CN107220775A - A kind of active power distribution network various visual angles collaboration vulnerability assessment method for considering information system effect - Google Patents
A kind of active power distribution network various visual angles collaboration vulnerability assessment method for considering information system effect Download PDFInfo
- Publication number
- CN107220775A CN107220775A CN201710405544.XA CN201710405544A CN107220775A CN 107220775 A CN107220775 A CN 107220775A CN 201710405544 A CN201710405544 A CN 201710405544A CN 107220775 A CN107220775 A CN 107220775A
- Authority
- CN
- China
- Prior art keywords
- mrow
- msub
- distribution network
- power distribution
- 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
- 230000000694 effects Effects 0.000 title claims abstract description 50
- 230000000007 visual effect Effects 0.000 title claims abstract description 22
- 238000000034 method Methods 0.000 title claims abstract description 17
- 230000003993 interaction Effects 0.000 claims abstract description 17
- 231100001261 hazardous Toxicity 0.000 claims abstract description 13
- 230000002195 synergetic effect Effects 0.000 claims abstract description 5
- 239000011159 matrix material Substances 0.000 claims description 19
- 230000007257 malfunction Effects 0.000 claims description 17
- 230000005540 biological transmission Effects 0.000 claims description 15
- 230000002079 cooperative effect Effects 0.000 claims description 13
- 238000004458 analytical method Methods 0.000 claims description 9
- 238000012544 monitoring process Methods 0.000 claims description 6
- 238000004891 communication Methods 0.000 claims description 5
- 238000011156 evaluation Methods 0.000 claims description 4
- 230000007774 longterm Effects 0.000 claims description 4
- 230000001939 inductive effect Effects 0.000 claims description 3
- 239000004615 ingredient Substances 0.000 claims description 3
- 238000006116 polymerization reaction Methods 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 230000015572 biosynthetic process Effects 0.000 claims description 2
- 230000015556 catabolic process Effects 0.000 claims description 2
- 238000012937 correction Methods 0.000 claims description 2
- 230000000875 corresponding effect Effects 0.000 claims description 2
- 238000009472 formulation Methods 0.000 claims description 2
- 230000006872 improvement Effects 0.000 claims description 2
- 239000000203 mixture Substances 0.000 claims description 2
- 238000004445 quantitative analysis Methods 0.000 claims description 2
- 238000003786 synthesis reaction Methods 0.000 claims description 2
- 230000005611 electricity Effects 0.000 claims 1
- 230000007613 environmental effect Effects 0.000 claims 1
- 230000016507 interphase Effects 0.000 abstract 1
- 240000002853 Nelumbo nucifera Species 0.000 description 6
- 235000006508 Nelumbo nucifera Nutrition 0.000 description 6
- 235000006510 Nelumbo pentapetala Nutrition 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 5
- 238000011160 research Methods 0.000 description 4
- 230000004888 barrier function Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 210000004209 hair Anatomy 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000010030 laminating Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000007474 system interaction Effects 0.000 description 1
- 230000009885 systemic effect Effects 0.000 description 1
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
- 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)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Educational Administration (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Development Economics (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The present invention provides a kind of active power distribution network various visual angles collaboration vulnerability assessment method for considering information system effect, and the randomness occurred first against power distribution network external disaster sets up certainty randomness topology controlment；Based on system panoramic information, the information physical element fault probability of Multiple Time Scales collaboration influence under hazardous condition is determined；Then the active power distribution network function group failure probability model for considering information system effect is set up；Various running statuses and grid structure under the source net load interaction pattern of active power distribution network are estimated, the vulnerability assessment system under the source net load interaction pattern that active power distribution network is merged with information system is built, while assessing between distribution network structure structure and running status, physical system cooperates with fragility with the interphase interaction of information system；Local collaboration vulnerability inder, Regional Synergetic vulnerability inder and the global collaborative vulnerability inder system finally set up on space scale, more comprehensively, specifically assess the fragility of active power distribution network.
Description
Technical field
The present invention relates to distribution technique field, and in particular to a kind of active power distribution network various visual angles of consideration information system effect
Cooperate with vulnerability assessment method.
Background technology
With continually introducing for information technology, active power distribution network is developed rapidly, and power distribution network has turned into collection physics, information and led to
Letter technology is in the complex information physical system of one.Especially in recent years extreme external disaster and information system under fire phenomenon frequency
It is numerous to occur, to considering that the collaboration vulnerability assessment of active power distribution network progress various visual angles of information system effect is particularly important.
At present, the vulnerability assessment method of power network：The only consideration having in distribution network failure probability under analyzing hazardous condition
Physical system components, do not consider the probability of malfunction of information system component, and most of do not consider disaster period physical message member
The collaboration influence of external environment condition Multiple Time Scales is born in part life cycle management, probabilistic forecasting is not accurate enough；Setting up power distribution network
What is had during topology controlment only considers the certainty topological model of power distribution network itself, does not consider hazardous condition lower outer portion disaster
Randomness influence；What is had does not consider information system in each important ring of source net lotus in each vulnerability inder of analysis active power distribution network
Save the influence to active power distribution network fragility so that assessment result is excessively unilateral, not enough laminating is actual；What is had is considering power distribution network
Only application Complex Networks Theory and the theoretical grid structure and running status to power distribution network of risk effect is carried out during vulnerability inder
Analysis, do not account for synergy and grid structure and running status between actual active power distribution network and information system it
Between synergy, cause assessment result not comprehensive enough；The vulnerability inder of current power distribution network is more to be accounted for from single part,
Power distribution network fragility not from space scale to region and the overall situation is estimated, not enough to be provided for power distribution network Risk-warning
Foundation.
Therefore, from information physical system and external disaster on power distribution network influence, active power distribution network and information system source net lotus
Under interaction, Complex Networks Theory, the theoretical various visual angles with Risk Utility theoretical research of cooperative effect, to grid structure and operation shape
State, information carry out cooperateing with vulnerability assessment with the power distribution network that physical system acts synergistically, and the power supply for being favorably improved power distribution network can
By property, prevent large-scale blackout, so as to ensure the safe and stable operation of power distribution network.
The content of the invention
In view of the deficiency that prior art is present, the invention aims to provide one kind based on panoramic information and consider
The active power distribution network various visual angles collaboration vulnerability assessment method of information system effect.
