CN113011775A - Event-driven power distribution network information physical system risk assessment calculation method - Google Patents
Event-driven power distribution network information physical system risk assessment calculation method Download PDFInfo
- Publication number
- CN113011775A CN113011775A CN202110370176.6A CN202110370176A CN113011775A CN 113011775 A CN113011775 A CN 113011775A CN 202110370176 A CN202110370176 A CN 202110370176A CN 113011775 A CN113011775 A CN 113011775A
- Authority
- CN
- China
- Prior art keywords
- power distribution
- distribution network
- risk
- physical system
- information
- 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.)
- Granted
Links
- 238000004364 calculation method Methods 0.000 title claims abstract description 24
- 238000012502 risk assessment Methods 0.000 title claims abstract description 20
- 238000013507 mapping Methods 0.000 claims abstract description 8
- 238000000034 method Methods 0.000 claims description 16
- 230000008569 process Effects 0.000 claims description 9
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 230000008878 coupling Effects 0.000 claims description 3
- 238000010168 coupling process Methods 0.000 claims description 3
- 238000005859 coupling reaction Methods 0.000 claims description 3
- 238000011156 evaluation Methods 0.000 abstract description 4
- 230000006378 damage Effects 0.000 description 6
- 238000012423 maintenance Methods 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 230000003993 interaction Effects 0.000 description 3
- 230000007246 mechanism Effects 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 230000004927 fusion Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 206010000369 Accident Diseases 0.000 description 1
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000007123 defense Effects 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000004438 eyesight Effects 0.000 description 1
- 238000009413 insulation Methods 0.000 description 1
- 238000002955 isolation Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000010399 physical interaction Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
- 238000012038 vulnerability analysis Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Strategic Management (AREA)
- General Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- Tourism & Hospitality (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Health & Medical Sciences (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention provides a risk assessment and calculation method for a power distribution network information physical system based on event driving. And then, based on a cross-space cascading failure evolution model, providing and establishing a distribution network operation quantitative risk assessment index. Finally, a risk assessment calculation method of the power distribution network information physical system based on event driving is provided. The invention discloses a risk evaluation calculation method of a power distribution network information physical system, which aims at extracting key elements of the power distribution network cross-information-physical space cascading failure, provides description on risk conduction of different levels and propagation and mapping relations of risks among the different levels, and provides a calculation evaluation method for the risks of the power distribution network information physical system based on an event-driven model.
Description
Technical Field
The invention relates to the technical field of power grid information physical systems, in particular to a risk assessment and calculation method for a power distribution network information physical system based on event driving.
Background
The power grid information physical system deeply combines the data processing process of the information communication network and the calculation analysis with the process of the power grid physical system, so that the level of the power grid in the aspects of deep and accurate operation analysis, optimized decision and control, complex scene adaptability, intellectualization and the like is greatly improved. The traditional classical theory, method and model do not see, recognize and analyze the existing power grid with information physical interweaving fusion and interaction from the perspective and eye sight of information physical deep fusion, do not consider the complex interaction mechanism and action of information and physics, and split and isolate the association between heterogeneous systems. The research on the key theoretical method of the power grid information physical system is beneficial to safe and reliable operation of the power grid under the complex time-varying random scene. At present, research on risk assessment and calculation of the power distribution network cyber-physical system is rarely carried out at home and abroad.
Disclosure of Invention
In order to solve the risk assessment of the information physical system of the power distribution network, the invention provides a risk assessment calculation method of the information physical system of the power distribution network based on event driving, and the technical scheme is as follows:
a risk assessment and calculation method for a power distribution network information physical system based on event driving comprises the following steps:
s1: analyzing an information physical system of the power distribution network, extracting cross-information-physical space cascading failure elements, and establishing risk propagation and mapping relations of different levels;
s2: establishing a power distribution network information physical system cross-space cascading failure evolution model for description based on event driving;
s3: based on a cross-space cascading failure evolution model, a risk index system and a failure hazard function of the power distribution network information physical system are proposed and established;
s4: and carrying out state division and state conversion rule division on the power distribution network information physical system according to the risk indexes and the fault hazard function result.
Optionally, the distribution network cyber-physical system includes, but is not limited to, a distribution automation terminal, a distributed power source, a controllable load.
Optionally, the cross-information-physical space cascading failure is not less than 20 cross-information-physical space cascading failure scenarios.
