CN107909197B - Statistical analysis method for operation mode of large branch based on feeder tree - Google Patents

Statistical analysis method for operation mode of large branch based on feeder tree Download PDF

Info

Publication number
CN107909197B
CN107909197B CN201711113075.0A CN201711113075A CN107909197B CN 107909197 B CN107909197 B CN 107909197B CN 201711113075 A CN201711113075 A CN 201711113075A CN 107909197 B CN107909197 B CN 107909197B
Authority
CN
China
Prior art keywords
feeder
information array
devices
path
branch path
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
Application number
CN201711113075.0A
Other languages
Chinese (zh)
Other versions
CN107909197A (en
Inventor
殷自力
许书锟
陈宇星
王清凉
黄文英
朱宗毅
张伟
张珠玉
李吉昌
陈朋
段渴望
高玉羊
吴建栋
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
State Grid Corp of China SGCC
State Grid Fujian Electric Power Co Ltd
Integrated Electronic Systems Lab Co Ltd
Fuzhou Power Supply Co of State Grid Fujian Electric Power Co Ltd
Original Assignee
State Grid Corp of China SGCC
State Grid Fujian Electric Power Co Ltd
Integrated Electronic Systems Lab Co Ltd
Fuzhou Power Supply Co of State Grid Fujian Electric Power Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by State Grid Corp of China SGCC, State Grid Fujian Electric Power Co Ltd, Integrated Electronic Systems Lab Co Ltd, Fuzhou Power Supply Co of State Grid Fujian Electric Power Co Ltd filed Critical State Grid Corp of China SGCC
Priority to CN201711113075.0A priority Critical patent/CN107909197B/en
Publication of CN107909197A publication Critical patent/CN107909197A/en
Application granted granted Critical
Publication of CN107909197B publication Critical patent/CN107909197B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G06Q10/047Optimisation of routes or paths, e.g. travelling salesman problem
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06Energy or water supply
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • Health & Medical Sciences (AREA)
  • Marketing (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Tourism & Hospitality (AREA)
  • Quality & Reliability (AREA)
  • Development Economics (AREA)
  • Game Theory and Decision Science (AREA)
  • Operations Research (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Public Health (AREA)
  • Water Supply & Treatment (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Power Engineering (AREA)
  • Mobile Radio Communication Systems (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)

Abstract

The invention relates to a statistical analysis method for a large branch operation mode based on a feeder tree. The method comprises the following steps: firstly, establishing a feeder tree information array FTIM, and recording the topological connection relation of feeder equipment by the array; secondly, establishing a feeder tree trunk path information array FZIM, and recording a trunk path topological connection relation between a transformer substation outgoing switch and a tie switch of a feeder line by the array; generating a branch path father node adjacency list FFT according to the feeder tree information array FTIM and the feeder tree trunk path information array FZIM; and finally, generating a large branch path information array FLIM according to the feeder tree information array FTIM and the branch path father node adjacency list FFT. The method has better adaptability and certain practical value when analyzing the feeder line operation mode and searching the operation state of the large branch.

