CN111313408B - Power grid fragile line identification method considering transient energy correlation - Google Patents
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Abstract
The invention discloses a power grid fragile line identification method considering transient energy correlation, which comprises the following steps: mapping the power grid branches into nodes to generate an unauthorized network according to the serial numbers of the power transmission lines of the power system; simulating and calculating branch potential energy according to the N-2-stage interlocking fault, and giving the side right to the unlicensed network; and then, calculating point weights based on the side weights, and identifying key nodes of the network according to a branch potential energy Talar entropy method, so as to obtain key fragile line numbers in the power grid. The method can quickly and effectively identify the fragile branch which plays a key role in fault propagation, and then adopts corresponding solution measures to improve the safe operation level of the large power grid and show the practical engineering application value.
Description
Technical Field
The invention relates to the technical field of vulnerability assessment and safe operation assessment of a power system, in particular to a power grid fragile line identification method considering transient energy association.
Background
In recent years, with the gradual development of uncertain power sources such as wind power and photovoltaic power, impact loads such as high-speed rails and the like, the scale of a power system is gradually enlarged, the structure is more and more complex, internal and external factors can influence the safety and stability of the operation of the power system, the cascading failure of the system can be easily caused under the condition of some sudden failures, large-area power failure is caused, and great challenges are brought to the safety and stability operation of a power grid. And large-scale power failure accidents have serious influence on the life and social order of people. In 2019, the number 8 and 5 printing ni is affected by more than 3000 thousands of people who have a major power failure accident due to the failure of the power transmission line, and power supply is recovered in 9 hours. In 2019, 8 and 9, a large-scale power failure accident occurs in england and wilson areas of uk. The direct cause of the accident is that the gas turbine set and the offshore wind turbine set continuously jump to cause a large power shortage of the system. The system frequency is greatly reduced to trigger the low-frequency load shedding device, and finally, power failure occurs in partial areas. In the development process of these power failure accidents, although the forms of the power failure accidents are different, most of the power failure accidents start from the failure or overload of one element of the system, and then cause the successive failures of the elements. Research has shown that certain critical lines or components in the system play an important role in the fault propagation process. The accurate and rapid identification of the key lines has important significance for the prevention and safe operation of the grid cascading failure. At present, the vulnerability analysis of the power system is mostly based on a complex network theory, and the vulnerability of the system is evaluated by taking the electric medium number, the transmission medium number and the tidal current medium number as indexes. In addition, the vulnerability assessment method based on the probability theory, such as the method based on the risk theory, the Monte Carlo simulation method and the like, reflects the safety level of the actual operation of the system, but has large calculation amount and is difficult to apply on line.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide a method for identifying a fragile line of an electrical power system, which accurately and quickly identifies the fragile line of the electrical power system, and takes active defense measures to reduce the power failure risk caused by a fault as much as possible, and improve the safety and stability of the operation of the power grid. The technical scheme is as follows:
a grid fragile line identification method considering transient energy correlation comprises the following steps:
step 1: mapping the branch into nodes according to the serial number of the transmission line in the power grid to generate an empty graph;
step 2: based on the 2-stage interlocking fault simulation traversal of the N power transmission lines, calculating branch potential energy;
and step 3: establishing a connecting edge in the empty graph according to the potential energy change of the branch, giving the potential energy of the branch as a weight, and establishing a state transfer related network of the power system;
and 4, step 4: identifying the importance of nodes in the state transition related network according to a branch potential energy Talar entropy identification method, and sequencing the nodes from high to low according to indexes to form a node importance sequence;
and 5: and obtaining branch serial numbers of fragile lines in the power grid according to the corresponding relation between the nodes in the state transfer related network and the original power system branches.
Further, the specific method for calculating the branch potential energy is as follows:
step 21: calculating load flow data of the power system in normal operation;
step 22: sequentially cutting off one branch according to the line number, and calculating the active power variation, the reactive power variation, the voltage angle difference variation and the voltage amplitude difference variation of each branch when the network runs under the N-1 fault;
step 23: judging whether the remaining branches have the situation of power flow out-of-limit under the N-1 fault; if yes, the branch m is considered to be broken due to the fact that the first branch k is broken, the branch m is continuously broken, and active power variation, reactive power variation, voltage phase angle difference variation and voltage amplitude difference variation of each remaining branch under the condition of remaining N-2 faults are recalculated;
step 24: calculating branch potential energy variation of the rest branches caused by the branch K being disconnected according to the branch data of the network under the fault condition and in normal operation;
if the N-2 fault does not occur, calculating branch potential energy of the remaining N-1 branches by using branch potential energy of the network under the condition of the N-1 fault;
and if the N-2 fault occurs, calculating the branch potential energy of the branch m which is disconnected for the second time by using the branch data calculated under the N-1 fault condition, and calculating the branch potential energy of the rest N-2 branches by using the branch data calculated under the N-2 fault condition.
