CN109768543B - Elastic bottom-preserving net rack search modeling method based on mixed integer linear programming - Google Patents
Elastic bottom-preserving net rack search modeling method based on mixed integer linear programming Download PDFInfo
- Publication number
- CN109768543B CN109768543B CN201811549801.8A CN201811549801A CN109768543B CN 109768543 B CN109768543 B CN 109768543B CN 201811549801 A CN201811549801 A CN 201811549801A CN 109768543 B CN109768543 B CN 109768543B
- Authority
- CN
- China
- Prior art keywords
- node
- net rack
- line
- mixed integer
- current
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Abstract
The invention relates to the technical field of guaranteed-bottomed net rack planning, in particular to an elastic guaranteed-bottomed net rack searching and modeling method based on mixed integer linear programming, which comprises the following specific steps of S1: establishing an objective function taking the line electrical betweenness as a reference factor; s2: establishing equality constraint of an optimization model, and establishing node current equality constraint on the basis of a kirchhoff current law; s3: establishing inequality constraints of an optimization model, wherein the inequality constraints comprise generator power limit constraints, line power limit constraints, economy constraints and connectivity constraints; s4: and solving the mixed integer programming model to obtain a search result of the bottom-preserving net rack. The invention can effectively avoid the problems of low solving efficiency, poor robustness and uncertain result of the traditional intelligent algorithm. The mixed integer programming model can be effectively solved by utilizing the existing mature algorithm, and the speed and the accuracy of searching the bottom-preserving net rack are improved.
Description
Technical Field
The invention relates to the technical field of guaranteed-space network frame planning, in particular to an elastic guaranteed-space network frame search modeling method based on mixed integer linear programming.
Background
In recent years, a series of heavy-loss blackout accidents are caused by the fact that a Chinese power grid is damaged by extreme natural disasters such as freezing, typhoon, earthquake and the like for many times, and the blackout accidents of a power system are more and more closely concerned. In general, a large-scale power failure accident is caused by a fault caused by internal or external factors, so that some fragile lines or important nodes in a power grid are quitted from running, large-scale power flow transfer is caused, linkage faults are further caused, and the large-scale power failure accident is finally caused. Therefore, it is necessary to search for a key line in the power grid, and perform a differential design on the environment of the key line, so as to improve the disaster resistance of the key line, which is of great significance to enhance the operation stability of the power system, reduce the secondary investment of rush repair and reconstruction of the power grid due to natural disasters, and ensure the safe and reliable operation of the power grid under severe natural disasters.
The method for searching the bottom-protecting net rack relates to a complex network theory and large-scale power system dynamic research. The method can reflect the actual transmission condition of the power flow, and the physical background is more in line with the reality of the power system. During the searching process, the bottom-guaranteeing network frame must always satisfy the system power flow constraint and the connectivity constraint. Therefore, the correctness and complexity of the established constraint equation directly influence the complexity of the search result and the programming calculation of the bottom-preserving net rack.
In the existing method for searching and modeling the bottom-preserving net rack, the system power flow constraint is considered more to meet the constraint condition of safe operation of a power grid, and a mixed integer nonlinear programming model is established. The traditional power flow constraint is based on a node power expression, and the formula is as follows:
in the formula, P i Injecting active power, Q, for each node i Reactive power, U, is injected for each node i 、U j Node voltages of nodes i and j, respectively, n is the number of system nodes, G ij 、B ij The conductance and susceptance, delta, of the branches connecting nodes i, j, respectively ij For node i voltage phase angle delta i Voltage phase angle delta from node j j The difference between them.
At present, a mature algorithm can perfectly solve the mixed integer nonlinear programming problem, when the mixed integer nonlinear programming problem is solved, various artificial intelligence algorithms can be adopted only, improvement is continuously carried out, and a calculation result is changed after each solution. Therefore, the traditional method for searching and modeling the bottom-preserving net rack has high solving difficulty, needs multiple searching no matter what intelligent algorithm is adopted, has low speed and low efficiency, and cannot meet the high-speed and simple modeling requirements of a modern power system. Therefore, how to establish an effective and rapid bottom-preserving net rack search model is a crucial problem for stable operation and post-disaster reconstruction of a power system.