Description

Statistical analysis method for operation mode of large branch based on feeder tree
Technical Field
The invention relates to the field of analysis of operation modes of a power distribution network, in particular to a statistical analysis method of operation modes of large branches based on a feeder tree.
Background
The power supply reliability is an important index for measuring the intelligent degree of the power distribution network, and the action plan of the national network 'thirteen-five' also incorporates the index into a work report.
The operation mode of the power distribution network is the key for ensuring the safe and reliable operation of the power distribution network, is the basis for ensuring the reliability of power supply, and needs to supply power to important users including lifeline users, power-protection users, government users and sensitive users firstly when the operation mode is analyzed. In order to reduce the power outage area when a fault occurs, the power supply for the large branch needs to be ensured, so that the large branch of the power distribution network feeder line needs to be analyzed and counted.
In conclusion, the research on the statistical analysis method of the large branch of the feeder line of the power distribution network has important practical significance for formulating a reliable and effective operation mode.
Disclosure of Invention
The invention aims to provide a statistical analysis method for a large branch operation mode based on a feeder tree, which has better adaptability and certain practical value when the method is used for analyzing the feeder operation mode and searching the large branch operation state
In order to achieve the purpose, the technical scheme of the invention is as follows: a statistical analysis method for operation modes of large branches based on a feeder tree comprises the following steps,
s1, establishing a feeder tree information array FTIM, and recording the topological connection relation of feeder equipment by the array;
s2, establishing a feeder tree trunk path information array FZIM, and recording a trunk path topological connection relation between a substation outgoing switch and a tie switch of a feeder line by the array;
s3, generating a branch path father node adjacency list FFT according to the feeder tree information array FTIM and the feeder tree trunk path information array FZIM;
s4, generating a large branch path information array FLIM according to the feeder tree information array FTIM and the branch path father node adjacency list FFT.
In an embodiment of the present invention, the specific implementation procedure in step S1 is as follows,
establishing a feeder tree information array FTIM:
Figure BDA0001465610760000021
wherein, each row represents the parent-child topological connection relation of one device, i is 1,2,3, …, n, fti1Is the name of the ith device of the feeder line, fti2Name of parent node connected for feeder ith device, fti3And the sub-node set is connected with the ith device of the feeder line.
In an embodiment of the present invention, the specific implementation process of step S2 is as follows,
establishing a feeder tree trunk path information array FZIM,
Figure BDA0001465610760000022
wherein each action is a trunk path, fzijThe name of j-th equipment in the ith trunk path of the feeder line is shown, i is 1,2,3, …, and n is the number of trunk paths; j is 1,2,3, …, m, m is the number of devices included in the longest trunk path, if fzijIf not, take-1.
In an embodiment of the present invention, the specific implementation process of step S3 is as follows,
s31, taking any line i in the feeder tree trunk path information array FZIM, and sequentially selecting the jth (j is 1,2,3 … m) data fz according to the sequenceijAnd proceeds to step S32 to perform the processing;
s32, searching column 1 and fz in feeder tree information array FTIMijIf the devices in the child nodes of the devices with the same name are all located on the main path, returning to step S31, if the devices in the child nodes of the devices with the same name contain devices on the non-main path, putting all devices on the non-main path into the branch path parent node adjacency table FFT, and if the devices already exist in the FFT, not processing the devices; the specific description is as follows:
FFT=[ff1,ff2,ff3,…,ffk,…ffw]
wherein ff iskThe name of the parent node device of the branch path is shown, k is 1,2,3 … w, and w is the number of the parent node devices of the separating gate data;
and S33, repeating the step S31 and the step S32 until all the rows in the feeder tree trunk path information array FZIM are processed.
In an embodiment of the present invention, the specific implementation process of step S4 is as follows,
s41, taking any one ff in branch path father node adjacent table FFTkSearching all the devices supplied with power at the downstream according to the feeder tree information array FTIM, and calculating the power distribution supplied by the devicesThe number N of transformers, step S42;
s42, if the number N of distribution transformers is greater than or equal to the predetermined limit number VAL, the device ff is usedkThe branch path of the father node is a large branch path, and all the devices of the father node are written into a large branch path information array FLIM according to the topological relation; if the number N of distribution transformers is less than the prescribed limit number VAL, returning to step S41;
Figure BDA0001465610760000031
wherein each action is a large branch path, flpqFor the name of the q-th device in the p-th large branch path of the feeder line, p is 1,2,3, …, g and g are the large branch path number. q is 1,2,3, …, h, h is the number of devices in the longest branch path, if flpqIf the signal does not exist, taking-1;
and S43, repeating the step S41 and the step S42 until all the devices in the FFT of the branch path parent node adjacency list are analyzed.