Optionally, the cross-space cascading failure evolution model is used for performing failure source analysis on the information network, the secondary device and the primary device.
Optionally, the risk propagation and mapping relationships at different levels are a risk propagation model of the power distribution network information physical system in a three-layer space, and the risk propagation model is a propagation process between information leak spaces, information flow propagation in a secondary device space, and energy flow propagation in a primary device space.
Optionally, the risk indicator of the power distribution network information physical system is a function considering superposition of information space risks on physical network risks, a severity function of the information space risks, a coupling function of information space and physical network risk factors, and a corresponding severity function of the physical network risks.
The system according to the above embodiment has the following effects:
a risk assessment calculation method for a power distribution network information physical system is provided, key elements of the power distribution network are extracted according to cross-information-physical space cascading failures, risk conduction description of different levels and propagation and mapping relations of risks among different levels are provided, and a calculation assessment method is provided for risks of the power distribution network information physical system based on an event driven model. The method focuses on analyzing the vulnerability or the hazard of the nodes in a specific scene or a topological structure in the aspect of interaction influence between the information system and the physical system in the risk evaluation of the power distribution network information physical system, and the power distribution network information physical risk is evaluated more accurately.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a schematic diagram of a cross-information-physical space cascading failure scenario analysis in accordance with an embodiment of the present invention;
fig. 2 is a flowchart of a risk assessment calculation method for an event-driven power distribution network cyber-physical system according to an embodiment of the present invention.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
As shown in fig. 1, for the attack risk type, according to the attack mode and resource level mastered by the attacker, the attacker can firstly launch a network attack on the information system; and secondly, when the network attack is started, the physical equipment is damaged to cause the cooperative fault. In the process of launching the information attack, different types of information attacks can be launched aiming at security holes existing in the information equipment to cause different types of information faults, such as equipment denial of service, communication delay, communication interruption and data tampering. The risk indicators are affected when the power system works in different states, such as a normal state, an abnormal state, and a fault state. The abnormal state represents that one or more risk indexes in the physical system are out of limit, and the fault state represents that equipment in the power grid is in fault or failure. In summary, the power distribution network information physical system can be divided into different scenes according to the information fault type, the power system state and the considered attack type.
On this basis, as shown in fig. 2, the embodiment discloses a risk assessment and calculation method for an event-driven power distribution network cyber-physical system, which includes the following steps:
s1: analyzing an information physical system of the power distribution network, extracting cross-information-physical space cascading failure elements, and establishing risk propagation and mapping relations of different levels; the risk propagation and mapping relations of different levels are a risk propagation model of the power distribution network information physical system in a three-layer space, namely a propagation process among information leak spaces, information flow propagation in a secondary equipment space and energy flow propagation in a primary equipment space.
S2: establishing a power distribution network information physical system cross-space cascading failure evolution model for description based on event driving;
s3: based on a cross-space cascading failure evolution model, a risk index system and a failure hazard function of the power distribution network information physical system are proposed and established;
s4: and carrying out state division and state conversion rule division on the power distribution network information physical system according to the risk indexes and the fault hazard function result.
Wherein:
step S1 further includes: the method comprises the steps of firstly analyzing risk sources of an information space, providing a modeling expression method for key risk factor items, analyzing an information physical system of the power distribution network, extracting cascading failure factors of the information-physical space, and establishing randomness and node vulnerability analysis of an information-physical space risk transmission path.
Step S2 further includes: based on event driving, namely according to the characteristics of different faults, the power distribution network information physical system cross-space cascading fault evolution model comprises the following three types of faults:
1) physical failure: the physical layer segment fails. Usually, when a fault occurs, the feeder automation algorithm can control the corresponding switch to realize the isolation of the fault and the transfer of the load, so that the fault influence range is limited in a certain area.
2) Information failure: meaning that an information system component has failed. Information faults may have an impact on the operation of the power system or may exist in the form of hidden faults. Hidden information faults cannot directly damage an electric power system, and often need to be coordinated with physical faults to affect the electric power system, for example, when a physical layer fails, the stable operation of the system cannot be affected by the denial of service of power distribution terminal equipment.
3) Information-physical cooperative failure: the physical layer segment and the information system component fail simultaneously or sequentially. The type of fault has the characteristics that the faults can be mutually matched, and iteration is alternately performed among different levels, so that a large influence is caused on the power system, and generally, the hazard of the type of fault to the power system is greater than the sum of the hazards of an independent information fault and a physical fault.