The backbone network frame construction problem is a multivariable, nonlinear and multi-constraint combined optimization problem, and most of solutions to the problems in recent years adopt artificial intelligence algorithms.
The method comprises the steps of establishing a core backbone network frame based on an improved BBO optimization algorithm and the survivability of a power grid [ J ]. China Motor engineering journal 2014,34(16): 2659-. ' core backbone net rack search [ J ] based on improved binary quantum particle swarm algorithm, China Motor engineering journal, 2014,34(34): 6127-. The backbone net rack searching method is used for searching the backbone net rack by adopting a guided firework algorithm in the study of [ D ]. Nanchang university, 2018 ]. "network reconstruction with comprehensive consideration of node importance and line betweenness [ J ] power system automation, 2010,34(12): 29-33." search for backbone net frames using Discrete Particle Swarm Optimization (DPSO). The method for constructing and evaluating the power grid differentiation core backbone net rack researches [ D ]. Wuhan university, 2017. "search the backbone net rack by using an improved quantum-behaved particle swarm algorithm in the same writing. The methods adopt artificial intelligent algorithm to solve, and the problems of low calculation speed, uncertain result, easy falling into local optimum and the like generally exist. The method has great limitation in solving the problem of searching the bottom-preserving net rack and needs to be improved.
Disclosure of Invention
In order to solve the problems, the invention provides an elastic bottom-preserving net rack search modeling method based on mixed integer linear programming, which has the following specific technical scheme:
a mixed integer linear programming-based elastic bottom-preserving net rack searching and modeling method comprises the following steps:
s1: establishing an objective function taking the line electrical betweenness as a reference factor; wherein, the variable is the branch running state, 0 is exit, and 1 is commissioning;
s2: establishing equality constraint of an optimization model, and establishing node current equality constraint on the basis of kirchhoff current law;
s3: establishing inequality constraints of an optimization model, wherein the inequality constraints comprise generator power limit constraints, line power limit constraints, economy constraints and connectivity constraints;
s4: and solving the mixed integer programming model to obtain a search result of the bottom-preserving net rack.
Preferably, the objective function established in step S1 with the line electrical permittivity as a reference factor is specifically:
wherein x ij Is the running state of the branch, 0 is exit, 1 is commissioning, x ij ∈{0,1},
Ω l Represents the set of all lines in the system;
w ij the search weight of the sub-network is referred to the line electric dielectric number, and the weight of the line electric dielectric number is set to be 1, namely the sub-network search weight is equal to the electric dielectric number of each line; the calculation method of the line electric permittivity is as follows:
in the formula I mn (i, j) is the current induced on the line (i, j) after adding the unit injection current element between the 'generation-load' nodes (m, n); w is a group of m The rated capacity or actual output of the generator is taken as the weight of the power generation node m, W n Taking actual or peak load as the weight of the load node n; g and L are the set of all power generation and load nodes.
Preferably, the node current equation established in step S2 is constrained by:
in the formula I ji Is the current flowing from the j node into the i node; I.C. A ij Is the current flowing from the i node to the j node; g i Injecting current at the i node for the generator; d is a radical of i A load current at a load i node; omega b For the set of all buses in the system, Ω l Representing the set of all lines in the system.
Preferably, the generator power limitation constraint in step S3 is specifically:
in the formula, g i To provide the output for the power generation node i,
is the upper limit of the output of the power generation node i, omega bs A collection of power generation nodes reserved for the bottom-preserving grid.
Preferably, the line power limitation constraint in step S3 is specifically:
wherein, | I ij L is the absolute value of the current value transmitted from node I to node j on line (I, j), if I ij The negative number represents a reverse flow of current,
transmitting an upper current limit for the line; x is the number of ij Is the running state of the branch, 0 is exit, 1 is commissioning, x ij ∈{0,1},
Ω l Representing the set of all lines in the system.
Preferably, the economic constraint in step S3 is specifically: setting the total number of lines to be less than a certain value to meet the economical efficiency, and setting a constraint equation as follows:
wherein n is the total number of expected lines and is set according to the actual situation and the difference requirement; x is the number of ij Is the running state of the branch, 0 is exit, 1 is put into operation, x ij ∈{0,1},
Ω l Representing the set of all lines in the system.
