CN112001626A - Method for evaluating toughness of power distribution network in typhoon weather, storage medium and equipment - Google Patents
Method for evaluating toughness of power distribution network in typhoon weather, storage medium and equipment Download PDFInfo
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Abstract
The invention discloses a three-stage evaluation method, a storage medium and equipment for the toughness of a power distribution network in typhoon weather, wherein when no typhoon disaster occurs, the influence of the typhoon disaster on the power distribution network and the response process of the power distribution network to the typhoon disaster are simulated and analyzed, and the pre-disaster toughness index of the power distribution network is counted and calculated; in the typhoon disaster occurrence process, calculating toughness indexes in the power distribution network disaster according to real-time data returned by the power distribution network data acquisition and monitoring control system; acquiring actual data of emergency response and emergency repair of the power distribution network after the typhoon leaves the environment, and calculating a post-disaster toughness index of the power distribution network; the three-stage toughness level of the power distribution network is quantized, and the pre-disaster firmness degree, the in-disaster resisting capability, the post-disaster recovery efficiency and the comprehensive toughness of the power distribution network for coping with typhoon disasters are quantized. The method can be used for guiding reinforcement of the elements of the power distribution network when no typhoon occurs, emergency control in the process of typhoon disaster and emergency repair and power restoration after typhoon disaster, and provides quantitative basis for system planning, operation scheduling and restoration decision.
Description
Technical Field
The invention belongs to the technical field of power distribution network planning, and particularly relates to a method, a storage medium and equipment for evaluating the toughness of a power distribution network in typhoon weather.
Background
The normal operation of modern society relies on reliable power supply, and the reliability of power systems in a normal state has been receiving attention. In recent years, the power grid is influenced by more and more typhoon weather with small probability and high loss, and the risk of large-area power failure loss exists. The power distribution network is used as a key link for directly serving users, is more fragile compared with a main network, has lower redundancy and automation degree, and is easy to suffer from serious equipment and load loss in typhoon weather. After typhoon landing, the tripping area of the distribution network equipment is large in amount and time, permanent faults are large, fault equipment is difficult to recover in time, and serious large-scale power failure accidents are easy to happen.
The toughness of the power distribution network embodies the capability of the power distribution network in resisting extreme disasters, reducing fault loss and recovering power supply as soon as possible. For effectively promoting the toughness level of distribution network under typhoon weather, improve the distribution network and take place the response and the recovery ability after resisting and absorbing capacity, typhoon of in-process and taking place at the prevention when the typhoon does not take place and manage the ability, need to divide and promote the three decision-making stage of distribution network calamity reply ability: before, during and after the disaster, an evaluation index system for scientifically evaluating the multi-period toughness level of the power distribution network is established.
At present, the missing area of a load curve of a power distribution network is mostly adopted as a toughness index of the power distribution network, the toughness of the power distribution network cannot be reflected from multiple dimensions such as robustness and rapidity, current indexes focus on evaluating the expected disaster coping capacity of the power distribution network, the method is only suitable for toughness evaluation when the power distribution network does not bear disasters, the method aims at guiding planning and construction of the power distribution network, and cannot be applied to the resisting process of the power distribution network when typhoon disasters occur and the emergency repair process of the power distribution network after the typhoon disasters. At the present stage, an index system suitable for evaluating the toughness of the power distribution network before, during and after typhoon disasters is lacked, and the expected robustness of the power distribution network when typhoon does not occur, the real-time resisting capability in the typhoon occurring process and the response and recovery efficiency after typhoon occurs are difficult to be effectively quantized.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a method, a storage medium and equipment for evaluating the toughness of a power distribution network in typhoon weather, comprehensively consider the uncertainty of typhoon disasters and the uncertainty of power distribution network element faults, perform simulation analysis on typhoons with different catastrophe strengths and required to be dealt with by the power distribution network, and analyze the potential influence of the typhoon disasters on the power distribution network.
The invention adopts the following technical scheme:
a three-stage evaluation method for toughness of a power distribution network in typhoon weather comprises the following steps:
s1, determining the occurrence and intensity characteristics of typhoon disasters, simulating a typhoon generator to generate a large number of simulated typhoon crossing scenes, evaluating the failure rate of power distribution network elements and determining a random outage state, simulating a load transfer process in the disasters, simulating a post-disaster power supply recovery process, calculating scene power distribution network toughness indexes, and calculating the pre-disaster toughness indexes of the power distribution network in a statistical manner;
s2, in the typhoon disaster occurrence process, according to the real-time data returned by the power distribution network data acquisition and monitoring control system, calculating toughness indexes in the power distribution network disaster;
s3, acquiring actual data of emergency response and emergency repair of the power distribution network after typhoon leaves, and counting and calculating the post-disaster toughness index of the power distribution network;
s4, integrating bottom layer indexes of the pre-disaster stage, the middle disaster stage and the post-disaster stage of the S1, quantizing the three-stage toughness level of the power distribution network by using an analytic hierarchy process, and quantizing the toughness levels of the power distribution network at the pre-disaster stage, the middle disaster stage and the post-disaster stage;
and S5, outputting evaluation results of the target layer and the criterion layer according to the analytic hierarchy process, and respectively using the evaluation results as the comprehensive toughness level of the power distribution network in typhoon weather and the toughness level evaluation values of the power distribution network in the early stage, the middle stage and the later stage of the disaster to finish the toughness evaluation of the power distribution network.
