CN114998051B - Maximum flow theory-based key line identification method for electric-gas coupling system - Google Patents
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Abstract
The invention discloses a method for identifying key lines of an electric-gas coupling system based on a maximum flow theory, which is based on the maximum flow theory and combines with a complex network theory, so that the traditional line medium number is improved, the defect that the energy or power among nodes of a comprehensive energy system is always transmitted along the shortest path among the nodes is overcome, all possible transmission paths of the comprehensive energy system are considered, and the characteristics of the comprehensive energy system are more met. Meanwhile, from the two aspects of structural importance and state importance of the circuit, a circuit comprehensive importance index reflecting the centrality and transmission bearing capacity of the circuit structure is established, so that the identification of the key circuit of the comprehensive energy system is more accurate and reliable, and a new thought and method for the identification of the key circuit of the comprehensive energy system are provided. The invention can be used for identifying key lines of a comprehensive energy system, can be popularized and used for identifying key lines of a thermodynamic system, a traffic system, a logistics system and other large-scale complex systems, and has wide application value.
Description
Technical Field
The invention relates to the field of comprehensive energy system safety and reliability, in particular to identification of key and fragile lines of a system, and prevention and blocking of system faults.
Background
At present, new energy is rapidly developed, new energy is greatly developed in all countries of the world so as to change the energy development mode, reduce environmental pollution and optimize the structure of traditional energy, and the new energy will play more and more roles in the future. The social development has greatly increased the coupling degree of natural gas system and electric power system to the demand of clean energy, and comprehensive energy system has brought forward the bright prospect of rapid development, has also put forward higher requirement to comprehensive energy system operational reliability and security simultaneously. The current research mainly focuses on modeling simulation, planning optimization and fault evaluation of the system, and the vulnerability evaluation for the comprehensive energy system is less. However, the weak link of the system has a great influence on the safe and reliable operation of the system, and once the system fails, serious safety accidents and huge economic losses are likely to be caused. Therefore, in order to prevent and block cascading failures of the integrated energy system and improve the reliability of the system, it is necessary to explore a method capable of rapidly and accurately identifying key circuits of the integrated energy system.
At present, the identification of the fragile links is mainly focused on a power system, and the related research on a comprehensive energy system is very few. Chen Xiaogang et al (2006) improve the original line betweenness to weighted line betweenness based on complex network theory to identify key lines of the power system. However, the shortest path of this approach does not meet the practical situation of the power system. The following studies have all made improvements in overcoming the shortcomings of the shortest path: liang Cai et al (2013) propose the concept of tide betters, which considers the directionality of the power grid and the specific of tide distribution, and is more in line with the characteristics of the power grid; ju Wenyun et al (2012) define a line transmission importance index based on maximum current and complex network theory in combination with power transmission distribution factors in the grid direct current power flow; wang Tao et al (2014) propose a concept of power betweenness based on power flow tracking, taking into account the system power flow analysis results; liu Xiaoli et al (2016) provide comprehensive medium indexes in consideration of factors such as relay protection vulnerable contribution degree, node voltage change, geographical environment and the like, so that vulnerable lines can be more comprehensively identified; liu Yu et al (2019) construct a cascading failure time-space diagram with both grid accident chain timing and spatial distribution characteristics for identifying the propagation mechanism of the vulnerable line barrier of the power system and the influence caused by the propagation mechanism. However, the above work is performed on an electric power system and is not expanded to a comprehensive energy system. Wang Xunting et al (2018) only evaluate the vulnerability of the integrated energy system from topology and energy flow, but do not identify critical lines; tao Chunyi (2021) proposes a weak link identification of an electric comprehensive energy system based on a time Petri network, and mainly considers the cause relation and time sequence difference of cascading failures; li Caibao et al (2021) identified the critical lines of the distribution grid in the integrated energy system and evaluated the elasticity of the integrated energy system, but did not identify the critical lines of the entire system; wang Bo et al (2022) to identify key lines of the integrated energy system from a data driven perspective; chen Lijuan et al (2021) propose toughness indexes for the robustness of the comprehensive energy system under extreme disasters, and consider the change of source load and the randomness of faults at the same time, so as to judge the weak points of the comprehensive energy system; huang Kuian et al (2021) identified the integrated energy system based on complex network theory and improved the line betweenness, but did not overcome the shortcomings of the minimum path, unlike the actual situation of the integrated energy system.