Preferably, the connectivity constraint in step S3 specifically includes:
wherein omega l Represents the set of all lines in the system; omega b Representing the set of all bus bars in the system;
represents the flow of power k from node i to node j;
indicating that power k flows from node j to node i; x is the number of ij Is the running state of the branch, 0 is exit, 1 is put into operation, x ij ∈{0,1},
y ij Representing the line direction from node i to node j; y is ji Representing the line direction from node j to node i; x, y and f are all binary variables; k, i, j all belong to the set of all network nodes.
The invention has the beneficial effects that: the invention can effectively avoid the problems of low solving efficiency, poor robustness and uncertain result of the traditional intelligent algorithm. The mixed integer programming model can be effectively solved by utilizing the existing mature algorithm, and the speed and the accuracy of searching the bottom-preserving net rack are improved.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only one embodiment of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is an IEEE14 node system connectivity topology.
Detailed Description
For a better understanding of the present invention, reference is made to the following detailed description taken in conjunction with the accompanying drawings in which:
in this embodiment, taking the IEEE14 node system shown in fig. 1 as an example to describe the specific implementation details, a method for searching and modeling an elastic net rack based on mixed integer linear programming includes the following steps:
a mixed integer linear programming-based elastic bottom-preserving net rack search modeling method comprises the following steps:
s1: establishing an objective function taking the line electrical betweenness as a reference factor; wherein, the variable is the branch running state, 0 is exit, and 1 is commissioning. First, an objective function is established as follows:
wherein x ij Is the running state of the branch, 0 is exit, 1 is put into operation, x ij ∈{0,1},
Ω l Representing the set of all lines in the system.
The IEEE14 node system line set is:
{i 1-2 ,i 1-5 ,i 2-3 ,i 2-4 ,i 2-5 ,i 3-4 ,i 4-5 ,i 4-7 ,i 4-9 ,i 5-6 ,i 6-11 ,i 6-12 ,i 6-13 ,i 7-8 ,i 7-9 ,i 9-10 ,i 9-14 ,i 10-11 ,i 12-13 ,i 13-14 }。
w ij the search weight of the sub-network is referred to the line electric dielectric number, and the line electric dielectric number weight is set to be 1 because the target function of the model only considers the line electric dielectric number, namely the sub-network search weight is equal to each line electric dielectric number. The 'electrical betweenness' is the occupation condition of power transmission between the 'power generation-load' node pairs on each line. Considering the influence of different node generating capacity and load level, the physical background is more in line with the reality of the power system than the node or branch node's "betweenness" (i.e. the number of times passed by the shortest path between buses). And solving the electrical parameters of the IEEE14 node system circuit according to a circuit electrical parameter formula. The calculation method of the line electrical permittivity is as follows:
in the formula I mn (i, j) is the current induced on the line (i, j) after adding the unit injection current element between the 'generation-load' nodes (m, n); w m The rated capacity or actual output of the generator is taken as the weight of the power generation node m, W n Taking actual or peak load as the weight of the load node n; g and L are the set of all power generation and load nodes.