Further, when calculating branch potential energy of the remaining branches to establish a continuous edge in the null graph and weighting the continuous edge:
if the N-2 fault does not occur, the connection edge weight of the branch possibly connected with the k node in the empty graph is the branch potential energy variation of the remaining branch after the k branch is disconnected in the power grid;
if an N-2 fault occurs, the connecting edge weight of a branch (i-j) taking a k branch which is disconnected for the first time and a m branch which is disconnected for the second time as nodes in the empty graph is the branch potential energy variation of the branch m under the fault condition of N-1, and the connecting edge weight of the possible branches which are connected with the k node is the residual branch potential energy variation under the fault condition of N-2.
Furthermore, the method for identifying the Taier entropy based on the branch potential energy further comprises the following steps:
step 41: calculating the point weight of the node u in the state transition related network:
wherein, gamma isuA set of adjacent nodes that are nodes u; euvFor an edge e in a state-dependent networkuvThe continuous side weight is the variable quantity of the potential energy of the v branch caused by the opening and closing of the u branch;
step 42: calculating the continuous edge weight normalization value of the edges u-v:
step 43: calculating the degree of the node u:
nu＝(nu++nu-)/2
wherein n isu+Is the sum of potential energy variations of other branches caused by the disconnection of the corresponding u branch in the power grid, nu-The sum of the potential energy variations of the u branch caused by the disconnection of the corresponding other branches in the power grid;
step 44: calculating branch potential energy entropy degree of a node u in the state transition related network:
the invention has the beneficial effects that: according to the invention, the potential energy accumulation condition of the residual branch after the 2-stage interlocking fault traversal of the N transmission lines is considered, and the continuous edge is constructed and weighted. The active and reactive power changes of network tide after faults caused by disturbance, and the amplitude and phase changes of bus voltage are fully considered, the topological structure characteristics and the state characteristics of the network are combined, and the vulnerability of the branch is more comprehensively evaluated. The power grid constrained by the kirchhoff law is converted into a complex network, and the vulnerability assessment problem of the branch is converted into a node vulnerability assessment problem which is better processed. The state transfer network taking branch potential energy as weight can comprehensively reflect the topological structure and the state characteristic of the power grid. Secondly, the information entropy theory is introduced into the vulnerability assessment research of the power system to characterize the disorder degree and the unbalance degree of the system.
Drawings
Fig. 1 is a diagram of an IEEE39 node system architecture.
Detailed Description
The invention is described in further detail below with reference to the figures and specific embodiments.
In this embodiment, taking an IEEE39 node system as an example, the specific steps of the power grid fragile line identification method based on consideration of branch potential energy and talr entropy are described in detail:
step 1: and mapping the empty graph, constructing a continuous edge and assigning a weight to the continuous edge: sequentially mapping the power grid branches into nodes to generate an empty graph according to the serial numbers of the power transmission lines of the power system; calculating residual branch potential energy according to branch data variable quantities including active power variable quantities, reactive power variable quantities, voltage phase angle difference variable quantities and voltage amplitude difference variable quantities under the condition of 2-stage interlocking fault simulation traversal of the N power transmission lines, constructing a connecting edge and giving the branch potential energy to the weight of the connecting edge; the method comprises the following specific steps:
sequentially mapping N nodes in the empty graph according to the serial numbers of the power transmission lines from 1 to N of the power grid;
calculating the initial steady-state load flow of the system in normal operation by using MATPOWER;
calculating the transient energy variation of the k-th branch m after the branch is disconnected based on the formula (1):
in the formula, i and j are the node numbers of the branch m,
and
respectively the phase angle difference delta of the branch m (i-j) in the power gridijDifferential voltage UijActive power PijAnd reactive power QijCorresponding initial state values. GijIs the conductance of branch i-j, BijSusceptance, U, for branch i-jiAnd UjThe voltage amplitudes of node i and node j, respectively. cos deltaijAnd sin deltaijThe cosine value and sine value of the branch phase angle.
And according to the serial number of the line, performing a line disconnection experiment from the line 1 to the line N in sequence, calculating the active power variation, the reactive power variation, the voltage phase angle difference variation and the voltage amplitude difference variation of the remaining branches of the N-1 network, and then calculating the transient energy variation. And if the active power distribution of the branch m exceeds the line load capacity of the branch k after the branch k is disconnected, considering that the k line fault causes an m line fault, continuously disconnecting the m line, recalculating the active power variation, the reactive power variation, the voltage angle difference variation and the voltage amplitude difference variation of the remaining lines of the N-2 network, and then calculating the transient energy variation.