Specifically, step S1 specifically includes:
s101, defining typhoon disaster characteristics, considering uncertainty of natural disasters, and generating a large number of simulated disaster scenes through sampling of a typhoon disaster generator;
s102, according to a vulnerability curve of vulnerable equipment of the power distribution network under a disaster, considering uncertainty of element faults, and generating an element running state under a simulated disaster scene through sampling of a power distribution network element fault rate model;
s103, simulating a load transfer process in the disaster, searching for a power distribution network load loss node in the disaster process based on a connectivity principle and breadth, and recording the load loss condition and the accumulated loss electric quantity of the power distribution network at each moment in the disaster;
s104, simulating a post-disaster power supply recovery process, allocating post-disaster rush-repair team to repair distribution network elements by using a greedy algorithm which ensures single-step optimization, and recording the load recovery condition and the accumulated recovery electric quantity of the distribution network at each moment after disaster;
s105, generating a performance level curve of the power distribution network system according to simulation results of the load transfer in the disaster and the power supply recovery process after the disaster, and calculating a pre-disaster toughness index of the power distribution network in a scene by using the performance curve;
s106, according to the convergence criterion of the Monte Carlo simulation, all typhoon disaster scenes are integrated, the statistical average value of indexes before the typhoon in each scene is calculated to serve as an expected value, and the toughness index before the power distribution network disaster in the typhoon weather is obtained.
Further, the pre-disaster toughness indexes of the power distribution network are specifically as follows:
and (3) the system load loss probability under disasters: the expected damage degree of the system is reflected, and the probability of losing the power load of the power distribution network under the simulated typhoon disaster is calculated through a Monte Carlo method;
load loss expectation under disaster: the expected damage degree of the system is reflected, and the expected value of the loss load of the power distribution network under the simulated typhoon disaster is calculated through a Monte Carlo method;
expected loss of electric quantity under disasters: the expected damage degree of the system is reflected, and the expected value of the loss electric quantity of the power distribution network under the simulated typhoon disaster is calculated through a Monte Carlo method;
the load loss proportion expectation under the load shedding condition is as follows: reflecting the expected damage degree of the system, and eliminating scenes that power users are not affected when the expected value of the load loss proportion of the power distribution network under the typhoon disaster is calculated through a Monte Carlo method, and only considering the typhoon scenes of the load loss of the power distribution network;
the system island operation probability: the probability that the power distribution system and the main network are operated in a split mode and only depend on the power supply of the distributed power sources in the power distribution system is reflected;
the probability of occurrence of isolated nodes in the system is as follows: the probability that the power users and the power distribution network run separately and only depend on the distributed power sources deployed by the users or the emergency power generation cars of the power supply companies is reflected;
regional power supply capacity margin: and (4) a statistical value of the difference between the maximum power supply capacity of the area where the power distribution network is located and the load demand of the power distribution network.
Specifically, in step S2, the toughness index in the power distribution network disaster is specifically:
the accumulated loss proportion of the power distribution network equipment in the disaster: the ratio of the number of the tripping devices to the total number of the distribution network devices in the typhoon disaster occurrence process is calculated through real-time data returned by the distribution network data acquisition and monitoring control system;
the cumulative loss proportion of the power distribution network load in the disaster: calculating the ratio of the load lost compared with the historical contemporaneous load predicted value to the load predicted value in the typhoon disaster occurrence process through real-time data returned by the power distribution network information acquisition system;
available distributed power supply capacity: the method reflects the electric power load amount which can be supplied by the distributed power supply in the power distribution network area in the typhoon disaster occurrence process.
Specifically, in step S3, the post-disaster toughness index of the power distribution network is specifically:
the duration from typhoon departure to load start recovery: reflecting the response time of the power distribution network subjected to typhoon attack, and calculating through actual data of emergency response after disaster;
recovery ratio within one hour from load recovery: the recovery efficiency of the distribution network at the first-stage emergency repair after suffering from typhoon attack is reflected, and the actual data of the emergency repair after the disaster is calculated;
length of time for load recovery to a specified proportion: the recovery efficiency of the power distribution network subjected to typhoon attack is reflected, the power loss caused by the fault of large primary equipment is eliminated, and the actual data calculation of the post-disaster first-aid repair is carried out;
system load recovery efficiency: the overall recovery efficiency of the power distribution network subjected to typhoon attack is reflected, and actual data of post-disaster first-aid repair are calculated;
important load recovery efficiency: the emergency repair power restoration efficiency of the power distribution network subjected to typhoon attack on important lifeline loads is reflected, and actual data calculation of emergency repair after disasters is carried out;
economic efficiency of the system recovery process: and (4) reflecting the economic index of the recovery process of the power distribution network after the disaster, namely the amount of money needed to recover the unit load.
Specifically, step S4 specifically includes:
s401, establishing a hierarchical structure model: dividing an evaluation target, an evaluation criterion and an evaluation object into a highest layer, a middle layer and a lowest layer according to the structure shown in figure 1;
s402, constructing a judgment comparison matrix: when determining the weight among the factors of each level, comparing every two factors with each other, and evaluating the grade according to the importance degree of the factors;
s403, performing level single ordering and consistency check according to the consistency check index CI, searching a corresponding average random consistency index RI, calculating CR as CI/RI, judging the consistency of the matrix to accept when CR is less than 0.1, and otherwise, correcting the judgment matrix;
s404, calculating a combined weight coefficient W of the bottom layer itemsiComprehensively evaluating the total evaluation target table of the evaluation objects to obtain the final score F of the evaluation target, carrying out consistency test on the layer total sequence, and carrying out consistency test by a high layerAnd inspecting the lower layer by layer.
Further, in step S403, the consistency check index CI is calculated as follows:
wherein m is the sub-index number of the checked level, lambdamaxIs the maximum characteristic root, λiCharacteristic roots of the comparison matrix in pairs for the sub-objects of the layer under examination, aijFor comparing elements of the matrix, wiThe method is characterized in that the column vector of the comparison matrix is normalized, and then the ith element of the normalized vector after row calculation is carried out.
