CN104579867B - Based on the power communication network construction process of node aggregation coefficient - Google Patents
Based on the power communication network construction process of node aggregation coefficient Download PDFInfo
- Publication number
- CN104579867B CN104579867B CN201410710163.9A CN201410710163A CN104579867B CN 104579867 B CN104579867 B CN 104579867B CN 201410710163 A CN201410710163 A CN 201410710163A CN 104579867 B CN104579867 B CN 104579867B
- Authority
- CN
- China
- Prior art keywords
- node
- influence
- value
- power communication
- factor
- 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
- 238000004891 communication Methods 0.000 title claims abstract description 62
- 230000002776 aggregation Effects 0.000 title claims abstract description 45
- 238000004220 aggregation Methods 0.000 title claims abstract description 45
- 238000000034 method Methods 0.000 title claims abstract description 17
- 238000010276 construction Methods 0.000 title claims abstract description 9
- 230000008569 process Effects 0.000 title abstract description 3
- 230000003287 optical effect Effects 0.000 claims abstract description 4
- 239000011159 matrix material Substances 0.000 claims description 22
- 238000010606 normalization Methods 0.000 claims description 6
- 238000004458 analytical method Methods 0.000 claims description 5
- 238000005259 measurement Methods 0.000 claims description 4
- 239000000470 constituent Substances 0.000 claims 1
- 230000000379 polymerizing effect Effects 0.000 abstract 2
- 238000009826 distribution Methods 0.000 description 6
- 230000009471 action Effects 0.000 description 5
- 230000009467 reduction Effects 0.000 description 4
- 238000011156 evaluation Methods 0.000 description 3
- 230000005484 gravity Effects 0.000 description 3
- 238000004519 manufacturing process Methods 0.000 description 3
- 238000006116 polymerization reaction Methods 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- ZZUFCTLCJUWOSV-UHFFFAOYSA-N furosemide Chemical compound C1=C(Cl)C(S(=O)(=O)N)=CC(C(O)=O)=C1NCC1=CC=CO1 ZZUFCTLCJUWOSV-UHFFFAOYSA-N 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 238000013439 planning Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000013024 troubleshooting Methods 0.000 description 1
Landscapes
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention provides a kind of power communication network construction process based on node aggregation coefficient, comprises the steps: to obtain the network model of power telecom network; Wherein, described network model comprises node and link, and described node is the signal equipment in power communication system, and described link is each bar optical cable connecting node; Calculate the polymerizing factor of described node; Obtain the network model being attached with corresponding polymerizing factor on each node, the network model obtained is carried out the reliability determination of Network topology and power communication system. The power communication network that the inventive method builds, can significantly improve the accuracy of the reliability determination of power communication system.
Description
Technical Field
The invention relates to the technical field of power communication systems, in particular to a power communication network construction method based on a node aggregation coefficient.
Background
The power communication system is an important component of the power system, and the reliability of the power communication system directly influences the safe production and the reliable operation of the power system. The reliability of the power communication system is determined, the operation condition of the current network can be known on the whole, and weak links and faults can be found in time, so that direct basis is provided for troubleshooting and network reconstruction, the stability of the power communication network is further guaranteed, and the communication quality is improved.
As a communication private network of a power system, the shortest path between nodes in the network describes the distance between the nodes, and the average shortest distance of the network reflects the tightness between the nodes of the network, so that the method can be used for measuring the reliability of the overall connection of the network. However, the average shortest distance is only considered from the topology point of view, and the positions and roles of the nodes in the power communication network are obviously different. However, most of the current power communication network models only represent nodes and links, and describe the direct compactness of the nodes through the shortest paths between the nodes, so that the reliability of the power communication system is relatively low.
Disclosure of Invention
Based on the above, the invention provides a power communication network construction method based on a node aggregation coefficient, and the power communication network constructed by the method can obviously improve the accuracy of reliability measurement of a power communication system.
A power communication network construction method based on node aggregation coefficients comprises the following steps:
acquiring a network model of the power communication network; the network model comprises nodes and links, wherein the nodes are communication equipment in the power communication system, and the links are all optical cables for connecting the nodes;
calculating an aggregation coefficient for the node by:
wherein, WiIs a node viD (k, z) is a node vkAnd vzThe shortest path value in between;is a node vkThe polymerization coefficient of (a);
and acquiring a network model with corresponding aggregation coefficients attached to each node, and performing network topology analysis and reliability measurement of the power communication system on the acquired network model.