At present, the identification research of key circuits is mainly focused on a power system, and the research of the key circuits of the comprehensive energy system is in a starting stage, so that the comprehensive energy system has a wide development space.
Disclosure of Invention
The invention mainly overcomes the defects in the prior art, and aims to provide an electric-gas coupling system key line identification method based on a maximum flow theory.
In order to achieve the technical purpose, the invention adopts the following technical scheme:
the method for identifying the key circuit of the electric-gas coupling system based on the maximum flow theory is characterized by comprising the following steps:
s1: and establishing a network topological graph of the electric-gas coupling system, and simplifying equipment and branches into nodes and edges of the graph. Wherein, the power supply and the air source are used as a source point s, the gas turbine and the P2G (electric conversion gas) are used as intermediate connection nodes, the electric load for the terminal is used as a sink point t, and the power transmission and the gas transmission pipelines are used as edges.
S2: let the electric-gas coupling system network g= (V, E), V represents the nodes of the system, E represents the edges of the system, eachThe edges all have a capacity c (v i ,v j ) Abbreviated as c ij The flow rate of the edge is f (v i ,v j ) E, abbreviated as f ij . The network maximum flow mathematical model of the electro-pneumatic coupling system is:
max v(f)
i.e. the source ingress is 0, the sink egress is 0, the ingress of the intermediate node is equal to the egress, and the traffic on each edge is less than its capacity. The network flow v (f) satisfying such a condition in the capacity network G is called a feasible flow.
S3: because the energy sources of the power grid and the gas grid are different, natural gas flow is converted into power, and the power grid are calculated under a unified frame:
W g ＝ζHQ
wherein: w (W) g Is converted natural gas power; zeta is the electricity generation efficiency of natural gas combustion; h is the heat value of natural gas; q is the mass flow of natural gas.
S4, because the maximum flow problem is single source and single sink, and the electric-gas coupling system is a multi-source and multi-sink network, a virtual source point S and a sink point T are arranged in the electric-gas coupling system and are respectively connected with all source points and sink points, and the capacity of the edge is set to be infinite.
S5: a feasible path from a source to a sink, where network flows on the path can increase at least the minimum capacity of the edges in the path, is called an augmented path. The amplified path was searched using the Fold-Fulkerson algorithm. The Fold-Fulkerson algorithm search procedure is as follows:
initially, the streams on each side of the augmented path set are marked as zero, i.e., f ij =0. For each augmented path from source to sink, let the residual r= infinity.
Further, for augmentationEdge E on the path ij ，r＝min(r,(c ij -f ij ))。
Further, for edge E on the augmented path ij ，f ij ＝f ij +r。
The flow is augmented along an augmented path starting with any one of the possible flows on the network, and iterating until the augmented path is no longer present in the network.
S6: the traditional line betweenness is improved, the concept of branch transmission hub betweenness is provided, and the concept is defined as the ratio of the number of the augmented paths comprising the branch I to the total number of all the augmented paths of the comprehensive energy system:
wherein: η (eta) l Transmitting a hub betweenness for a branch of branch l; n (ij) is the total number of all the amplifying paths of the comprehensive energy system; n (N) l (ij) is the number of augmented paths comprising branch l.
S7: the active power W of the amplifying path is taken as a line weight, a branch bearing capacity medium index is established, and the ratio of the sum of the weighted transmission capacities of the amplifying path containing the branch I in the comprehensive energy system to the sum of the weighted maximum flows in the electric-gas coupling system is defined:
wherein: w (p) is the active power of the amplification path p. f (f) l To increase the capacity of the flow through branch l in the path, f max Maximum current, μ, for an electro-pneumatic coupling system l Is the branch bearing capacity medium index of the branch l.