Further, in step S404, the final score F of the evaluation target is:
wherein, FiFor each index value score, WiN is the index number.
Another aspect of the invention is a computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to perform any of the methods described.
Another technical solution of the present invention is a computing device, including:
one or more processors, memory, and one or more programs stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing any of the methods.
Compared with the prior art, the invention has at least the following beneficial effects:
the invention relates to a three-stage evaluation method for toughness of a power distribution network in typhoon weather, which evaluates the toughness of the power distribution network in response to typhoon disasters from three criteria layers of expected robustness degree before the disasters, real-time resisting capability in the disasters and post-disaster first-aid repair recovery efficiency, and reflects the toughness level of the power distribution network from the dimensions of probability, expected value, electric power, ratio, time, efficiency and the like in an evaluation index system. The three-stage evaluation index system quantifies the expected strength degree of the power distribution network when no typhoon occurs, the real-time resisting capability in the typhoon occurrence process and the response and recovery efficiency after the typhoon occurs, and can be used for guiding the reinforcement and strengthening of power distribution network elements when no typhoon occurs, the emergency control in the typhoon disaster process and the emergency repair and restoration after the typhoon disaster.
Furthermore, uncertainty of the typhoon disaster and uncertainty of faults of the power distribution network elements are comprehensively considered, simulation analysis is carried out on typhoons with different catastrophe strengths, which need to be dealt with by the power distribution network, and potential influence of the typhoon disaster on the power distribution network is analyzed. A large number of simulated typhoon transit scenes are generated by constructing a typhoon simulation generator for random sampling, and an analysis scene is provided for calculating the toughness indexes before the power distribution network disaster; converting a typhoon passing scene into a fault scene of the power distribution network element by combining the vulnerability curve of the power distribution network element, and simulating the influence of extreme typhoon weather on the power distribution network; and simulating a load transfer process and a post-disaster power supply recovery process in a disaster, and analyzing a response process of the power distribution network under the typhoon disaster. The method for evaluating the pre-disaster toughness of the power distribution network in typhoon weather considers the potential threat and dynamic characteristics of typhoon disasters and provides basic support for calculation of pre-disaster evaluation indexes of the power distribution network.
Furthermore, seven power distribution network pre-disaster toughness evaluation indexes are set from three aspects of system expected damage degree, system island probability and power supply capacity margin, the expected robustness degree of the power distribution network facing future typhoon disasters is reflected, the method is applied to risk control when the power distribution network does not suffer from typhoon disasters, is used for guiding disaster prevention and reduction and planning construction of the power distribution network, and provides reference for power distribution network weak link identification, key element reinforcement and toughness improvement expansion planning.
Further, three toughness evaluation indexes in power distribution network disaster are set from three aspects of equipment loss, load loss and available distributed power supply capacity in the disaster, the real-time resisting capacity of the power distribution network facing typhoon disaster is analyzed, the method is applied to disaster-resistant operation scheduling when the power distribution network encounters typhoon disaster, and is used for visually displaying loss conditions in the power distribution network disaster, guiding emergency control in the power distribution network disaster, reducing fault diffusion and power failure risks and lightening power failure loss in the disaster.
Furthermore, six power distribution network post-disaster toughness evaluation indexes are set from the three aspects of response speed, recovery efficiency and recovery economy, the power distribution network post-disaster recovery efficiency and economy are calculated, the method is applied to the evaluation of power distribution network post-disaster element repair and load recovery measures, the effectiveness of the post-disaster recovery strategy is measured, the advantages and disadvantages of the adopted power supply recovery strategy are analyzed, and a decision basis is provided for the emergency response and the rapid recovery of the power distribution network to typhoon disasters in the future.
Further, the expected robustness degree of the power distribution network in the stage before the disaster, the real-time resisting capability of the power distribution network in the stage during the disaster and the power supply recovery efficiency of the power distribution network in the stage after the disaster are comprehensively considered, a three-stage hierarchical structure model of the toughness of the power distribution network is established, the toughness of the power distribution network in typhoon weather is refined layer by layer, and the three-stage hierarchical structure model is decomposed into an evaluation target, an evaluation criterion and an evaluation object. The importance degree of each factor is compared pairwise through engineering experience, the difference of the relative importance of the indexes is reflected, the evaluation of the importance of each index is considered to be subjective judgment, and the importance of the weight determined by an objective method in engineering practice cannot be completely matched, so that the weight definition by a subjective method is more scientific and reasonable. On the basis, qualitative and quantitative analysis is carried out, the toughness levels of the power distribution network in the pre-disaster stage, the middle disaster stage and the post-disaster stage are quantized in a criterion layer, and comprehensive quantitative evaluation is carried out on the toughness of the power distribution network in typhoon weather in a target layer.
Further, byThe consistency test index CI measures the inconsistency of the constructed comparison matrix, and the sum method is adopted to simplify the calculation, thereby simplifying the calculation complexity of the hierarchical analysis. Since the comparison matrix A is n-order positive reciprocal matrix, its maximum eigenvalue lambdamaxN, if and only ifmaxWhen n, a is a uniform matrix. Lambda [ alpha ]maxThe more the value is larger than n, the more serious the inconsistency of the comparison matrix A is, the more the eigenvector corresponding to the maximum eigenvalue is used as the weight vector of the influence degree of the compared factor on a certain factor of the upper layer, and the larger the inconsistency is, the larger the judgment error is caused. Using lambdamaxN, constructing a consistency check index CI to measure the inconsistency degree of the comparison matrix A, wherein the consistency is larger when the CI value is smaller. Because any column of the uniform array is the characteristic vector, the column vector of the positive and reciprocal array with good consistency is approximate to the characteristic vector, and therefore the average in the arithmetic sense can be taken to simplify the calculation complexity of the maximum characteristic value and the characteristic vector.
