CN111864731B - Method and device for screening reliability improvement measures of power distribution network and storage medium - Google Patents
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Abstract
The invention relates to the technical field of power distribution networks, and discloses a method, a device and a storage medium for screening reliability improving measures of a power distribution network, wherein the method comprises the following steps: acquiring a plurality of reliability improving measures of the power distribution network; classifying the reliability improvement measures according to the reliability improvement dimension of the power distribution network; calculating a reliability parameter of the reliability improvement measure under each category; the reliability parameter is used for indicating the influence degree of the reliability improving measures on the cost of the power distribution network; selecting reliability improving measures according to the reliability parameters; and applying the selected reliability improvement measures to the power distribution network. The method and the device improve the accuracy of screening the reliability improvement measures of the power distribution network and realize the optimization of the large-scale reliability improvement measures.
Description
Technical Field
The invention relates to the technical field of power distribution networks, in particular to a method and a device for screening reliability improving measures of a power distribution network and a storage medium.
Background
At present, a plurality of methods are adopted to optimize the reliability improvement measures of the power distribution network; among them, there are mainly a method of optimizing modeling and a method of evaluating a scheme. When the method based on the optimization modeling is used for optimizing the reliability improving measures of the power distribution network, due to the fact that the large-scale power distribution network has various types and quantities of the reliability improving measures and involves a large number of basic parameters and operation parameters, the problem scale and the decision variable number are large, the solution is easy to fall into local optimization, even convergence cannot be achieved, and the screening accuracy is low. When the method based on scheme evaluation is used for optimizing the reliability improvement measures of the power distribution network, possible power grid improvement schemes need to be listed firstly, and the technical economy comparison is carried out on alternative schemes by constructing an index system or an optimization model, so that the method is widely applied in engineering practice; however, the existing method based on scheme evaluation has low modeling precision and low screening accuracy.
Disclosure of Invention
The invention aims to provide a method and a device for screening reliability improving measures of a power distribution network and a storage medium, which can improve the accuracy of screening the reliability improving measures of the power distribution network and realize the optimization of large-scale reliability improving measures.
In order to solve the technical problem, the invention provides a screening method of measures for improving the reliability of a power distribution network, which comprises the following steps:
acquiring a plurality of reliability improving measures of the power distribution network;
classifying the reliability improvement measures according to the reliability improvement dimensionality of the power distribution network;
calculating a reliability parameter of the reliability improvement measure under each category; the reliability parameter is used for indicating the influence degree of reliability improvement measures on the cost of the power distribution network;
selecting the reliability improving measures according to the reliability parameters;
and applying the selected reliability improvement measures to the power distribution network.
Preferably, the reliability improvement dimensionality of the power distribution network comprises three dimensionalities of frequency of equipment outage occurrence of the power distribution network, time length of each outage of the equipment of the power distribution network and user range of each outage influence of the equipment of the power distribution network; then the process of the first step is carried out,
the calculating the reliability parameter of the reliability improvement measure in each category specifically includes:
calculating the equivalent fault rate of the power distribution network blocks under the dimension of the frequency of the power distribution network equipment outage, and using the equivalent fault rate as a reliability parameter of a corresponding reliability improvement measure under the category;
calculating equivalent average repair time of the distribution network blocks under the dimension of the time length of each outage of the equipment of the distribution network, and taking the equivalent average repair time as a reliability parameter of a corresponding reliability improvement measure under the category;
and acquiring the outage time of the power distribution network blocks under the dimension of the user range influenced by each outage of the equipment of the power distribution network, and using the outage time as a reliability parameter of a corresponding reliability improvement measure under the category.
As a preferred scheme, the calculating an equivalent fault rate of a power distribution network block in a dimension of a frequency of occurrence of equipment outage of the power distribution network, as a reliability parameter of a corresponding reliability improvement measure in the category, specifically includes:
calculating a failure rate for each type of equipment within the distribution grid segment in a dimension of a frequency of occurrence of equipment outages of the distribution grid by:
wherein λ isα,cIs the failure rate of the c-th element under the failure type α; lambda [ alpha ]α,iThe fault rate of the ith power failure responsibility reason under the fault type alpha is shown; i represents a power failure responsibility reason set;
according to the fault rate of each type of equipment in the distribution network block, calculating the equivalent fault rate of the distribution network block by the following formula:
wherein λ isα,sThe equivalent fault rate of the power distribution network blocks is the fault rate under the fault type alpha; lambda [ alpha ]α,cIs the failure rate of the c-th element under the failure type α; n is an element set contained in the power distribution network block;
and taking the calculated equivalent fault rate of the power distribution network blocks as the reliability parameters of the corresponding reliability improvement measures in the category.
