CN109687438A - It is a kind of meter and high-speed rail impact load effect under power grid vulnerable line discrimination method - Google Patents
It is a kind of meter and high-speed rail impact load effect under power grid vulnerable line discrimination method Download PDFInfo
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- H—ELECTRICITY
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- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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- H—ELECTRICITY
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Abstract
It is a kind of meter and high-speed rail impact load effect under power grid vulnerable line discrimination method, it the steps include: that (1) considers the random fluctuation characteristic of high iron load, the probabilistic model of high iron load is established using the combination of normal distribution and bi-distribution, and N-1 probabilistic load flow is then carried out in IEEE39 node system；(2) correlation networks of electric system are established according to N-1 probabilistic load flow result；(3) using the vulnerable line in weighting K nuclear decomposition method Identification of Power System on the basis of correlation networks.The present invention carries out equivalent description to high iron load, and the correlation net of foundation can take into account the topological structure feature and operating status characteristic for considering electric system, the vulnerable line in the accurate identification system of energy.The present invention, for its load big ups and downs, impact characteristics, proposes a kind of weighting K nuclear decomposition method based on Monte Carlo simulation, under the background of the extensive high-speed rail access power grid in China to recognize the vulnerable line in power grid.
Description
Technical field
The present invention relates to vulnerable line discrimination method in power grid vulnerability analysis, to prevent power grid cascading failure propagation,
Prevent power grid and have a power failure on a large scale to play a key role.
Background technique
In recent years, worldwide large-scale blackout frequently occurs.Huge economic damage is caused to state and society
It becomes estranged serious social influence, causes people to the strong interest again of Power System Reliability.Studies have shown that general power grid
Have a power failure on a large scale be by individual component failure, cause cascading failure during power flow transfer, the system of eventually leading to collapses
It bursts, wherein only a few critical circuits play the role of adding fuel to the flames to the diffusion for range of having a power failure on a large scale.Therefore, these passes how to be recognized
Key route has important theoretical research and practical application value.
Existing technology can be mainly divided into two major classes according to the starting point difference of modeling.The first kind is based on electric system shape
Step response, based on the Static and dynamic performance of electric system, is described using Load flow calculation as core with probability or deterministic method
The cascading failure communication process of power grid has used entropy theory method, risk assessment method, energy function method and cascading failure simulation
Method, to achieve the purpose that vulnerable line recognizes.The above method mainly considers the transfer of the Line Flow under grid disturbance and divides
Cloth characteristic, node voltage offset, the disturbance of virtual injecting power, system lose load etc..Second class is based on Complex Networks Theory,
Using the topological structure of power grid as core.Using in network structure angle value and the indexs such as betweenness vulnerable line is recognized, wrap
Include the indexs such as electrical betweenness, trend betweenness, power betweenness and mixed flow betweenness.In addition, based on K nuclear decomposition, PageRank, most
The discrimination method flowed greatly is put forward one after another.The above method takes full advantage of under the physical attribute and static parameter and disturbance of power grid
The characteristics such as power transfer, but primarily directed to traditional load, and example was divided in the case where certainty load
Analysis.In view of the fast development of China express railway, high iron load accounting is gradually increased.High iron load has strong impact
And randomness, there is the influence that can not ignore to power grid.Above-mentioned discrimination method rarely has the effect for considering high-speed railway load.
Summary of the invention
It is an object of the present invention to provide the power grid vulnerable line discrimination methods under a kind of meter and the effect of high-speed rail impact load, it is intended to
Based on actual measurement high-speed rail load data, the probabilistic model of high iron load is established, the Monte Carlo simulation in probabilistic load flow is utilized
Method considers to recognize vulnerable line under high iron load effect using improved weighting K core index.
The object of the present invention is achieved like this,
Step 1: the modeling of high-speed rail part throttle characteristics
Firstly, according to high iron load big ups and downs, impact characteristics and its probability density distribution, as shown in Figure 1, utilizing normal state
The combination of distribution and bi-distribution establishes the probabilistic model of high iron load.