Furthermore, the calculated combination weight coefficient and the bottom index score are integrated, the toughness level of the power distribution network under the typhoon disaster is scientifically and comprehensively evaluated, the system toughness evaluation dimension is extended by taking the time dimension as a basic axis, and a clear promotion direction is provided for planning construction, disaster prevention and reduction of the elastic power distribution network. On one hand, the comprehensive toughness score can be applied to transverse comparison of toughness levels among power distribution networks in different areas; on the other hand, the method can also be applied to longitudinal comparison of the power distribution network in different development stages, and can provide quantitative basis for power grid planning, scheduling and decision recovery.
In conclusion, the toughness of the power distribution network is evaluated from three aspects of expected robustness before disaster, real-time resisting capability in the disaster and recovery efficiency of emergency repair after the disaster, and the comprehensive toughness of the power distribution network for typhoon disasters is comprehensively quantized by a three-stage evaluation index system.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
FIG. 1 is a frame diagram of a three-stage evaluation index system for toughness of a power distribution network;
FIG. 2 is a diagram of distribution network toughness evaluation levels and stages;
FIG. 3 is an application flow chart of a three-stage evaluation index system for toughness of a power distribution network;
FIG. 4 is a diagram of an improved IEEE-33 node test power distribution system topology;
fig. 5 is a graph of performance of a test distribution system in a test typhoon, wherein (a) is a component failure and repair process, and (b) is a load loss and recovery process.
Detailed Description
Referring to fig. 1, firstly, the toughness indexes of the power distribution network are divided into three levels according to different periods of typhoon occurrence, a three-stage power distribution network toughness evaluation index system is constructed, the toughness levels of the power distribution network are quantized from different sides, in order to quantitatively evaluate the toughness levels of the power distribution network in response to typhoon disasters, system performance needs to be evaluated from different stages, and the toughness levels of the power distribution network are reflected from a plurality of layers. In the face of impact of typhoon disasters on the power distribution network, the power distribution network has enough robustness, and faults of power distribution network equipment and load loss of power consumers are reduced as much as possible; the method has the rapidity of emergency response, and reduces the time for repairing the power distribution network equipment after disaster and recovering power transmission of users as far as possible.
Referring to fig. 2, the toughness of the distribution network corresponds to the following characteristics:
analyzing and predicting expected loss of the disaster on the power distribution network before the typhoon disaster, combing weak links of the power distribution network, and taking preventive measures such as reinforcing key equipment and checking high-risk hidden danger points;
during typhoon disasters, effective scheduling and control measures can be taken to reduce the disturbance of the disasters on equipment and power supply loads, rather than passively waiting for typhoon departure;
after typhoon disasters, a recovery scheme can be rapidly formulated, and rapid fault restoration and load recovery are realized. All three characteristics are indispensable to the toughness of the distribution network.
The method is characterized in that the occurrence and development process of typhoon disasters and the response process of the power distribution network are extended in the time dimension and divided into three time stages: before, during and after a disaster, a multi-stage toughness evaluation index system is constructed, and application scenes of indexes are distinguished according to divided stages.
1) Stage before disaster
The expected robustness degree of the power distribution network facing typhoon disasters is emphasized in the pre-disaster stage, and the expected robustness degree of the power distribution network facing future disasters is reflected in the aspects of the expected damage degree of the system, the island probability of the system and the power supply capacity margin, so that the method is used for guiding the disaster prevention and reduction of the power distribution network and planning construction, and provides reference for identification of weak links of the power distribution network and reinforcement of key elements. The specific indexes are as follows:
(1) and (3) the system load loss probability under disasters: the expected damage degree of the system is reflected, and the probability of losing the power load of the power distribution network under the simulated typhoon disaster is calculated through a Monte Carlo method;
(2) load loss expectation under disaster: the expected damage degree of the system is reflected, the robustness dimension of the toughness of the power distribution network is emphasized, and the expected value of the loss load of the power distribution network under the simulated typhoon disaster is calculated through a Monte Carlo method, wherein the unit is MW;
(3) expected loss of electric quantity under disasters: the expected damage degree of the system is reflected, the robustness and rapidity dimension of the toughness of the power distribution network are comprehensively considered, and the expected value of the loss electric quantity of the power distribution network under the simulated typhoon disaster is calculated through a Monte Carlo method, wherein the unit is MWh;
(4) the load loss proportion expectation under the load shedding condition is as follows: the method includes the steps that the expected damage degree of a system is reflected, the condition is basically expected, when the expected value of the load loss proportion of the power distribution network under the typhoon disaster is calculated through a Monte Carlo method, scenes where power users are not affected are eliminated, and only typhoon scenes of the load loss of the power distribution network are taken into account;
(5) the system island operation probability: the probability that the power distribution system and the main network are operated in a split mode and only depend on the power supply of the distributed power sources in the power distribution system is reflected;
(6) the probability of occurrence of isolated nodes in the system is as follows: the probability that the power users and the power distribution network run separately and only depend on the distributed power sources deployed by the users or the emergency power generation cars of the power supply companies is reflected;
(7) regional power supply capacity margin: and the statistical value of the difference between the maximum power supply capacity of the area where the power distribution network is located and the load demand of the power distribution network is obtained according to the historical operation data statistics of the power distribution network in a normal mode.