As a preferred scheme, the calculating, in the dimension of the length of each outage of the equipment of the power distribution network, the repair time of the power distribution network blocks as the reliability parameter of the corresponding reliability improvement measure in the category specifically includes:
calculating the fault rate of each type of equipment in the distribution network block by the following formula under the dimension of the time length of each outage of the equipment of the distribution network:
wherein λ isα,cIs the failure rate of the c-th element under the failure type α; lambda [ alpha ]α,iThe fault rate of the ith power failure responsibility reason under the fault type alpha is shown; i represents a power failure responsibility reason set;
calculating the total time for fault recovery of the equipment of the power distribution network under each power failure responsibility reason through the following formula:
Tα,γ,i＝Tα,1+Tα,2+Tα,3+max(max(Tα,4,Tα,5,Tα,5')+Tα,6,Tα,7)+Tα,8+Tα,9
wherein, Tα,γ,iThe total time for repairing the fault of the ith power failure responsibility reason under the fault type alpha; t isα,1The fault report duration under the fault type alpha; t isα,2The time length of emergency repair in place under the fault type alpha is shown; t isα,3Locating an operation duration for a fault under the fault type alpha; t isα,4The fault isolation operation duration under the fault type alpha is set; t isα,5The time for the first-aid repair team to reach the position under the fault type alpha is long; t isα,5'The time for the work ticket to be handled under the fault type alpha; t isα,6The dismantling duration of the fault equipment under the fault type alpha is determined; t isα,7The length of time for distributing the first-aid repair materials in place under the fault type alpha is long; t isα,8Repairing time for fault equipment under the fault type alpha; t isα,9Recovering the power supply operation time for all users under the fault type alpha;
according to the total fault repair time and the corresponding fault rate of the equipment of the power distribution network under each power failure responsibility reason, the repair time of each type of equipment is calculated through the following formula:
wherein, γα,cIs the repair time of the c-th element under the fault type alpha; t isα,γ,iThe total time for repairing the fault of the ith power failure responsibility reason under the fault type alpha; lambda [ alpha ]α,iThe fault rate of the ith power failure responsibility reason under the fault type alpha is shown;
according to the fault rate and the corresponding repair time of each type of equipment in the distribution network block, calculating the equivalent average repair time of the distribution network block by the following formula:
wherein, γα,sThe equivalent average repair time of the power distribution network blocks under the fault type alpha is shown; lambda [ alpha ]α,cIs the failure rate of the c-th element under the failure type α; gamma rayα,cIs the repair time of the c-th element under the fault type alpha; n is an element set contained in the power distribution network block;
and taking the calculated equivalent average repair time of the power distribution network blocks as a reliability parameter of the reliability improvement measure in the category.
As a preferred scheme, the obtaining of the outage time of the power distribution network blocks in the dimension of the user range affected by each outage of the equipment of the power distribution network, as the reliability parameter of the reliability improvement measure in the category, specifically includes:
dividing the distribution network into a plurality of areas based on switching devices in the distribution network under the dimension of user range affected by each outage of the devices of the distribution network;
and acquiring the outage time of the load node after each area fails to work as a reliability parameter of the reliability improving measure in the category.
In order to solve the same technical problem, an embodiment of the present invention further provides a screening apparatus for reliability improvement measures of a power distribution network, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, where the processor implements the above-mentioned screening method for reliability improvement measures of a power distribution network when executing the computer program.
In order to solve the same technical problem, an embodiment of the present invention further provides a computer-readable storage medium, where a program is stored on the storage medium, and when the program runs, the method for screening the reliability improvement measures for the power distribution network is implemented.
Compared with the prior art, the invention provides a method, a device and a storage medium for screening reliability improving measures of a power distribution network.
Drawings
Fig. 1 is a schematic flow chart of a method for screening reliability enhancement measures for a power distribution network according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an initial distribution network load node down time category provided by an embodiment of the present invention;
FIG. 3 is a schematic diagram of the class of outage times of the load nodes of the distribution network after adding the tie-switch according to the embodiment of the present invention;
FIG. 4 is a schematic diagram of the class of outage times of load nodes of the power distribution network after section switches are added according to the embodiment of the invention;
fig. 5 is a schematic diagram of a class of outage times of load nodes of a power distribution network after automatic construction of the power distribution network according to an embodiment of the present invention;
FIG. 6 is a flow chart illustrating device failure event statistics provided by an embodiment of the present invention;
fig. 7 is a schematic flowchart of device repair time statistics provided in an embodiment of the present invention;
FIG. 8 is a schematic flow chart illustrating secondary optimization of reliability enhancement measures provided by an embodiment of the present invention;
fig. 9 is a schematic structural diagram of a screening device for measures for improving reliability of a power distribution network according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flow chart of a method for screening measures for improving reliability of a power distribution network according to an embodiment of the present invention.