According to the electric power communication network construction method based on the node aggregation coefficients, the network model of the electric power communication network is obtained, the aggregation coefficients of all nodes are obtained by combining the node weights and the shortest paths among the nodes for all nodes in the network model, the network model with the corresponding aggregation coefficients attached to all the nodes is obtained, and the reliability determination accuracy of the electric power communication system can be remarkably improved.
Drawings
Fig. 1 is a schematic flow chart of a method for constructing a power communication network based on a node aggregation coefficient according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a power communication transmission backbone network of a power saving network in an embodiment of a method for constructing a power communication network based on a node aggregation coefficient according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to examples and drawings, but the present invention is not limited thereto.
As shown in fig. 1, the present invention is a schematic flow chart of a method for constructing a power communication network based on node aggregation coefficients, and the method includes the following steps:
s11, acquiring a network model of the power communication network; the network model comprises nodes and links, wherein the nodes are communication equipment in the power communication system, and the links are all optical cables for connecting the nodes;
s12, calculating the aggregation coefficient of the nodes according to the following formula:
wherein, WiIs a node viD (k, z) is a node vkAnd vzThe shortest path value in between;is a node vkThe polymerization coefficient of (a);
s13, acquiring a network model with corresponding aggregation coefficients attached to each node, and performing network topology analysis and reliability measurement of the power communication system on the acquired network model;
in the embodiment, in consideration of the obvious difference in the status and the action of each node in the power communication network, the status and the action of important nodes in the provincial power communication backbone network, such as a provincial dispatching center and a 500KV substation, are greater than those of other nodes, and the compactness between the important nodes contributes more to the overall reliability of the network. Therefore, a node aggregation coefficient concept is introduced, and the node weight and the node compactness are combined to comprehensively analyze the position of the network node in the network topology;
the node weight considers the position and the action of the node, and the power communication network node weight can be considered from two aspects, namely the position and the action of a site where the power communication network node is located in a power grid; the second is the position and role of the power communication network nodes in the communication network, such as evaluating the node weight from the aspects of node types (including aggregation nodes and common nodes) and node devices (processing capability and forwarding capability).
In the power communication network, the more closely the important nodes are connected with other important nodes in the network, the more reasonable the network topology is, and the more reliable the network is. The node aggregation coefficient in this embodiment represents a weighted average shortest distance between one node and another node, and takes the weight of the node into consideration. The node aggregation coefficient can be used for measuring the average distance between the node and the important node, and the smaller the distance between the node and the important node is, the denser the distribution of the important node around the node is, and the higher the aggregation coefficient of the node is. The property of the aggregation coefficient has practical application value in the power communication network, for example, the dispatching center undertakes the monitoring and control tasks of the power system, needs to process a large amount of power service information, the denser the distribution of the important nodes around the dispatching center is, the more reasonable the power communication network topology is, and the higher the network reliability is.
Assuming that V is a node in the unweighted network graph G ═ V, E, node VkThe polymerization coefficient of (a) is calculated as follows:
wherein, WiIs a node viNode weight value of WzIs a node vzD (k, z) is a node vkAnd vzThe shortest path value in between;
is node vkAnd vzThe reciprocal of the shortest path between the nodes represents the compactness between the two nodes, and the shorter the distance between the nodes is, the larger the value is, the higher the compactness between the nodes is. The value range of the node tightness is (0,1)]When the compactness value is 1, the two nodes are directly connected, and the two nodes are connected most closely at the moment.
By node vkFor the center, calculating the compactness between other nodes in the network and the node, and simultaneously considering the nodeThe weight of the point itself is used to obtain an index which can reflect the average degree of tightness of the distribution of the nodes around the nodeI.e. the node aggregation coefficient. The larger the node aggregation coefficient is, the denser the distribution of important nodes around the node is, and the distance between the center of gravity of the network and the node vkThe more recent, the more important the position of the corresponding node on the network topology.
Node aggregate coefficientThe importance of the nodes and the connection status of the nodes with the important nodes are described, the position of the nodes in the network can be reflected, the distribution status of the network important nodes is analyzed by utilizing the node aggregation coefficient indexes, the higher the connection tightness between the important nodes is, the closer the center of gravity of the network is to the important nodes, the more reasonable the network structure is, the higher the overall connection reliability is, the lower the risk of the corresponding network structure is, and the accuracy of network reliability determination can be obviously improved.