Wherein, the step S3 further includes: based on the cross-space cascading failure evolution model, the superposition of information space risks on physical network risks is considered, and the cross-space cascading failure evolution model is used for analyzing the failure sources of the information network, the secondary equipment and the primary equipment, and establishing a fused risk index system and a failure hazard function. The following 1-3 are risk indicators, and 4 is fault hazard function calculation.
1) Severity of line overload
In the event of a failure of a component in the distribution network, the outage duration for some subscribers can be reduced by transferring the load as the network configuration allows, but this may lead to a line overload situation. When the line is in an overload state for a long time, the lead continuously heats, the insulating layer of the lead is accelerated to age, the power loss and the voltage loss of the line are increased, and even the short circuit fire accident caused by the deterioration and the damage of the insulation is caused. The line overload risk reflects the possibility and harm degree of line overload in the system caused by the accident of the power distribution network.
The severity of line overload was:
defining the overload severity of the line as Sev_ovlo(L) the load factor L of the line (the ratio of the current flowing through the line to the rated current) determines the severity of overload on the line. The line load rate L0 is 0.8.
2) Line voltage out-of-limit severity
When the voltage in the system deviates from the standard value, the line loss is increased, the normal operation of the equipment is influenced, the service life of the electric appliance is shortened, and even the electric appliance is burnt. The risk of low bus voltage is reflected in the possibility and harm degree of bus voltage drop in the system caused by accidents occurring in the power distribution network.
The severity of line overload was:
Sev_vovi(U)＝exp(|U-U0|)-1
defining a low voltage severity function S for a busev_vovi(U), the voltage amplitude U of each line determines the low voltage severity of the bus. Bus voltage U0 takes 0.8.
3) Severity of load loss
The power distribution network is largely different from the main network in that the power distribution network is directly connected with users, and power failure at a load point directly causes interruption of user power. Aiming at the characteristic of a power distribution network, a load point power failure risk index is established. The index represents the possibility and the degree of damage of the power distribution network caused by accidents to power failure of load points in the system.
Defining the load point power outage severity function as:
Sev_lolo(W)＝exp(W/W0)-1
in the formula W0Is the total load of the line. And W is line load outage capacity.
4) Fault hazard calculation
The power distribution network risk evaluation system provided by this subsection defines line overload risk index, voltage out-of-limit risk index and load loss risk index to respectively reflect the possibility of line current overload, voltage out-of-limit, user power supply interruption and the severity of consequences. And performing weighted synthesis on the 3 risk indexes according to the degree of influence of each risk on the operation of the power grid to obtain the harmfulness of the power distribution network under the fault.
f＝δovloSev_ovlo(L)+δvoviSev_vovi(U)+δloloSev_lolo(W)
In the formula: deltaovlo、δvovi、δloloAre the weighting factors of the different risk factors.
Reliability faults of the conventional power distribution network can be adjusted through feedback of an information system, such as feeder automation, so that the influence of the faults is reduced to the minimum or limited within a certain limit. CPS (control Performance Standard) of power distribution networkThe method is characterized in that more of the faults are usually caused by information attack or information-physical cooperative attack, compared with the traditional power distribution network reliability fault, the harmfulness caused by the faults is usually larger, and the faults are usually caused by deliberate damage of a system attacker, and the damage-benefit ratio Q of the attacker to the target fault z starting attack can be obtained by supposing that the attacker comprehensively considers the harmfulness of the target fault and the defense level of the attack target in the process of selecting the attack targetz：
In the formula: snode，zA set of fault nodes contained in a target fault z; diFor the fault protection level of the node, if i is an information node, DiThe system can represent the protection and monitoring mechanism of the information system or equipment to the faults; if i is a physical node, DiAnd the type (overhead line and cable line) and the operation and maintenance condition of the line in the physical topology are shown.
In the process of selecting an attack target by an attacker, according to QzTo determine the possibility of attack on different target faults, the probability P of occurrence of the fault z can be obtainedz：
In the formula: sFaultIs the set of all failures in the CPSDN.