In the embodiment of the invention, the method for screening the reliability improvement measures of the power distribution network comprises the following steps of S11-S15:
s11, acquiring a plurality of reliability improving measures of the power distribution network;
it is understood that the reliability improvement measure is a measure determined based on the distribution network for improving the reliability of the distribution network.
S12, classifying the reliability improvement measures according to the reliability improvement dimensionality of the power distribution network;
specifically, a reliability improvement dimension for determining the reliability level of the power distribution network is determined, and all the reliability improvement measures are divided under the corresponding reliability improvement dimension.
S13, calculating the reliability parameters of the reliability improving measures in each category; the reliability parameter is used for indicating the influence degree of reliability improvement measures on the cost of the power distribution network;
s14, selecting the reliability improving measures according to the reliability parameters;
and S15, applying the selected reliability improvement measures to the power distribution network.
In the embodiment of the invention, the reliability improvement measures are classified through the reliability improvement dimension of the power distribution network, the reliability parameters of the reliability improvement measures in each class are calculated, and then the reliability improvement measures are selected according to the reliability parameters, so that the screening accuracy of the reliability improvement measures of the power distribution network is improved, and the optimization of the large-scale reliability improvement measures is realized. Moreover, the embodiment of the invention realizes cost-benefit optimization under the reliability target.
In a preferred embodiment, the reliability improvement dimension of the power distribution network includes three dimensions of frequency of occurrence of equipment outage of the power distribution network, duration of each outage of equipment of the power distribution network, and user range of influence of each outage of equipment of the power distribution network.
It can be understood that the reliability level of the power distribution network is comprehensively determined by three dimensions of frequency of occurrence of equipment outage, duration of each outage and user range of influence of each outage. Therefore, all reliability improvement measures can be quantitatively analyzed by dividing into "preventing the occurrence of equipment outage" (reducing outage frequency) and "alleviating the influence of equipment outage on the power outage of a user" (reducing outage duration and influencing the power outage range of the user).
Preferably, in the three dimensions, all the reliability improvement measures can be further combed, and the various reliability improvement measures are classified into a capital class and a management class, wherein the capital class measures are realized mainly by increasing investment, and the management class measures are realized mainly by enhancing enterprise management, as shown in table 1.
TABLE 1 all reliability enhancement measures
In order to implement further refinement modeling, an incidence relation between a lifting measure and a topological structure and a reliability parameter needs to be established. Therefore, various measures in three dimensions are firstly classified, and then quantitative analysis is carried out on the influence mechanisms of different measure classes.
Specifically, in a preferred embodiment, in step S13, the calculating the reliability parameter of the reliability improvement measure in each category specifically includes the following steps S131 to S133:
s131, calculating the equivalent fault rate of the power distribution network blocks under the dimensionality of the frequency of the power distribution network equipment outage, and using the equivalent fault rate as a reliability parameter of a corresponding reliability improvement measure under the category;
s132, calculating equivalent average repair time of the power distribution network blocks under the dimension of the time length of each outage of the equipment of the power distribution network, and taking the equivalent average repair time as a reliability parameter of a corresponding reliability improvement measure under the category;
s133, under the dimension of the user range influenced by each outage of the equipment of the power distribution network, acquiring the outage time of the power distribution network blocks as reliability parameters of corresponding reliability improvement measures in the category.
It should be noted that, in the embodiment of the present invention, the execution sequence of steps S131 to S133 is not limited, for example, step S133 may be executed first, step S132 is executed, and step S131 is executed finally, or steps S131 to S133 may also be executed at the same time, which is not described herein again.
Further, in step S131, calculating an equivalent failure rate of the power distribution network blocks in the dimension of the frequency of occurrence of the equipment outage of the power distribution network, as a reliability parameter of a corresponding reliability improvement measure in the category, specifically including steps S1311 to S1313:
s1311, calculating the fault rate of each type of equipment in the distribution network block through the following formula under the dimension of the frequency of the equipment outage of the distribution network:
wherein λ isα,cIs the failure rate of the c-th element under the failure type α; lambda [ alpha ]α,iThe fault rate of the ith power failure responsibility reason under the fault type alpha is shown; i represents a power failure responsibility reason set;
s1312, according to the fault rate of each type of equipment in the distribution network block, calculating the equivalent fault rate of the distribution network block by the following formula:
wherein λ isα,sTo be at faultUnder the type alpha, the equivalent fault rate of the power distribution network blocks; lambda [ alpha ]α,cIs the failure rate of the c-th element under the failure type α; n is an element set contained in the power distribution network block;
s1313, taking the calculated equivalent fault rate of the power distribution network blocks as reliability parameters of corresponding reliability improvement measures in the category.
