CN111008454B - Intelligent substation reliability assessment method based on information physical fusion model - Google Patents

Intelligent substation reliability assessment method based on information physical fusion model Download PDF

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CN111008454B
CN111008454B CN201911013155.8A CN201911013155A CN111008454B CN 111008454 B CN111008454 B CN 111008454B CN 201911013155 A CN201911013155 A CN 201911013155A CN 111008454 B CN111008454 B CN 111008454B
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reliability
information network
reliability index
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CN111008454A (en
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李俊娥
许昂
袁凯
陈洋荣
刘开培
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Wuhan University WHU
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/16—Electric power substations

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Abstract

The invention discloses an intelligent substation reliability evaluation method based on an information physical fusion model, which comprises the steps of firstly constructing an information physical fusion system model capable of reflecting a power primary system and an information network topological structure, and then aiming at a power primary system side of an intelligent substation, obtaining reliability indexes of equipment nodes according to actual operation conditions; for the information network side, reliability indexes of all devices and communication links of the information network side are analyzed based on an analytic hierarchy process, then the mode and process of interaction influence of the primary power system and the information network are analyzed in detail, and a method for quantitatively analyzing the interaction influence of the primary power system and the information network is provided, so that the reliability indexes of the primary power system side of the intelligent substation under the interaction of the primary power system and the information network are obtained. On the basis, a reliability evaluation method of the intelligent substation is provided based on a Monte Carlo simulation method. The invention has accurate and reliable analysis result; and the evaluation result is more in line with the actual operation condition.

Description

Intelligent substation reliability assessment method based on information physical fusion model
Technical Field
The invention relates to the technical field of power system evaluation, in particular to an intelligent substation reliability evaluation method based on an information physical fusion model.
Background
The intelligent substation is used as an important ring in an intelligent power grid, a primary power system and an information network are deeply fused, and interaction between energy flow and information flow is more and more obvious. In the development process of a transformer substation, the structures and functions of a primary power system and an information network are greatly changed, new technologies such as gigabit Ethernet high-speed communication, microsecond-level high-precision synchronous sampling, an unconventional transformer and the like are widely adopted in an intelligent transformer substation, and compared with a traditional transformer substation, the intelligent transformer substation is more complex in system structure, so that the new technologies bring great innovation to a power system, and meanwhile, the reliability problem of the intelligent transformer substation is also widely concerned.
In the prior art, the adopted reliability assessment method is to respectively assess a primary power system and an information network of an intelligent substation so as to obtain an assessment result.
The inventor of the present application finds that the method of the prior art has at least the following technical problems in the process of implementing the present invention:
while the intelligent substation information network provides support for the operation control of the primary power system, the reliability characteristics of the intelligent substation information network also affect the primary power system, and meanwhile, the failure of the primary power system also affects the normal operation of information equipment in the information system, so that the traditional reliability evaluation method is no longer suitable for the intelligent substation.
Therefore, the method in the prior art has the technical problem that the evaluation result is unreliable.
Disclosure of Invention
In view of this, the invention provides an intelligent substation reliability evaluation method based on an cyber-physical model, which is used for solving or at least partially solving the technical problem that an evaluation result of the method in the prior art is unreliable.
In order to solve the technical problem, the invention provides an intelligent substation reliability assessment method based on an information physical fusion model, which comprises the following steps:
step S1: constructing an information physical fusion model of the intelligent substation, wherein the information physical fusion model comprises a power primary system and an information network;
step S2: determining the reliability index of the primary power system and the reliability index of the information network;
step S3: determining an interaction influence index of the primary power system and the information network according to the interaction between the primary power system and the information network;
step S4: and according to the reliability index of the primary power system, the reliability index of the information network and the interaction influence index of the primary power system and the information network, reliability evaluation is carried out on the intelligent substation.
In one embodiment, step S1 specifically includes:
step S1.1: for the primary power system, a first network model with the power transmission line as a branch and the power equipment as a node is established;
step S1.2: establishing a second network model with a communication link as a branch and communication equipment as a node in the information network;
step S1.3: and constructing an information physical fusion model of the intelligent substation based on the constructed first network model, the constructed second network model and the interaction between the power equipment in the primary power system and the communication equipment in the information network.