According to the calculation of the CPS fault probability of the power distribution network, in the actual planning, maintenance, operation and maintenance of the power distribution network, investment or maintenance is usually carried out by taking information equipment or lines as units so as to obtain the fault probability of different nodes. Probability P of node i failingi NodeComprises the following steps:
in the formula: scor，iIs a failure set containing node i.
According to the overload, voltage out-of-limit and load loss indexes of the power distribution network and the probability of different faults in the power distribution network calculated in the step S2, different risk factor indexes and overall risk indexes of the power distribution network can be obtained, and the specific steps are as follows:
1) system overload risk indicator
In the formula SfaultThe set of all faults of the distribution network CPS.
2) System voltage out-of-limit risk indicator
3) System load loss risk indicator
4) Total risk indicator of system
Rover_all＝λovlo，fRover_load+λvoviRvoltage_violate+λlolo，fRloss_load+λfrde，fRfrequency_deviation
In summary, in the aspect of CPS fault transmission and evolution, the mechanism of information physical interaction in the power system is analyzed, the operation risk types of the power system under information attack are summarized, and the power grid information physical fault transmission and state transfer processes are described; in the aspect of risk indexes of the information physical system of the power distribution network, various power distribution network risk analysis scenes are constructed on the basis of information attack characteristics and the running state of the physical system, a power distribution network CPS risk index system containing system risk states, node risk characteristics and system coupling degrees is established, and CPS risks of the power distribution network are described from different dimensions.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.
Claims (6)
1. A risk assessment and calculation method for a power distribution network information physical system based on event driving is characterized by comprising the following steps:
s1: analyzing an information physical system of the power distribution network, extracting cross-information-physical space cascading failure elements, and establishing risk propagation and mapping relations of different levels;
s2: establishing a power distribution network information physical system cross-space cascading failure evolution model for description based on event driving;
s3: based on the cross-space cascading failure evolution model, a power distribution network information physical system risk index system and a failure hazard function are proposed and established;
s4: and carrying out state division and state conversion rule division on the power distribution network information physical system according to the risk indexes and the fault hazard function result.
2. The risk assessment calculation method based on the event driven power distribution network cyber-physical system according to claim 1, wherein the power distribution network cyber-physical system includes but is not limited to a power distribution automation terminal, a distributed power source, a controllable load.
3. The risk assessment and calculation method based on the event-driven power distribution network cyber-physical system according to claim 1, wherein the cross cyber-physical space cascading failure is not less than 20 cross cyber-physical space cascading failure scenarios.
4. The risk assessment and calculation method based on the event-driven power distribution network cyber-physical system according to claim 1, wherein the cross-space cascading failure evolution model is used for performing failure source analysis on an information network, a secondary device and a primary device.
5. The risk assessment and calculation method based on the event-driven power distribution network cyber-physical system as claimed in claim 1, wherein the risk propagation and mapping relationship of different levels is a three-level-space power distribution network cyber-physical system risk propagation model, which is a propagation process between information leak spaces, information flow propagation in a secondary device space, and energy flow propagation in a primary device space.
6. The risk assessment and calculation method based on the event-driven power distribution network cyber-physical system as claimed in claim 1, wherein the risk indicator of the power distribution network cyber-physical system is a function of severity of cyber-space risk, a function of coupling between cyber-space and cyber-physical risk factors, and a function of severity of cyber-physical risk.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110370176.6A CN113011775B (en) | 2021-04-06 | 2021-04-06 | Event-driven risk assessment calculation method for information physical system of power distribution network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110370176.6A CN113011775B (en) | 2021-04-06 | 2021-04-06 | Event-driven risk assessment calculation method for information physical system of power distribution network |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113011775A true CN113011775A (en) | 2021-06-22 |
| CN113011775B CN113011775B (en) | 2023-03-10 |
Family
ID=76388386