It should be noted that, the reliability improvement measure is improved for the reason of power failure responsibility, so that the failure rate of each device is affected, the failure rate of each block in the evaluation is further affected, and finally the reliability index of the system is affected.
Further, in step S132, the step of calculating the repair time of the power distribution network blocks in the dimension of the length of each outage of the equipment of the power distribution network as the reliability parameter of the corresponding reliability improvement measure in the category specifically includes steps S1321 to S1325:
s1321, calculating the fault rate of each type of equipment in the distribution network block by the following formula under the dimension of the time length of each outage of the equipment of the distribution network:
wherein λ isα,cIs the failure rate of the c-th element under the failure type α; lambda [ alpha ]α,iThe fault rate of the ith power failure responsibility reason under the fault type alpha is shown; i represents a power failure responsibility reason set;
s1322, calculating the total fault repair time of the equipment of the power distribution network under each power failure responsibility reason through the following formula:
Tα,γ,i＝Tα,1+Tα,2+Tα,3+max(max(Tα,4,Tα,5,Tα,5')+Tα,6,Tα,7)+Tα,8+Tα,9 (4)
wherein, Tα,γ,iThe total time for repairing the fault of the ith power failure responsibility reason under the fault type alpha; t isα,1The fault report duration under the fault type alpha; t isα,2The time length of emergency repair in place under the fault type alpha is shown; t isα,3Locating an operation duration for a fault under the fault type alpha; t isα,4The fault isolation operation duration under the fault type alpha is set; t isα,5The time for the first-aid repair team to reach the position under the fault type alpha is long; t isα,5'The time for the work ticket to be handled under the fault type alpha; t isα,6The dismantling duration of the fault equipment under the fault type alpha is determined; t isα,7The length of time for distributing the first-aid repair materials in place under the fault type alpha is long; t isα,8Repairing time for fault equipment under the fault type alpha; t isα,9Recovering the power supply operation time for all users under the fault type alpha;
s1323, according to the total fault repair time and the corresponding fault rate of the equipment of the power distribution network under each power failure responsibility reason, calculating the repair time of each type of equipment through the following formula:
wherein, γα,cIs the repair time of the c-th element under the fault type alpha; t isα,γ,iThe total time for repairing the fault of the ith power failure responsibility reason under the fault type alpha; lambda [ alpha ]α,iThe fault rate of the ith power failure responsibility reason under the fault type alpha is shown;
s1324, calculating the equivalent average repair time of the power distribution network block according to the fault rate and the corresponding repair time of each type of equipment in the power distribution network block by the following formula:
wherein, γα,sThe equivalent average repair time of the power distribution network blocks under the fault type alpha is shown; lambda [ alpha ]α,cIs the failure rate of the c-th element under the failure type α; gamma rayα,cFor repairing the c-th element under the fault type alphaA (c) is added; n is an element set contained in the power distribution network block;
s1325, the calculated equivalent average repair time of the power distribution network blocks is used as a reliability parameter of corresponding reliability improvement measures in the category.
It should be noted that, the reliability improvement measure improves each time period of the actual fault repair work flow, so that the power failure time and the upstream and downstream power restoration time of each equipment fault are affected, the power failure time of each block in the evaluation is further affected, and finally the reliability index of the system is affected.
Further, in step S133, the step of obtaining the outage time of the power distribution network blocks in the dimension of the user range affected by each outage of the equipment of the power distribution network as the reliability parameter of the corresponding reliability improvement measure in the category specifically includes steps S1331 to S1332:
s1331, under the dimension of a user range affected by equipment outage of the power distribution network, dividing the power distribution network into a plurality of areas based on switch equipment in the power distribution network;
and S1332, acquiring the outage time of the load node after the fault occurs in each area, and using the outage time as a reliability parameter of a corresponding reliability improvement measure in the category.
Specifically, in the power distribution network, the network may be divided into several areas with switchgear (including circuit breakers, sectionalizers, disconnectors, fuses, etc.) as boundaries, and branches (including circuit breakers, transformers, etc.) included in each area are grouped into one block. According to the different off-time of the load nodes, the fault block load can be classified into A, B, C, D four types, as shown in fig. 2. The specific load node outage time categories are shown in table 2.