2) In the middle of the disaster
The real-time defense capacity of the power distribution network facing typhoon disasters is emphasized in the middle stage of the disaster, the real-time defense capacity of the power distribution network facing the disasters is analyzed from three aspects of equipment loss, load loss and available distributed power supply capacity in the disaster, and the real-time defense capacity is used for visually displaying loss conditions in the power distribution network disaster, guiding emergency control in the power distribution network disaster, reducing fault diffusion and power failure risks and reducing power failure loss in the disaster. The specific indexes are as follows:
(1) the accumulated loss proportion of the power distribution network equipment in the disaster: the ratio of the number of the tripping devices to the total number of the distribution network devices in the typhoon disaster occurrence process is calculated by real-time data returned by the distribution network data acquisition and monitoring control system, and the index changes along with the occurrence and development process of the typhoon;
(2) the cumulative loss proportion of the power distribution network load in the disaster: in the typhoon disaster occurrence process, compared with the ratio of the lost load amount of the historical contemporaneous load predicted value to the load amount predicted value, the index is calculated through real-time data returned by the power distribution network information acquisition system and changes along with the typhoon occurrence process;
(3) available distributed power supply capacity: the method reflects the electric power load amount which can be supplied by the distributed power supply in the power distribution network area in the typhoon disaster occurrence process.
3) Post-disaster stage
The recovery efficiency of the power distribution network after the typhoon disaster is emphasized in the post-disaster stage, the recovery efficiency of the power distribution network after the typhoon disaster is calculated from three aspects of response speed, recovery efficiency and recovery economy, the effectiveness of the recovery strategy after the disaster is measured, the quality of the adopted power supply recovery strategy is analyzed, and a decision basis is provided for the power distribution network to cope with the typhoon disaster in the future. The specific indexes are as follows:
(1) the duration from typhoon departure to load start recovery: the response time of the power distribution network subjected to typhoon attack is reflected, and the response time is calculated through actual data of emergency response after disaster;
(2) recovery ratio within one hour from load recovery: the recovery efficiency of the distribution network at the initial stage of emergency repair after suffering from typhoon attack is reflected and calculated through actual data of emergency repair after disaster;
(3) length of time for load recovery to a specified proportion: the recovery efficiency of the power distribution network subjected to typhoon attack is reflected, but the focus is on measuring the power load with small influence, the power loss caused by the fault of large-scale primary equipment which is difficult to repair is eliminated, and the recovery efficiency is calculated through actual data of emergency repair after disasters, and the unit is h;
(4) system load recovery efficiency: the overall recovery efficiency of the power distribution network subjected to typhoon attack is reflected, and the overall recovery efficiency is calculated through actual data of post-disaster rush repair, and the unit is MW/h;
(5) important load recovery efficiency: the emergency repair power restoration efficiency of the power distribution network subjected to typhoon attack on important lifeline loads is reflected, and the emergency repair power restoration efficiency is calculated through actual data of emergency repair after disasters and has the unit of MW/h;
(6) economic efficiency of the system recovery process: and the economic index of the recovery process of the power distribution network after the disaster, namely the amount of money needed to recover the unit load, is reflected, and the unit is ten thousand yuan/MW.
Referring to fig. 3, the three-stage evaluation method for the toughness of the power distribution network in typhoon weather includes the following steps:
s1, determining the occurrence and intensity characteristics of typhoon disasters, generating a large number of simulated typhoon disaster scenes through a simulated typhoon generator, analyzing the influence of typhoon on the power distribution network, and simulating and calculating pre-disaster toughness indexes of the power distribution network under typhoon weather, wherein the pre-disaster toughness indexes specifically comprise system load loss probability under disasters, load loss expectation under disasters, electric quantity loss expectation under disasters, load loss proportion expectation under load shedding conditions, system island operation probability and system isolated node probability.
S101, defining typhoon disaster characteristics, considering uncertainty of natural disasters, and generating a large number of simulated disaster scenes through sampling of a typhoon disaster generator;
s102, according to a vulnerability curve of vulnerable equipment of the power distribution network under a disaster, considering uncertainty of element faults, and generating an element running state under a simulated disaster scene through sampling of a power distribution network element fault rate model;
s103, simulating a load transfer process in a disaster: searching for a power distribution network load loss node in the disaster process based on a connectivity principle and breadth, and recording the load loss condition and the accumulated loss electric quantity of the power distribution network at each moment in the disaster;
s104, simulating a post-disaster power supply recovery process: allocating elements of a distribution network for repairing by a post-disaster rush-repair team by using a greedy algorithm which ensures single-step optimization, and recording the load recovery condition and the accumulated recovery electric quantity of the distribution network at each moment after the disaster;
s105, generating a performance level curve of the power distribution network system shown in the figure 2 according to simulation results of the load transfer in the disaster and the power supply recovery process after the disaster, and calculating the pre-disaster toughness index of the power distribution network in the scene by using the performance curve;
the specific method comprises the following steps: determining the system load loss amount in the disaster scene according to the maximum difference value of the system load curve and the performance curve in the ordinate direction; determining the system loss electric quantity under the disaster scene according to the area of a graph enclosed by the system load curve and the performance curve; and judging whether the system loses load, whether an island operation phenomenon occurs in the system and whether an isolated node occurs in the system under the disaster scene according to simulation results of the load transfer process in the disaster and the power supply recovery process after the disaster.
S106, according to the convergence criterion of the Monte Carlo simulation, all typhoon disaster scenes are integrated, the statistical average value of indexes before the typhoon in each scene is calculated to serve as an expected value, and the toughness index before the power distribution network disaster in the typhoon weather is obtained.