In one embodiment, the primary power system includes a primary power device and a power transmission line, the information network includes a communication link and a communication device, and step S2 specifically includes:
step S2.1: determining the reliability index of the primary power system according to the availability of the primary power equipment and the availability of the power transmission line;
step S2.2: and determining the reliability index of the information network according to the availability of the communication link, the reliability of the transmission data, the availability of the communication equipment and the importance of the communication equipment to the transmission of the communication service.
In one embodiment, step S2.1 specifically includes:
step S2.1.1: determining a reliability index R of the primary electric power equipment according to the availability of the primary electric power equipmentp(Ap,i)：
Figure BDA0002244809900000021
Wherein λ isiIndicating an electric primary appliance Ap,iFailure rate of uiFor powering primary equipment Ap,iThe repair rate of (1), MTBR, represents the power primary equipment Ap,iMean time between repairs, MTBF stands for power primary ap,iMean time between failures of (1);
step S2.1.2: determining the reliability index R of the transmission line according to the availability of the transmission linep[Bp(i,j)]：
Figure BDA0002244809900000031
In the formula (2), Rp[Bp(i,j)]Representing a slave power primary appliance Ap,iTo the electric primary equipment Ap,jTransmission line Bp(i, j) reliability index, λi,jIs the failure rate of the transmission line, ui,jThe repair rate of the transmission line; subscript p represents the grid side, i and j represent the numbers of the electric primary devices;
step S2.1.3: and taking the reliability index of the primary power equipment and the reliability index of the power transmission line as the reliability index of the primary power system.
In one embodiment, step S2.2 specifically includes:
step S2.2.1: determining a reliability index R of the communication link according to the availability of the communication link and the credibility of the transmission datac(Bc,k)：
Rc(Bc,k)＝Rc[Bc(i',j')]＝Ai',j'·(1-D) (3)
Where k denotes the kth communication link, Rc[Bc(i',j')]Representing a slave communication device Ac,i'To communication device Ac,j'Branch B ofc(i ', j'); subscript c denotes an information side, i 'and j' denote numbers of communication devices; d represents the error rate of the transmitted data in the communication link, Ai',j'Which indicates the availability of the link or links,
Figure BDA0002244809900000032
λi',j'and ui',j'Respectively representing communication links Bc(i ', j') failure rate, repair rate, MTBR and MTBF respectively representing communication link Bc(i ', j') an average repair interval time and an average fault interval time;
step S2.2.2: determining the reliability index R of the communication equipment according to the availability of the communication equipment and the importance of the communication equipment to the communication service transmissionc(Ac,i')：
Figure BDA0002244809900000033
Wherein λ ise,i'Representing the equivalent failure rate of the communication device to the system reliability,
Figure BDA0002244809900000034
the method is used for representing the importance of communication equipment to communication service transmission and is determined by adopting an analytic hierarchy process
Figure BDA0002244809900000035
Value of (A)i'Is the failure rate of the communication device; u. ofi'I' represents the number of the communication device as the repair rate of the communication device;
step S2.2.3: and taking the reliability index of the communication link and the reliability index of the communication equipment as the reliability index of the information network.
In one embodiment, step S3 specifically includes:
step S3.1: determining a transmission path of data flow between an information network and a power primary system;
step S3.2: calculating the reliability index of each data stream;
step S3.3: and obtaining the interactive influence index of the primary power system and the information network according to the reliability index of each data stream.
In one embodiment, step S3.2 is to calculate the reliability index of the data stream according to equation (5):
R[L(i',j')]＝f(Ac，1,Ac，2,...,Ac,i',Bc,1,Bc,2,...,Bc,k)
＝Rc(Ac,1)Rc(Ac,2)...Rc(Ac,i')·Rc(Bc,1)Rc(Bc,2)...Rc(Bc,k) (5)
in the formula (5), R [ L (i ', j')]Representing a data stream transmission reliability index, Ac,i'Representing the communication node, B, through which the data stream transmission path passesc,kRepresenting the communication link through which the data stream transmission path passes.