As shown in fig. 2, a node aggregation coefficient is analyzed by taking a power transmission backbone network of a certain power saving network as an example;
according to the above steps of this embodiment, the aggregation coefficients of the nodes in the example network are calculated by combining the node-related data, and the obtained aggregation coefficient results of the nodes are shown in the following table:
as can be seen from the above table, node v1Is the middle adjusting point with the highest weight and the aggregation coefficient of 0.5555, which is the maximum of all the nodes of the network, therefore, the position and the weight of the middle adjusting point are positioned in the networkThe weight positions are matched; in addition, node v2And v11The node is a local adjusting point, is a regional scheduling center, has a small jurisdiction range, and has a relatively small but reasonable aggregation coefficient. Comprehensive analysis shows that the topological position of each node of the network is basically matched with the weight position of each node, and the network structure design is reasonable, so that the aggregation coefficient has wide application prospect in network reliability analysis and network planning.
In a preferred embodiment, the node weight value can be obtained by:
s21, acquiring the site type and the site scale of the node, and determining the site level, the site level influence value, the site scale and the site scale value influence value of the node according to a preset site factor influence rule;
s22, acquiring the power supply load of the node, and determining the load grade, the load grade influence value, the load size and the load size influence value of the node according to a preset load factor influence rule;
s23, determining the influence score value of each node according to the factor index set, and calculating a node relative influence matrix under each factor index; wherein the factor index set comprises a plurality of factor indexes, and the factor indexes comprise the site grade, the site scale, the load grade and the load size;
s24, adding and summing the relative influence according to the node relative influence matrix under each factor index to obtain a node comprehensive relative influence matrix;
s25, normalizing the node comprehensive relative influence matrix to obtain a power grid influence factor value of each node;
in a preferred embodiment, the site type includes a dispatch center, a substation, or a power plant;
the power communication network node is located at a site which comprises a dispatching center, a transformer substation, a power plant and the like, the similar sites also distinguish voltage classes or management classes, if a 500KV transformer substation is higher in grade than a 220KV transformer substation, the influence is large, the 500KV transformer substation belongs to the jurisdiction of a network dispatching center (a regional power grid dispatching center), the 220KV transformer substation is governed by a central dispatching center (a provincial power grid dispatching center), and the site class is directly reflected by the status of the site in a power grid; in addition, the site scale also affects the node status, for example, the transformer substation is divided into a hub station, a regional station and a terminal station according to the scale, the transformer substations of different scales have different functions and actions and different corresponding statuses, and meanwhile, the influence degree of the scheduling center can be distinguished according to the scale of the site governed by the scheduling center. Therefore, the site category factor of the node is evaluated from two factors of site level and site scale.
For objectively evaluating site category factors, three factor evaluation criteria of node grade and node scale are established according to relevant regulations of power enterprise production management, and are shown in the following table:
in summary, the site level includes a special level, a first level or a second level, and each level may correspond to a different numerical value; the station scales comprise a hub station, a regional station and a terminal station, and each scale can correspond to different values; according to the category factor of the site where the node is located, according to the preset site factor influence rule and according to the information of the site where each node is located, the corresponding site type influence value and the corresponding site scale value influence value are given to the node. The specific influence values of the site types and the site scale values corresponding to different site types and site scales can be set according to actual needs.
For the transformer substation directly serving the power consumer or the dispatching node indirectly serving the power consumer, the provincial production unit, the provincial power dispatching plant and other nodes, the importance degree of the served users has a great influence on the influence of the nodes, and therefore the station load grades are distinguished according to the power consumer grades served by the power loads.
According to the relevant national regulations, power consumers are divided into important power consumers and other power consumers, the important power consumers are important in social, political and economic lives of a country or a region (city), and power interruption to the important power consumers can cause personal casualties, large environmental pollution, large political influences, large economic losses, and serious social and public order disorder power utilization units or power utilization places with special requirements on power supply reliability. The important power user list is provided by a power supply enterprise according to the industry range and the power consumption load characteristics of the important power users determined by the relevant departments of the local people's governments, and is approved by the relevant departments of the local people's governments above the county level and then reported to the power supervision organization for record. According to the requirement of power supply reliability and the degree of power supply interruption hazard, important users can be classified into special-level, first-level and second-level important power users and temporary important power users.
The special level important users are power users which have a particularly important role in managing national affairs and can possibly harm national safety when power supply is interrupted; the primary important users refer to power users which may be affected by the interruption of power supply; secondary important users, which are power users that may have great influence and loss when power supply is interrupted; the temporary important power consumers refer to power consumers (large-scale hydro hubs, tunnel construction and heavy-duty temporary power conservation consumers) needing temporary special power supply guarantee.