If the N-2 fault does not occur, calculating branch potential energy of the remaining N-1 branches by using branch potential energy of the network under the condition of the N-1 fault; and if the N-2 fault occurs, calculating the branch potential energy of the branch m which is disconnected for the second time by using the branch data calculated under the N-1 fault condition, and calculating the branch potential energy of the rest N-2 branches by using the branch data calculated under the N-2 fault condition.
And constructing continuous edges in the empty graph according to the transient energy change, and giving weights to the continuous edges.
If the N-2 fault does not occur, the connection edge weight of the branch possibly connected with the k node in the empty graph is the branch potential energy variation of the remaining branch after the k branch is disconnected in the power grid; if an N-2 fault occurs, the connecting edge weight of a branch (i-j) taking a k branch which is disconnected for the first time and a m branch which is disconnected for the second time as nodes in the empty graph is the branch potential energy variation of the branch m under the fault condition of N-1, and the connecting edge weight of the possible branches which are connected with the k node is the residual branch potential energy variation under the fault condition of N-2.
Step 2: the weak branch evaluation method considering branch potential energy and Tahr entropy comprises the following steps: counting node point weights according to the given side weights, identifying key nodes of the network according to a branch potential energy Tyr entropy method, and sequencing branch potential energy entropy degrees PEED to obtain a node importance sequence in the state transition related network; and obtaining the fragile line number of the original system according to the corresponding relation between the state transfer correlation network and the original power system. The method comprises the following specific steps:
according to the information entropy theory, there is a Taler entropy index of the unbalance degree of the computing system as formula (2):
where n represents the number of uncertainty events in the system, xiRepresents the probability of occurrence of the ith uncertainty event, and h (x) represents the actual information entropy value of the system. The larger the tyler entropy the more unbalanced the system.
Introducing a Talar entropy index into the power system, taking the degree of a node u (a branch u in the original power system) as the uncertainty corresponding to the disconnection of the branch, and defining potential energy entropy according to a preset node side weight:
in formula (3), PEEDuThe potential energy entropy of a branch circuit for switching on and off a power transmission line u, u and v are node numbers in a state-related network, and nuDegree, Γ, of a node u in a state-dependent networkuIs a set of contiguous nodes to node u. Definition EuvIn a state-dependent networkEdge euvAnd the point weight of the node u is as follows:
puvfor the edge weights e in state-dependent networksuvNormalization value:
wherein, the degree of the node u is defined as:
in the formula, nu+Is the sum of potential energy variations of other branches caused by the disconnection of the corresponding u branch in the power grid, nu-And the sum of the potential energy variation of the u branch is caused by the disconnection of the corresponding other branches in the power grid.
According to the Tyr entropy definition, when the branch potential energy entropy degree PEED is larger, the branch potential energy distribution in the system is more unbalanced due to tide impact after the branch u is opened and disconnected, the branch potential energy is mainly accumulated on a certain line in the system, the branch in the system is more easily overloaded, and even cascading failure is caused; on the contrary, the smaller the branch potential energy entropy degree PEED is, the more balanced the system potential energy distribution caused by the tidal current impact is represented, the branch with large capacity bears more tidal current impact, the branch with small capacity bears less tidal current impact, and the system is in a relatively balanced state. The index effectively identifies the influence of the tidal active power and the reactive power of the electric power system on the branch potential energy, and is closer to the actual operation condition of the electric power system. The vulnerability of different branches of the system can be reflected by sequencing the PEEDs.
Simulation verification:
in order to verify the effectiveness and the practicability of the method, an IEEE39 node system (comprising 39 nodes and 46 branches) is selected as a force to perform simulation verification on the method and the model, and the structure diagram of the IEEE39 node system is shown in figure 1. Attacking the branches in sequence according to the line numbers, calculating the transient potential energy of the rest branches, calculating the potential energy entropy degree PEED of the branch, and sorting the branches from high to low according to the PEED size as shown in Table 1.
Table 1 IEEE39 Branch potential energy Tyr entropy PEED sequencing result
The line vulnerability attack can be used for identifying the influence degree of the fault on the system, and on the basis, the AC-OPA model is adopted to carry out deliberate attack on the line according to the serial number so as to verify the effectiveness of the invention. The simulation times are set to be N times, and the average load loss of each line after being attacked is calculated, as shown in (7).