S8: normalizing the indexes in S6 and S7:
wherein: η (eta) lmax 、μ lmax The maximum value of branch transmission pivot medium number and branch bearing capacity medium number of the branch I of the electric-gas coupling system, eta ij 、μ ij Respectively normalized values of the corresponding indexes.
S9: establishing a comprehensive criticality index lambda of the branch:
λ＝α 1 η ij +α 2 μ ij
wherein: alpha 1 、α 2 The weight coefficients of the two branch indexes are respectively. Here take alpha 1 ＝α 2 ＝0.5。
S10: and calculating the comprehensive importance index of all branches in the electric-gas coupling system, and listing the lines with high comprehensive importance index as key lines.
The method for identifying the key circuit of the electric-gas coupling system based on the maximum flow theory, provided by the invention, is based on the maximum flow theory and the complex network theory, improves the traditional circuit betweenness, overcomes the defect that the energy or power between the nodes of the integrated energy system is always transmitted along the shortest path between the nodes, considers all possible transmission paths of the integrated energy system, and is more accurate and more in line with the characteristics of the integrated energy system. Meanwhile, from the two aspects of structural importance and state importance of the circuit, a circuit comprehensive importance index reflecting the centrality and transmission bearing capacity of the circuit structure is established, so that the identification of the key circuit of the comprehensive energy system is more accurate and reliable, and a new thought and method for the identification of the key circuit of the comprehensive energy system are provided. The invention can be used for identifying key circuits of an electric-gas coupling system, can be popularized and used for identifying key circuits of an electric-gas-heat comprehensive energy system, a traffic system, a logistics system and other large-scale complex systems, and has wide application value.
The beneficial effects are that:
compared with the prior art, the invention has the following beneficial effects:
based on the maximum flow theory and the complex network theory, the traditional line medium number is improved, the defect that the energy or power between the nodes of the integrated energy system is supposed to always propagate along the shortest path between the nodes is overcome, and all possible transmission paths of the integrated energy system are considered, so that the characteristics of the integrated energy system are more accurate and more accordant. Meanwhile, from the two aspects of structural importance and state importance of the circuit, a circuit comprehensive importance index reflecting the centrality and transmission bearing capacity of the circuit structure is established, so that the identification of the key circuit of the comprehensive energy system is more accurate and reliable, and a new thought and method for the identification of the key circuit of the comprehensive energy system are provided. The invention can be used for identifying key lines of a comprehensive energy system, can be popularized and used for identifying key lines of a thermodynamic system, a traffic system, a logistics system and other large-scale complex systems, and has wide application value.
Drawings
FIG. 1 is a block diagram of an electro-pneumatic coupling test system;
FIG. 2 is a diagram of the topology of an electro-pneumatic coupling system;
FIG. 3 is a schematic diagram of a multi-source multi-sink conversion to single source single sink;
FIG. 4 is a flow chart of critical line identification for an electro-pneumatic coupling system;
FIG. 5 is a graph of branch criticality index after normalization of the electro-pneumatic coupling system;
FIG. 6 is a top 15 key leg identification result graph of the electro-pneumatic coupling system rank;
FIG. 7 is a graph of the power reduction rate of an electro-pneumatic coupling system under various scenarios;
FIG. 8 is a graph of maximum flow capacity of an electro-pneumatic coupling system under different scenarios;
Detailed Description
The present invention will be described in further detail with reference to the following examples in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Examples:
a method for identifying key lines of an electric-gas coupling system based on a maximum flow theory comprises the following steps:
s1: and establishing a network topological graph of the electric-gas coupling system, and simplifying equipment and branches into nodes and edges of the graph. Wherein, the power supply and the air source are used as a source point s, the gas turbine and the P2G (electric conversion gas) are used as intermediate connection nodes, the electric load for the terminal is used as a sink point t, and the power transmission and the gas transmission pipelines are used as edges.
S2: let the electric-gas coupling system network g= (V, E), V represents the nodes of the system, E represents the edges of the system, each edge having a capacity c (V i ,v j ) Abbreviated as c ij The flow rate of the edge is f (v i ,v j ) E, abbreviated as f ij . The network maximum flow mathematical model of the electro-pneumatic coupling system is:
max v(f)
i.e. the source ingress is 0, the sink egress is 0, the ingress of the intermediate node is equal to the egress, and the traffic on each edge is less than its capacity. The network flow v (f) satisfying such a condition in the capacity network G is called a feasible flow.