The size of the site load is an important reference index of the influence degree of the site. The load size of the station in the power grid is not a fixed value and changes along with the change of the load of the power grid, but the relative size of the load of the station in the power grid is relatively stable, so that the load size of the station is evaluated by utilizing the load proportion of the station in the power grid. A complete failure of a site or its jurisdiction and an outages will result in a grid derating load, i.e. the maximum reduction in the actual load of the grid during the occurrence of an accident.
The accident grade caused by the reduction of the supply load of the power grid is distinguished as shown in the following table:
according to the fact that the station where the node is located or the jurisdiction range of the station completely fails and the level difference of the power grid power reduction load accidents caused by external power failure serves as an evaluation standard for evaluating the node load size factor, the load level factor is synthesized, and the node load factor evaluation criterion is obtained and is shown in the following table.
In summary, the load grades include special grade, first grade or second grade, and each grade can correspond to different numerical values; presetting a corresponding influence force value according to the load grade; the load is the power grid load of the node, the load is determined according to the power grid reduction load accident level, and a corresponding influence value is preset.
In a preferred embodiment, the set of factor indicators is: k ═ KnN is 1,2, ·, N; in this example, knReferring to the factor indicators above: site level, site size, load level and load size, where N equals 4, k1、k2、k3、k4Respectively refer to the four indexes.
The step of determining the influence score value of each node according to the factor index set and calculating the relative influence matrix of the nodes under each factor index comprises the following steps:
and calculating to obtain the relative influence matrix of the nodes according to the following formula:
wherein each node constitutes a node set V ═ Vi1,2, ·, I; the influence score of each node in the node set is { s }i(kn)}，si(kn)∈{1,2,...,Skn}，si(kn) Is a node viAt factor index knThe lower influence value;
representing a node viAnd vjAt factor index knRelative impact value of; when the value of i is equal to j,when i ≠ j,
for the same factor index knSumming the row vector elements of the lower node relative influence matrix to obtain a factor index knLower node relative influence moment array
Wherein the node comprehensive relative influence matrix is
In a preferred embodiment, when the node comprehensive relative influence matrix is normalized, the node comprehensive relative influence moment matrix is normalized by adopting a normalization method based on membership.
The step of normalizing the node comprehensive relative influence moment array by adopting a normalization method based on membership comprises the following steps:
normalizing the node comprehensive relative influence matrix through the following formula to obtain the power grid influence factor value of each node, wherein the node viThe grid impact factor values of (a) are:
wherein,F(vi) Is a node viThe value of the grid impact factor of (c), the value range is ∈ (0,1) for the preset normalization parameter.
The method for constructing the power communication network based on the node aggregation coefficient has the following beneficial effects: and a node aggregation coefficient index is provided, and the index combines the importance of the nodes and the compactness of the nodes, so that the positions of the nodes of the power communication network in the network topology can be more comprehensively described. The node weight is considered when the node aggregation coefficient is calculated, and the node weight describes the position and the function of the node and is irrelevant to the network where the node is located and the topological structure of the node. The node aggregation coefficient describes the connection condition of the node and the important node and can reflect the position of the node in the network. By utilizing the node aggregation coefficient index, the distribution condition of the network important nodes can be more comprehensively analyzed. The closer the connection tightness between the important nodes is, the closer the center of gravity of the network is to the important nodes, the more reasonable the network structure is, the higher the overall connection reliability is, the lower the risk of the corresponding network structure is, and the accuracy of the reliability determination of the power communication system can be obviously improved.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (7)
1. A power communication network construction method based on node aggregation coefficients is characterized by comprising the following steps:
acquiring a network model of the power communication network; the network model comprises nodes and links, wherein the nodes are communication equipment in the power communication system, and the links are all optical cables for connecting the nodes;
calculating an aggregation coefficient for the node by:
wherein, WiIs a node viD (k, z) is a node vkAnd vzThe shortest path value in between;is a node vkV is a set of node labels in the power communication network;
and acquiring a network model with corresponding aggregation coefficients attached to each node, and performing network topology analysis and reliability measurement of the power communication system on the acquired network model.