In an embodiment, the transmission path of the data stream includes an SAV message transmission path and a GOOSE message transmission path, and step S3.3 specifically includes:
according to the SAV message transmission reliability index and the GOOSE message transmission reliability index, calculating an interaction influence index R of the primary power system and the information networkp(Ap,i')'：
Rp(Ap,i')'＝Rp(Ap,i')Rg[L(i',j')]Rs[L(i',j')] (6)
Wherein R isp(Ap,i') Representing an index of reliability, R, of primary electric devices in an electric primary system interacting with an information networks[L(i',j')]Representing a corresponding SAV message transmission reliability index, Rg[L(i',j')]And expressing the GOOSE message transmission reliability index.
In one embodiment, the method further comprises: optimizing SAV message transmission reliability index by adopting measurement information deviation rate, and further optimizing interaction influence index R of primary power system and information networkp(Ap,i') Optimizing to obtain optimized interactive influence index, wherein the optimized SAV message transmission reliability index is Rs[L(i',j')]'：
Rs[L(i',j')]'＝(1-ξr)Rs[L(i',j')] (7)
Wherein ξrIndicating the deviation ratio of the measurement information,the device is used for representing the deviation occurrence probability of the measurement information transmitted to the merging unit and the original measurement information;
the optimized interactive influence index is Rp(Ap,i')”：
Rp(Ap,i')”＝Rp(Ap,i')Rg[L(i',j')]Rs[L(i',j')]' (8)
Wherein R iss[L(i',j')]' is calculated by equation (7).
In one embodiment, step S4 specifically includes: and taking the reliability index of the primary power system, the reliability index of the information network and the interaction influence index of the primary power system and the information network as input, and adopting a Monte Carlo simulation method to carry out reliability evaluation on the intelligent substation.
One or more technical solutions in the embodiments of the present application have at least one or more of the following technical effects:
the invention provides an intelligent substation reliability evaluation method based on an information physical fusion model, which comprises the steps of firstly constructing the information physical fusion model of an intelligent substation, and then determining the reliability index of a primary power system and the reliability index of an information network; then, according to the interaction between the primary electric power system and the information network, determining an interaction influence index of the primary electric power system and the information network; and then, reliability evaluation is carried out on the intelligent substation according to the reliability index of the primary power system, the reliability index of the information network and the interactive influence index of the primary power system and the information network.
According to the evaluation method provided by the invention, after the reliability index of the primary power system and the reliability index of the information network are respectively determined, the interactive influence index of the primary power system and the information network is also determined according to the interaction between the primary power system and the information network, so that the reliability index of the primary power system side of the intelligent substation under the interaction between the primary power system and the information network can be obtained, and on the basis, reliability evaluation is carried out.
Furthermore, the reliability index of the intelligent substation communication equipment is analyzed by adopting an analytic hierarchy process, and the object is regarded as a system, and qualitative and quantitative combination is carried out, so that the reliability index of the information network is more consistent with the actual operation condition.
Further, the interactive influence of the primary power system and the information network of the intelligent substation is quantitatively analyzed according to the transmission process of the information service, so that the interactive influence index is more accurate and reliable.
Furthermore, on the basis of a Monte Carlo simulation method, the interaction between the primary power system and the information network is considered, the reliability evaluation method of the intelligent substation is provided, and the evaluation result is more consistent with the actual operation condition.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic flow chart of an intelligent substation reliability evaluation method based on an cyber-physical model according to the present invention;
FIG. 2 is a flow chart of an implementation of the method provided by the present invention;
FIG. 3 is a schematic diagram of an cyber-physical model of an intelligent substation;
FIG. 4 is a schematic view of an analytic hierarchy process model;
FIG. 5 is a schematic diagram of interaction between a primary power system and an information network of an intelligent substation;
FIG. 6 is a process level message flow diagram of an intelligent substation;
FIG. 7 is an electrical main wiring diagram of the D2-1 intelligent substation power primary system.
FIG. 8 is a schematic diagram of a minimum path set of an electrical main connection of an intelligent substation;
fig. 9 is a flowchart of the reliability evaluation of the intelligent substation based on the monte carlo simulation method.
Detailed Description
The invention aims to provide an intelligent substation reliability evaluation method based on an information physical fusion model, aiming at the technical problem that the evaluation result is unreliable due to neglect of interaction influence between a primary power system and an information network in the prior art, and the purpose of improving the reliability of the evaluation result is achieved.