To achieve these goals, technical solution of the present invention is as follows：
A kind of active power distribution network various visual angles collaboration vulnerability assessment method for considering information system effect, it is characterised in that
Comprise the following steps：
Step 1：Based on the panoramic information for the active power distribution network for considering information system effect, many times under hazardous condition are determined
The probability of malfunction of yardstick collaboration influence information physical element, the panoramic information includes but is not limited to geography information, external environment condition
Information, power network battalion's auxiliary tone information and risk and fault message；
Step 2：Certainty-randomness topological structure built-up pattern of active power distribution network and external disaster is set up, it is described true
Qualitative-randomness topological structure built-up pattern is：
G=(N, L)
Wherein, G is that distribution network has N number of node, undirected, the sparse graph of having the right, W on L bars side after simplifying processing0For
Power distribution network connection weight matrix, matrix element wijFor the per unit reactance of transmission line between node i and node j, 1≤i, j≤N, wi'jFor
Consider disaster randomness influence node i and node j between transmission line per unit reactance；DhIt is respective type disaster to distribution
The influence coefficient of net, k is the Disasters Type number for considering single disaster and many disasters polymerization situation, WuFor power distribution network and outside
The certainty of disaster-randomness connection weight matrix, μ is the amendment system for ensureing certainty-randomness connection weight matrix physical characteristic
Number；
Step 3：On the basis of certainty-randomness topological structure built-up pattern of power distribution network and external disaster, using again
Miscellaneous network theory characteristic finds out the fragile source of active power distribution network system for considering information system effect, while considering different communication network
The influence of structure and degree of redundancy to information system, and the event of the fragile source related elements of physics in the system, information is simulated respectively
Barrier situation；
Step 4：Consider that information system acts on the influence to active power distribution network element, with reference to Multiple Time Scales under hazardous condition
The information physical element fault probability of influence, obtains the probability of malfunction based on function group, and to carrying out based on function ingredients solution
Cascading failure is recognized；
Step 5：Various running statuses and grid structure under the net load interaction pattern of source are commented using Risk Utility theory
Estimate, wherein mains side includes：The grid-connected rate of distributed power source, emergency power supply, UPS utility ratios and bus fragile degree；Distribution network side
Including：Node fragile degree, voltage limit risk and degree of balance index；Load side includes：Lose load risk, overload risk and bear
Lotus power supplying efficiency；
Step 6：Consider that the active power distribution network various visual angles of information system effect are cooperateed with using cooperative effect theoretical appraisal fragile
Property, local vulnerability inder, region vulnerability inder and the global vulnerability inder system set up on space scale.
Compared with prior art, the present invention possesses following beneficial effect：
(1) randomness that the present invention occurs for power distribution network external disaster, establishes the determination of power distribution network and external disaster
Property-randomness topology controlment, analysis result is more met the running situation of power distribution network under hazardous condition；
(2) situation for combining information and physical component in long history disaster record, in a short time equipment fortune of the invention
Disaster capacity factor situation and currently the situation of element operation troubles during disaster does not occur for row time limit and resistance, based on the complete of system
Scape information, determines the information physical element fault probability of Multiple Time Scales collaboration influence under hazardous condition, makes element fault probability
Prediction is more accurate；Simultaneously in view of effect of the information system to power distribution network, the active power distribution network for considering information system effect is set up
Function group failure probability model, more fully reflects the characteristics of current information physical system is merged；
(3) present invention various under the source net load interaction pattern to active power distribution network running statuses and grid structure are commented
When estimating, the influence of monitoring host computer in information system, interchanger and Region control unit is also contemplated for into, active power distribution network is set up
Vulnerability assessment system under the source net load interaction pattern merged with information system, from multi-angle to considering information system effect
Active power distribution network is analyzed, while the synergy between information and distribution network is reflected, with critically important reality
With value；
(4) present invention is directed to active power distribution network local power characteristic and power transmission efficiency, and based on power distribution network and outside
The certainty of disaster-randomness connection weight matrix, proposes active power balance degree index and load power supplying efficiency index, preferably
Overcome the drawbacks of going to assess power distribution network fragility from single angle physical angle in the past, improve identification precision and identification effect；
(5) present invention introduces the structure dependent vulnerability inder of active power distribution network and the fragility relevant with information system
Index, and consider that the collaboration for the active power distribution network that information system is acted on is fragile using cooperative effect theoretical appraisal based on These parameters
Property, the preferably influence of analysis distribution network structure structure and running status, information system and physical system synergy is improved
Power distribution network reliability of operation and the degree of accuracy；The part set up simultaneously on space scale cooperates with vulnerability inder, Regional Synergetic crisp
Weak property index and global collaborative vulnerability inder system, more comprehensively, specifically assesses the fragility of active power distribution network, to power distribution network
Safe and reliable operation provide foundation, to prevention large-scale blackout play an important role.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
There is the accompanying drawing used required in technology description to be briefly described, it should be apparent that, drawings in the following description are this hairs
Some bright embodiments, for those of ordinary skill in the art, without having to pay creative labor, can be with
Other accompanying drawings are obtained according to these accompanying drawings.
Fig. 1 present invention considers the active power distribution network various visual angles collaboration vulnerability assessment flow chart of information system effect；
Fig. 2 present invention considers the active power distribution network various visual angles collaboration vulnerability assessment research block diagram of information system effect；
The probability of malfunction figure influenceed under Fig. 3 present invention prediction hazardous conditions under information physical element Multiple Time Scales；
Fig. 4 information physical system interaction model figures of the present invention；
Fig. 5 information physical system function group probability of malfunction figures of the present invention；
Fragility system figure under Fig. 6 net load interaction patterns in active power distribution network source of the present invention.
Embodiment
To make the purpose, technical scheme and advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention
In accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is
A part of embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art
The every other embodiment obtained under the premise of creative work is not made, belongs to the scope of protection of the invention.
The present invention is from information physical system and external disaster on power distribution network influence, active power distribution network and information system source net lotus
Under interaction, Complex Networks Theory, the theoretical various visual angles with Risk Utility theoretical research of cooperative effect, to grid structure and operation shape
State, information carry out cooperateing with vulnerability assessment with the power distribution network that physical system acts synergistically, and its research process is as shown in Figure 2.
The invention discloses a kind of active power distribution network various visual angles collaboration vulnerability assessment method for considering information system effect,
As shown in figure 1, it comprises the following steps：
Step 1：Based on the panoramic information for the active power distribution network for considering information system effect, many times under hazardous condition are determined
The probability of malfunction of yardstick collaboration influence information physical element, the panoramic information includes but is not limited to geography information, external environment condition
Information, power network battalion's auxiliary tone information and risk and fault message, as shown in figure 3, it comprises the following steps：
Step 1.1：Consider pregnant calamity environment, the interaction of Flood inducing factors and supporting body respectively obtains message elements
With the element situation in the long history disaster of physical component record, in a short time power equipment operation time limit and resistance disaster ability
Coefficient and the current element operation troubles probability not occurred under disaster state.