2. The method for constructing the power communication network based on the node aggregation coefficient according to claim 1, wherein the node weight value is obtained by:
acquiring the site type and the site scale of the node, and determining the site level, the site level influence value, the site scale and the site scale value influence value of the node according to a preset site factor influence rule;
acquiring the power supply load of the node, and determining the load grade, the load grade influence value, the load size and the load size influence value of the node according to a preset load factor influence rule;
determining the influence score value of each node according to the factor index set, and calculating a node relative influence matrix under each factor index; wherein the factor index set comprises a plurality of factor indexes, and the factor indexes comprise the site grade, the site scale, the load grade and the load size;
adding and summing the relative influence according to the node relative influence matrix under each factor index to obtain a node comprehensive relative influence matrix;
and normalizing the node comprehensive relative influence matrix to obtain a power grid influence factor value of each node as the node weight value.
3. The method for constructing the power communication network based on the node aggregation coefficient as claimed in claim 2, wherein the site type includes a dispatch center, a substation, or a power plant.
4. The method for constructing a power communication network of node aggregation coefficients according to claim 2, wherein:
the factor index set is: k ═ Kn},n＝1,2,...,N，N＝4；
The step of determining the influence score value of each node according to the factor index set and calculating the relative influence matrix of the nodes under each factor index comprises the following steps:
and calculating to obtain the relative influence matrix of the nodes according to the following formula:
wherein each node viConstituent node set B ═ BiI, I is the total number of nodes; the influence score of each node in the node set is { s }i(kn)}，si(kn) Is node biAt factor index knThe lower influence value;
representing a node viAnd vjAt factor index knRelative impact value of; when the value of i is equal to j,when i ≠ j,
for the same factor index knSumming the row vector elements of the lower node relative influence matrix to obtain a factor index knLower node relative influence moment array
5. The method for constructing the power communication network of the node aggregation coefficient according to claim 4, wherein the node comprehensive relative influence matrix is
6. The method for constructing the power communication network of the node aggregation coefficient according to claim 5, wherein a normalization method based on membership is adopted to normalize the comprehensive relative influence moment matrix of the nodes when normalizing the comprehensive relative influence matrix of the nodes.
7. The method for constructing the power communication network of the node aggregation coefficient according to claim 6, wherein the step of normalizing the node comprehensive relative influence moment array by using a normalization method based on membership comprises:
normalizing the node comprehensive relative influence matrix through the following formula to obtain the power grid influence factor value of each node, wherein the node viThe grid impact factor values of (a) are:
wherein,F(vi) Is a node viThe value of the grid impact factor of (c),for the normalization parameter, the value range is ∈ (0, 1).
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410710163.9A CN104579867B (en) | 2014-11-28 | 2014-11-28 | Based on the power communication network construction process of node aggregation coefficient |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410710163.9A CN104579867B (en) | 2014-11-28 | 2014-11-28 | Based on the power communication network construction process of node aggregation coefficient |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104579867A CN104579867A (en) | 2015-04-29 |
| CN104579867B true CN104579867B (en) | 2016-06-08 |
Family
ID=53095124
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410710163.9A Active CN104579867B (en) | 2014-11-28 | 2014-11-28 | Based on the power communication network construction process of node aggregation coefficient |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104579867B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107480849B (en) * | 2017-06-28 | 2021-04-02 | 北京邮电大学 | Space dimension reduction method and device applied to power grid |
| CN107453897B (en) * | 2017-07-03 | 2021-11-19 | 北京邮电大学 | Node importance evaluation method and device, electronic equipment and storage medium |
| CN107612703B (en) * | 2017-07-27 | 2020-08-25 | 中国人民解放军国防信息学院 | Two-dimensional aggregated joint tactical communication system model, construction method and application method |
| CN116667918A (en) * | 2023-05-31 | 2023-08-29 | 国网冀北电力有限公司承德供电公司 | Optical cable reliability analysis method, system, equipment and storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102035256A (en) * | 2010-11-26 | 2011-04-27 | 山东电力研究院 | Auxiliary decision method for recovering group multiattitude of power system |