Wherein, Ploss(i) And the average load loss rate of the system after the ith line is attacked is shown. Obviously, Ploss(i) The larger the branch, the more fragile it is. From PlossThe derived weak line ordering is called a Cascading Failure Simulation (CFS) ordering.
The first n straight lines identified by the proposed method are compared with the first n straight lines in the CFS sequence. If there are k lines matching the CFS sequence, we define the recognition accuracy as k/n.
TABLE 2 alignment of Branch potential energy Tyr entropy sequences and CFS sequences in IEEE39 node system
Table 2 shows the comparison result of the recognition result of the branch potential entropy degree with the first 17 lines of the CFS sequence, wherein the first column represents the branch importance degree, the second column is the CFS fragile line sequence, and the third column is the fragile line sequence recognized by the branch potential entropy degree. In the most fragile 17 lines, 17 lines are all consistent with the CFS sequence, and the precision is 100%, which shows that the method is reliable and effective and has better precision compared with other methods.
Claims (3)
1. A grid fragile line identification method considering transient energy correlation is characterized by comprising the following steps:
step 1: mapping the branch into nodes according to the serial number of the transmission line in the power grid to generate an empty graph;
step 2: based on the 2-stage interlocking fault simulation traversal of the N power transmission lines, calculating branch potential energy;
and step 3: establishing a connecting edge in the empty graph according to the potential energy change of the branch, giving the potential energy of the branch to the weight of the connecting edge, and establishing a state transition related network of the power system;
and 4, step 4: identifying the importance of nodes in the state transition related network according to a branch potential energy Talar entropy identification method, and sequencing the nodes from high to low according to indexes to form a node importance sequence;
the method for identifying the Taier entropy based on the branch potential energy specifically comprises the following steps:
step 41: calculating the point weight of the node u in the state transition related network:
wherein, gamma isuA set of adjacent nodes that are nodes u; euvFor an edge e in a state-dependent networkuvThe continuous side weight is the variable quantity of the potential energy of the v branch caused by the opening and closing of the u branch;
step 42: calculating the continuous edge weight normalization value of the edges u-v:
step 43: calculating the degree of the node u:
nu＝(nu++nu-)/2
wherein n isu+Is the sum of potential energy variations of other branches caused by the disconnection of the corresponding u branch in the power grid, nu-The sum of the potential energy variations of the u branch caused by the disconnection of the corresponding other branches in the power grid;
step 44: calculating branch potential energy entropy degree of a node u in the state transition related network:
and 5: and obtaining branch serial numbers of fragile lines in the power grid according to the corresponding relation between the nodes in the state transfer related network and the original power system branches.
2. The method for identifying the vulnerable line of the power grid considering the transient energy correlation as claimed in claim 1, wherein the specific method for calculating the branch potential energy is as follows:
step 21: calculating load flow data of the power system in normal operation;
step 22: sequentially cutting off one branch according to the line number, and calculating the active power variation, the reactive power variation, the voltage angle difference variation and the voltage amplitude difference variation of each branch when the network runs under the N-1 fault;
step 23: judging whether the remaining branches have the situation of power flow out-of-limit under the N-1 fault; if yes, the branch m is considered to be broken due to the fact that the first branch k is broken, the branch m is continuously broken, and active power variation, reactive power variation, voltage phase angle difference variation and voltage amplitude difference variation of each remaining branch under the condition of remaining N-2 faults are recalculated;
step 24: calculating branch potential energy variation of the rest branches caused by the branch K being disconnected according to the branch data of the network under the fault condition and in normal operation;
if the N-2 fault does not occur, calculating branch potential energy of the remaining N-1 branches by using branch potential energy of the network under the condition of the N-1 fault;
and if the N-2 fault occurs, calculating the branch potential energy of the branch m which is disconnected for the second time by using the branch data calculated under the N-1 fault condition, and calculating the branch potential energy of the rest N-2 branches by using the branch data calculated under the N-2 fault condition.
3. The method for identifying the fragile line of the power grid considering the transient energy correlation as claimed in claim 2, wherein when calculating branch potential energy of the remaining branches to establish the connected edges in the null graph and weighting the connected edges:
if the N-2 fault does not occur, the connecting edge weight of the branch connected with the k node in the empty graph is the branch potential energy variation of the rest branches after the k branch is disconnected in the power grid;
if an N-2 fault occurs, the connecting edge weight of a branch with a k branch which is disconnected for the first time and a m branch which is disconnected for the second time as nodes in the null graph is the branch potential energy variation of the branch m under the fault condition of N-1, and the connecting edge weight of the branch which is connected with the k node is the residual branch potential energy variation under the fault condition of N-2.
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