S3: because the energy sources of the power grid and the gas grid are different, natural gas flow is converted into power, and the power grid are calculated under a unified frame:
W g ＝ζHQ
wherein: w (W) g Is converted natural gas power; zeta is the electricity generation efficiency of natural gas combustion; h is the heat value of natural gas; q is the mass flow of natural gas.
S4, because the maximum flow problem is single source and single sink, and the electric-gas coupling system is a multi-source and multi-sink network, a virtual source point S and a sink point T are arranged in the electric-gas coupling system and are respectively connected with all source points and sink points, and the capacity of the edge is set to be infinite.
S5: a feasible path from a source to a sink, where network flows on the path can increase at least the minimum capacity of the edges in the path, is called an augmented path. The amplified path was searched using the Fold-Fulkerson algorithm. The Fold-Fulkerson algorithm search procedure is as follows:
initially, the streams on each side of the augmented path set are marked as zero, i.e., f ij =0. For each augmented path from source to sink, let the residual r= infinity.
Further, for edge E on the augmented path ij ，r＝min(r,(c ij -f ij ))。
Further, for edge E on the augmented path ij ，f ij ＝f ij +r。
The flow is augmented along an augmented path starting with any one of the possible flows on the network, and iterating until the augmented path is no longer present in the network.
S6: the traditional line betweenness is improved, the concept of branch transmission hub betweenness is provided, and the concept is defined as the ratio of the number of the augmented paths comprising the branch I to the total number of all the augmented paths of the comprehensive energy system:
wherein: η (eta) l Transmitting a hub betweenness for a branch of branch l; n (ij) is the total number of all the amplifying paths of the comprehensive energy system; n (N) l (ij) is the number of augmented paths comprising branch l.
S7: the active power W of the amplifying path is taken as a line weight, a branch bearing capacity medium index is established, and the ratio of the sum of the weighted transmission capacities of the amplifying path containing the branch I in the comprehensive energy system to the sum of the weighted maximum flows in the electric-gas coupling system is defined:
wherein: w (p) is the active power of the amplification path p. f (f) l To increase the capacity of the flow through branch l in the path, f max Maximum current, μ, for an electro-pneumatic coupling system l Is the branch bearing capacity medium index of the branch l.
S8: normalizing the indexes in S6 and S7:
wherein: η (eta) lmax 、μ lmax The maximum value of branch transmission pivot medium number and branch bearing capacity medium number of the branch I of the electric-gas coupling system, eta ij 、μ ij Respectively normalized values of the corresponding indexes.
S9: establishing a comprehensive criticality index lambda of the branch:
λ＝α 1 η ij +α 2 μ ij
wherein: alpha 1 、α 2 The weight coefficients of the two branch indexes are respectively. Here take alpha 1 ＝α 2 ＝0.5。
S10: and calculating the comprehensive importance index of all branches in the electric-gas coupling system, and listing the lines with high comprehensive importance index as key lines.
Example 1:
the data used in this example were from the disclosure (volume P et al 2015) of a 20 node natural gas system for belgium in the gas-to-gas coupling test system and an IEEE30 node power system for the power system, as shown in fig. 1. The IEEE30 node power system nodes 24, 25, 30 are set to P2G, and are connected to the natural gas system 8, 13, 14 nodes. Nodes 3, 6, 7 of the belgium 20-node natural gas system are modified to gas turbines and are connected with power system nodes 1, 2, 8. The test system has 3 gas sources which are respectively connected with nodes 1, 2 and 5 of the natural gas system, and 2 compressors which are respectively positioned on branches connected with nodes 8 and 9 and branches connected with nodes 17 and 18. The conventional generator set has three locations, one at each of the electrical system nodes 5, 11, 13.