According to the objective function, the principle of the invention for searching the bottom-preserving network frame is that the importance of the selected line in the network is as high as possible. The node electrical parameters of the IEEE14 node system are calculated as shown in table 1:
TABLE 1IEEE14 node Electrical characteristics
| Line number | Value of electric dielectric constant | Line number | Dielectric value |
| 1,2 | 1.8594 | 9,10 | 0.5338 |
| 1,5 | 1.0789 | 9,14 | 0.4528 |
| 5,6 | 1.0318 | 6,13 | 0.4394 |
| 2,4 | 1.0141 | 6,11 | 0.4317 |
| 4,5 | 0.8979 | 10,11 | 0.42 |
| 2,3 | 0.8892 | 4,9 | 0.4049 |
| 2,5 | 0.8795 | 13,14 | 0.3824 |
| 3,4 | 0.815 | 6,12 | 0.2603 |
| 7,9 | 0.7036 | 12,13 | 0.1947 |
| 4,7 | 0.6884 |
S2: some important power supply nodes and load nodes must be reserved in the selected bottom-protecting net rack, and the power supply to the important loads and the power exchange capacity between the important loads are ensured. There are 3 power nodes and 11 load nodes in the IEEE14 node system, assuming that the backbone network maintains all nodes and the power of each node does not change. And (3) establishing equality constraint of an optimization model, and establishing node current equality constraint on the basis of kirchhoff current law:
in the formula I ji Is the current flowing from the j node into the i node; i is ij Is the current flowing from the i node to the j node; g i Injecting current at the i node for the generator; d i A load current at a load i node; omega b For the set of all buses in the system, the set of buses is { i } 1 ,i 2 ,i 3 ,i 4 ,i 5 ,i 6 ,i 7 ,i 8 ,i 9 ,i 10 ,i 11 ,i 12 ,i 13 ,i 14 }，Ω l Representing the set of all lines in the system. Namely, the traditional power flow equation constraint is replaced by the current constraint under the condition of meeting the practical engineering situation. The operation parameters of the IEEE14 node system are shown in table 2:
TABLE 2 operating parameters of IEEE14 node system
| Node number | P G | Q G | P L | Q L |
| 1 | 60 | 0 | 0 | 0 |
| 2 | 40 | 42.4 | 21.7 | 12.7 |
| 3 | 0 | 23.39 | 94.2 | 19.0 |
| 4 | 0 | 0 | 47.8 | -3.9 |
| 5 | 0 | 0 | 7.6 | 1.6 |
| 6 | 0 | 12.24 | 11.2 | 7.5 |
| 7 | 0 | 0 | 0 | 0 |
| 8 | 0 | 17.36 | 0 | 0 |
| 9 | 0 | 0 | 29.5 | 16.6 |
| 10 | 0 | 0 | 9 | 5.8 |
| 11 | 0 | 0 | 3.5 | 1.8 |
| 12 | 0 | 0 | 6.1 | 1.6 |
| 13 | 0 | 0 | 13.5 | 5.8 |
| 14 | 0 | 0 | 14.9 | 5 |
The admittance of the IEEE14 node system is shown in table 3:
TABLE 3 admittance of IEEE14 node system
S3: establishing inequality constraints of an optimization model, wherein the inequality constraints comprise generator power limit constraints, line power limit constraints, economic constraints and connectivity constraints;
s31: in order to ensure that the selected power generation node can safely operate while meeting the requirement of the reserved load, the output of the generator must be limited, and the inequality of the power limit of the generator is established as follows:
in the formula, gi is the output of the power generation node i,
the upper limit of the output of the power generation node i, omega bs A collection of power generation nodes reserved in the bottom-preserving net rack. Assuming no loss of power supply nodes, the set of power generation nodes is { i } 1 ,i 2 ,i 3 }。
S32: the output of the generator is limited, and simultaneously, the transmission power on the circuit of the bottom-protecting net rack must be ensured not to exceed the limit, the current limit on the circuit is used as the circuit power limit in the invention, the directivity of the tide is reflected, and the inequality constraint of the circuit power is established as follows:
in the formula, | I ij L is the absolute value of the current value transmitted from node I to node j on line (I, j), if I ij The negative number represents a reverse flow of current,
for line transmissionThe upper limit of the transmission current can take a value of 100. x is the number of ij Is the running state of the branch, 0 is exit, 1 is put into operation, x ij ∈{0,1},
Ω l Representing the set of all lines in the system.
S33: according to the requirements of the research target and principle of the bottom-preserving net rack, the searched lines should be as few as possible, so that the total number of the lines is set to be less than a certain value to meet the economic efficiency, and a constraint equation is set as follows:
wherein n is the total number of expected lines and is set according to the actual situation and the difference requirement; x is the number of ij Is the running state of the branch, 0 is exit, 1 is put into operation, x ij ∈{0,1},
Ω l Representing the set of all lines in the system. The number of the expected lines of the IEEE14 node system is set to be 12. And (4) establishing inequality constraint of the number of lines, so that the searching of the bottom-protecting net rack meets the economic constraint.