As the preferred embodiment of the present invention, pregnant calamity environment not only answers calamity ability, disaster data, physics to set including power network
Standby parameter, includes the relevant parameter of information equipment；Flood inducing factors not only consider Disasters Type, the frequency, intensity, it is also contemplated that information
The attack condition of system, external disaster here is no longer limited to outside natural calamity, also by information, the failure of network with deliberating
Attack takes into account, while hazard-affected body also includes the situation of communication equipment and message processing device, from comprehensive to considering information
The panoramic information of the active power distribution network of systemic effect is analyzed.
Step 1.2：According to meteorological disaster forecast model and panoramic information, calculating considers long-term, short-term and calamity does not occur
Probability distribution parameters of the evil period information with bearing external disaster influence in physical component life cycle management, exist so as to obtain element
Stoppage in transit probability under hazardous condition, the influence caused to quantitative analysis disaster.
As the preferred embodiment of the present invention, combine long-term, short-term and that disaster period information does not occur is first with physics
External disaster influence is born in part life cycle management, is that failure predication is carried out to physical component mostly at present, and be limited only to
The prediction probability of malfunction of disaster period element does not occur.Here not only allow for long-term, short-term and and do not occur disaster period member
Machine operation in part life cycle management, it is also contemplated that the situation of information system component, makes element fault probability prediction knot
The more accurate reality of more fitting of fruit.
Step 2：Set up certainty-randomness topological structure built-up pattern of active power distribution network and external disaster.It is used as this
The preferred embodiment of invention, active power distribution network is handled, obtained by simplifying with N number of node, the nothing on L bars side first
To, have the right sparse graph G, i.e.,：
G=(N, L)
Define initial power distribution network connection weight matrix W0, its matrix element wijFor the reactance perunit of transmission line between node i and node j
Value, wherein 1≤i, j≤N
Consider that single disaster and the polymerization of many disasters influence on the randomness of power distribution network, now matrix element wi'jTo consider calamity
The matrix element of evil randomness influence, be
To ensure that certainty-randomness connection weight matrix physical characteristic introduces correction factor μ, power distribution network and outside calamity are obtained
Harmful certainty-randomness connection weight matrix Wu
Step 3：On the basis of certainty-randomness topological structure built-up pattern of power distribution network and external disaster, using again
Miscellaneous network theory characteristic finds out the fragile source of active power distribution network system for considering information system effect, while considering different communication network
The influence of structure and degree of redundancy to information system, and the event of the fragile source related elements of physics in the system, information is simulated respectively
Barrier situation.
As the preferred embodiment of the present invention, improved first with the node fragile degree in Complex Networks Theory and circuit
The fragile source of the data search physical system such as betweenness；Then and according to heterogeneous networks communication structure, such as：It is star-like, bus-type, ring
Shape lamp topology controlment and the redundant configuration situation of its own, also according to Complex Networks Theory to node fragile degree and line
Road betweenness is calculated, and finds out the fragile source of information system, is that the following fragile source progress simulation to physical message system is carried
For data supporting.
Step 4：Consider that information system acts on the influence to active power distribution network element, with reference to Multiple Time Scales under hazardous condition
The information physical element fault probability of influence, obtains the probability of malfunction based on function group, and to carrying out based on function ingredients solution
Cascading failure is recognized, as shown in figure 5, its specific steps includes：
Step 4.1：According to the raw information of information physical element, sampled by non-sequential Monte Carlo, obtain information system
System functional status and primary system element state；
Step 4.2：Information as shown in Figure 4-electric power interactively, primary element function group failure is asked for if being not present
Probability；In the present embodiment, function group is made up of shielded element, such as circuit, transformer load outlet, breaker and
The disconnecting link of gate-dividing state constitutes the interface element of function group, and the probability of malfunction of each function group is that single order multiple failure rate is equal to this
The probability of at least one element failure in function group
In formula：GiRepresent function group i；PkFor element k fault rate.
Step 4.3：If existence information-electric power interactively, ask for considering the element function group after information system effect
Probability of malfunctionIn the present embodiment, the availability of message elements can be according to operation, protection, control etc. in real system
Function is defined.
In formula, A'kTo consider the availability of element after Information System Function effect, AkNot consider that Information System Function is made
Element availability,For the synthesis availability of message elements function.In the present embodiment, the availability of message elements can
To be defined according to the function such as operation, protection, control in real system.
Step 4.4：Analysis obtains considering the active power distribution network function group probability of malfunction that information system is acted on more than
And try to achieve the probability of malfunction of failure path according to N-k fault path search models,
In the present embodiment, it is contemplated that effect of the information system to power distribution network, current information physical is sufficiently reflected
The characteristics of system globe area.
Step 5：Various running statuses and grid structure under the net load interaction pattern of source are commented using Risk Utility theory
Estimate, wherein mains side includes：The grid-connected rate of distributed power source, emergency power supply, UPS utility ratios and bus fragile degree；Distribution network side
Including：Node fragile degree, voltage limit risk and degree of balance index；Load side includes：Lose load risk, overload risk and bear
Lotus power supplying efficiency.
As the preferred embodiment of the present invention, the various running statuses under the source net load interaction pattern to active power distribution network
When being estimated with grid structure, by the influence of monitoring host computer, interchanger and Region control unit in information system be also contemplated for into
Come, the vulnerability assessment system set up under the source net load interaction pattern that active power distribution network is merged with information system, from multi-angle pair
Consider that the active power distribution network of information system effect is analyzed, with critically important practical value.
Its specific steps includes：
Step 5.1：Various running statuses under source net load interaction pattern to considering the active power distribution network that information system is acted on
It is estimated with grid structure, such as Fig. 6 is the fragility system under active power distribution network lotus interactive model, wherein
The analysis of mains side vulnerability inder includes：The grid-connected rate of distributed power source, emergency power supply, UPS utility ratios, bus are fragile
Degree and monitoring host computer function Availability Index；
Distribution network side integrated risk vulnerability inder includes：Node fragile degree, voltage limit risk, degree of balance index and
Interchanger Availability Index；
Load side vulnerability inder includes：Lose load risk, overload risk, load power supplying efficiency and Region control unit
Availability；
Step 5.2：The architectural vulnerability of active power distribution network is assessed using Complex Networks Theory, evaluation index includes：Node
Fragile degree, bus fragile degree；
Using the severity of Risk Utility theoretical appraisal function group individual event risk, wherein evaluation index includes：Voltage out-of-limit
Risk, mistake load risk, overload risk；
Step 5.3：Certainty based on power distribution network and external disaster-randomness connection weight matrix, and for multiple source power distribution
Net local power can reduce distinguishing feature of the big power supply by the active power of remote line transmission to load, define the whole network
Active power balance degree is：
Wherein, w'ijTo consider the matrix element of disaster randomness influence, plFor the active power of line transmission；It is whole
Equilibrium degree of the individual active power distribution network active power in transmission range,Smaller explanation is remote, the wattful power of high capacity transmission
Rate is fewer, is more advantageously implemented that the whole network is active to be uniformly distributed.