Step 2: calculating the Monte Carlo the N-1 Probabilistic Load Flow for considering high-speed rail part throttle characteristics
In conjunction with the probabilistic model of high iron load, using IEEE39 as analysis object, as shown in Fig. 2, by several passes therein
Key load (red arrow) is substituted for high iron load.Then 5000 N-1 probability are carried out to system using Monte Carlo Analogue Method
Load flow calculation obtains 5000 groups of branch powers, and probabilistic method is recycled to find out its mathematic expectaion.
Step 3: the correlation networks of electric power networks are constructed according to branch power coupled relation
The topological structure feature of power grid and the state characteristic of system operation are considered in order to balance, establish the phase of electric system
Closing property network, as shown in Figure 3.Based on the foundation of the correlation networks probabilistic load flow of the N-1 in step 1, with former power grid
In transmission line of electricity be node, with after the line disconnection caused All other routes trend increase be side construct a new net
Network, the network are referred to as the correlation networks of original power system.The building of correlation networks not only allows between route and route
Topology connection structure, and quantified the state between route and route and contacted.Then, the identification of vulnerable line is converted to
The identification of fragile node.
Step 4: recognizing vulnerable line using weighting K nuclear decomposition method
Traditional K nuclear decomposition, which is all based on, haves no right Undirected networks, it is believed that the bigger node of K core value, different degree are higher.But it walks
The correlation networks established in rapid 2 are bidirectional weighting networks, are improved to traditional K nuclear decomposition, as shown in figure 4, in weighting K
In nuclear decomposition, node only subtracts the node to the strength of association of adjacent node when removing, and retains adjacent node to the shadow of the node
It rings.It is successively decomposed since the smallest node of weighting degree, obtains the K core value of each node in correlation networks.K core value is bigger, table
The bright node is more fragile, and the establishment process further according to correlation networks in step 2 is it is found that the node in correlation networks is corresponding former
The fragility of route in electric system.
The correlation networks established in step 3 are bidirectional weighting networks, are improved to traditional K nuclear decomposition, in weighting K
In nuclear decomposition, node only subtracts the node to the strength of association of adjacent node when removing, and retains adjacent node to the shadow of the node
It rings；It is successively decomposed since the smallest node of weighting degree, obtains the K core value of each node in correlation networks；Due to network edge
Node still may present and high build up phenomenon, i.e., high K core value, small influence power；Therefore utilize node and its adjacent node and secondary neighbour
Connect the K core value of node to improve accuracy of identification, i.e.,
In formula, Ks_d (i) is the depth K core value of node i, reflects the influence power of node i；Ks (i) is the K core value of node i；
ijIndicate that the adjacent node of node i concentrates j-th of node, ΩiFor the adjacent node collection of node i；Indicate node ijK-th
Adjacent node,Indicate node ijAdjacent node collection, m0Indicate the K core value weight of node i, m1Indicate the adjacent section of node i
The weight of the sum of point K core value, m2Indicate the weight of the sum of secondary adjacent node K core value of node i, and m0+m1+m2=1；Obviously,
The value of Ks_d is bigger, and corresponding transmission line of electricity is more fragile；
Analyzed using IEEE-39 node system as example, in calculate node system topology every route plus
K core value is weighed, descending sort is carried out according to the size of weighting K core value to route, so that it is determined that the critical circuits of system.
The beneficial effects of the present invention are:
(1) the present invention is based on high-speed rail part throttle characteristics, establish the pdf model of high-speed rail load impact characteristic, for containing height
Electric network swim calculating under the effect of iron impact load lays the foundation；
(2) effective power flow of the network constraint information between transmission line of electricity is considered in the present invention, and is based on electric power networks object
The vulnerable line discrimination method of attribute and static parameter is managed, there is preferably identification accuracy and validity；
(3) present invention can inhibit cascading failure communication strategy to provide new thinking to instruct electric power networks to develop, finding,
It is of great significance for the planning and safe and stable operation of electric system.