S34: according to the research target and principle requirement of the bottom-preserving net rack, the searched bottom-preserving net rack should meet the topological connectivity constraint, namely the backbone net rack is a connected graph. The connectivity constraint is specifically:
wherein omega l Represents the set of all lines in the system; omega b Representing the set of all bus bars in the system;
represents the flow of power k from node i to node j;
indicating that power k flows from node j to node i; x is the number of ij Is the running state of the branch, 0 is exit, 1 is put into operation, x ij ∈{0,1},
y ij Representing the line direction from node i to node j; y is ji Representing the line direction from node j to node i; x, y and f are all binary variables; k, i, j all belong to the set of all network nodes. And establishing connectivity constraint to ensure that the safe and reliable operation of the bottom-protecting net rack and the necessary searching principle of a communication topological structure are met.
S4: and solving the mixed integer programming model to obtain a search result of the bottom-preserving net rack. The method specifically comprises the following steps: the CPLEX algorithm is utilized to solve the searching model of the guaranteed-space net rack established by the invention, and the searching result of the guaranteed-space net rack is analyzed to strive to ensure that the net rack circuit gas dielectric index is maximum on the premise that the final scheme meets the requirements.
Therefore, the mixed integer linear programming model established by the invention is used for searching the bottom-preserving net rack, and the problems of low efficiency and high uncertainty in solving the nonlinear problem caused by the algorithm are effectively avoided. The technology for solving the mixed integer linear programming problem by using the CPLEX algorithm is mature, the problem of searching the bottom-preserving net rack under different requirements based on the model provided by the invention is solved, the calculation speed is high, the robustness is good, the flexibility is high, the expansibility is strong, and the efficiency of searching the bottom-preserving net rack is effectively improved.
The present invention is not limited to the above-described embodiments, which are merely preferred embodiments of the present invention, and the present invention is not limited thereto, and any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A mixed integer linear programming-based elastic bottom-preserving net rack search modeling method is characterized by comprising the following steps: the method comprises the following steps:
s1: establishing an objective function taking the line electrical betweenness as a reference factor; wherein, the variable is the branch running state, 0 is exit, and 1 is commissioning;
s2: establishing equality constraint of an optimization model, and establishing node current equality constraint on the basis of a kirchhoff current law;
s3: establishing inequality constraints of an optimization model, wherein the inequality constraints comprise generator power limit constraints, line power limit constraints, economy constraints and connectivity constraints; the connectivity constraint in step S3 specifically includes:
wherein omega l Represents the set of all lines in the system; omega b Representing the set of all bus bars in the system;
represents the flow of power k from node i to node j;
indicating that power k flows from node j to node i; x is the number of ij Is the running state of the branch, 0 is exit, 1 is commissioning, x ij ∈{0,1},
y ij Representing the line direction from node i to node j; y is ji Representing the line direction from node j to node i; x, y and f are all binary variables; i, j all belong to the set of all network nodes;
s4: and solving the mixed integer programming model to obtain a search result of the bottom-preserving net rack.
2. The method for searching and modeling the elastic bottom-preserving net rack based on the mixed integer linear programming as claimed in claim 1, wherein: the established objective function taking the line electrical permittivity as a reference factor in the step S1 is specifically:
wherein x ij Is the running state of the branch, 0 is exit, 1 is put into operation, x ij ∈{0,1},
Ω l Represents the set of all lines in the system;
w ij the search weight of the sub-network is referred to the line electric dielectric number, and the weight of the line electric dielectric number is set to be 1, namely the sub-network search weight is equal to the electric dielectric number of each line; the calculation method of the line electrical permittivity is as follows:
in the formula I mn (i, j) is the current induced on the line (i, j) after adding the unit injection current element between the 'generation-load' nodes (m, n); w m The rated capacity or actual output of the generator is taken as the weight of the power generation node m, W n Taking actual or peak load as the weight of the load node n; g and L are all power generation and load nodesA set of points.