Modeling an electro-pneumatic coupling system. Generators, sources, buses, coupling elements, loads, etc. are modeled as nodes and connected transmission lines are modeled as edges. The network is considered a directed graph and the direction is defined by any steady state traffic analysis. The connection links are weighted according to the active power transmitted so that they maintain the flow direction. The model network is asymmetric, meaning that in steady state, if there is one flow from node i to node j, then there is no flow from node j to node i. The topology of the electro-pneumatic coupling system is shown in fig. 2 and each branch is numbered. The bolded nodes in the graph are the source nodes, the black-marked nodes are the coupling elements, and the sink nodes are nodes 14, 23, 56, 49.
The Fold-Fulkerson algorithm is used to search for the augmented path and network maximum flows. Recording all the augmentation paths, and simultaneously calculating the active power of each side on each augmentation path, wherein the power converted by the natural gas is calculated by the following formula:
W g ＝ζHQ
wherein: w (W) g Is converted natural gas power; zeta is the electricity generation efficiency of natural gas combustion; h is the heat value of natural gas; q is the mass flow of natural gas.
After all the amplification paths in the system are searched, calculating the branch transmission hub medium number of each branch:
wherein: η (eta) l Transmitting a hub betweenness for a branch of branch l; n (ij) is the total number of all the amplifying paths of the comprehensive energy system; n (N) l (ij) is the number of augmented paths comprising branch l.
And calculating the active power of each augmented path and the capacity flowing through each side, and substituting the network maximum flow into the following branch bearing capacity medium number of the branch to be calculated.
Wherein: w (p) is the active power of the amplification path p. f (f) l To increase the capacity of the flow through branch l in the path, f max Maximum current, μ, for an electro-pneumatic coupling system l Is the branch bearing capacity medium index of the branch l.
Normalizing the two indexes, and calculating to obtain the comprehensive criticality index of the branch circuit:
λ＝α 1 η ij +α 2 μ ij
wherein: η (eta) lmax 、μ lmax The maximum value of branch transmission pivot medium number and branch bearing capacity medium number of the branch I of the electric-gas coupling system, eta ij 、μ ij Normalized values of the corresponding indexes, alpha 1 、α 2 The weight coefficients of the two branch indexes are respectively. Here take alpha 1 ＝α 2 ＝0.5。
And sequencing the comprehensive criticality indexes of each branch, and taking the branch with high comprehensive criticality index as the critical branch of the electric-gas coupling system. The respective branch indexes are shown in fig. 5.
The branches with the top 15 of the branch comprehensive criticality index ranking are screened out as the critical branches, as shown in table 1.
Table 1 key branches with top 15 comprehensive criticality index ranking
In order to verify the correctness of the screening branch, two scenes are set to attack the branch of the electric-gas coupling system. Scene one: randomly attacking an electric-gas coupling system branch; scene II: and attacking the screened key branch of the electric-gas coupling system. The energy supply decline rate of the electric-gas coupling system and the reduction of the maximum flow capacity of the electric-gas coupling system in different scenes are obtained, as shown in fig. 7 and 8.
As can be seen from fig. 7, the power supply decrease rate of the electro-pneumatic coupling system is proportional to the attack number, and the more attack numbers, the higher the power supply decrease rate of the system. When the branches of the electric-gas coupling system are attacked randomly, the energy supply decline rate of the system is smaller than the energy supply decline rate of the critical attack branches, after the system branches are attacked six times, the energy supply decline rate of the system in the scene 1 is 0.397, and the energy supply decline rate of the system in the scene 2 is as high as 0.765 and is far higher than that of the random attack system branches. The key branch circuit has an important function on the safe and stable operation of the system.
As can be seen from fig. 8, when the electric-gas coupling system branch is randomly attacked, the maximum flow capacity of the system is slowly reduced, and after 6 attacks, the maximum flow capacity of the system is reduced to 89.6%; when the critical branch of the system is attacked, the maximum flow capacity of the system is rapidly reduced, and the maximum flow capacity of the system is reduced to 65.4% after 6 times of attack. The impact caused by the key branches of the attack system is far greater than that caused by random attack.
In summary, the state of the critical branch is concerned and the critical branch is controlled, which has important significance for preventing the cascading failure of the electric-gas coupling system and improving the safety and stability of the system. The key branches screened by the method are accurate and reliable.