S2, calculating toughness indexes in the power distribution network disaster in the typhoon weather according to real-time data returned by the power distribution network data acquisition and monitoring control system in the typhoon disaster occurrence process, wherein the toughness indexes in the power distribution network disaster specifically comprise the accumulated loss proportion of power distribution network equipment in the disaster, the accumulated loss proportion of power distribution network load and the power supply capacity of an available distributed power supply;
s3, calculating post-disaster toughness indexes of the power distribution network in typhoon weather according to post-disaster emergency response and actual data of first-aid repair after typhoon departure, wherein the post-disaster toughness indexes specifically comprise the duration from typhoon departure to load start recovery, the recovery proportion within one hour from load recovery, the time length from load recovery to a specified proportion, system load recovery efficiency, important load recovery efficiency and economic efficiency of a system recovery process;
s4, integrating bottom layer indexes of three stages before, during and after the disaster, quantizing the three-stage toughness level of the power distribution network by using an analytic hierarchy process, and comprehensively quantizing the toughness level of the power distribution network in the three stages before, during and after the disaster;
s401, establishing a hierarchical structure model: dividing an evaluation target, an evaluation criterion and an evaluation object into a highest layer, a middle layer and a lowest layer according to the structure shown in figure 1;
s402, constructing a judgment comparison matrix: when determining the weight among the factors of each level, comparing every two factors with each other, and evaluating the grade according to the importance degree of the factors; table 1 lists the common 9 importance levels and their assignments;
table 1 common 9 importance levels and their assignments
S403, hierarchical single sorting and consistency checking: the consistency check index CI is calculated as follows:
wherein m is the sub-index number of the checked level, lambdamaxIs the maximum feature root, aijIn order to compare the elements of the matrix,withe method is characterized in that the column vector of the comparison matrix is normalized, and then the ith element of the normalized vector after row calculation is carried out.
Searching a corresponding average random consistency index RI, calculating CR which is CI/RI, and when CR is less than 0.1, considering that the consistency of the judgment matrix is acceptable, otherwise, properly correcting the judgment matrix;
s404, checking the total hierarchical ordering and consistency thereof: the total sorting weight is synthesized by the weights under the single criterion from top to bottom, and the combined weight coefficient W of each index is calculatediAnd comprehensively evaluating the total evaluation target of the evaluation object:
wherein F is the final score of the evaluation target, FiScore each index value. And (5) carrying out consistency check on the total hierarchical ordering, wherein the check is carried out layer by layer from a high layer to a low layer.
And S5, outputting evaluation results of the target layer and the criterion layer according to the analytic hierarchy process, and respectively using the evaluation results as the comprehensive toughness level of the power distribution network in typhoon weather and the toughness level evaluation values of the power distribution network in three stages of before disaster, in disaster and after disaster to finish the toughness evaluation of the power distribution network.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, 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 some, but not all, embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. 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.
Referring to fig. 4, a simple test case is shown. In an improved IEEE-33 node power distribution system, a node 1 is a substation power supply node, the rest 32 nodes are load nodes, the total active load of the system is 3715kW, and the nodes 7-9, 24-25 and 29-31 are important loads. In the system, 2 connecting feeders capable of carrying out load transfer are arranged, a micro gas turbine is arranged at a node 8, and the maximum active power output is 100 kW. To develop subsequent analyses, modified IEEE-33 node power distribution systems were deployed in Guangzhou city. The spatial span of the distribution grid is typically very small compared to the diameter of the wind ring of a typhoon, so all distribution lines in the example system are considered to be in the same geographical environment area.
Aiming at the pre-disaster toughness evaluation of the power distribution network, a large number of typhoon process scenes are generated by sampling by using a Guangzhou city typhoon simulation generator, and the influence of typhoon disasters with different intensities on a test system is simulated. In the evaluation, the simulation time resolution of the load transfer in disaster and the power restoration simulation after disaster is set to be 1 min; setting the number of first-aid repair teams after the power distribution network disaster to be 2; setting the repair time of a damaged distribution line to obey the exponential distribution with the mean value of 3 h; the convergence criterion of the monte carlo simulation is that the variance coefficient beta is less than 5%. The evaluation result of the pre-disaster index of the test power distribution system obtained by calculation by adopting the Monte Carlo simulation method is shown in Table 2.
Table 2 evaluation results of testing pre-disaster indicators of power distribution system
Because different types of indexes exist in the comprehensive elastic index system and the dimensions and values of the indexes have great difference, the index values need to be normalized, so that the dimensions of all the indexes are kept consistent, and unified processing and calculation can be performed. The normalized values were converted to scores according to the membership function using a fuzzy evaluation method, and are listed in table 2.
For power distribution network disaster neutralization and post-disaster evaluation, analysis and calculation are needed according to specific typhoon disasters encountered by the power distribution network. With No. 22 typhoons "mangosteen" in 2018 as the test typhoon, a performance curve graph of the power distribution system in the process of resisting in a disaster and recovering after the disaster under the test typhoon is shown in fig. 5. According to the performance curve of the response process, the indexes of the distribution network in the typhoon weather and the indexes after the disaster and the scores of the indexes can be obtained through statistics, and the indexes are shown in table 3. In the calculation of the post-disaster economic index, the cost required for repairing a distribution line is set to be 1 ten thousand yuan.
TABLE 3 evaluation results of in-disaster and post-disaster indicators for testing power distribution systems
In the process of evaluating the comprehensive toughness of the power distribution network in typhoon weather, weights of indexes at all levels corresponding to superior indexes are calculated by means of an analytic hierarchy process, so that the final toughness score of the power distribution network can be calculated by means of the scores of all indexes, and a pairing comparison matrix of a first layer can be established as shown in table 4 according to the characteristics and evaluation requirements of the power distribution network.