TABLE 2 load node downtime classifications
The reliability improvement measures are improved according to the number of the topological blocks of the power distribution network and the types of the blocks, so that the power failure time of each block in the evaluation is influenced, and finally the reliability index of the system is influenced. Typical measures to improve outage impact user range are analyzed as follows:
(1) improve rack liaison and to changeing power supply support
This measure changes the partition type. When a fault occurs, due to the fact that the interconnection switch is arranged at the downstream of the fault, the D-type load at the downstream of the fault point can be changed into the C-type load, and the fault power failure range after the fault is manually isolated is reduced. After the tie switch is newly installed and the fault is isolated downstream of the fault point, the class D load of the existing tie switch is changed to a class C load, as shown in fig. 3.
(2) Improving the supporting capability of line subsection contra-rotating power supply
This measure increases the number of partitions and reduces the amount of load of the partitions. After the fault occurs, because the number of the blocks is increased, the load capacity of the blocks is reduced, more blocks of users can recover power supply at the upstream of the fault point, more blocks (loads) can be transferred at the downstream of the fault point, and the power failure range is reduced. After adding the section switch, a part of the load points of the class D are changed into the class B and the class C with less power failure time, as shown in FIG. 4.
(3) Distribution network automation construction
This measure changes the partition type. When a fault occurs, because the automatic switches are installed on the upstream and the downstream of the fault, the B-type load on the upstream of the fault point and the C-type load on the downstream of the fault point are changed into the A-type load, and the fault power failure range before the manual fault isolation is obviously reduced. After the switch has the specific automation function, the switch performs automatic positioning, isolation, upstream power restoration and downstream power conversion operation, and except for the fault area, other load node types are changed into a type a loads, as shown in fig. 5.
In a preferred embodiment, before implementing step S11, the method further comprises:
and acquiring a fault event of the power distribution network, and finely evaluating the reliability of the power distribution network based on the fault event.
Specifically, the method mainly aims at the power failure of distribution network users/load points caused by the failure outage of distribution network equipment, and extracts detailed reliability parameters from multi-source data to perform accurate fault modeling:
(1) equipment failure time statistics flow: firstly, reading a fault event of the power distribution network from a fault first-aid repair work order, and obtaining a fault equipment name, an equipment ID, a power failure responsibility reason and a power failure type; secondly, according to the equipment ID, inquiring regional characteristics such as a district and a county to which the equipment belongs, a transformer substation to which the equipment belongs, a feeder line to which the equipment belongs and the like, and characteristics such as equipment type, a manufacturer and an equipment model; finally, according to the statistical rule of the equipment failure rate, the failure event is classified according to the power failure responsibility reason, and then secondary subdivision statistics is performed according to the characteristics of the equipment power failure type, the equipment category, the area type, the equipment brand and the like, as shown in fig. 6.
(2) Equipment repair time statistics flow: firstly, reading a fault event of the power distribution network from a fault first-aid repair work order, and obtaining a fault equipment name, an equipment ID, a power failure responsibility reason and a power failure type; secondly, according to the equipment ID, inquiring regional characteristics such as a district and a county to which the equipment belongs, a transformer substation to which the equipment belongs, a feeder line to which the equipment belongs and the like, and characteristics such as equipment type, a manufacturer and an equipment model; finally, classifying and counting each time period of the fault event according to the statistical rule of the equipment repair time and the characteristics of power failure responsibility reasons, equipment power failure types, equipment types, area types, equipment brands and the like; and updates the statistical number of the fault events of the time period under the characteristic, and calculates the average value of the time period under the characteristic, as shown in fig. 7.
And after the operation is finished, evaluating by adopting a complex power distribution network reliability evaluation blocking algorithm. Specifically, fault enumeration is carried out by taking a block as a unit, and node and system reliability indexes are quickly formed.
In a preferred embodiment, in order to improve the refinement optimization efficiency of the reliability improvement measure and consider the resource limitation, the reliability improvement measure is preliminarily screened according to the priority of the improvement measure, and after the step S12 is implemented, the method further includes S12 '-S13':
s12', calculating the grade score of the reliability improvement measure under each dimensionality through the following formula;
grade (P + C) × F (7)
Wherein P is an improvement potential value and is used for evaluating the residual improvement potential of the power enterprise aiming at the measure, the assigning range is 1-5 points, and the greater the improvement potential is, the higher the assigning is; c is a cost grade value used for representing the investment cost required by the electric power enterprise to take the measure, the assigning range is 1-5 points, and the smaller the investment cost is, the higher the assigning is; f is an implementation work effective value and is used for expressing the degree of improvement of the reliability index after the expert primarily evaluates measures taken by the power enterprise, the score range is 1-3, and the higher the improvement degree is, the higher the score is;
s13', according to the grade scores, the reliability improving measures under each dimensionality are screened for the first time.