Compared with the prior art, the invention has the following beneficial effects: firstly, establishing a feeder tree information array FTIM, and recording the topological connection relation of feeder equipment by the array; secondly, establishing a feeder tree trunk path information array FZIM, and recording a trunk path topological connection relation between a transformer substation outgoing switch and a tie switch of a feeder line by the array; generating a branch path father node adjacency list FFT according to the feeder tree information array FTIM and the feeder tree trunk path information array FZIM; finally, generating a large branch path information array FLIM according to the feeder tree information array FTIM and the branch path father node adjacency list FFT; the method has better adaptability and certain practical value when analyzing the operation mode of the feeder line and searching the operation state of the large branch.
Detailed Description
The technical solution of the present invention is specifically explained below.
The invention relates to a statistical analysis method for a big branch operation mode based on a feeder tree, which comprises the following steps,
s1, establishing a feeder tree information array FTIM, and recording the topological connection relation of feeder equipment by the array;
s2, establishing a feeder tree trunk path information array FZIM, and recording a trunk path topological connection relation between a substation outgoing switch and a tie switch of a feeder line by the array;
s3, generating a branch path father node adjacency list FFT according to the feeder tree information array FTIM and the feeder tree trunk path information array FZIM;
s4, generating a large branch path information array FLIM according to the feeder tree information array FTIM and the branch path father node adjacency list FFT.
Establishing a feeder tree information array FTIM, and recording the topological connection relation of feeder equipment by the array, which is specifically described as follows:
establishing a feeder tree information array FTIM:
Figure BDA0001465610760000041
wherein, each row represents the parent-child topological connection relation of one device, i is 1,2,3, …, n, fti1Is the name of the ith device of the feeder line, fti2Name of parent node connected for feeder ith device, fti3And the sub-node set is connected with the ith device of the feeder line.
Establishing a feeder tree trunk path information array FZIM, and recording a trunk path topological connection relation between a substation outgoing switch and a tie switch of a feeder by the array, wherein the detailed description is as follows:
establishing a feeder tree trunk path information array FZIM,
Figure BDA0001465610760000042
wherein each action is a trunk path, fzijThe name of j-th equipment in the ith trunk path of the feeder line is shown, i is 1,2,3, …, and n is the number of trunk paths; j is 1,2,3, …, m, m is the number of devices included in the longest trunk path, if fzijIf not, take-1.
Generating a branch path father node adjacency list FFT according to a feeder tree information array FTIM and a feeder tree trunk path information array FZIM, which is specifically described as follows:
s31, taking any line i in the feeder tree trunk path information array FZIM, and sequentially selecting the jth (j is 1,2,3 … m) data fz according to the sequenceijAnd proceeds to step S32 to perform the processing;
s32, searching column 1 and fz in feeder tree information array FTIMijIf the devices in the child nodes of the devices with the same name are all located on the main path, returning to step S31, if the devices in the child nodes of the devices with the same name contain devices on the non-main path, putting all devices on the non-main path into the branch path parent node adjacency table FFT, and if the devices already exist in the FFT, not processing the devices; the specific description is as follows:
FFT=[ff1,ff2,ff3,…,ffk,…ffw]
wherein ff iskThe name of the parent node device of the branch path is shown, k is 1,2,3 … w, and w is the number of the parent node devices of the separating gate data;
and S33, repeating the step S31 and the step S32 until all the rows in the feeder tree trunk path information array FZIM are processed.
Generating a large branch path information array FLIM according to the feeder tree information array FTIM and the branch path father node adjacency list FFT, which is specifically described as follows:
s41, taking any one ff in branch path father node adjacent table FFTkSearching all the devices supplied with power at the downstream according to the feeder tree information array FTIM, calculating the number N of the distribution transformers supplied with power, and entering the step S42;
s42, if the number N of distribution transformers is greater than or equal to the predetermined limit number VAL, the device ff is usedkThe branch path of the father node is a large branch path, and all the devices of the father node are written into a large branch path information array FLIM according to the topological relation; if the number N of distribution transformers is less than the prescribed limit number VAL, returning to step S41;
Figure BDA0001465610760000051
wherein each action is a large branch path, flpqFor the name of the q-th device in the p-th large branch path of the feeder line, p is 1,2,3, …, g and g are the large branch path number. q is 1,2,3, …, h, h is the number of devices in the longest branch path, if flpqIf the signal does not exist, taking-1;
and S43, repeating the step S41 and the step S42 until all the devices in the FFT of the branch path parent node adjacency list are analyzed.
The above are preferred embodiments of the present invention, and all changes made according to the technical scheme of the present invention that produce functional effects do not exceed the scope of the technical scheme of the present invention belong to the protection scope of the present invention.