The invention is based on the maximum flow theory and the complex network theory, improves the traditional line medium number, overcomes the defect that the energy or power between the nodes of the integrated energy system is supposed to always propagate along the shortest path between the nodes, considers all possible transmission paths of the integrated energy system, and is more accurate and more in line with the characteristics of the integrated energy system. Meanwhile, from the two aspects of structural importance and state importance of the circuit, a circuit comprehensive importance index reflecting the centrality and transmission bearing capacity of the circuit structure is established, so that the identification of the key circuit of the comprehensive energy system is more accurate and reliable, and a new thought and method for the identification of the key circuit of the comprehensive energy system are provided. The invention can be used for identifying key lines of a comprehensive energy system, can be popularized and used for identifying key lines of a thermodynamic system, a traffic system, a logistics system and other large-scale complex systems, and has wide application value.
The present invention is not limited to the above-mentioned embodiments, but is not limited to the above-mentioned embodiments, and any person skilled in the art can make some changes or modifications to the equivalent embodiments without departing from the scope of the technical solution of the present invention, but any simple modification, equivalent changes and modifications to the above-mentioned embodiments according to the technical substance of the present invention are still within the scope of the technical solution of the present invention.
Claims (1)
1. The method for identifying the key circuit of the electric-gas coupling system based on the maximum flow theory is characterized by comprising the following steps:
s1: establishing a network topological graph of the electric-gas coupling system, and simplifying equipment and branches into nodes and edges of the graph; the power supply and the air source are used as a source point s, the gas turbine and the electric transfer gas are used as intermediate connecting nodes, the electric load of the terminal is used as a sink point t, and the power transmission and the gas transmission pipeline are used as edges;
s2: let the electric-gas coupling system network g= (V, E), V represents the nodes of the system, E represents the edges of the system, each edge having a capacity c (V i ,v j ) Abbreviated as c ij The flow rate of the edge is f (v i ,v j ) E, abbreviated as f ij The network maximum flow mathematical model of the electro-pneumatic coupling system is:
namely, the source point ingress is 0, the sink point egress is 0, the inflow of the intermediate node is equal to the outflow, the flow of each side is smaller than the capacity of the intermediate node, and the network flow v (f) meeting the condition in the capacity network G is called a feasible flow;
s3: because the energy sources of the power grid and the gas grid are different, natural gas flow is converted into power, and the power grid are calculated under a unified frame:
W g ＝ζHQ
wherein: w (W) g Is converted natural gas power; zeta is the electricity generation efficiency of natural gas combustion; h is the heat value of natural gas; q is the mass flow of natural gas;
s4: because the maximum flow problem is single source and single sink, and the electric-gas coupling system is a multi-source multi-sink network, a virtual source point S and a sink point T are arranged in the electric-gas coupling system and are respectively connected with all source points and sink points, and the capacity of the side is set to be ++;
s5: the feasible paths from the source point to the sink point, network flows on the paths can at least increase the minimum capacity of edges in the paths, the paths are called as augmentation paths, the augmentation paths are searched by using a Fold-Fulkerson algorithm, and the search process of the Fold-Fulkerson algorithm is as follows:
initially, the streams on each side of the augmented path set are marked as zero, i.e., f ij For each augmented path from source to sink, let the residual r= infinity, = 0;
further, for edge E on the augmented path ij ，r＝min(r,(c ij -f ij ))；
Further, for edge E on the augmented path ij ，f ij ＝f ij +r；
Starting from any feasible flow on the network, carrying out amplification on the flow along the amplification path, and continuously iterating until the amplification path is no longer existed in the network;