TABLE 4 pairwise comparison matrix of criteria layers
The maximum eigenvalue of the comparison matrix is calculated to be lambdamax3.0655, the normalized feature vector is the weight vector, W (0.0738,0.2828,0.6434)T. Performing consistency check, wherein the consistency check index is
Since RI can be obtained as 0.58 by looking up the random consistency index value shown in table 5, the consistency ratio is set to
As can be seen, the comparison matrix passes the consistency check.
TABLE 5 table of random consistency index values
For each bottom layer index under the same criterion layer, assuming that the importance of each index is equal, the weight vectors of the index layer can be obtained as
The underlying indices and the weights of each index layer relative to the previous level can be calculated according to the above two steps. For the criterion layer, the respective criterion layer score is calculated as follows:
wherein, FkScore, w, representing each criterion layerkWeight, f, representing each underlying indexkScore, n, representing each underlying indicatorkRepresenting the number of bottom layer indices at the k-th criterion layer. The score calculation results for each criterion layer are shown in table 6.
TABLE 6 calculation results of index scores of respective criterion layers
For the toughness of the power distribution network as a target layer, the comprehensive score is calculated as follows:
wherein, FkScore, W, representing each criterion layerkRepresenting the weight of each criterion layer and n representing the number of criterion layers. From the above, the comprehensive toughness score of the tested power distribution system for typhoon disasters is F-82.9. According to the three-stage evaluation method of the toughness of the power distribution network, the situation that the resistance capability in a disaster of a power distribution system is poor can be seen, and the redundancy of the system needs to be improved through extension planning or the robustness of the system needs to be enhanced through windproof reinforcement of elements. Aiming at the comprehensive elasticity evaluation result of the power distribution network, the toughness construction condition score value of the test system is in a medium level, and the toughness of the system for typhoon weather needs to be improved through preventive planning and disaster-resistant scheduling measures.
In summary, the three-stage evaluation method for the toughness of the power distribution network in the typhoon weather, provided by the invention, divides three decision stages for improving the toughness of the power distribution network, namely before disaster, during disaster and after disaster, considers the robustness, the resisting capability and the recovery efficiency, carries out comprehensive evaluation on the toughness of the power distribution network corresponding to the typhoon disaster, and provides quantitative basis for system planning, operation scheduling and decision recovery.
As will be appreciated by one skilled in the art, 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 flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams 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 above-mentioned contents are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modification made on the basis of the technical idea of the present invention falls within the protection scope of the claims of the present invention.
Claims (10)
1. A three-stage evaluation method for toughness of a power distribution network in typhoon weather is characterized by comprising the following steps:
s1, determining the occurrence and intensity characteristics of typhoon disasters, simulating a typhoon generator to generate a large number of simulated typhoon crossing scenes, evaluating the failure rate of power distribution network elements and determining a random outage state, simulating a load transfer process in the disasters, simulating a post-disaster power supply recovery process, calculating scene power distribution network toughness indexes, and calculating the pre-disaster toughness indexes of the power distribution network in a statistical manner;
s2, in the typhoon disaster occurrence process, according to the real-time data returned by the power distribution network data acquisition and monitoring control system, calculating toughness indexes in the power distribution network disaster;
s3, acquiring actual data of emergency response and emergency repair of the power distribution network after typhoon leaves, and counting and calculating the post-disaster toughness index of the power distribution network;
s4, integrating bottom layer indexes of the pre-disaster stage, the middle disaster stage and the post-disaster stage of the S1, quantizing the three-stage toughness level of the power distribution network by using an analytic hierarchy process, and quantizing the toughness levels of the power distribution network at the pre-disaster stage, the middle disaster stage and the post-disaster stage;
and S5, outputting evaluation results of the target layer and the criterion layer according to the analytic hierarchy process, and respectively using the evaluation results as the comprehensive toughness level of the power distribution network in typhoon weather and the toughness level evaluation values of the power distribution network in the early stage, the middle stage and the later stage of the disaster to finish the toughness evaluation of the power distribution network.
2. The three-stage evaluation method for the toughness of the power distribution network under the typhoon weather according to the claim 1, wherein the step S1 is specifically as follows:
s101, defining typhoon disaster characteristics, considering uncertainty of natural disasters, and generating a large number of simulated disaster scenes through sampling of a typhoon disaster generator;
s102, according to a vulnerability curve of vulnerable equipment of the power distribution network under a disaster, considering uncertainty of element faults, and generating an element running state under a simulated disaster scene through sampling of a power distribution network element fault rate model;
s103, simulating a load transfer process in the disaster, searching for a power distribution network load loss node in the disaster process based on a connectivity principle and breadth, and recording the load loss condition and the accumulated loss electric quantity of the power distribution network at each moment in the disaster;
s104, simulating a post-disaster power supply recovery process, allocating post-disaster rush-repair team to repair distribution network elements by using a greedy algorithm which ensures single-step optimization, and recording the load recovery condition and the accumulated recovery electric quantity of the distribution network at each moment after disaster;
s105, generating a performance level curve of the power distribution network system according to simulation results of the load transfer in the disaster and the power supply recovery process after the disaster, and calculating a pre-disaster toughness index of the power distribution network in a scene by using the performance curve;
s106, according to the convergence criterion of the Monte Carlo simulation, all typhoon disaster scenes are integrated, the statistical average value of indexes before the typhoon in each scene is calculated to serve as an expected value, and the toughness index before the power distribution network disaster in the typhoon weather is obtained.