3. The method for searching and modeling the elastic bottom-preserving net rack based on the mixed integer linear programming as claimed in claim 1, wherein: the node current equation established in step S2 is constrained by:
in the formula I ji Is the current flowing from the j node into the i node; I.C. A ij Is the current flowing from the i node to the j node; g i Injecting current at the i node for the generator; d i A load current at a load i node; omega b For the set of all buses in the system, Ω l Representing the set of all lines in the system.
4. The method for searching and modeling the elastic bottom-preserving net rack based on the mixed integer linear programming as claimed in claim 1, wherein: the power limit constraint of the generator in step S3 is specifically:
in the formula, g i The output is provided for the power generation node i,
the upper limit of the output of the power generation node i, omega bs A collection of power generation nodes reserved in the bottom-preserving net rack.
5. The method for searching and modeling the elastic bottom-preserving net rack based on the mixed integer linear programming as claimed in claim 1, wherein: the line power limitation constraint in step S3 specifically includes:
in the formula, | I ij L is the absolute value of the current value transmitted from node I to node j on line (I, j), if I ij Is negative to represent the current flowing in the reverse direction,
transmitting an upper current limit for the line; x is a radical of a fluorine atom ij Is the running state of the branch, 0 is exit, 1 is put into operation, x ij ∈{0,1},
Ω l Representing the set of all lines in the system.
6. The method for searching and modeling the elastic bottom-preserving net rack based on the mixed integer linear programming as claimed in claim 1, wherein: the economic constraint in step S3 is specifically: setting the total number of lines to be less than a certain value to meet the economical efficiency, and setting a constraint equation as follows:
wherein n is the total number of expected lines and is set according to the actual situation and the difference requirement; x is the number of ij Is the running state of the branch, 0 is exit, 1 is put into operation, x ij ∈{0,1},
Ω l Representing the set of all lines in the system.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811549801.8A CN109768543B (en) | 2018-12-18 | 2018-12-18 | Elastic bottom-preserving net rack search modeling method based on mixed integer linear programming |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811549801.8A CN109768543B (en) | 2018-12-18 | 2018-12-18 | Elastic bottom-preserving net rack search modeling method based on mixed integer linear programming |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109768543A CN109768543A (en) | 2019-05-17 |
| CN109768543B true CN109768543B (en) | 2022-09-20 |
Family
ID=66451494
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811549801.8A Active CN109768543B (en) | 2018-12-18 | 2018-12-18 | Elastic bottom-preserving net rack search modeling method based on mixed integer linear programming |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109768543B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111900722B (en) * | 2020-07-03 | 2022-03-15 | 武汉大学 | Construction method of bottom-preserving power grid backbone grid structure considering recovery capability |
| CN112052543B (en) * | 2020-08-11 | 2022-12-23 | 广西大学 | Bottom-preserving net rack search modeling method based on mixed integer second-order cone programming |
| CN113792977A (en) * | 2021-08-16 | 2021-12-14 | 南方电网科学研究院有限责任公司 | Energy storage planning method, device, equipment and medium for bottom-guaranteed power grid |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103151777A (en) * | 2013-03-27 | 2013-06-12 | 国家电网公司 | Power grid differentiation-based core backbone network architecture construction method |
| CN105389629A (en) * | 2015-11-10 | 2016-03-09 | 国网四川省电力公司经济技术研究院 | Power grid planning method by combining power grid structural vulnerability |
| CN105528645A (en) * | 2015-11-05 | 2016-04-27 | 国家电网公司 | Frangibility prediction method for large power grid |
| CN105787143A (en) * | 2014-12-25 | 2016-07-20 | 北京仿真中心 | Method and system for adjusting structure of complex network based on backbone network |
| CN107506854A (en) * | 2017-08-04 | 2017-12-22 | 国网浙江省电力公司经济技术研究院 | A kind of 220kV Power grid structure planing methods for considering differentiation scene |
| CN107679658A (en) * | 2017-09-28 | 2018-02-09 | 国网四川省电力公司经济技术研究院 | A kind of Transmission Expansion Planning in Electric method under the access of clean energy resource at high proportion |
-