Step 5.4：According to the power transmission efficiency of active power distribution network, generating capacity should be considered, also to be counted and generator
The impact effect of load is increased with distance and decayed rapidly, so that the load power supplying efficiency for defining load bus i is：
In formula：dij(i∈VD,j∈VG) for based on certainty-randomness topological structure built-up pattern load bus i with
Most short electrical path between generating node j, VDFor load bus number, VGFor generator nodes, PDiFor having for load bus i
Workload amount, PGjFor generating node j active installed capacity；
Step 5.5：Ask for the vulnerability inder α (l relevant with active power distribution network system architecturei), it is contemplated that node is important
Degree and circuit improve betweenness index and distribution network system structure is closely related, in order to preferably assess power distribution network in grid structure side
The fragility in face, so introducing the vulnerability inder α (l related to active power distribution network structurei),
In formula：For the importance of i-th of node, MiFor the node number of degrees of i-th of node, Pi
For the injecting power characteristic of i-th of node, k1、k2For weight, and k1+k2=1, SbaseFor system reference power；B (m, n)=max
(B (m, i), B (j, n)) is the improvement betweenness of circuit, and (m, i), (j, n) are respectively all lines being connected with node m and node n
Road；Represent function group number；max{IiB (m, n) } it is highest fragile structure degree in function group, α, β are weight, and alpha+beta
=1.
Step 5.6：Ask for the vulnerability inder δ (l relevant with information systemi), in order to preferably assess power distribution network in letter
The fragility of system aspects is ceased, the vulnerability inder δ (l relevant with active power distribution network information system is introducedi),
δ(li)=Afz×Afj×Afq
In formula：AfzFor the function availability of monitoring host computer, AfjFor the function availability of interchanger, AfqFor Region control list
The function availability of member.
Step 6：Consider that the active power distribution network various visual angles of information system effect are cooperateed with using cooperative effect theoretical appraisal fragile
Property, local vulnerability inder, region vulnerability inder and the global vulnerability inder system set up on space scale, its specific step
Suddenly include：
Step 6.1：Consider that the active power distribution network various visual angles of information system effect are cooperateed with using cooperative effect theoretical appraisal crisp
Weak property, according to the cooperative effect between system architecture and state, between information and physical system, sets up and considers information system effect
Active power distribution network collaboration vulnerability assessment model：
Vxti=Vxyi+Vxwi=α (li)R(Xt,f)γ+α(li)δ(li)η
In formula：VxyiFor system architecture vulnerability index is cooperateed with running status；VxwiCooperateed with for information with physical system crisp
Weak property index；VxtiCooperateed with to consider system architecture with running status, the vulnerability index that information is cooperateed with physical system；α
(li) it is the vulnerability index relevant with system architecture；R(Xt,f) it is risk indicator mainly relevant with system running state, Xt,f
For the time t method of operation, pr(Ri) it is i-th of uncertain disturbances RiThe possibility of generation,Be
RiThe order of severity of the lower system loss of disturbance, wiFor the breakdown loss value of corresponding index；γ is the association factor of structure and state,
It is taken as γ=P/Pmax, P is realtime power, PmaxFor circuit maximum transmission power；η is the association factor of information and physics, is taken as
The information-based configuration degree of active power distribution network.
In the present embodiment, it is interrelated between system architecture and running status, all, there is cooperative effect, be
Unite full-load run when cooperative effect it is most strong, therefore according to this between system architecture and state, between information and physical system
Cooperative effect, proposes to consider the active power distribution network collaboration vulnerability assessment model of information system effect.
Step 6.2：Local collaboration vulnerability inder, Regional Synergetic vulnerability inder and the global association set up on space scale
With vulnerability inder system.In present embodiment, local collaboration vulnerability inder VlocalMajor embodiment active power distribution network is to load
Local support effect, Regional Synergetic vulnerability inder VareaFragile degree in a certain formulation region of major embodiment, global area
The weakness VtotalThe fragility for the active power distribution network for considering information system effect is mainly assessed on the whole, wherein
In formula：VxtiTo consider that the active power distribution network of information system effect cooperates with the weakness；nDIt is total for load bus
Number；EiFor the load power supplying efficiency of node i；M is the sum of grid nodes；λlFor the weakness of failure path；k1、k2For
Weight, and k1+k2=1；nLThe interstitial content passed through for failure path；λLjFor the weakness of each node in failure path,
max{λLjIt is highest node fragile degree on failure path.
Finally it should be noted that：Various embodiments above is merely illustrative of the technical solution of the present invention, rather than its limitations；To the greatest extent
The present invention is described in detail with reference to foregoing embodiments for pipe, it will be understood by those within the art that：Its according to
The technical scheme described in foregoing embodiments can so be modified, or which part or all technical characteristic are entered
Row equivalent substitution；And these modifications or replacement, the essence of appropriate technical solution is departed from various embodiments of the present invention technology
The scope of scheme.