s6: the traditional line betweenness is improved, the concept of branch transmission hub betweenness is provided, and the concept is defined as the ratio of the number of the augmented paths comprising the branch I to the total number of all the augmented paths of the comprehensive energy system:
wherein: η (eta) l Transmitting a hub betweenness for a branch of branch l; n (ij) is the total number of all the amplifying paths of the comprehensive energy system; n (N) l (ij) is the number of augmented paths comprising branch l;
s7: the active power W of the amplifying path is taken as a line weight, a branch bearing capacity medium index is established, and the ratio of the sum of the weighted transmission capacities of the amplifying path containing the branch I in the comprehensive energy system to the sum of the weighted maximum flows in the electric-gas coupling system is defined:
wherein: w (p) is the active power of the amplification path p, f l To increase the capacity of the flow through branch l in the path, f max Maximum current, μ, for an electro-pneumatic coupling system l A branch bearing capacity medium index of the branch l;
s8: normalizing the indexes in S6 and S7:
wherein: η (eta) lmax 、μ lmax The maximum value of branch transmission pivot medium number and branch bearing capacity medium number of the branch I of the electric-gas coupling system, eta ij 、μ ij Respectively normalizing the corresponding indexes;
s9: establishing a comprehensive criticality index lambda of the branch:
λ＝α 1 η ij +α 2 μ ij
wherein: alpha 1 、α 2 The weight coefficients of the two branch indexes are respectively, and alpha is taken as the weight coefficient 1 ＝α 2 ＝0.5；
S10: and calculating the comprehensive importance index of all branches in the electric-gas coupling system, and listing the lines with high comprehensive importance index as key lines.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105912835A (en) * | 2016-03-15 | 2016-08-31 | 华侨大学 | Power line vulnerability identification model building method taking wind farm access into consideration |
| CN106779309A (en) * | 2016-11-24 | 2017-05-31 | 华北电力大学（保定） | The multi-level discrimination method of critical circuits multi-angle |
| CN107623319A (en) * | 2017-08-17 | 2018-01-23 | 广东电网有限责任公司惠州供电局 | A kind of power network critical circuits discrimination method based on more evaluation indexes |
| CN111311437A (en) * | 2020-04-02 | 2020-06-19 | 华北电力大学 | Natural gas key pipeline identification method and system based on complex network theory |
| CN113420994A (en) * | 2021-06-28 | 2021-09-21 | 山东大学 | Method and system for evaluating structure flexibility of active power distribution network |
| CN114355829A (en) * | 2022-01-07 | 2022-04-15 | 西南石油大学 | Natural gas pipeline multi-state fault model and electric-gas coupling cascading fault simulation method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6694499B2 (en) * | 2001-12-04 | 2004-02-17 | Sun Microsystems, Inc. | Verifying decoupling capacitance using a maximum flow determination of a network |
-
2022
- 2022-05-30 CN CN202210600462.1A patent/CN114998051B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105912835A (en) * | 2016-03-15 | 2016-08-31 | 华侨大学 | Power line vulnerability identification model building method taking wind farm access into consideration |
| CN106779309A (en) * | 2016-11-24 | 2017-05-31 | 华北电力大学（保定） | The multi-level discrimination method of critical circuits multi-angle |
| CN107623319A (en) * | 2017-08-17 | 2018-01-23 | 广东电网有限责任公司惠州供电局 | A kind of power network critical circuits discrimination method based on more evaluation indexes |
| CN111311437A (en) * | 2020-04-02 | 2020-06-19 | 华北电力大学 | Natural gas key pipeline identification method and system based on complex network theory |
| CN113420994A (en) * | 2021-06-28 | 2021-09-21 | 山东大学 | Method and system for evaluating structure flexibility of active power distribution network |
| CN114355829A (en) * | 2022-01-07 | 2022-04-15 | 西南石油大学 | Natural gas pipeline multi-state fault model and electric-gas coupling cascading fault simulation method |
Non-Patent Citations (3)
| Title |
|---|
| The Comprehensive Identification Model of Critical Lines in Electric Power Grid Based on Utility Theory and Cooperative Game;Ran Li 等;《2016 IEEE PES Transmission&Distribution Conference and Exposition-Latin America》;20170105;第1-6页 * |
| 基于最大流传输贡献度的电力网关键线路和节点辨识;鞠文云 等;《电力系统自动化》;20120510;第36卷(第9期);第6-12页 * |
| 基于负荷介数和电气欧拉距离的电网关键环节辨识;江浩;吕飞鹏;孔德洪;;电力系统及其自动化学报;20161015(第10期);第92-97页 * |
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