Specifically, in step S13', in each dimension, the reliability improvement measure whose level score is greater than the preset level score threshold is selected, so as to implement primary screening of the reliability improvement measure in each dimension.
It should be noted that the "hierarchical logic" design of equation (7) responds most strongly to "implementation efficiency" because the ability to successfully "select" based on reliability cost-effectiveness is clearly the most important in optimizing expenses based on reliability cost-effectiveness. The "improvement potential rating" and "expense rating" represent the improvement potential and cost expense of a project, so that changes to the system and the initiation of new projects can be preliminarily assessed.
After the reliability improvement measures in each dimension are primarily screened, only the reliability parameters of the primarily screened reliability improvement measures can be calculated, so that the data volume of the subsequently selected reliability improvement measures is effectively reduced, and the detailed description is omitted.
Further, in a preferred embodiment, in step S14, the selecting the reliability improving measure according to the reliability parameter includes:
and selecting a reliability improvement measure that the reliability parameter accords with a preset condition.
It should be noted that the preset condition may be set according to an actual use condition, for example, a preset reliability parameter range is met.
In another preferred embodiment, the reliability improvement measure through primary screening can be used as a carrier to perform secondary optimization, and cross-domain optimization is performed on various types of improvement measure items:
specifically, the method may further include:
after calculating the reliability parameters of the reliability improving measures in each category, calculating the cost increment of the reliability improving measures according to the reliability parameters of the reliability improving measures;
calculating marginal benefit of the reliability improvement measure according to the cost increment;
sequencing all the reliability improving measures of the power distribution network according to the marginal benefit;
and selecting a reliability improving measure which meets a preset marginal benefit condition.
Specifically, the secondary optimization takes the lifting strategy passing through the primary screening as a carrier, and carries out cross-domain optimization on various lifting measure items:
(1) delicately modeling measure boundary condition delineation
The embodiment of the invention takes the feeder line as a basic unit and takes the actual habit of production business of an application unit as a basis, and develops a modeling analysis process from capital investment to influence reliability index. Firstly, determining improved objects of different lifting measures, and proposing a specific improvement principle, an improvement step length and an implementation upper limit thereof; secondly, measuring and calculating corresponding costs under different step lengths; then, exhausting the concrete scheme under each step within the limit of the measure by taking a feeder line as a unit; thirdly, substituting each specific scheme of the lifting strategy into the algorithm to determine respective marginal benefit; and finally, sequencing all the hoisting strategies and the specific schemes of all the feeders according to marginal benefits. Namely, the boundary condition determination of the feeder line lifting strategy is completed, the secondary optimization of the supporting lifting measures is carried out, and the process is detailed in an example analysis part.
(2) Mechanism analysis of reliability parameter influence by reliability improvement measures
The analysis of the influence mechanism of the reliability parameter is realized through step S13, and the present invention is not described herein again.
(3) Secondary optimization of reliability enhancement measures
The secondary optimization of the reliability improving measures of the power distribution network mainly adopts marginal benefit increment/cost increment (iB/iC) analysis, maximizes the benefit of reliability of paid expenses for purchasing by selecting measures with high return rate, and finally sorts and optimizes all the reliability improving measures of the power distribution network according to the marginal benefit descending order.
It should be noted that, in the process of performing optimized ordering on the reliability improvement measures by using the iB/iC principle, there may be a mutual exclusion relationship between the reliability improvement measures, that is, when the reliability improvement measure a is implemented, the reliability improvement measure B cannot be implemented. For example, when a power utility wishes to achieve as high a reliability as possible within certain budget limits, first, various reliability enhancement measures are listed, but these measures may include adding 1 section switch (a1) and 2 section switches (a 2). When the marginal benefit of a1 is higher than a2, the ranking of the lifting measures is a1, B, C, A2, D, E. When the budget funds are abundant, the implementation measures A1, B, C, A2 and D are selected. However, it should be noted that the optimal configuration of 2 section switches is not to continue the optimal configuration of one section switch on the basis of the optimal configuration of another section switch, and according to the optimization theory, the positions of the section switches configured in a2 and a1 may be completely different. Therefore, when the reliability improvement measure a2 is selected, the reliability improvement measure a1 is abandoned, and finally, the reliability improvement measures are B, C, A2 and D, E. The flow of the above-described reliability enhancement measure cost optimization method is shown in fig. 8.