Claims (5)
1. consider information system effect active power distribution network various visual angles collaboration vulnerability assessment method, it is characterised in that including with
Lower step：
Step 1：Based on the panoramic information for the active power distribution network for considering information system effect, Multiple Time Scales under hazardous condition are determined
Collaboration influence information physical element probability of malfunction, the panoramic information include but is not limited to geography information, external environmental information,
Power network seeks auxiliary tone information and risk and fault message；
Step 2：Set up certainty-randomness topological structure built-up pattern of active power distribution network and external disaster, the certainty-
Randomness topological structure built-up pattern is：
G=(N, L)
<mrow>
<msubsup>
<mi>w</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mo>&prime;</mo>
</msubsup>
<mo>=</mo>
<mi>&mu;</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>w</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>+</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>h</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>k</mi>
</munderover>
<msub>
<mi>D</mi>
<mi>h</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
Wherein, G is that distribution network has N number of node, undirected, the sparse graph of having the right, W on L bars side after simplifying processing0For distribution
Net connection weight matrix, matrix element wijFor the per unit reactance of transmission line between node i and node j, 1≤i, j≤N, w'ijTo consider
The per unit reactance of transmission line between the node i and node j of the influence of disaster randomness；DhIt is respective type disaster to power distribution network
Coefficient is influenceed, k is the Disasters Type number for considering single disaster and many disasters polymerization situation, WuFor power distribution network and external disaster
Certainty-randomness connection weight matrix, μ for ensure certainty-randomness connection weight matrix physical characteristic correction factor；
Step 3：On the basis of certainty-randomness topological structure built-up pattern of power distribution network and external disaster, complex web is utilized
Network theoretical characteristicses find out the fragile source of active power distribution network system for considering information system effect, while considering different communication network structure
Influence with degree of redundancy to information system, and the failure feelings of the fragile source related elements of physics in the system, information are simulated respectively
Condition；
Step 4：Consider that information system acts on the influence to active power distribution network element, influenceed with reference to Multiple Time Scales under hazardous condition
Information physical element fault probability, obtain the probability of malfunction based on function group, and to carrying out based on the chain of function ingredients solution
Fault identification；
Step 5：Various running statuses and grid structure under the net load interaction pattern of source are estimated using Risk Utility theory, its
Middle mains side includes：The grid-connected rate of distributed power source, emergency power supply, UPS utility ratios and bus fragile degree；Distribution network side includes：
Node fragile degree, voltage limit risk and degree of balance index；Load side includes：Load risk, overload risk and load is lost to supply
Electrical efficiency；
Step 6：The active power distribution network various visual angles collaboration fragility of information system effect is considered using cooperative effect theoretical appraisal, is built
Local vulnerability inder, region vulnerability inder and global vulnerability inder system on vertical space scale.
2. the active power distribution network various visual angles collaboration vulnerability assessment side according to claim 1 for considering information system effect
Method, it is characterised in that described step 1 comprises the following steps：
Step 1.1：Consider pregnant calamity environment, the interaction of Flood inducing factors and supporting body respectively obtains message elements and thing
The element situation in the long history disaster record of element is managed, in a short time power equipment operation time limit and resistance disaster capacity factor
Do not occur the element operation troubles probability under disaster state currently；
Step 1.2：According to meteorological disaster forecast model and panoramic information, calculating considers long-term, short-term and when not occurring disaster
Phase information and the probability distribution parameters that external disaster influence is born in physical component life cycle management, so as to obtain element in disaster
Under the conditions of stoppage in transit probability, the influence caused to quantitative analysis disaster.
3. the active power distribution network various visual angles collaboration vulnerability assessment side according to claim 1 for considering information system effect
Method, it is characterised in that described step 4 comprises the following steps：
Step 4.1：According to the information of information physical element, sampled by non-sequential Monte Carlo, obtain Information System Function shape
State and primary system element state；
Step 4.2：Information-electric power interactively whether there is according to information, physical component condition adjudgement, asked for if in the absence of if
Primary element function group probability of malfunction；The function group is made up of shielded element, and the probability of malfunction of each function group is one
Rank multiple failure rate is equal to the probability of at least one element failure in the function group
<mrow>
<msub>
<mi>P</mi>
<mrow>
<msub>
<mi>NG</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mo>=</mo>
<mn>1</mn>
<mo>-</mo>
<msub>
<mi>&Pi;</mi>
<mrow>
<mi>k</mi>
<mo>&Element;</mo>
<msub>
<mi>G</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<mrow>
<mn>1</mn>
<mo>-</mo>
<msub>
<mi>P</mi>
<mi>k</mi>
</msub>
</mrow>
<mo>)</mo>
</mrow>
</mrow>
In formula：GiRepresent function group i；PKFor element K fault rate；
Step 4.3：If existence information-electric power interactively, ask for considering the element function group failure after information system effect
Probability
<mrow>
<msub>
<mi>P</mi>
<mrow>
<msub>
<mi>YG</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mo>=</mo>
<mn>1</mn>
<mo>-</mo>
<msub>
<mi>&Pi;</mi>
<mrow>
<mi>k</mi>
<mo>&Element;</mo>
<msub>
<mi>G</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<msubsup>
<mrow>
<mo>=</mo>
<mi>A</mi>
</mrow>
<mi>k</mi>
<mo>&prime;</mo>
</msubsup>
</mrow>
<mrow>
<msubsup>
<mi>A</mi>
<mi>k</mi>
<mo>&prime;</mo>
</msubsup>
<mo>=</mo>
<msub>
<mi>A</mi>
<mi>k</mi>
</msub>
<mo>&times;</mo>
<msub>
<mi>A</mi>
<msub>
<mi>f</mi>
<mi>k</mi>
</msub>
</msub>
</mrow>
In formula, A'kTo consider the availability of element after Information System Function effect, AkNot consider Information System Function effect
Element availability,For the synthesis availability of message elements function；
Step 4.4：Analysis obtains considering the active power distribution network function group probability of malfunction that information system is acted on more than
<mrow>
<msub>
<mi>P</mi>
<msub>
<mi>G</mi>
<mi>i</mi>
</msub>
</msub>
<mo>=</mo>
<msub>
<mi>P</mi>
<mrow>
<msub>
<mi>NG</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>P</mi>
<mrow>
<msub>
<mi>YG</mi>
<mi>i</mi>
</msub>
</mrow>
</msub>
</mrow>
And the probability of malfunction of failure path is tried to achieve according to N-k fault path search models.