Claims (1)

1. A statistical analysis method for operation modes of large branches based on a feeder tree is characterized in that: comprises the following steps of (a) carrying out,
s1, establishing a feeder tree information array FTIM, and recording the topological connection relation of feeder equipment by the array;
s2, establishing a feeder tree trunk path information array FZIM, and recording a trunk path topological connection relation between a substation outgoing switch and a tie switch of a feeder line by the array;
s3, generating a branch path father node adjacency list FFT according to the feeder tree information array FTIM and the feeder tree trunk path information array FZIM;
s4, generating a large branch path information array FLIM according to the feeder tree information array FTIM and the branch path father node adjacency list FFT;
the specific implementation process in step S1 is as follows,
establishing a feeder tree information array FTIM:
Figure FDA0003103064190000011
wherein, each row represents the parent-child topological connection relation of one device, i is 1,2,3, …, n, fti1Is the name of the ith device of the feeder line, fti2Name of parent node connected for ith device of feeder line,fti3A set of sub-nodes connected for the ith device of the feeder line;
the specific implementation process of step S2 is as follows,
establishing a feeder tree trunk path information array FZIM,
Figure FDA0003103064190000012
wherein each action is a trunk path, fzijThe name of j-th equipment in the ith trunk path of the feeder line is shown, i is 1,2,3, …, and n is the number of trunk paths; j is 1,2,3, …, m, m is the number of devices included in the longest trunk path, if fzijIf the signal does not exist, taking-1;
the specific implementation process of step S3 is as follows,
s31, taking any line i in the feeder tree trunk path information array FZIM, and sequentially selecting the jth (j is 1,2,3 … m) data fz according to the sequenceijAnd proceeds to step S32 to perform the processing;
s32, searching column 1 and fz in feeder tree information array FTIMijIf the devices in the child nodes of the devices with the same name are all located on the main path, returning to step S31, if the devices in the child nodes of the devices with the same name contain devices on the non-main path, putting all devices on the non-main path into the branch path parent node adjacency table FFT, and if the devices already exist in the FFT, not processing the devices; the specific description is as follows:
FFT=[ff1,ff2,ff3,…,ffk,…ffw]
wherein ff iskThe name of the parent node device of the branch path is shown, k is 1,2,3 … w, and w is the number of the parent node devices of the separating gate data;
s33, repeating the step S31 and the step S32 until all the rows in the feeder tree trunk path information array FZIM are processed;
the specific implementation process of step S4 is as follows,
s41, taking any one ff in branch path father node adjacent table FFTkAccording to the feeder tree information array FTIM search methodAll the devices supplied with power by the downstream, and the number N of the distribution transformers supplied with power by the devices is calculated, and the step S42 is carried out;
s42, if the number N of distribution transformers is greater than or equal to the predetermined limit number VAL, the device ff is usedkThe branch path of the father node is a large branch path, and all the devices of the father node are written into a large branch path information array FLIM according to the topological relation; if the number N of distribution transformers is less than the prescribed limit number VAL, returning to step S41;
Figure FDA0003103064190000021
wherein each action is a large branch path, flpqThe name of the q device in the p-th large branch path of the feeder line is shown, and p is 1,2,3, …, g and g are the number of the large branch paths; q is 1,2,3, …, h, h is the number of devices in the longest branch path, if flpqIf the signal does not exist, taking-1;
and S43, repeating the step S41 and the step S42 until all the devices in the FFT of the branch path parent node adjacency list are analyzed.
CN201711113075.0A 2017-11-13 2017-11-13 Statistical analysis method for operation mode of large branch based on feeder tree Active CN107909197B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201711113075.0A CN107909197B (en) 2017-11-13 2017-11-13 Statistical analysis method for operation mode of large branch based on feeder tree

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201711113075.0A CN107909197B (en) 2017-11-13 2017-11-13 Statistical analysis method for operation mode of large branch based on feeder tree

Publications (2)

Publication Number Publication Date
CN107909197A CN107909197A (en) 2018-04-13
CN107909197B true CN107909197B (en) 2021-08-31

Family

ID=61844844

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201711113075.0A Active CN107909197B (en) 2017-11-13 2017-11-13 Statistical analysis method for operation mode of large branch based on feeder tree

Country Status (1)

Country Link
CN (1) CN107909197B (en)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112421612B (en) * 2020-11-03 2023-01-06 北京科东电力控制系统有限责任公司 Medium-voltage main line branch line analysis method based on distribution network operation state
CN115425652B (en) * 2022-11-07 2023-01-24 广东电网有限责任公司肇庆供电局 Method and system for identifying key main path of power distribution network based on parent-child node information array
CN115459272B (en) * 2022-11-09 2023-03-24 广东电网有限责任公司肇庆供电局 Minimum distribution sub-network dividing method and system based on feeder switch information array

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103426126A (en) * 2013-08-07 2013-12-04 华南理工大学 Generation method for segmental contact topological relationship of feeder line group of regional power grid
CN103631998A (en) * 2013-11-27 2014-03-12 国家电网公司 Power distribution network modeling method for local topology changes
CN104281749A (en) * 2014-10-10 2015-01-14 广州供电局有限公司 Innovation graph method based DG (distributed generation) power distribution network included topology identification method
CN104505820A (en) * 2014-10-24 2015-04-08 广东工业大学 Power distribution network intelligent reconstruction method based on multi-information associated utilization
CN104810829A (en) * 2015-05-26 2015-07-29 中国电力科学研究院 Network structure simplification processing method for power distribution network reconstruction
CN104914356A (en) * 2015-06-21 2015-09-16 国家电网公司 Distribution network fault positioning method based on network structure matrix
CN107024638A (en) * 2016-02-02 2017-08-08 天津理工大学 A kind of electrical power distribution network fault location method and device based on modified evolutionary programming

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2008087257A1 (en) * 2007-01-18 2008-07-24 Suomen Punainen Risti, Veripalvelu Novel methods and reagents directed to production of cells
CN103150425B (en) * 2013-02-06 2015-12-23 上海交通大学 Based on the power distribution network line chart automatic generation method of topological hierarchy
CN105488269A (en) * 2015-11-29 2016-04-13 国家电网公司 CIM based automatic graph-forming system for power transmission and distribution network
CN105977975B (en) * 2016-06-23 2019-01-18 国家电网公司 Feeder line topology based on switch syntople is distributed method
CN107037322B (en) * 2017-04-14 2019-12-17 积成电子股份有限公司 power distribution network low-current grounding fault positioning method based on steady-state characteristics

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103426126A (en) * 2013-08-07 2013-12-04 华南理工大学 Generation method for segmental contact topological relationship of feeder line group of regional power grid
CN103631998A (en) * 2013-11-27 2014-03-12 国家电网公司 Power distribution network modeling method for local topology changes
CN104281749A (en) * 2014-10-10 2015-01-14 广州供电局有限公司 Innovation graph method based DG (distributed generation) power distribution network included topology identification method
CN104505820A (en) * 2014-10-24 2015-04-08 广东工业大学 Power distribution network intelligent reconstruction method based on multi-information associated utilization
CN104810829A (en) * 2015-05-26 2015-07-29 中国电力科学研究院 Network structure simplification processing method for power distribution network reconstruction
CN104914356A (en) * 2015-06-21 2015-09-16 国家电网公司 Distribution network fault positioning method based on network structure matrix
CN107024638A (en) * 2016-02-02 2017-08-08 天津理工大学 A kind of electrical power distribution network fault location method and device based on modified evolutionary programming

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
配电系统安全域的数学定义与存在性证明;肖峻 等;《中国电机工程学报》;20160920;第36卷(第18期);4828-4836 *

Also Published As

Publication number Publication date
CN107909197A (en) 2018-04-13

Similar Documents

Publication Publication Date Title
Ardakanian et al. On identification of distribution grids
Cui et al. Enhance high impedance fault detection and location accuracy via $\mu $-PMUs
CN107909197B (en) Statistical analysis method for operation mode of large branch based on feeder tree
CN111505433B (en) Low-voltage transformer area indoor variable relation error correction and phase identification method
Liu et al. Knowledge-based system for distribution system outage locating using comprehensive information
CN106777150A (en) A kind of cross-system data transfer device for merging operation of power networks environment and facility information
CN106934068A (en) The method that robot is based on the semantic understanding of environmental context
CN113189451A (en) Power distribution network fault positioning studying and judging method, system, computer equipment and storage medium
CN104038375A (en) Alarm processing analysis system and method of broadcasting and TV access network
CN110348114B (en) Non-precise fault identification method for power grid completeness state information reconstruction
CN100576680C (en) Big grid equipment overload is at the intelligence connection blanking method of line sensitivity
CN107271853A (en) Electrical power distribution automatization system distribution low current grounding localization method and system
CN106056466B (en) Bulk power grid critical circuits recognition methods based on FP-growth algorithm
CN116073381B (en) Automatic equipment point distribution decision method considering reliability of power distribution network
CN106603538A (en) Invasion detection method and system
CN108510162B (en) Safety efficiency evaluation method for active power distribution network
CN105634781B (en) Multi-fault data decoupling method and device
CN106159940B (en) The optimal points distributing methods of PMU based on network load specificity analysis
CN111614083B (en) Big data analysis method suitable for 400V power supply network topology identification
US20150227639A1 (en) System data compression system and method thereof
CN106886655A (en) A kind of improvement minimal path reliability based on distribution geographical topology data determines method
Zeng et al. Risk assessment method for smart substation secondary system based on deep neural network
Shao et al. A network risk assessment methodology for power communication business
Zhang et al. Fault detection based on discriminant analysis theory in electric power system
CN104240039B (en) Power system fault analyzing method taking uncertainty influence into consideration

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