In the embodiment of the invention, on the basis of the reliability refined evaluation result, the experience level logic function is used for primarily screening the reliability improvement measures of the large-scale power distribution network, and then the reliability improvement measures are further sorted and screened based on the reliability marginal benefit, so that the cost benefit optimization under the specified capital investment or reliability target is realized. In addition, the embodiment of the invention implements granularity by taking the feeder line as a measure, realizes cross-domain optimization among different lifting strategies of time, frequency and range, improves the scientific and reasonable degree of medium-voltage distribution network modification measure decision, and can provide specific reference for power supply enterprises to improve and modify the reliability of the distribution network.
Referring to fig. 9, another embodiment of the present invention correspondingly provides a schematic structural diagram of a screening apparatus for reliability improvement measures of a power distribution network.
The screening device 100 for reliability improvement measures of a power distribution network provided by the embodiment of the present invention includes a processor 101, a memory 102, and a computer program stored in the memory 102 and configured to be executed by the processor 101, and when the processor executes the computer program, the processor implements the above-mentioned screening method for reliability improvement measures of a power distribution network.
In the embodiment of the present invention, the screening device 100 for reliability enhancement measures for a power distribution network is used to classify the reliability enhancement measures according to the reliability enhancement dimensions of the power distribution network, calculate the reliability parameters of the reliability enhancement measures in each category, and select the reliability enhancement measures according to the reliability parameters, so as to improve the accuracy of screening the reliability enhancement measures for the power distribution network and realize the optimization of large-scale reliability enhancement measures. Moreover, the embodiment of the invention realizes cost-benefit optimization under the reliability target.
Illustratively, the computer program may be partitioned into one or more modules/units that are stored in the memory 102 and executed by the processor 101 to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program in the screening apparatus 100 for reliability improvement measures of the power distribution network.
The Processor 101 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 102 may be used to store the computer programs and/or modules, and the processor 101 implements various functions of the screening apparatus 100 for reliability improvement measures of the power distribution network by running or executing the computer programs and/or modules stored in the memory 102 and calling the data stored in the memory 102. The memory 102 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
The module/unit integrated with the screening apparatus 100 for reliability improvement measures of the power distribution network may be stored in a computer-readable storage medium if it is implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
It should be noted that the above-described device embodiments are merely illustrative, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. In addition, in the drawings of the embodiment of the apparatus provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, and may be specifically implemented as one or more communication buses or signal lines. One of ordinary skill in the art can understand and implement it without inventive effort.
In summary, the present invention provides a method, an apparatus, and a storage medium for screening reliability enhancement measures for a power distribution network, wherein the reliability enhancement measures are classified according to reliability enhancement dimensions of the power distribution network, reliability parameters of the reliability enhancement measures in each class are calculated, and then the reliability enhancement measures are selected according to the reliability parameters, so that accuracy of screening the reliability enhancement measures for the power distribution network is improved, and optimization of large-scale reliability enhancement measures is achieved. Moreover, the embodiment of the invention realizes cost-benefit optimization under the reliability target.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and substitutions can be made without departing from the technical principle of the present invention, and these modifications and substitutions should also be regarded as the protection scope of the present invention.
Claims (5)
1. A method for screening reliability improvement measures of a power distribution network is characterized by comprising the following steps:
acquiring a plurality of reliability improving measures of the power distribution network;
classifying the reliability improvement measures according to the reliability improvement dimensionality of the power distribution network;
calculating a reliability parameter of the reliability improvement measure under each category; the reliability parameter is used for indicating the influence degree of reliability improvement measures on the cost of the power distribution network;
selecting the reliability improving measures according to the reliability parameters;
applying the selected reliability improvement measure to the power distribution network;
the reliability improvement dimensionality of the power distribution network comprises three dimensionalities of frequency of equipment outage occurrence of the power distribution network, time length of each outage of the equipment of the power distribution network and user range of each outage influence of the equipment of the power distribution network; then the process of the first step is carried out,
the calculating the reliability parameter of the reliability improvement measure in each category specifically includes:
calculating the equivalent fault rate of the power distribution network blocks under the dimension of the frequency of the power distribution network equipment outage, and using the equivalent fault rate as a reliability parameter of a corresponding reliability improvement measure under the category;
calculating equivalent average repair time of the distribution network blocks under the dimension of the time length of each outage of the equipment of the distribution network, and taking the equivalent average repair time as a reliability parameter of a corresponding reliability improvement measure under the category;
acquiring the outage time of the power distribution network blocks under the dimension of the user range influenced by each outage of the equipment of the power distribution network, and using the outage time as a reliability parameter of a corresponding reliability improvement measure in the category;
the method comprises the following steps of calculating the equivalent fault rate of the power distribution network blocks under the dimensionality of the frequency of the power distribution network during equipment outage, and taking the equivalent fault rate as a reliability parameter of a corresponding reliability improvement measure under the category, wherein the method specifically comprises the following steps:
calculating a failure rate for each type of equipment within the distribution grid segment in a dimension of a frequency of occurrence of equipment outages of the distribution grid by:
wherein λ isα,cIs the failure rate of the c-th element under the failure type α; lambda [ alpha ]α,iThe fault rate of the ith power failure responsibility reason under the fault type alpha is shown; i represents a power failure responsibility reason set;
according to the fault rate of each type of equipment in the distribution network block, calculating the equivalent fault rate of the distribution network block by the following formula:
wherein λ isα,sThe equivalent fault rate of the power distribution network blocks is the fault rate under the fault type alpha; lambda [ alpha ]α,cIs the failure rate of the c-th element under the failure type α; n is an element set contained in the power distribution network block;
and taking the calculated equivalent fault rate of the power distribution network blocks as the reliability parameters of the corresponding reliability improvement measures in the category.