4. the active power distribution network various visual angles collaboration vulnerability assessment side according to claim 1 for considering information system effect
Method, it is characterised in that described step 5 comprises the following steps：
Step 5.1：Various running statuses and net under source net load interaction pattern to considering the active power distribution network that information system is acted on
Frame structure is estimated, wherein
The analysis of mains side vulnerability inder includes：The grid-connected rate of distributed power source, emergency power supply, UPS utility ratios, bus fragile degree and
Monitoring host computer function Availability Index；
Distribution network side integrated risk vulnerability inder includes：Node fragile degree, voltage limit risk, degree of balance index and exchange
Machine Availability Index；
Load side vulnerability inder includes：Lose load risk, overload risk, load power supplying efficiency and Region control unit available
Rate；
Step 5.2：The architectural vulnerability of active power distribution network is assessed using Complex Networks Theory, evaluation index includes：Node is fragile
Degree, bus fragile degree；
Using the severity of Risk Utility theoretical appraisal function group individual event risk, wherein evaluation index includes：Voltage limit risk,
Lose load risk, overload risk；
Step 5.3：Certainty based on power distribution network and external disaster-randomness connection weight matrix, and for multiple source power distribution net office
Portion powers the distinguishing feature that can reduce big power supply by the active power of remote line transmission to load, defines the whole network active
Power-balance degree is：
<mrow>
<mover>
<mi>p</mi>
<mo>&OverBar;</mo>
</mover>
<mo>=</mo>
<mfrac>
<mrow>
<msub>
<mi>&Sigma;</mi>
<mi>l</mi>
</msub>
<msubsup>
<mi>w</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mo>&prime;</mo>
</msubsup>
<mo>&times;</mo>
<msub>
<mi>p</mi>
<mi>l</mi>
</msub>
</mrow>
<mrow>
<msub>
<mi>&Sigma;</mi>
<mi>l</mi>
</msub>
<mrow>
<mo>(</mo>
<msubsup>
<mi>w</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mo>&prime;</mo>
</msubsup>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
</mrow>
Wherein, w'ijTo consider the matrix element of disaster randomness influence, plFor the active power of line transmission, l is impedance perunit
Value；
Step 5.4：The decay of generating capacity and generator to loading effects effect is taken into account, the power of analysis active power distribution network is passed
Defeated efficiency, the load power supplying efficiency for defining load bus i is：
<mrow>
<msub>
<mi>E</mi>
<mi>i</mi>
</msub>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<mrow>
<msub>
<mi>P</mi>
<mrow>
<mi>D</mi>
<mi>i</mi>
</mrow>
</msub>
<msub>
<mi>V</mi>
<mi>D</mi>
</msub>
</mrow>
</mfrac>
<munder>
<mo>&Sigma;</mo>
<mrow>
<mi>j</mi>
<mo>&Element;</mo>
<msub>
<mi>V</mi>
<mi>G</mi>
</msub>
</mrow>
</munder>
<mfrac>
<msub>
<mi>P</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
</msub>
<msup>
<mn>2</mn>
<mrow>
<msub>
<mi>d</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
</mfrac>
</mrow>
In formula：dij(i∈VD,j∈VG) saved for the load bus i based on certainty-randomness topological structure built-up pattern with generating electricity
Most short electrical path between point j, PDiFor load bus i burden with power amount, PGjFor generating node j active installed capacity,
VDIt is load bus number, VGIt is generator nodes；
Step 5.5：Ask for the vulnerability inder α (l relevant with active power distribution network system architecturei)
<mrow>
<mi>&alpha;</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>l</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>&alpha;</mi>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>j</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msub>
<mi>n</mi>
<msub>
<mi>G</mi>
<mi>i</mi>
</msub>
</msub>
</munderover>
<mrow>
<mo>(</mo>
<mfrac>
<mrow>
<msub>
<mi>I</mi>
<mi>i</mi>
</msub>
<mo>&CenterDot;</mo>
<mi>B</mi>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>)</mo>
</mrow>
</mrow>
<msub>
<mi>n</mi>
<msub>
<mi>G</mi>
<mi>i</mi>
</msub>
</msub>
</mfrac>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mi>&beta;</mi>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
<mo>{</mo>
<msub>
<mi>I</mi>
<mi>i</mi>
</msub>
<mo>&CenterDot;</mo>
<mi>B</mi>
<mrow>
<mo>(</mo>
<mi>m</mi>
<mo>,</mo>
<mi>n</mi>
<mo>)</mo>
</mrow>
<mo>}</mo>
</mrow>
In formula：For the importance of i-th of node, MiFor the node number of degrees of i-th of node, PiFor i-th
The injecting power characteristic of individual node, k1、k2For weight, and k1+k2=1, SbaseFor system reference power；B (m, n)=max (B (m,
I), B (j, n)) be circuit improvement betweenness, (m, i), (j, n) are respectively all circuits being connected with node m and node n；Table
Show function group number；max{IiB (m, n) } it is highest fragile structure degree in function group, α, β are weight, and alpha+beta=1；
Step 5.6：Ask for the vulnerability inder δ (l relevant with information systemi)
δ(li)=Afz×Afj×Afq
In formula：AfzFor the function availability of monitoring host computer, AfjFor the function availability of interchanger, AfqFor Region control unit
Function availability.
5. the active power distribution network various visual angles collaboration vulnerability assessment side according to claim 1 for considering information system effect
Method, it is characterised in that described step 6 comprises the following steps：
Step 6.1：The active power distribution network various visual angles collaboration fragility of information system effect is considered using cooperative effect theoretical appraisal,
According to the cooperative effect between system architecture and state, between information and physical system, set up and consider having for information system effect
Source power distribution network collaboration vulnerability assessment model：
<mrow>
<mi>R</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>X</mi>
<mrow>
<mi>t</mi>
<mo>,</mo>
<mi>f</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munder>
<mo>&Sigma;</mo>
<mi>i</mi>
</munder>
<msub>
<mi>p</mi>
<mi>r</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>R</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
</mrow>
<msub>
<mi>S</mi>
<mrow>
<mi>e</mi>
<mi>v</mi>
</mrow>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>R</mi>
<mi>i</mi>
</msub>
<mo>,</mo>
<msub>
<mi>w</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
Vxti=Vxyi+Vxwi=α (li)R(Xt,f)γ+α(li)δ(li)η
In formula：VxyiFor system architecture vulnerability index is cooperateed with running status；VxwiFor information fragility is cooperateed with physical system
Index；VxtiCooperateed with to consider system architecture with running status, the vulnerability index that information is cooperateed with physical system；α(li) be
The vulnerability index relevant with system architecture；R(Xt,f) it is risk indicator mainly relevant with system running state, Xt,fFor the time