Detailed description of the invention
(a) is high-speed rail daily load probability density in Fig. 1, and (b) is that high-speed rail daily load probability is close after rejecting zero load in Fig. 1
Degree.
Fig. 2 is IEEE39 node system figure.
Fig. 3 is physics wiring and correlation networks mapping graph.
Fig. 4 is weighting K nuclear decomposition process.
Fig. 5 is network adjacent node structure chart.
Fig. 6 is transmission line of electricity weighting K core value column diagram.
Fig. 7 is system mistake load accounting line chart after calculated attack.
Specific embodiment
With reference to the accompanying drawing, the present invention is further described in detail.
The present invention is based on the identifications of traditional vulnerable line to rarely have the deficiency for considering high-speed rail fluctuating load, and it is high to propose a kind of consideration
The vulnerable line discrimination method of iron fluctuating load.This method is based on actual measurement high-speed rail load data, using in probabilistic load flow
Monte-carlo Simulation Method proposes a kind of vulnerable line considered under high iron load effect using improved weighting K- core index
Discrimination method.Specific embodiment is as follows:
Step 1: calculating the Monte Carlo the N-1 Probabilistic Load Flow for considering high-speed rail part throttle characteristics
(1) high-speed rail impact load specificity analysis
The characteristics of frequent random fluctuation is presented in high-speed rail traction substation load.According to certain substation's measured data, 2018 3
Month high iron load average accounting 10.21% in electric system total load, maximum accounting 33.82%, peak load reaches
49.6MW.Therefore, high iron load has random fluctuation, impact characteristics.
(2) high-speed rail Load Probability model is established
High iron load is set as stochastic variable X, the probability density statistical chart of high-speed rail part throttle characteristics can be obtained, such as Fig. 1 (a) institute
Show.It can be seen that high iron load from its probability density statistical chart and bi-distribution be totally presented, there are an extremely strong sharp cutting edge of a knife or a sword arteries and veins
Punching, this spike are in the position that load is zero, and the probability for showing that zero load occurs is very big.Practical high-speed rail route fortune
When row, because two power supply arm lengths about 60km of an AT power supply system, are not to have EMU to lead at one all the time
Draw and run on two supply arms of electric substation, this has resulted in the intermittence of load of traction substation, and intermittent very frequent.
Meanwhile if zero load rejected from data, high iron load shows apparent normal distribution again, such as Fig. 1 (b)
It is shown.From Fig. 1 (b) as can be seen that high-speed rail load density function more agrees with normal distribution.Therefore, by the general of high iron load
Rate density resolve into be normal distribution and bi-distribution combination.Only there are two types of possible knots in each test of bi-distribution
Fruit, and it is mutually indepedent whether two kinds of results generations.The load of one traction substation or be zero or non-zero, it is assumed that high
The case where probability that the case where iron load is zero occurs is p, high iron load non-zero probability of occurrence is 1-p, in the probability of this 1-p
Under to think that high iron load obeys mean value be μ, variance σ2Normal distribution N (μ, σ2).Therefore the probability density function of high iron load
It is represented by formula (1).
It is carried out generating high-speed rail load simulation data Shi Kecong following two step, each value of stochastic variable is mutually only
It is vertical.
Step1: first generating a random number R between 0~1, if R < p, high-speed rail load value X=0 terminates.Otherwise turn
Enter step 2.
Step2: taking an obedience mathematic expectaion at random is μ, variance σ2Normal distribution value as high-speed rail load value, if
X=0 then gives up this value, is transferred to step 1, otherwise terminates.
