Also stored in the memory space are one or more instructions, which may be one or more computer programs (including program code), adapted to be loaded and executed by the processor. The computer readable storage medium herein may be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. One or more instructions stored in a computer-readable storage medium may be loaded and executed by a processor to implement the steps of a method for evaluating toughness of a power transmission line in strong convection weather in the above-described embodiments.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing is illustrative of the present application and is not to be construed as limiting thereof, but rather as providing for the use of additional embodiments and advantages of all such modifications, equivalents, improvements and similar to the present application are intended to be included within the scope of the present application as defined by the appended claims.
Claims (12)
1. The method for evaluating the toughness of the power transmission line in strong convection weather is characterized by comprising the following steps of:
partitioning the power transmission line according to the geographic position of the line;
determining the total fault probability of each partition based on the line running time, a pre-constructed tower fault probability model, real-time monitoring data and forecast data;
determining the average fault repair time of each partition based on the line fault history data and the maintenance time;
determining a toughness evaluation index based on the total fault probability of each partition and the average fault repair time of each partition in combination with the highest voltage level of the power transmission line;
and evaluating the toughness of the power transmission line under strong convection weather based on the toughness evaluation index.
2. The method of claim 1, wherein determining the total failure probability for each partition based on line run time, pre-constructed tower failure probability model, real-time monitoring data, and forecast data comprises:
obtaining the reference fault probability of each tower based on the line running time and a pre-constructed tower fault probability model;
analyzing the real-time monitoring data and the forecast data, determining a weighted coefficient sum of strong convection weather fault probabilities, and calculating fault probabilities of various elements;
determining an overhead line fault rate based on the reference fault probability and the strong convection weather fault probability weighting coefficient;
determining a total fault probability of each partition based on the fault probabilities of the various types of elements and the overhead line fault rate;
the tower fault probability model is established by utilizing Webull distribution and combining historical standing account data of the power transmission line;
the various types of elements include towers and various grades of wire.
3. The method of claim 2, wherein the overhead line fault rate is calculated as:
wherein:is the fault rate of the overhead line; lambda (lambda) 0 (t) is a reference fault rate function; w is a strong convection weather fault probability weighting coefficient.
4. The method of claim 2, wherein the total failure probability of each partition is calculated as:
wherein: lambda's' m For the total failure probability of partition m,is the fault rate of the overhead line; j is an element type number, wherein the wire number is 1, and the tower number is 2; />The number of the ith type of elements in the mth partition; />Is the i-th type element failure rate.
5. The method of claim 1, further comprising, prior to partitioning the transmission line based on the geographic location of the line: and numbering each power transmission line.
6. The method of claim 1, wherein the average failover time for each partition is calculated by:
wherein t 'is' m The average fault repair time of the partition m is the partition number;is the fault rate of the overhead line; j is the element type number; />The number of the ith type of elements in the mth partition; />Failure rate for the i-th type of element; />Mean fault repair time for the line; />Mean time to fail-over for the i-th type of element.
7. The method of claim 1, wherein the toughness assessment index is calculated as:
wherein L is a toughness evaluation index of the power transmission line in strong convection weather; q (t) is the basic running state of the transmission line; t is t 0 The moment when strong convection occurs; t is t 3 N is the power transmission line partition set at the power transmission line state recovery time; p (P) m Loss of power for a partition load, V m Is the highest voltage level of the overhead transmission line area, t' m For the average failover time of partition m, λ' m Is the total failure probability of partition m.
8. The method of claim 1, wherein the evaluating the toughness of the power transmission line in strong convection weather based on the toughness evaluation index comprises:
judging whether the toughness evaluation index is larger than a preset initial toughness evaluation index of a set multiple;
if the difference is larger than the preset value, the toughness of the transmission line is poor in strong convection weather, and disaster prevention measures are needed; otherwise, the toughness of the transmission line is stronger in strong convection weather, and disaster prevention measures are not needed;
the initial toughness evaluation index is determined based on the voltage level of the power transmission line, fault history data and maintenance time.
9. A system for evaluating toughness of a power transmission line in strong convection weather, comprising:
the partitioning module is used for partitioning the power transmission line according to the geographic position of the line;
the probability calculation module is used for determining the total fault probability of each partition based on the line running time, a pre-constructed tower fault probability model, real-time monitoring data and forecast data;
the time calculation module is used for determining the average fault repair time of each partition based on the line fault historical data and the maintenance time;
the evaluation index calculation module is used for determining a toughness evaluation index based on the total fault probability of each partition and the average fault repair time of each partition in combination with the highest voltage level of the power transmission line;
and the evaluation module is used for evaluating the toughness of the power transmission line under strong convection weather based on the toughness evaluation index.
10. The system of claim 9, wherein the probability calculation module is specifically configured to:
obtaining the reference fault probability of each tower based on the line running time and a pre-constructed tower fault probability model;
analyzing the real-time monitoring data and the forecast data, determining a weighted coefficient sum of strong convection weather fault probabilities, and calculating fault probabilities of various elements;
determining an overhead line fault rate based on the reference fault probability and the strong convection weather fault probability weighting coefficient;
determining a total fault probability of each partition based on the fault probabilities of the various types of elements and the overhead line fault rate;
the tower fault probability model is established by utilizing Webull distribution and combining historical standing account data of the power transmission line;
the various types of elements include towers and various grades of wire.
11. A computer device, comprising: one or more processors;
the processor is used for storing one or more programs;
a method of evaluating transmission line toughness under strong convection weather according to any one of claims 1 to 8, when the one or more programs are executed by the one or more processors.
12. A computer readable storage medium, characterized in that it has stored thereon a computer program which, when executed, implements a method for evaluating the toughness of a transmission line in strong convection weather according to any one of claims 1 to 8.
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