The t method of operation, pr(Ri) it is i-th of uncertain disturbances RiThe possibility of generation,It is in RiDisturbance
The order of severity of lower system loss, wiFor the breakdown loss value of corresponding index；γ is the association factor of structure and state, is taken as γ
=P/Pmax, P is realtime power, PmaxFor circuit maximum transmission power；η is the association factor of information and physics, is taken as active match somebody with somebody
The information-based configuration degree of power network；
Step 6.2：Local collaboration vulnerability inder, Regional Synergetic vulnerability inder and the global collaborative set up on space scale are crisp
Weak property index system；Local collaboration vulnerability inder VlocalMajor embodiment active power distribution network is acted on the local support of load, area
Domain collaboration vulnerability inder VareaFragile degree in a certain formulation region of major embodiment, global area the weakness VtotalMainly
The fragility for the active power distribution network for considering information system effect is assessed on the whole, wherein
<mrow>
<msub>
<mi>V</mi>
<mrow>
<mi>l</mi>
<mi>o</mi>
<mi>c</mi>
<mi>a</mi>
<mi>l</mi>
</mrow>
</msub>
<mo>=</mo>
<msub>
<mi>V</mi>
<mrow>
<mi>x</mi>
<mi>t</mi>
<mi>i</mi>
</mrow>
</msub>
<munder>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>&Element;</mo>
<msub>
<mi>V</mi>
<mi>D</mi>
</msub>
</mrow>
</munder>
<mfrac>
<msub>
<mi>E</mi>
<mi>i</mi>
</msub>
<msub>
<mi>n</mi>
<mi>D</mi>
</msub>
</mfrac>
</mrow>
<mrow>
<msub>
<mi>V</mi>
<mrow>
<mi>a</mi>
<mi>r</mi>
<mi>e</mi>
<mi>a</mi>
</mrow>
</msub>
<mo>=</mo>
<msub>
<mi>V</mi>
<mrow>
<mi>x</mi>
<mi>t</mi>
<mi>i</mi>
</mrow>
</msub>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>m</mi>
</munderover>
<mrow>
<mo>(</mo>
<mfrac>
<msub>
<mi>&lambda;</mi>
<mi>l</mi>
</msub>
<mi>m</mi>
</mfrac>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<msub>
<mi>V</mi>
<mrow>
<mi>t</mi>
<mi>o</mi>
<mi>t</mi>
<mi>a</mi>
<mi>l</mi>
</mrow>
</msub>
<mo>=</mo>
<msub>
<mi>V</mi>
<mrow>
<mi>x</mi>
<mi>t</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>{</mo>
<msub>
<mi>k</mi>
<mn>1</mn>
</msub>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>j</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<msub>
<mi>n</mi>
<mi>L</mi>
</msub>
</munderover>
<mrow>
<mo>(</mo>
<mfrac>
<msub>
<mi>&lambda;</mi>
<mrow>
<mi>L</mi>
<mi>j</mi>
</mrow>
</msub>
<msub>
<mi>n</mi>
<mi>L</mi>
</msub>
</mfrac>
<mo>)</mo>
</mrow>
<mo>+</mo>
<msub>
<mi>k</mi>
<mn>2</mn>
</msub>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
<mo>{</mo>
<msub>
<mi>&lambda;</mi>
<mrow>
<mi>L</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>}</mo>
<mo>}</mo>
</mrow>
In formula：VxtiTo consider that the active power distribution network of information system effect cooperates with the weakness；nDFor load bus sum；EiFor
The load power supplying efficiency of node i；M is the sum of grid nodes；λlFor the weakness of failure path；k1、k2For weight, and
k1+k2=1；nLThe interstitial content passed through for failure path；λLjFor the weakness of each node in failure path, max { λLj}
For highest node fragile degree on failure path.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710405544.XA CN107220775B (en) | 2017-06-01 | 2017-06-01 | Active power distribution network multi-view cooperative vulnerability assessment method considering information system effect |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710405544.XA CN107220775B (en) | 2017-06-01 | 2017-06-01 | Active power distribution network multi-view cooperative vulnerability assessment method considering information system effect |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107220775A true CN107220775A (en) | 2017-09-29 |
| CN107220775B CN107220775B (en) | 2020-04-07 |
Family
ID=59948033
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710405544.XA Expired - Fee Related CN107220775B (en) | 2017-06-01 | 2017-06-01 | Active power distribution network multi-view cooperative vulnerability assessment method considering information system effect |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107220775B (en) |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108959072A (en) * | 2018-06-14 | 2018-12-07 | 北京航空航天大学 | A kind of group system elasticity assessment method based on complex network |
| CN110826842A (en) * | 2019-09-09 | 2020-02-21 | 天津大学 | Power distribution network risk control method in typhoon scene |
| CN110854907A (en) * | 2019-11-07 | 2020-02-28 | 华北电力大学 | Collaborative optimization operation method and system for power distribution network wind power plant under communication fault |
| CN110943983A (en) * | 2019-11-22 | 2020-03-31 | 南京邮电大学 | Network security prevention method based on security situation awareness and risk assessment |
| CN110971565A (en) * | 2018-09-29 | 2020-04-07 | 全球能源互联网研究院有限公司 | Source network load system vulnerability evaluation method and system based on malicious attack modeling |
| CN111191872A (en) * | 2019-11-22 | 2020-05-22 | 国家电网有限公司 | Power grid multi-dimensional toughness evaluation system and method |
| CN111369388A (en) * | 2020-03-09 | 2020-07-03 | 华北电力大学 | Method and system for evaluating anti-vulnerability of urban power grid |
| CN111798163A (en) * | 2020-07-28 | 2020-10-20 | 南京邮电大学 | Active power distribution network security assessment method |
| CN111865700A (en) * | 2020-08-03 | 2020-10-30 | 国网浙江省电力有限公司经济技术研究院 | Information node screening method and related device for electric power information physical system |
| CN112865198A (en) * | 2021-03-31 | 2021-05-28 | 南华大学 | Power distribution network global optimization scheduling method based on time scale |
| CN113642944A (en) * | 2021-10-15 | 2021-11-12 | 中国电力科学研究院有限公司 | Large power grid static security risk analysis method, system, equipment and storage medium |
| CN117117926A (en) * | 2023-10-25 | 2023-11-24 | 国网江西省电力有限公司经济技术研究院 | Power distribution network energy storage configuration method and system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104123682A (en) * | 2014-07-28 | 2014-10-29 | 国家电网公司 | Distribution network fault risk assessment method based on meteorology influence factors |
| CN105117840A (en) * | 2015-08-20 | 2015-12-02 | 国网智能电网研究院 | Risk assessment method of power system considering role of information system |
| CN105760979A (en) * | 2015-08-14 | 2016-07-13 | 中国电力科学研究院 | Power system transient risk evaluation method taking natural disasters into consideration |
| US20160241031A1 (en) * | 2015-02-18 | 2016-08-18 | Nec Laboratories America, Inc. | Dynamic probability-based power outage management system |
-
2017
- 2017-06-01 CN CN201710405544.XA patent/CN107220775B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104123682A (en) * | 2014-07-28 | 2014-10-29 | 国家电网公司 | Distribution network fault risk assessment method based on meteorology influence factors |
| US20160241031A1 (en) * | 2015-02-18 | 2016-08-18 | Nec Laboratories America, Inc. | Dynamic probability-based power outage management system |