| CN102751722A (en) * | 2012-06-18 | 2012-10-24 | 上海交通大学 | Grid network optimization method based on shortest feasible path and historical flow data |
| CN103345552A (en) * | 2013-06-28 | 2013-10-09 | 广东电网公司电力调度控制中心 | Method and device for assessing reliability of power ICT communication network |
| CN103476051A (en) * | 2013-09-11 | 2013-12-25 | 华北电力大学（保定） | Method for evaluating importance of nodes in communication network |
| CN103473715A (en) * | 2013-09-09 | 2013-12-25 | 国家电网公司 | Method for evaluating reliability of power distribution network provided with distributed photovoltaic system |
| CN103870631A (en) * | 2014-02-15 | 2014-06-18 | 中国能源建设集团广东省电力设计研究院 | Construction method for intelligent power transmission network layout model based on 3S technology |
-
2014
- 2014-11-28 CN CN201410710163.9A patent/CN104579867B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102035256A (en) * | 2010-11-26 | 2011-04-27 | 山东电力研究院 | Auxiliary decision method for recovering group multiattitude of power system |
| CN102751722A (en) * | 2012-06-18 | 2012-10-24 | 上海交通大学 | Grid network optimization method based on shortest feasible path and historical flow data |
| CN103345552A (en) * | 2013-06-28 | 2013-10-09 | 广东电网公司电力调度控制中心 | Method and device for assessing reliability of power ICT communication network |
| CN103473715A (en) * | 2013-09-09 | 2013-12-25 | 国家电网公司 | Method for evaluating reliability of power distribution network provided with distributed photovoltaic system |
| CN103476051A (en) * | 2013-09-11 | 2013-12-25 | 华北电力大学（保定） | Method for evaluating importance of nodes in communication network |
| CN103870631A (en) * | 2014-02-15 | 2014-06-18 | 中国能源建设集团广东省电力设计研究院 | Construction method for intelligent power transmission network layout model based on 3S technology |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104579867A (en) | 2015-04-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104579868B (en) | Powerline network construction method based on pitch point importance | |
| WO2023035499A1 (en) | Method and system for comprehensive evaluation of resilience of power distribution network | |
| CN106529696B (en) | Early warning method and early warning device for equipment in power grid | |
| CN101800426B (en) | Safety level evaluation method of power grid | |
| CN102437573B (en) | Evaluation and control method and system for reliability of electric distribution network based on fuzzy modeling | |
| CN104408549A (en) | Running state evaluation method of urban distribution network | |
| CN109214702A (en) | Urban power distribution network operation level and power supply capacity fuzzy synthetic appraisement method based on AHP- entropy assessment | |
| CN104579867B (en) | Based on the power communication network construction process of node aggregation coefficient | |
| CN104156881A (en) | Comprehensive power distribution network fault risk assessment method | |
| CN107453897B (en) | Node importance evaluation method and device, electronic equipment and storage medium | |
| CN104392391A (en) | Power grid running safety risk quantification method | |
| CN104050373B (en) | The security risk quantitative estimation method of PCM equipment in a kind of power communication | |
| CN105678469A (en) | Risk assessment method for relay protection equipment in intelligent substation | |
| CN107633320A (en) | A kind of power network line importance appraisal procedure based on weather prognosis and risk assessment | |
| CN103810533A (en) | Cloud-model-based power distribution network fault risk identification method | |
| CN113592128A (en) | Big data electric wire netting operation monitoring system | |
| CN108681800A (en) | A kind of fortune inspection methods of risk assessment of distributed new access power distribution network | |
| CN105096207A (en) | Important power user power supply reliability estimation method based on analytic hierarchy process | |
| CN104363127B (en) | Based on the power communication network construction process of the electric network influencing factor | |
| CN103632311A (en) | Fault examining system and method for power grid operation | |
| CN108551166A (en) | A kind of grid equipment and section ultra-short term, alarm and steady prosecutor method | |
| CN104166940A (en) | Method and system for assessing power distribution network operation risk | |
| CN112202597A (en) | Method for evaluating importance of communication network node in low-voltage distribution area | |
| CN102930408A (en) | State evaluation method based on information fusion for secondary equipment of 750 kV power grid | |
| Nanab et al. | A quantitative method for assessing the resilience of infrastructure systems |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CP01 | Change in the name or title of a patent holder | ||
| CP01 | Change in the name or title of a patent holder |
Address after: 510699 No. 75 Meihua Road, Yuexiu District, Guangzhou City, Guangdong Province Co-patentee after: Zhongtong Unicom Established Information Technology Co., Ltd. Patentee after: POWER DISPATCH CONTROL CENTER, GUANGDONG POWER GRID CO., LTD. Address before: 510699 No. 75 Meihua Road, Yuexiu District, Guangzhou City, Guangdong Province Co-patentee before: Sichuan Enrising Information Technology Co., Ltd. Patentee before: POWER DISPATCH CONTROL CENTER, GUANGDONG POWER GRID CO., LTD. |