2018
- 2018-12-18 CN CN201811549801.8A patent/CN109768543B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103151777A (en) * | 2013-03-27 | 2013-06-12 | 国家电网公司 | Power grid differentiation-based core backbone network architecture construction method |
| CN105787143A (en) * | 2014-12-25 | 2016-07-20 | 北京仿真中心 | Method and system for adjusting structure of complex network based on backbone network |
| CN105528645A (en) * | 2015-11-05 | 2016-04-27 | 国家电网公司 | Frangibility prediction method for large power grid |
| CN105389629A (en) * | 2015-11-10 | 2016-03-09 | 国网四川省电力公司经济技术研究院 | Power grid planning method by combining power grid structural vulnerability |
| CN107506854A (en) * | 2017-08-04 | 2017-12-22 | 国网浙江省电力公司经济技术研究院 | A kind of 220kV Power grid structure planing methods for considering differentiation scene |
| CN107679658A (en) * | 2017-09-28 | 2018-02-09 | 国网四川省电力公司经济技术研究院 | A kind of Transmission Expansion Planning in Electric method under the access of clean energy resource at high proportion |
Non-Patent Citations (3)
| Title |
|---|
| Electric betweenness and its application in vulnerable line identification in power system;L. Xu等;《Proceedings of the CSEE》;20101231;第33-39页 * |
| 基于改进二进制量子粒子群算法的核心骨干网架搜索;王浩磊 等;《中 国 电 机 工 程 学 报》;20141205;第6127-6132页 * |
| 基于最优潮流的配电网络重构计算;阳育德等;《中国电工技术学会学术年会——新能源发电技术论坛论文集》;20131031;第1-6页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109768543A (en) | 2019-05-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109768543B (en) | Elastic bottom-preserving net rack search modeling method based on mixed integer linear programming | |
| CN109274095A (en) | Low-voltage distribution network users topology estimation method and system based on mutual information | |
| CN111416359A (en) | Power distribution network reconstruction method considering weighted power flow entropy | |
| CN107316113B (en) | Power transmission network planning method and system | |
| CN108808715B (en) | Multi-terminal flexible direct system static safety analysis method considering direct current network fault power | |
| CN108933445A (en) | DC grid short-circuit current calculation method based on the loop method of analysis | |
| CN109598377B (en) | AC/DC hybrid power distribution network robust planning method based on fault constraint | |
| CN107332277B (en) | Active power distribution network island operation method considering source load storage operation characteristics | |
| CN108667027A (en) | Ac and dc systems power flow transfer search containing flexible direct current and quantitative analysis method | |
| CN112467748A (en) | Double-time-scale distributed voltage control method and system for three-phase unbalanced active power distribution network | |
| CN112255567A (en) | Method for quickly determining short-circuit current of power distribution network containing photovoltaic power supply | |
| CN109617079B (en) | Method for analyzing existence and stability of tidal current solution of direct-current power distribution system | |
| CN112052543B (en) | Bottom-preserving net rack search modeling method based on mixed integer second-order cone programming | |
| CN106991229B (en) | Wind power plant equivalent modeling method for complex topology | |
| CN107196307B (en) | A kind of method that electric network active trend is quickly estimated after transformer fault | |
| CN110061495B (en) | Method for identifying core network of power system based on cut constraint | |
| CN110165712B (en) | Backbone net rack planning modeling method based on network flow constraint derivation | |
| CN113675872B (en) | Multi-direct-current simultaneous commutation failure coordination recovery ordering method based on sending end stability constraint | |
| CN111092453B (en) | Power grid key line identification method for multipoint access photovoltaic power supply | |
| Zhou et al. | MILP-based splitting strategy searching considering island connectivity and voltage stability margin | |
| CN112668747A (en) | Optimal configuration method of harmonic source positioning measurement device considering measurement redundancy | |
| CN105470946A (en) | Dynamo-electric transient simulation algorithm for power distribution network containing distributed power supply | |
| CN117371154B (en) | Power grid planning system of industrial frequency division interconnection system with M3C frequency conversion station for site selection and volume fixation | |
| CN107562971B (en) | Alternating current/direct current power grid power flow calculation method based on PSS/E | |
| Li et al. | Wind farms reactive power optimization using genetic/tabu hybrid algorithm |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |