AU2020103195A4 - A Method for Detecting Vulnerability of Large-scale Power Grid Based On Complex Network - Google Patents
A Method for Detecting Vulnerability of Large-scale Power Grid Based On Complex Network Download PDFInfo
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- 238000012545 processing Methods 0.000 claims abstract description 7
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
- G05B19/0428—Safety, monitoring
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/048—Monitoring; Safety
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/001—Methods to deal with contingencies, e.g. abnormalities, faults or failures
- H02J3/0012—Contingency detection
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0275—Fault isolation and identification, e.g. classify fault; estimate cause or root of failure
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0275—Fault isolation and identification, e.g. classify fault; estimate cause or root of failure
- G05B23/0281—Quantitative, e.g. mathematical distance; Clustering; Neural networks; Statistical analysis
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02B90/20—Smart grids as enabling technology in buildings sector
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
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- Engineering & Computer Science (AREA)
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- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
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Abstract
The invention discloses a large-scale power grid vulnerability monitoring method based
on a complex network, which comprises the following steps of: establishing a power grid
topological model, simplifying the model, analyzing the model, monitoring the vulnerability
of the model and evaluating and processing the monitoring result; based on the complex
network theory, the power grid topological model created by this invention can improve the
evaluation capability of the model, represent the structural characteristics of the power grid
through a group of model, draw a node degree distribution diagram and a median distribution
diagram of the selected power grid through an artificial intelligence processing module in a
graph module, enable the power grid topological model information and characteristic
parameters to be easy to analyze and calculate through simplifying the topological model with
low requirements on calculation performance, simultaneously, use four attack modes to attack
the power grid model, which makes the monitoring data more comprehensive, ensures the
monitoring accuracy of power grid vulnerability to a certain extent, realizes the reasonable
quantification of electrical dynamic characteristics and static mechanism vulnerability
response, and effectively monitors the vulnerable links in the power grid.
-1/1
Establishment of Power Grid Topological Model
Simplification of Power Grid Topological Model
Analysis of Power Grid Topological Model
Vulnerability Monitoring of Power Grid
Topological Model
Evaluation and Treatment of Monitoring Results
Figure 1
Description
-1/1
Establishment of Power Grid Topological Model
Simplification of Power Grid Topological Model
Analysis of Power Grid Topological Model
Vulnerability Monitoring of Power Grid Topological Model
Evaluation and Treatment of Monitoring Results
Figure 1
A Method for Detecting Vulnerability of Large-scale Power Grid Based On Complex Network
The invention relates to the technical field of power grid vulnerability monitoring, in particular
to a large-scale power grid vulnerability monitoring method based on a complex network.
The increasing scale of power grid and large-scale interconnection of power grid is a trend in
the development of modern power system. Large power grid has achieved a wide range of resource
optimization, with the continuous expansion of power grid scale and the increasing complexity of
new components, it not only optimizes the configuration of the power grid, but also presents a new
challenge to the reliability of the system. Power grid blackout is often a chain reaction caused by
local faults of the vulnerable parts in power grid topological structure, thereby causing the collapse
of the whole system. Effectively monitoring the vulnerable parts of the large power grid, searching
for vulnerable nodes and lines, and taking defensive measures in advance can effectively increase
the reliability of the power grid, reduce the occurrence probability of power outage accidents, and
improve the overall stability of the system;
The traditional method of power grid monitoring is to establish dynamic mathematical
equation based on the working characteristics of distributed power grid, and then get to know the
structure of system through the calculation and simulation of the equation, as well as the analysis of
mathematical model. However, because of the dynamic nature of the network structure, it is
difficult to be characterized by a set of fixed network equations and mathematical models. As
components or systems such as electric vehicles, energy storage, microgrid and the like with dual
characteristics of power supply and load are connected to the power grid on a large scale, the
change of power supply and load becomes the norm, which makes the system network modeling
relatively difficult. In addition, the huge and complex network dynamic mathematical model is
extremely difficult to calculate and analyze, and the calculation performance requirement is high,
which is difficult to meet the requirements of real-time and monitoring accuracy. Therefore, the invention proposes a large-scale power grid vulnerability monitoring method based on a complex network so as to solve the problems existing in the prior art.
In response to the above problems, the invention aims to provide a large-scale power grid vulnerability monitoring method based on a complex network. This method bases on the complex
network theory, improves the evaluation ability of topological model, characterizes the structural
characteristics of the power grid by one set of model and reduces the difficulty of modeling. By
simplifying the topological model, the information and characteristic parameters of the power grid topological model can be easily analyzed and calculated. The requirement for calculation
performance is not high. At the same time, four groups of attack modes are adopted to attack the
power grid model, so that the monitoring data are more comprehensive, the monitoring accuracy of power grid vulnerability is ensured to a certain extent, the reasonable quantification of electrical
dynamic characteristics and static mechanism vulnerability response is realized, and the vulnerable
parts in the power grid are effectively monitored.
In order to realize the object of the invention, the invention is accomplished through the
following technical scheme: a large-scale power grid vulnerability monitoring method based on a complex network, which comprises the following steps:
Step 1, establish a power grid topological model
First, select the power grid to be monitored. Then, according to the complex network theory, the generator is abstracted as the injected power on the generator outlet bus. The substation is
modeled according to the equivalent circuit, and the power supply and load on the low voltage side
are abstracted as active injected power on the corresponding bus at the same time. Then the
generator, substation and load are abstracted as network nodes, and the transmission line is abstracted as edges between nodes in the power grid to obtain the power grid topological model;
Step 2, simplify the power grid topological model
According to step 1, all power grid lines in the power grid topological model are simplified as undirected weighted edges, and the weight of the edges is the efficiency of the lines, then the initial value of the efficiency is set to be 1, and then the transmission lines with the same pole and parallel frame are merged to simplify the model without counting parallel capacitor branches to obtain a simplified power grid topological model;
Step 3, analyze the power grid topological model
According to step 2, at first, carry out information analysis on the power grid topological
model according to the obtained simplified power grid topological model. Then, calculate the
characteristic parameters of the power grid topological model according to the simplified power grid topological model. And then, according to the analyzed power grid topological model
information and the calculated characteristic parameters of it, the node degree distribution diagram
and the median distribution diagram of the selected power grid are drawn through the artificial intelligence processing module in the graphics module;
Step 4: monitor the vulnerability of the model
According to step 3, firstly, four attack modes are adopted to attack the power grid topological
model according to the node degree distribution diagram and the median distribution diagram of the
power grid, and then the connectivity of the power grid topological model under the attack of
different modes is monitored and analyzed, and the area where the connectivity of the power grid decreases in the monitoring process is a vulnerable part in the selected power grid;
Step 5, evaluate and process the monitoring result
According to step 4, firstly, index evaluation is carried out on the vulnerable part in the monitored power grid, and then corresponding defense measures are made on the vulnerable part of
the power grid according to the index evaluation results.
Further improvement is that in step 1, the lines in the power grid topological model include all
lines except power plant and substation buses, and the network nodes in the power grid topological
model are divided into generator node sets, load node sets and substation node sets.
Further improvement is that in the step 2, when the model is simplified, the power grid system
is simplified to a sparse connected graph composed of different nodes and different edges, and a complex network is composed of different nodes and different edges.
The further improvement is that in the step 3, the analyzed power grid topological model
information includes the total number of nodes, the total number of edges, the number of power supply nodes, the number of terminal nodes and the number of contact nodes of the model.
The further improvement is that in the step 3, the calculated characteristic parameters of the power grid topological model include the network average degree of the model, the average
distance of the actual power grid, the clustering coefficient and the random network parameters.
Further improvement is that in the step 4, the four attack modes are common attack modes,
including random attack mode, attack mode based on node degree, attack mode based on node median and chain attack mode based on node median.
Further improvement is that in the step 5, the defense measures include optimizing the network
structure of the power grid and reasonably arranging the layout of the power supply, wherein the
optimization of the network structure reduces the load borne by key nodes and lines in the power grid, and reasonably arranging the layout of the power supply makes the distribution of power flow
in the power grid as reasonable as possible.
The invention has the beneficial effects of: based on the complex network theory, the power
grid topological model created by this invention can improve the evaluation capability of the model,
represent the structural characteristics of the power grid through a group of model, draw a node
degree distribution diagram and a median distribution diagram of the selected power grid through an artificial intelligence processing module in a graph module, enable the power grid topological
model information and characteristic parameters to be easy to analyze and calculate through
simplifying the topological model with low requirements on calculation performance, simultaneously, use four attack modes to attack the power grid model, which makes the monitoring data more comprehensive, ensures the monitoring accuracy of power grid vulnerability
to a certain extent, realizes the reasonable quantification of electrical dynamic characteristics and
static mechanism vulnerability response, and effectively monitors the vulnerable links in the power
grid, thus facilitating the protection of the vulnerable parts in the power grid, further ensuring the normal operation of the power grid, reducing the occurrence of power outages, and worthy of wide promotion.
Figure 1 is a flowchart of a vulnerability monitoring method of the present invention.
In order to deepen the understanding of the invention, the invention will be described in further
detail below with reference to examples, which are merely illustrative of the present invention and
are not intended to limit the protection scope of the invention.
According to Figure 1, this example provides a large-scale power grid vulnerability monitoring
method based on a complex network, comprising the following steps:
Step 1, establish a power grid topological model
First, select the power grid to be monitored. Then according to the complex network theory,
the generator is abstracted as the injected power on the generator outlet bus. The substation is
modeled according to the equivalent circuit. At the same time, the power supply and load on the low
voltage side are abstracted as active injection power on the corresponding bus. Generators,
substations and loads are then abstracted into network nodes, and the transmission lines are
abstracted as edges between nodes in the power grid to obtain a power grid topological model. The
lines in the power grid topological model include all lines except power plant and substation buses.
The network nodes in the power grid topological model are divided into generator node set, load
node set and substation node set.
Step 2, simplify the power grid topological model
According to step one, Firstly, all lines in the network topological model are simplified as
undirected weighted edges, The weight of the edges is the efficiency, Set the initial performance
value of the line to be 1, and then merge the transmission lines with the same pole and parallel
frame, simplify the model without considering the parallel capacitor branches, and obtain a
simplified power grid topological model. When the model is simplified, the power grid system is
simplified as a sparse connected graph composed of different nodes and different edges, and the complex network is composed of different nodes and different edges.
Step 3, analyze the power grid topological model
According to step 2, at first, analyze the information of the network topological model according to the obtained simplified network topological model. The information includes the total number of nodes, the total number of sides, the number of power supply nodes, the number of
terminal nodes and the number of contact nodes of the model. Then the characteristic parameters of the power network topological model are calculated according to the simplified power network
topological model. The calculated parameters include the average power of the model, the average distance of the actual power grid, the clustering coefficient and the random network parameters.
Then, according to the analyzed information and the calculated parameters, the node degree
distribution diagram and the intermediary distribution diagram of the selected power grid are drawn through the artificial intelligence processing module in the graphics module;
Step 4: monitor the vulnerability of the model
According to step 3, firstly, four attack modes are used to attack the topological model of the
power grid according to the node degree distribution diagram and the median distribution diagram
of the power grid. Then monitoring and analyzing the connectivity of power network topological
model under different attacks. During the monitoring process, the area where the connectivity of the power grid decreases is the vulnerable part in the selected power grid. Four attack modes are
common attack modes, including random attack mode, attack mode based on node degree, attack
mode based on node median and chain attack mode based on node median.
Step 5, evaluate and process the monitoring result
According to step 4, at first, evaluating the index of the vulnerable parts in the power grid.
Then, according to the evaluation result of the index, corresponding defense measures are made for
the vulnerable parts of the power grid. The defense measures include the optimization of the power grid network structure and the reasonable arrangement and layout of the power supply. The
optimization of the network structure reduces the load borne by the key nodes and lines in the
power grid, and the reasonable arrangement of the power supply layout makes the distribution of
power flow in the power grid as reasonable as possible.
Based on the complex network-based large-scale power grid vulnerability monitoring method and the complex network theory, the power grid topological model can improve the evaluation
capability of the model, represent the structural characteristics of the power grid through a group of
model, draw a node degree distribution diagram and a median distribution diagram of the selected
power grid through an artificial intelligence processing module in a graph module, enable the power grid topological model information and characteristic parameters to be easy to analyze and calculate
through simplifying the topological model with low requirements on calculation performance,
simultaneously, use four attack modes to attack the power grid model, which makes the monitoring data more comprehensive, ensures the monitoring accuracy of power grid vulnerability
to a certain extent, realizes the reasonable quantification of electrical dynamic characteristics and
static mechanism vulnerability response, and effectively monitors the vulnerable links in the power
grid,
The basic principles, main features and advantages of the invention have been shown and described above. It shall be understood by those skilled in the art that the invention is not limited to
the above-described embodiments, and that the above-described embodiments and description are
merely illustrative of the principles of the invention, and that various changes and modifications
may be made therein without departing from the spirit and scope of it, which fall within the scope of the claimed invention. The scope of the invention is defined by the appended claims and their
equivalents.