In order to achieve the above purpose, the main concept of the invention is as follows:
firstly, an information physical fusion system model capable of reflecting a power primary system and an information network topological structure is constructed, and then the reliability index of each equipment node is obtained according to the actual operation condition aiming at the power primary system side in the intelligent substation; for the information network side, reliability indexes of all devices and communication links of the information network side are analyzed based on an analytic hierarchy process, then a mode and a process of interaction influence of a primary power system and the information network are analyzed in detail, a method for quantitatively analyzing the interaction influence of the primary power system and the information network is provided, so that the reliability indexes of the primary power system side of the intelligent substation under interaction of the primary power system and the information network are obtained, and finally reliability evaluation is carried out on the basis of the reliability indexes, specifically, the reliability evaluation method of the intelligent substation based on a Monte Carlo simulation method can be used.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment provides an intelligent substation reliability evaluation method based on an cyber-physical model, please refer to fig. 1, and the method includes:
step S1: and constructing an information physical fusion model of the intelligent substation, wherein the information physical fusion model comprises a power primary system and an information network.
Specifically, the inventors of the present application found through a great deal of research and practice that:
while the intelligent substation information network provides support for the operation control of the primary power system, the reliability characteristics of the intelligent substation information network also affect the primary power system, and communication delay, error codes, interruption and various network attacks existing in the information network may affect the normal operation of primary power equipment, cause the failure/misoperation of a circuit breaker, and further affect the safe and stable operation of the whole system. Meanwhile, the normal operation of the information equipment in the information system is also affected by the primary power system fault, so that the information equipment loses the acquisition and control functions of the physical equipment, and the operation of the primary power system is further affected in return to form cascading faults.
Therefore, the traditional reliability assessment method is no longer suitable for the intelligent substation, the reliability assessment needs to be carried out from the perspective of information physical fusion, and the interaction influence process and mode of the primary power system and the information network should be considered while the uncertainty factor of the information network and the influence of the uncertainty factor on the primary power system are considered.
The information physical fusion model of the intelligent substation comprises two sides, namely a power primary system side and an information network side, and can be constructed by adopting a graph theory method in the specific implementation process.
In one embodiment, step S1 specifically includes:
step S1.1: for the primary power system, a first network model with the power transmission line as a branch and the power equipment as a node is established;
step S1.2: establishing a second network model with a communication link as a branch and communication equipment as a node in the information network;
step S1.3: and constructing an information physical fusion model of the intelligent substation based on the constructed first network model, the constructed second network model and the interaction between the power equipment in the primary power system and the communication equipment in the information network.
Specifically, interaction channels between power equipment in a primary power system in the intelligent substation and communication equipment of an information network are analyzed, for example, measurement information is transmitted between an electronic transformer and a merging unit, trip information is transmitted between an IED (intelligent electronic device) and a breaker, and the like, so that an information network fusion system model of the intelligent substation is constructed.
In a specific implementation process, as shown in fig. 3, a schematic diagram of an cyber-physical model of an intelligent substation is shown.
In the primary power system, a transformer, a breaker, a load and the like are abstractly described as nodes and defined as a set Ap：
Ap＝{Ap,1,Ap,2,...Ap,m} (9)
In the formula (9), Ap,1,Ap,2,...Ap,mRepresenting m power devices in a power primary system.
Abstracting the transmission line into branches, and defining the transmission line as a set Bp：
Bp＝{Bp,1,Bp,2,...,Bp,n} (10)
In the formula (10), Bp1,Bp2,...,BpnRepresenting n power devices in a power primary system.
In an information network, combining units, breaker IEDs, measurement and control/protection IEDs, switches and the like are abstractly described as nodes, and defined as a set Ac：
Ac＝{Ac,1,Ac,2,...,Ac,g} (11)
In the formula (11), Ac,1,Ac,2,...,Ac,gRepresenting g communication devices in the information network, e.g. communication nodes representing the data stream transmission paths.
The optical fiber transmission line is abstractly described as a link and defined as a set Bc：
Bc＝{Bc,1,Bc,2,...,Bc,k} (12)
In the formula (12), Bc,1,Bc,2,...,Bc,kRepresenting k communication devices in the information network, e.g. representing communication links over which data stream transmission paths pass.
In the primary power system, a network model with a power transmission line as a branch and power equipment as a node is established; in the information network, a network model is established in which communication links are used as branches and communication devices are used as nodes.
Step S2: and determining the reliability index of the primary power system and the reliability index of the information network.
During specific implementation, the reliability indexes of each device and branch of the primary power system and the information network are analyzed respectively, so that corresponding reliability indexes are obtained.
In one embodiment, the primary power system includes a primary power device and a power transmission line, the information network includes a communication link and a communication device, and step S2 specifically includes:
step S2.1: determining the reliability index of the primary power system according to the availability of the primary power equipment and the availability of the power transmission line;
step S2.2: and determining the reliability index of the information network according to the availability of the communication link, the reliability of the transmission data, the availability of the communication equipment and the importance of the communication equipment to the transmission of the communication service.
Specifically, reliability indexes of all devices and power transmission lines on the primary power system side of the intelligent substation are single, and therefore the availability of all the devices and the power transmission lines is counted according to the running condition of the intelligent substation. The reliability indexes of the intelligent substation information network side comprise indexes of communication links and communication equipment. For the reliability index of the communication link, the reliability of the reliability index is not only related to the availability of the communication link, but also related to the reliability of data transmission in the link, the reliability index of the communication equipment not only depends on the availability of the equipment, but also is related to the importance of the equipment on communication service transmission, the equipment is failed to influence the transmitted communication service, and for the communication service, the importance of each communication equipment on the transmission path on the reliable transmission of the service is different.
In one embodiment, step S2.1 specifically includes:
step S2.1.1: determining a reliability index R of the primary electric power equipment according to the availability of the primary electric power equipmentp(Ap,i)：
Figure BDA0002244809900000091
Wherein λ isiIndicating an electric primary appliance Ap,iFailure rate of uiFor powering primary equipment Ap,iThe repair rate of (1), MTBR, represents the power primary equipment Ap,iMean time between repairs, MTBF stands for power primary ap,iMean time between failures of (1);
step S2.1.2: determining the reliability index R of the transmission line according to the availability of the transmission linep[Bp(i,j)]：
Figure BDA0002244809900000092
In the formula (2), Rp[Bp(i,j)]Representing a slave power primary appliance Ap,iTo the electric primary equipment Ap,jTransmission line Bp(i, j) reliability index, λi,jIs the failure rate of the transmission line, ui,jThe repair rate of the transmission line; subscript p represents the grid side, i and j represent the numbers of the electric primary devices;
step S2.1.3: and taking the reliability index of the primary power equipment and the reliability index of the power transmission line as the reliability index of the primary power system.
Specifically, reliability indexes of each device and power transmission line on the primary power system side of the intelligent substation are single, the availability of each device and power transmission line is usually counted according to the operation condition of the intelligent substation, and the specific form of the obtained reliability index is shown in formulas (1) and (2).
In the specific implementation process, the reliability index of the primary power system can be obtained according to the formulas (1) and (2) and the collected data, wherein the collected data can be the existing reference data and the data provided by the manufacturer, and the reliability data of the main equipment in the primary power system is shown in table 1:
table 1: reliability data of electric primary equipment
Figure BDA0002244809900000101
In one embodiment, step S2.2 specifically includes:
step S2.2.1: determining a reliability index R of the communication link according to the availability of the communication link and the credibility of the transmission datac(Bc,k) (i.e., R)c[Bc(i',j')])：
Rc(Bc,k)＝Rc[Bc(i',j')]＝Ai',j'·(1-D) (3)
Where k denotes the kth communication link, Rc[Bc(i',j')]Representing a slave communication device Ac,i'To communication device Ac,j'Branch B ofc(i ', j'); subscript c denotes an information side, i 'and j' denote numbers of communication devices; d represents the error rate of the transmitted data in the communication link, Ai',j'Which indicates the availability of the link or links,
Figure BDA0002244809900000102
λi',j'and ui',j'Respectively representing communication links Bc(i ', j') failure rate, repair rate, MTBR and MTBF respectively representing communication link Bc(i ', j') an average repair interval time and an average fault interval time;
step S2.2.2: determining the reliability index R of the communication equipment according to the availability of the communication equipment and the importance of the communication equipment to the communication service transmissionc(Ac,i')：
Figure BDA0002244809900000103
Wherein λ ise,i'Representing the equivalent failure rate of the communication device to the system reliability,
Figure BDA0002244809900000104
the method is used for representing the importance of communication equipment to communication service transmission and is determined by adopting an analytic hierarchy process
Figure BDA0002244809900000105
Value of (A)i'Is the failure rate of the communication device; u. ofi'I' represents the number of the communication device as the repair rate of the communication device;
step S2.2.3: and taking the reliability index of the communication link and the reliability index of the communication equipment as the reliability index of the information network.