2. The method for screening reliability enhancement measures for a power distribution network according to claim 1, wherein the step of calculating the repair time of the power distribution network blocks in the dimension of the time length of each outage of the equipment of the power distribution network, as the reliability parameter of the corresponding reliability enhancement measure in the category specifically comprises:
calculating the fault rate of each type of equipment in the distribution network block by the following formula under the dimension of the time length of each outage of the equipment of the distribution network:
wherein λ isα,cIs the failure rate of the c-th element under the failure type α; lambda [ alpha ]α,iThe fault rate of the ith power failure responsibility reason under the fault type alpha is shown; i represents a power failure responsibility reason set;
calculating the total time for fault recovery of the equipment of the power distribution network under each power failure responsibility reason through the following formula:
Tα,γ,i＝Tα,1+Tα,2+Tα,3+max(max(Tα,4,Tα,5,Tα,5')+Tα,6,Tα,7)+Tα,8+Tα,9
wherein, Tα,γ,iThe total time for repairing the fault of the ith power failure responsibility reason under the fault type alpha; t isα,1The fault report duration under the fault type alpha; t isα,2The time length of emergency repair in place under the fault type alpha is shown; t isα,3Locating an operation duration for a fault under the fault type alpha; t isα,4The fault isolation operation duration under the fault type alpha is set; t isα,5The time for the first-aid repair team to reach the position under the fault type alpha is long; t isα,5'The time for the work ticket to be handled under the fault type alpha; t isα,6The dismantling duration of the fault equipment under the fault type alpha is determined; t isα,7The length of time for distributing the first-aid repair materials in place under the fault type alpha is long; t isα,8Repairing time for fault equipment under the fault type alpha; t isα,9Recovering the power supply operation time for all users under the fault type alpha;
according to the total fault repair time and the corresponding fault rate of the equipment of the power distribution network under each power failure responsibility reason, the repair time of each type of equipment is calculated through the following formula:
wherein, γα,cIs the repair time of the c-th element under the fault type alpha; t isα,γ,iThe total time for repairing the fault of the ith power failure responsibility reason under the fault type alpha; lambda [ alpha ]α,iThe fault rate of the ith power failure responsibility reason under the fault type alpha is shown;
according to the fault rate and the corresponding repair time of each type of equipment in the distribution network block, calculating the equivalent average repair time of the distribution network block by the following formula:
wherein, γα,sThe equivalent average repair time of the power distribution network blocks under the fault type alpha is shown; lambda [ alpha ]α,cIs the failure rate of the c-th element under the failure type α; gamma rayα,cIs the repair time of the c-th element under the fault type alpha; n is an element set contained in the power distribution network block;
and taking the calculated equivalent average repair time of the power distribution network blocks as the reliability parameters of the corresponding reliability improvement measures in the category.
3. The method for screening reliability enhancement measures for a power distribution network according to claim 1, wherein the step of obtaining the outage time of the power distribution network blocks in the dimension of the user range affected by each outage of the equipment of the power distribution network, as the reliability parameter of the corresponding reliability enhancement measure in the category specifically comprises:
dividing the distribution network into a plurality of areas based on switching devices in the distribution network under the dimension of user range affected by each outage of the devices of the distribution network;
and acquiring the outage time of the load node after each area fails as a reliability parameter of a corresponding reliability improvement measure in the category.
4. A screening apparatus for reliability enhancement measures of a power distribution network, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the screening method for reliability enhancement measures of a power distribution network according to any one of claims 1 to 3.
5. A computer-readable storage medium, characterized in that the storage medium has a program stored thereon, which when executed, implements the method for screening reliability enhancement measures for a power distribution network according to any one of claims 1 to 3.
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