Claims (7)
1. A large-scale power grid vulnerability monitoring method based on a complex network,
characterized in that it comprises the following steps:
Step 1, establish a power grid topological model
First, select the power grid to be monitored. Then, according to the complex network theory,
the generator is abstracted as the injected power on the generator outlet bus. The substation is
modeled according to the equivalent circuit, and the power supply and load on the low voltage side
are abstracted as active injected power on the corresponding bus at the same time. Then the
generator, substation and load are abstracted as network nodes, and the transmission line is
abstracted as edges between nodes in the power grid to obtain the power grid topological model;
Step 2, simplify that power grid topological model
According to step 1, all power grid lines in the power grid topological model are simplified as
undirected weighted edges, and the weight of the edges is the efficiency of the lines, then the initial
value of the efficiency is set to be 1, and then the transmission lines with the same pole and parallel
frame are merged to simplify the model without counting parallel capacitor branches to obtain a
simplified power grid topological model;
Step 3, analyze the power grid topological model
According to step 2, at first, carry out information analysis on the power grid topological
model according to the obtained simplified power grid topological model. Then, calculate the
characteristic parameters of the power grid topological model according to the simplified power
grid topological model. And then, according to the analyzed power grid topological model
information and the calculated characteristic parameters of it, the node degree distribution diagram
and the median distribution diagram of the selected power grid are drawn through the artificial
intelligence processing module in the graphics module;
Step 4: monitor the vulnerability of the model
According to step 3, firstly, four attack modes are adopted to attack the power grid topological model according to the node degree distribution diagram and the median distribution diagram of the power grid, and then the connectivity of the power grid topological model under the attack of different modes is monitored and analyzed, and the area where the connectivity of the power grid decreases in the monitoring process is a vulnerable part in the selected power grid;
Step 5, evaluate and process the monitoring result
According to step 4, firstly, index evaluation is carried out on the vulnerable part in the
monitored power grid, and then corresponding defense measures are made on the vulnerable part of
the power grid according to the index evaluation results.
2. A large-scale power grid vulnerability monitoring method based on a complex network
according to claim 1, characterized in that: in the first step, the lines in the power grid topological
model include all lines except power plant and substation buses, and the network nodes in the
power grid topological model are divided into generator node set, load node set and substation node
set.
3. A large-scale power grid vulnerability monitoring method based on a complex network
according to claim 1, characterized in that: in the second step, when the model is simplified, the
power grid system is simplified into a sparse connection graph composed of different nodes and
different edges, and the complex network is composed of different nodes and different edges.
4. A large-scale power grid vulnerability monitoring method based on a complex network
according to claim 1, characterized in that: in the step 3, the analyzed power grid topological model
information comprises the total number of nodes, the total number of edges, the number of power
supply nodes, the number of terminal nodes and the number of contact nodes of the model.
5. A large-scale power grid vulnerability monitoring method based on a complex network
according to claim 1, characterized in that: in the step 3, the calculated power grid topological
model characteristic parameters include the network average degree of the model, the average
distance of the actual power grid, the clustering coefficient and the random network parameters.
6. A large-scale power grid vulnerability monitoring method based on a complex network
according to claim 1, characterized in that: in the step 4, the four attack modes are common attack modes, including random attack mode, attack mode based on node degree, attack mode based on node median and chain attack mode based on node median.
7. A large-scale grid vulnerability monitoring method based on a complex network according to claim 1, characterized in that in step 5, the defense measures include optimizing the network
structure of the power grid and reasonably arranging the layout of the power supply, wherein the
optimization of the network structure reduces the load borne by key nodes and lines in the power
grid, and reasonably arranging the layout of the power supply makes the distribution of power flow in the power grid as reasonable as possible.
-1/1-
Establishment of Power Grid Topological Model 2020103195
Simplification of Power Grid Topological Model
Analysis of Power Grid Topological Model
Vulnerability Monitoring of Power Grid Topological Model
Evaluation and Treatment of Monitoring Results
Figure 1
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Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113094975A (en) * | 2021-03-22 | 2021-07-09 | 西安交通大学 | Method, system, equipment and storage medium for evaluating vulnerability of smart grid node |
| CN113220449A (en) * | 2021-04-27 | 2021-08-06 | 武汉大学 | Vulnerable line identification method and system based on edge calculation |
| CN113722868A (en) * | 2021-09-03 | 2021-11-30 | 湘潭大学 | Multi-index power grid node vulnerability assessment method fusing structure hole characteristics |
| CN113904786A (en) * | 2021-06-29 | 2022-01-07 | 重庆大学 | False data injection attack identification method based on line topology analysis and power flow characteristics |
| CN114169118A (en) * | 2021-12-17 | 2022-03-11 | 国网上海市电力公司 | Power distribution network topological structure identification method considering distributed power supply output correlation |
| CN114513442A (en) * | 2022-01-06 | 2022-05-17 | 国网山东省电力公司泰安供电公司 | Network security testing device and method based on power Internet of things |
| CN114793200A (en) * | 2021-01-25 | 2022-07-26 | 中国科学院沈阳自动化研究所 | Important Internet of things node identification method based on power Internet of things network structure |
| CN115099662A (en) * | 2022-07-07 | 2022-09-23 | 国网经济技术研究院有限公司 | Direct current transmission end power grid vulnerability evaluation method, system, medium and computing equipment |
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| CN115801591A (en) * | 2023-02-15 | 2023-03-14 | 聊城金恒智慧城市运营有限公司 | Quantitative calculation method for network security vulnerability assessment |
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