Specifically, the reliability index of the intelligent substation information network side comprises indexes of a communication link and communication equipment. For the reliability index of the communication link, the reliability is related to not only the availability of the communication link but also the reliability of the data transmitted in the link, and therefore the reliability index of the communication link is shown in formula (3).
Specifically, the specific implementation process for determining the reliability index of the communication device by using the analytic hierarchy process is as follows:
FIG. 4 is a schematic diagram of an analytic hierarchy process model for determining importance of a communication element based on consequences of failure of the element
Figure BDA0002244809900000111
By AHP method
Figure BDA0002244809900000112
The process of (2) is as follows:
(1) establishing a hierarchical analysis model;
the method comprises the steps of constructing a target layer which is the comprehensive influence of element failure on communication service, constructing a criterion layer which is the real-time influence, the reliability influence and the safety influence of the element failure on the communication service, wherein the real-time influence is reflected by signal time delay and signal interruption, the reliability is reflected by bit error rate and packet loss rate, and the safety is reflectedAn analytic hierarchy process model with data leakage reaction and communication equipment failure probability as index layer is shown in figure 4, wherein the index layer equipment is respectively C1:MU,C2:P&C unit, C3Breaker IED, C4A switch.
(2) Constructing a judgment matrix;
based on an AHP conventional 1-9 scale method, a judgment matrix M of a criterion layer to a target layer and a criterion layer to the criterion layer is established from top to bottom for an importance evaluation system of intelligent substation communication equipmentm,nAnd m and n are the number of rows and columns of the matrix. Wherein the scale method of 1-9 is shown in Table 2.
Table 2: 1 to 9 scale method
Figure BDA0002244809900000113
(3) Sorting the hierarchical lists;
the matrix is normalized for each column as shown below.
Figure BDA0002244809900000121
Where M is the decision matrix, W is the normalized vector, k is 1,2, …, and M is the number of rows in the matrix. Summing the normalized matrix by column and then by row, i.e.
Figure BDA0002244809900000122
Normalizing the resulting vector, i.e.
Figure BDA0002244809900000123
In the specific implementation process, the judgment matrix of the criterion layer to the target layer is as follows:
Figure BDA0002244809900000124
a decision matrix of the index layer versus the criterion layer is similarly established.
Figure BDA0002244809900000125
The normalized eigenvector of the computational matrix is:
Figure BDA0002244809900000126
Figure BDA0002244809900000127
then the maximum feature root is calculated, i.e.
Mλ＝λWl (16)
(4) Checking the consistency of the judgment matrix;
the consistency index of the judgment matrix is defined as:
Figure BDA0002244809900000131
wherein λ ismaxIs the maximum characteristic root of the judgment matrix M, and a is the matrix order.
The consistency ratio CR is calculated as:
Figure BDA0002244809900000132
when CR < 0.1, the consistency of the judgment matrix is considered to be acceptable; otherwise, the judgment matrix needs to be modified, and then the consistency check is started again until the judgment matrix meets the consistency judgment condition.
The consistency check of the decision matrix is explained in detail below by a specific example.
The maximum eigenvalue of the judgment matrix of the criterion layer to the target layer is calculated through matlab software simulation: lambda [ alpha ]max3.0940, its consistency index is:
Figure BDA0002244809900000133
wherein n is the matrix order. The random consistency index RI takes a value of 0.58.
The consistency ratio CR is calculated as:
Figure BDA0002244809900000134
the consistency of the decision matrix is considered acceptable.