(3) the N-1 trend based on Monte Carlo Analogue Method is calculated
It, will be in IEEE node system in conjunction with the probabilistic model of high iron load in order to consider fluctuation, the impact of high iron load
Several representative loads (1,8,20,39, as shown in Figure 2) be substituted for high iron load.Then Monte Carlo Analogue Method is utilized, according to
One group of load data is generated according to high-speed rail Load Probability model, N-1 probabilistic load flow is carried out, obtains each branch active power value.
It computes repeatedly 5000 times, obtains the calculated result of 5000 groups of branch powers.The mathematics of each branch is sought with the method for probability statistics
It is expected that.
Step 2: the correlation networks of electric power networks are constructed according to branch power coupled relation
It is verified according to N-1, if cut-offfing for branch can cause the active power of another branch to change, that
It can think that there are correlations between two transmission lines of electricity.As shown in figure 3, using the transmission of electricity branch in former power grid as correlation
The node of property network；Cause other branch power increments as the side right in correlation networks using after branch breaking, thus constructs
One bidirectional weighting network.
Step 3: recognizing vulnerable line using weighting K nuclear decomposition method
Classical K nuclear decomposition process is the recursive node removed all angle value in network and be less than or equal to K.In view of phase
The weighting characteristic of closing property network, improves traditional K nuclear decomposition, as shown in Figure 4 as follows.In weighting K nuclear decomposition, node
The node is only subtracted when removal to the strength of association of adjacent node, retains influence of the adjacent node to the node.Most from weighting degree
Small node starts successively to decompose, and obtains the K core value of each node in correlation networks.Since the node of network edge still may
High accumulation phenomenon, i.e., high K core value, small influence power is presented.Therefore using the K core value of node and its adjacent node and secondary adjacent node come
Accuracy of identification is improved, as shown in figure 5, i.e.
In formula, Ks_d (i) is the depth K core value of node i, reflects the influence power of node i；Ks (i) is the K core value of node i；
ijIndicate that the adjacent node of node i concentrates j-th of node, ΩiFor the adjacent node collection of node i；Indicate node ijK-th
Adjacent node,Indicate node ijAdjacent node collection, m0Indicate the K core value weight of node i, m1Indicate the adjacent section of node i
The weight of the sum of point K core value, m2Indicate the weight of the sum of secondary adjacent node K core value of node i, and m0+m1+m2=1；Obviously,
The value of Ks_d is bigger, and corresponding transmission line of electricity is more fragile；
It is analyzed using IEEE-39 node system as example, topological structure is as shown in Figure 2.According to the method for the present invention
The weighting K core value of every route is calculated, as shown in Figure 6.Descending sort is carried out according to the size of weighting K core value to route, thus
Determine the critical circuits of system.If the big route of weighting K core value is destroyed, massive blackout accident is just very likely resulted in.
Table 1 gives preceding 10 critical circuits in identification ranking results.
Table 1
From the point of view of recognition result, route 46,33,37,20,34,39 be generator egress line, therefore in structure it
Be in important passway for transmitting electricity.But the system shares 10 generator outlet routes, wherein No. 39 generators issue and active are
1000MW, and the generator being connected with above-mentioned route issues active mostly 500 or 600MW, but the branch being connected with No. 39 generators
Road 2 and 17 is simultaneously not belonging to important branch.Because being connected to one big load (1104MW), the load of generator on 39 nodes
It dissolves nearby, the power transmitted on branch 2 and 17 is in fact and little.This illustrates that this method not only allows for the structure spy of route
Property, it is also contemplated that the state characteristic of route reflects the correctness of discrimination method.
In order to analyze the validity of this method identification result, route is attacked according to the sequence and random selection of identification result
Mode carries out static calculated attack to electric power networks, the mistake load and other branches of system after every route of statistics is attacked
The out-of-limit situation of power.Using the mistake load condition of system after certain line disconnection as the measurement index of influence system safety, compare
System loses load condition in the case of two kinds.
Specific step is as follows:
Step 1: according to vulnerable line identification result, selecting initial attack route.