| CN105760979A (en) * | 2015-08-14 | 2016-07-13 | 中国电力科学研究院 | Power system transient risk evaluation method taking natural disasters into consideration |
| CN105117840A (en) * | 2015-08-20 | 2015-12-02 | 国网智能电网研究院 | Risk assessment method of power system considering role of information system |
Non-Patent Citations (1)
| Title |
|---|
| 刘晟: "电网脆弱性的评估理论及方法研究", 《中国优秀硕士学位论文全文数据库 工程科技II辑》 * |
Cited By (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108959072B (en) * | 2018-06-14 | 2020-08-25 | 北京航空航天大学 | Complex network-based cluster system elasticity evaluation method |
| CN108959072A (en) * | 2018-06-14 | 2018-12-07 | 北京航空航天大学 | A kind of group system elasticity assessment method based on complex network |
| CN110971565B (en) * | 2018-09-29 | 2023-04-28 | 全球能源互联网研究院有限公司 | Source network load system vulnerability evaluation method and system based on malicious attack modeling |
| CN110971565A (en) * | 2018-09-29 | 2020-04-07 | 全球能源互联网研究院有限公司 | Source network load system vulnerability evaluation method and system based on malicious attack modeling |
| CN110826842A (en) * | 2019-09-09 | 2020-02-21 | 天津大学 | Power distribution network risk control method in typhoon scene |
| CN110854907A (en) * | 2019-11-07 | 2020-02-28 | 华北电力大学 | Collaborative optimization operation method and system for power distribution network wind power plant under communication fault |
| CN110854907B (en) * | 2019-11-07 | 2021-04-06 | 华北电力大学 | Collaborative optimization operation method and system for power distribution network wind power plant under communication fault |
| CN110943983B (en) * | 2019-11-22 | 2020-10-30 | 南京邮电大学 | Network security prevention method based on security situation awareness and risk assessment |
| CN110943983A (en) * | 2019-11-22 | 2020-03-31 | 南京邮电大学 | Network security prevention method based on security situation awareness and risk assessment |
| CN111191872B (en) * | 2019-11-22 | 2024-04-09 | 国家电网有限公司 | Multi-dimensional toughness evaluation system and method for power grid |
| CN111191872A (en) * | 2019-11-22 | 2020-05-22 | 国家电网有限公司 | Power grid multi-dimensional toughness evaluation system and method |
| CN111369388A (en) * | 2020-03-09 | 2020-07-03 | 华北电力大学 | Method and system for evaluating anti-vulnerability of urban power grid |
| CN111369388B (en) * | 2020-03-09 | 2024-01-26 | 华北电力大学 | Anti-vulnerability assessment method and system for urban power grid |
| CN111798163B (en) * | 2020-07-28 | 2021-03-05 | 南京邮电大学 | Active power distribution network security assessment method |
| CN111798163A (en) * | 2020-07-28 | 2020-10-20 | 南京邮电大学 | Active power distribution network security assessment method |
| CN111865700B (en) * | 2020-08-03 | 2023-03-28 | 国网浙江省电力有限公司经济技术研究院 | Information node screening method and related device for electric power information physical system |
| CN111865700A (en) * | 2020-08-03 | 2020-10-30 | 国网浙江省电力有限公司经济技术研究院 | Information node screening method and related device for electric power information physical system |
| CN112865198A (en) * | 2021-03-31 | 2021-05-28 | 南华大学 | Power distribution network global optimization scheduling method based on time scale |
| CN113642944A (en) * | 2021-10-15 | 2021-11-12 | 中国电力科学研究院有限公司 | Large power grid static security risk analysis method, system, equipment and storage medium |
| CN113642944B (en) * | 2021-10-15 | 2022-01-07 | 中国电力科学研究院有限公司 | Large power grid static security risk analysis method, system, equipment and storage medium |
| CN117117926A (en) * | 2023-10-25 | 2023-11-24 | 国网江西省电力有限公司经济技术研究院 | Power distribution network energy storage configuration method and system |
| CN117117926B (en) * | 2023-10-25 | 2024-04-09 | 国网江西省电力有限公司经济技术研究院 | Power distribution network energy storage configuration method and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107220775B (en) | 2020-04-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107220775A (en) | A kind of active power distribution network various visual angles collaboration vulnerability assessment method for considering information system effect | |
| Afzal et al. | State‐of‐the‐art review on power system resilience and assessment techniques | |
| Umunnakwe et al. | Quantitative analysis of power systems resilience: Standardization, categorizations, and challenges | |
| Mohammed et al. | Available transfer capability calculation methods: A comprehensive review | |
| Sabouhi et al. | Electrical power system resilience assessment: A comprehensive approach | |
| Sansavini et al. | A stochastic framework for uncertainty analysis in electric power transmission systems with wind generation | |
| Wang et al. | Time‐varying failure rate simulation model of transmission lines and its application in power system risk assessment considering seasonal alternating meteorological disasters | |
| Wang et al. | On machine learning-based techniques for future sustainable and resilient energy systems | |
| CN106357414B (en) | Information interacting method and system for base station electric generation management | |
| CN106157174A (en) | To reduce power off time and the electricity power failure planning optimization decision method as target | |
| CN107633320A (en) | A kind of power network line importance appraisal procedure based on weather prognosis and risk assessment | |
| Kandaperumal et al. | AWR: Anticipate, withstand, and recover resilience metric for operational and planning decision support in electric distribution system | |
| CN105719062B (en) | A kind of power grid risk considering double probability of malfunction characteristic and weak link appraisal procedure | |
| Akdeniz et al. | A knowledge based decision support algorithm for power transmission system vulnerability impact reduction | |
| Guohua et al. | Vulnerability assessment of bulk power grid based on complex network theory | |
| CN107622360A (en) | A kind of critical circuits recognition methods for considering subjective and objective factor | |
| Hu et al. | Robustness evaluation of complex power grids containing renewable energy | |
| Zhang et al. | Assessment method and metrics of power system resilience after disasters | |
| CN108229841A (en) | A kind of data exception processing method and processing device | |
| Arab et al. | Dynamic maintenance scheduling for power systems incorporating hurricane effects | |
| CN107301479B (en) | Natural disaster risk-based multi-scene planning method for power transmission system | |
| Chen et al. | Unified data‐driven stochastic and robust service restoration method using non‐parametric estimation in distribution networks with soft open points | |
| CN108287290A (en) | A kind of power grid cascading fault pre-alarming analysis system based on the operation of big regional power grid | |
| Noorazar et al. | Data‐driven operation of the resilient electric grid: A case of COVID‐19 | |
| Wu et al. | Optimal black start strategy for microgrids considering the uncertainty using a data‐driven chance constrained approach |
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 | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20200407 |