Similarly, the consistency ratios of the judgment matrix of the judgment index layer to the judgment matrix of the criterion layer are: CR-0.0360, all meeting the consistency requirement.
(5) Calculating device importance
Figure BDA0002244809900000135
Calculating the weight of the relative importance of the index layer to the highest layer (target layer), namely the importance of each device in the index layer
Figure BDA0002244809900000136
Referred to as the overall hierarchical ordering. The sorting is performed layer by layer from the highest level to the lowest level. It should be noted that the reliability indexes of the communication devices on the transmission path have different importance degrees for reliable transmission of the service, and the importance degree of the communication device is set
Figure BDA0002244809900000137
The value can be taken from 0 to 1, which represents the loss caused by the functional failure of the equipment, and the equivalent failure rate lambda of the communication equipment to the system reliabilitye,i'Comprises the following steps:
Figure BDA0002244809900000138
the reliability index of the communication device shown in formula (4) can be obtained finally.
Specifically, after the judgment matrix is normalized, the weight of the relative importance of the index layer to the target layer can be obtained:
Figure BDA0002244809900000141
in the formula, W(P)A weight vector representing the criterion layer to the target layer,
Figure BDA0002244809900000142
a weight matrix representing the index layer relative to the criterion layer, and m is the number of elements of the criterion layer, and the elements in the obtained comprehensive weight are the importance of each device to the communication service, as shown in table 3.
Table 3: importance of communication device
Figure BDA0002244809900000143
In practical analysis, if the error rate of the transmitted data is low, the error rate can be described by using poisson distribution, and for simplifying calculation, the error rate of a communication link is assumed, and D is 1E-9.
The reliability data of the main communication devices and communication links in the information network, based on the above analysis of the reliability indicators of the communication devices and communication links and the data provided by the manufacturer, is shown in table 4.
Table 4: reliability data of communication device and communication link
Figure BDA0002244809900000144
Step S3: and determining the interaction influence index of the primary power system and the information network according to the interaction between the primary power system and the information network.
Specifically, the interaction between the primary power system and the information network is carried by the information service, and therefore, the interaction index can be quantified by determining the reliability value of the information service. In order to quantitatively analyze the interaction effect between the primary power system and the information network, firstly, a data stream transmission path between the information network and the primary power system needs to be determined, and then, an overall reliability value of an information service is determined according to reliability indexes of all steps in the data stream transmission process, so that the interaction effect index between the primary power system and the information network is obtained.
In one embodiment, step S3 specifically includes:
step S3.1: determining a transmission path of data flow between an information network and a power primary system;
step S3.2: calculating the reliability index of each data stream;
step S3.3: and obtaining the interactive influence index of the primary power system and the information network according to the reliability index of each data stream.
Specifically, as shown in fig. 5, a schematic diagram of interaction between the intelligent substation power primary system and the information network is shown. The information network mainly controls the state of the circuit breaker, the control process is realized by uploading SAV messages and downloading GOOSE messages, and the failure of information service transmission can cause the circuit breaker to be refused or mistakenly operated, so that the primary power system fails. The influence of the primary power system of the intelligent substation on the information network is mainly caused by power grid disturbance and space electromagnetic radiation, and the influence is generated on the information side through the measurement system. Disturbance or fault of a physical power grid can generate high-frequency transient signal components, and due to the limited bandwidth spectrum characteristic of the mutual inductor, the high-frequency transient components cannot be correctly sensed, so that the accuracy of a measuring system and the acquisition of state characteristics of the power grid can be influenced, and correct judgment and decision can be given by an information side; in addition, the normal work of the power supply of the power secondary system is influenced by the overlarge disturbance amplitude of the power grid, so that the correct processing of monitoring information and the sending and correct execution of control commands are influenced; in the transformer substation, electromagnetic interference can be generated by opening and closing operations of a circuit breaker or an isolating switch, insulation breakdown in a high-voltage loop or discharge of a lightning arrester and a spark gap, a power frequency electric field and a power frequency magnetic field generated when high-voltage equipment operates, transformer faults and the like, and the electromagnetic interference can cause measurement information distortion and information transmission errors and can cause electronic equipment faults when the electromagnetic interference is serious. In the sensing, processing and transmission processes, the measurement information which is influenced by the factors listed above and generates errors cannot timely and accurately reflect the operation state of the physical side, so that the control deviation of the information side to the physical side is caused, the misoperation or the rejection of the circuit breaker is caused, the operation of the physical side is influenced, and further, the interactive influence is formed.