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110370176.6A Active CN113011775B (en) | 2021-04-06 | 2021-04-06 | Event-driven risk assessment calculation method for information physical system of power distribution network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113011775B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103219795A (en) * | 2013-05-10 | 2013-07-24 | 温州大学 | High-voltage and high-power uninterruptible power supply device |
| CN111275291A (en) * | 2020-01-07 | 2020-06-12 | 昆明理工大学 | Power information physical system reliability analysis method based on risk transfer path |
| US20200244691A1 (en) * | 2019-01-29 | 2020-07-30 | Battelle Memorial Institute | Risk-informed autonomous adaptive cyber controllers |
| CN111697566A (en) * | 2020-05-19 | 2020-09-22 | 浙江工业大学 | Reliability assessment method for active power distribution network information physical system considering information failure |
| CN112039864A (en) * | 2020-08-25 | 2020-12-04 | 华北电力大学 | Method for analyzing cross-layer security risk of electric power CPS |
| CN112072647A (en) * | 2020-08-27 | 2020-12-11 | 国电南瑞科技股份有限公司 | CPS (Power distribution network control System) safety evaluation method and device considering communication fault influence |
-
2021
- 2021-04-06 CN CN202110370176.6A patent/CN113011775B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103219795A (en) * | 2013-05-10 | 2013-07-24 | 温州大学 | High-voltage and high-power uninterruptible power supply device |
| US20200244691A1 (en) * | 2019-01-29 | 2020-07-30 | Battelle Memorial Institute | Risk-informed autonomous adaptive cyber controllers |
| CN111275291A (en) * | 2020-01-07 | 2020-06-12 | 昆明理工大学 | Power information physical system reliability analysis method based on risk transfer path |
| CN111697566A (en) * | 2020-05-19 | 2020-09-22 | 浙江工业大学 | Reliability assessment method for active power distribution network information physical system considering information failure |
| CN112039864A (en) * | 2020-08-25 | 2020-12-04 | 华北电力大学 | Method for analyzing cross-layer security risk of electric power CPS |
| CN112072647A (en) * | 2020-08-27 | 2020-12-11 | 国电南瑞科技股份有限公司 | CPS (Power distribution network control System) safety evaluation method and device considering communication fault influence |
Non-Patent Citations (1)
| Title |
|---|
| 徐悦: ""数据篡改攻击下电力CPS电压控制策略研究"", 《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113011775B (en) | 2023-03-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Bahrami et al. | Reliability evaluation of power grids considering integrity attacks against substation protective IEDs | |
| Wang et al. | Risk-aware attacks and catastrophic cascading failures in US power grid | |
| CN110210229B (en) | Method and system for evaluating vulnerability of power grid information physical system and storage medium | |
| CN113301010B (en) | Method for judging importance degree of power information network data transmission channel under denial of service attack | |
| Yan et al. | Smart grid vulnerability under cascade-based sequential line-switching attacks | |
| CN115049270B (en) | Power system risk assessment method considering network attack success probability of transformer substation | |
| Semertzis et al. | Quantitative risk assessment of cyber attacks on cyber-physical systems using attack graphs | |
| Garlapati et al. | Agent based supervision of zone 3 relays to prevent hidden failure based tripping | |
| Damchi et al. | Preprocessing of distance and directional overcurrent relays coordination problem considering changes in network topology | |
| Amin et al. | Cyber attacks in smart grid–dynamic impacts, analyses and recommendations | |
| Panigrahi et al. | Structural vulnerability analysis in small‐world power grid networks based on weighted topological model | |
| Chen et al. | Reliability assessment of distribution network considering cyber attacks | |
| Liu et al. | Reinforcement learning for cyber-physical security assessment of power systems | |
| CN116015707A (en) | Network topology optimization method, device and terminal for power distribution network information physical system | |
| Salehpour et al. | Modeling cascading failures in coupled smart grid networks | |
| Zhou et al. | Vulnerability assessment of power cyber-physical system considering nodes load capacity | |
| CN113011775B (en) | Event-driven risk assessment calculation method for information physical system of power distribution network | |
| Liu et al. | Node Importance Evaluation of Cyber‐Physical System under Cyber‐Attacks Spreading | |
| CN113987852B (en) | High-risk circuit combination analysis method for electric power information physical system | |
| Ali et al. | Emerging coordinated cyber-physical-systems attacks and adaptive restoration strategies | |
| Li et al. | Risk Assessment of Cyber Physical Power System considering Attack Model | |
| Sahu et al. | Score: A security-oriented cyber-physical optimal response engine | |
| Wang et al. | Expected Failure Method and Its Analysis for Safety Evaluation in a Cyber-Physical Power System | |
| El Hariri et al. | An artificially intelligent physical model-checking approach to detect switching-related attacks on power systems | |
| Wei et al. | A Novel Cyber-physical Distribution Network Security Analysis and Evaluation Strategy Based on Correlation Characteristic Matrix |
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 |