Step 2: record faulty line updates network structure.
Step 3: island disposal carries out AC power flow calculating.
Step 4: judging whether there is that Line Flow is out-of-limit, if so, then cut-offfing the out-of-limit route of power, be transferred to step 2, otherwise
It is transferred to step 5.
Step 5: calculating the fault chains that the system caused by initial plant failure is lost load condition and caused by the route.
Then judge whether route is attacked to finish, if so, terminating process, be otherwise transferred to step 1.
Fig. 7 list preceding 5 critical circuits and stochastic line attack as a result, from the attack results of preceding 5 critical circuits
As can be seen that system loses load and is much larger than attacking at random as a result, illustrating this after preceding 5 routes of this method are under attack
The validity of discrimination method.
There is a small amount of long-range connection line in power grid, so that the volume load bus and generator node in network keep smaller
Electrical distance.After these line faults, the ability to transmit electricity of network can be greatly reduced.Route in IEEE39 node system
27 are just belonging to this kind of route, and cut-offfing for it directly results in system sectionalizing, form two isolated islands, 19,20,33,34 shape of interior joint
It include two generators and a load in island, the generated energy for needing to cut off close to half could maintain system at small isolated island
It operates normally.Other hand, another isolated island lead to that a large amount of loads must be cut off, but also lead due to generated energy deficiency
The excision of subsequent route is caused.Therefore, the normal operation of route 27 ensure that the power of 33, No. 34 generators can normally be sent outside,
In crucial transmission of electricity position, the validity of this method is illustrated.
In the emulation of cascading failure, the probability that every route occurs in fault chains has been counted, wherein non-power generator line
The probability that road 3,27,23 occurs in fault chains is respectively 0.67,0.43 and 0.49, shows that this three-line is easy by other
The interference of failure is the weak link of system, illustrates the correctness of this method.
Vulnerable line identification algorithm meter proposed by the present invention and high-speed rail load fluctuation characteristic, it is contemplated that the design feature of route
With state characteristic, vulnerable line is recognized using improved K nuclear decomposition method.Identification result is the fragile ring in system
Section, shows bigger load loss during calculated attack than randomly selected route.Therefore, this method is electric to finding
Force system cascading failure blocking strategy, the safety operation level for improving system and prevention power grid have a power failure on a large scale and have important meaning
Justice.
Claims (2)
1. the power grid vulnerable line discrimination method under a kind of meter and the effect of high-speed rail impact load, which is characterized in that consider first high
The random fluctuation characteristic of iron load, establishes the probabilistic model of high iron load, and N-1 probability is then carried out in IEEE39 node system
Load flow calculation；The correlation networks of electric system are established according to N-1 probabilistic load flow result；Finally, in correlation networks
On the basis of using weighting K nuclear decomposition method Identification of Power System in vulnerable line；Include the following steps:
Step 1: the modeling of high-speed rail part throttle characteristics
Firstly, according to the characteristics of high iron load big ups and downs and its probability density distribution, normal distribution and bi-distribution are utilized
Combination establishes the probabilistic model of high iron load, such as formula (1)；
In formula, f (x) indicates the probability density of high iron load, and x indicates that high-speed rail load values, p indicate general when high iron load is zero
Rate, μ indicate the mean value of high iron load, and σ indicates the variance of high iron load；
It is carried out when generating high-speed rail load simulation data by following two step, each value of stochastic variable is mutually indepedent；
Step1: first generating a random number R between 0~1, if R < p, high-speed rail load value X=0 terminates；Otherwise it is transferred to step
Rapid 2；
Step2: taking an obedience mathematic expectaion at random is μ, variance σ2Normal distribution value as high-speed rail load value, if X=0,
Then give up this value, is transferred to step 1, otherwise terminates；
Step 2: calculating the Monte Carlo the N-1 Probabilistic Load Flow for considering high-speed rail part throttle characteristics