3. The three-stage evaluation method for the toughness of the power distribution network under the typhoon weather is characterized in that the three-stage evaluation method for the toughness of the power distribution network before the disaster concretely comprises the following steps:
and (3) the system load loss probability under disasters: the expected damage degree of the system is reflected, and the probability of losing the power load of the power distribution network under the simulated typhoon disaster is calculated through a Monte Carlo method;
load loss expectation under disaster: the expected damage degree of the system is reflected, and the expected value of the loss load of the power distribution network under the simulated typhoon disaster is calculated through a Monte Carlo method;
expected loss of electric quantity under disasters: the expected damage degree of the system is reflected, and the expected value of the loss electric quantity of the power distribution network under the simulated typhoon disaster is calculated through a Monte Carlo method;
the load loss proportion expectation under the load shedding condition is as follows: reflecting the expected damage degree of the system, and eliminating scenes that power users are not affected when the expected value of the load loss proportion of the power distribution network under the typhoon disaster is calculated through a Monte Carlo method, and only considering the typhoon scenes of the load loss of the power distribution network;
the system island operation probability: the probability that the power distribution system and the main network are operated in a split mode and only depend on the power supply of the distributed power sources in the power distribution system is reflected;
the probability of occurrence of isolated nodes in the system is as follows: the probability that the power users and the power distribution network run separately and only depend on the distributed power sources deployed by the users or the emergency power generation cars of the power supply companies is reflected;
regional power supply capacity margin: and (4) a statistical value of the difference between the maximum power supply capacity of the area where the power distribution network is located and the load demand of the power distribution network.
4. The three-stage evaluation method for the toughness of the power distribution network under the typhoon weather according to claim 1, wherein in the step S2, the toughness index in the power distribution network disaster is specifically as follows:
the accumulated loss proportion of the power distribution network equipment in the disaster: the ratio of the number of the tripping devices to the total number of the distribution network devices in the typhoon disaster occurrence process is calculated through real-time data returned by the distribution network data acquisition and monitoring control system;
the cumulative loss proportion of the power distribution network load in the disaster: calculating the ratio of the load lost compared with the historical contemporaneous load predicted value to the load predicted value in the typhoon disaster occurrence process through real-time data returned by the power distribution network information acquisition system;
available distributed power supply capacity: the method reflects the electric power load amount which can be supplied by the distributed power supply in the power distribution network area in the typhoon disaster occurrence process.
5. The three-stage evaluation method for the toughness of the power distribution network under the typhoon weather according to the claim 1, wherein in the step S3, the post-disaster toughness index of the power distribution network is specifically as follows:
the duration from typhoon departure to load start recovery: reflecting the response time of the power distribution network subjected to typhoon attack, and calculating through actual data of emergency response after disaster;
recovery ratio within one hour from load recovery: the recovery efficiency of the distribution network at the first-stage emergency repair after suffering from typhoon attack is reflected, and the actual data of the emergency repair after the disaster is calculated;
length of time for load recovery to a specified proportion: the recovery efficiency of the power distribution network subjected to typhoon attack is reflected, the power loss caused by the fault of large primary equipment is eliminated, and the actual data calculation of the post-disaster first-aid repair is carried out;
system load recovery efficiency: the overall recovery efficiency of the power distribution network subjected to typhoon attack is reflected, and actual data of post-disaster first-aid repair are calculated;
important load recovery efficiency: the emergency repair power restoration efficiency of the power distribution network subjected to typhoon attack on important lifeline loads is reflected, and actual data calculation of emergency repair after disasters is carried out;
economic efficiency of the system recovery process: and (4) reflecting the economic index of the recovery process of the power distribution network after the disaster, namely the amount of money needed to recover the unit load.
6. The three-stage evaluation method for the toughness of the power distribution network under the typhoon weather according to the claim 1, wherein the step S4 is specifically as follows:
s401, establishing a hierarchical structure model: dividing an evaluation target, an evaluation criterion and an evaluation object into a highest layer, a middle layer and a lowest layer according to the structure shown in figure 1;
s402, constructing a judgment comparison matrix: when determining the weight among the factors of each level, comparing every two factors with each other, and evaluating the grade according to the importance degree of the factors;
s403, performing level single ordering and consistency check according to the consistency check index CI, searching a corresponding average random consistency index RI, calculating CR as CI/RI, judging the consistency of the matrix to accept when CR is less than 0.1, and otherwise, correcting the judgment matrix;
s404, calculating a combined weight coefficient W of the bottom layer itemsiAnd comprehensively evaluating the total evaluation target table of the evaluation object to obtain the final score F of the evaluation target, carrying out consistency inspection on the layer total sequence, and carrying out inspection layer by layer from a high layer to a low layer.
7. The three-stage evaluation method for the toughness of the power distribution network under the typhoon weather according to the claim 6, wherein in the step S403, the consistency check index CI is calculated as follows:
wherein m is the sub-index number of the checked level, lambdamaxIs the maximum characteristic root, λiCharacteristic roots of the comparison matrix in pairs for the sub-objects of the layer under examination, aijFor comparing elements of the matrix, wiThe method is characterized in that the column vector of the comparison matrix is normalized, and then the ith element of the normalized vector after row calculation is carried out.
8. The three-stage evaluation method for the toughness of the power distribution network under the typhoon weather according to the claim 6, wherein in the step S404, the final score F of the evaluation target is:
wherein, FiFor each index value score, WiN is the index number.
9. A computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to perform any of the methods of claims 1-8.
10. A computing device, comprising:
one or more processors, memory, and one or more programs stored in the memory and configured for execution by the one or more processors, the one or more programs including instructions for performing any of the methods of claims 1-8.
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