Several critical loads therein are substituted for height using IEEE39 as analysis object in conjunction with the probabilistic model of high iron load
Iron load；Then 5000 N-1 probabilistic load flows are carried out to system using Monte Carlo Analogue Method, obtaining 5000 groups of branches has
Function performance number recycles probabilistic method to find out its mathematic expectaion；
Step 3: the correlation networks of electric system are constructed according to branch power coupled relation
The topological structure feature of power grid and the state characteristic of system operation are considered in order to balance, establish the correlation of electric system
Network；Based on the foundation of the correlation networks probabilistic load flow of the N-1 in step 1, it is with the transmission line of electricity in former power grid
Node, being increased with the trend of caused All other routes after the line disconnection is that side right constructs a new network, claims the network
For the correlation networks of original power system；
Step 4: recognizing vulnerable line using weighting K nuclear decomposition method
The correlation networks established in step 3 are bidirectional weighting networks, are improved to traditional K nuclear decomposition, in weighting K core point
Xie Zhong, node only subtract the node to the strength of association of adjacent node, retain influence of the adjacent node to the node when removing；From
The smallest node of weighting degree starts successively to decompose, and obtains the K core value of each node in correlation networks；Due to the node of network edge
Still high accumulation phenomenon, i.e., high K core value, small influence power may be presented；Therefore utilize node and its adjacent node and secondary adjacent node
K core value improve accuracy of identification, i.e.,
In formula, Ks_d (i) is the depth K core value of node i, reflects the influence power of node i；Ks (i) is the K core value of node i；ijTable
Show that the adjacent node of node i concentrates j-th of node, ΩiFor the adjacent node collection of node i；Indicate node ijK-th of adjoining
Node,Indicate node ijAdjacent node collection, m0Indicate the K core value weight of node i, m1Indicate the adjacent node K core of node i
The weight of the sum of value, m2Indicate the weight of the sum of secondary adjacent node K core value of node i, and m0+m1+m2=1；Obviously, Ks_d
Value is bigger, and corresponding transmission line of electricity is more fragile；
It is analyzed using IEEE-39 node system as example, the weighting K core of every route in calculate node system topology
Value carries out descending sort according to the size of weighting K core value to route, so that it is determined that the critical circuits of system.
2. a kind of validation verification method of power grid vulnerable line discrimination method as described in claim 1, which is characterized in that be
The validity of analysis this method identification result, to electric power in the way of the sequence of identification result and random selection attack route
Network carries out static calculated attack, the out-of-limit feelings of power for losing load and other branches of system after every route of statistics is attacked
Condition；Using the mistake load condition of system after certain line disconnection as the measurement index of influence system safety, compare in the case of two kinds
System loses load condition；
Specific step is as follows:
Step 1: according to vulnerable line identification result, selecting initial attack route；
Step 2: record faulty line updates network structure；
Step 3: island disposal carries out AC power flow calculating；
Step 4: judging whether there is that Line Flow is out-of-limit, if so, then cut-offfing the out-of-limit route of power, be transferred to step 2, be otherwise transferred to
Step 5；
Step 5: calculating the fault chains that the system caused by initial plant failure is lost load condition and caused by the route；Then
Judge whether route is attacked to finish, if so, terminating process, is otherwise transferred to step 1.
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| CN110146785A (en) * | 2019-05-22 | 2019-08-20 | 南京工程学院 | A kind of vulnerable line recognition methods of power grid containing wind-solar power supply |
| CN110350522A (en) * | 2019-07-10 | 2019-10-18 | 西南交通大学 | A kind of electric system vulnerable line identifying method based on Weighted H index |
| CN111313408A (en) * | 2020-03-05 | 2020-06-19 | 西南交通大学 | Power grid fragile line identification method considering transient energy correlation |
| CN112003734A (en) * | 2020-07-28 | 2020-11-27 | 长沙理工大学 | Improved structure entropy based key node identification method for information physical system |
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