In one embodiment, step S3.2 is to calculate the reliability index of the data stream according to equation (5):
Figure BDA0002244809900000161
in the formula (5), R [ L (i ', j')]Representing a message transmission reliability index, Ac,i'Indicating the communication node, B, through which the message transmission path passesc,kRepresenting the communication link through which the message transmission path passes.
Specifically, according to the information service transmission process of the intelligent substation, a transmission path set L is definedi'-j'Representing the node through which a certain message passes from node i 'to node j'; as shown in fig. 6, according to the transmission process of the information service of the intelligent substation, the initial node and the final node of the GOOSE packet and the SAV packet can be determined, but the propagation path of the packet cannot be visually represented, so that a transmission path set L is definedi'-j'Indicating the node through which a message passes from communication node i 'to communication node j'.
Wherein, the device names corresponding to the nodes in fig. 6 are shown in table 5:
table 5: device name table corresponding to node (see figure 6)
Figure BDA0002244809900000162
The source and destination nodes of the information flow in fig. 6 are shown in table 6:
table 6: source and destination nodes of information flow
Figure BDA0002244809900000163
The information stream transmission path in FIG. 6 is shown in Table 7
Table 7: information stream transmission path
Figure BDA0002244809900000171
Because each node and branch in each message transmission path belong to a serial form, when reliability evaluation is performed on each message, the reliability index can be calculated by the formula (5).
In an embodiment, the transmission path of the data stream includes an SAV message transmission path and a GOOSE message transmission path, and step S3.3 specifically includes:
according to the SAV message transmission reliability index and the GOOSE message transmission reliability index, calculating an interaction influence index R of the primary power system and the information networkp(Ap,i')'：
Rp(Ap,i')'＝Rp(Ap,i')Rg[L(i',j')]Rs[L(i',j')] (6)
Wherein R isp(Ap,i') Representing a reliability index, R, representing a reliability index of a primary electric power installation in an electric primary system interacting with an information networks[L(i',j')]Representing a corresponding SAV message transmission reliability index, Rg[L(i',j')]And expressing the GOOSE message transmission reliability index.
Specifically, the main influence of the information network on the primary power system is the control of the state of the circuit breaker in the primary power system by the trip message, and the reliability of message propagation represents the reliability of the action of the information network on the primary power system, so that the reliability index of the circuit breaker interacting with the information network in the primary power system is shown in formula (6) in consideration of the influence factor of the information network, and in the present embodiment, the primary power equipment is the circuit breaker.
In one embodiment, the method further comprises: optimizing SAV message transmission reliability index by adopting measurement information deviation rate, and further optimizing interaction influence index R of primary power system and information networkp(Ap,i') Optimizing to obtain optimized interactive influence index, wherein the optimized SAV message transmission reliability index is Rs[L(i',j')]'：
Rs[L(i',j')]'＝(1-ξr)Rs[L(i',j')] (7)
Wherein ξrThe deviation rate of the measurement information is represented and used for representing the deviation occurrence probability of the measurement information transmitted to the merging unit and the original measurement information;
the optimized interactive influence index is Rp(Ap,i')”：
Rp(Ap,i')”＝Rp(Ap,i')Rg[L(i',j')]Rs[L(i',j')]' (8)
Wherein R iss[L(i',j')]' is calculated by equation (7).
Specifically, the influence of the primary power system on the information network is mainly realized by measuring information and transmitting the information. Electronic transformer faults will cause measurement information deviation and lag, and thus SAV message information deviation and uploading lag. Therefore, the invention adopts the formula (7) to analyze the reliability index of the SAV message, thereby optimizing the transmission reliability index of the SAV message.
The reliability of the trip message transmission is reduced due to the reduction of the uploading reliability of the SAV message, so that the control function of the information network on the circuit breaker is invalid. Therefore, the influence of the primary power system on the communication system is considered, and the influence result is finally reflected in the primary power system.
In summary, after the interaction between the primary power system and the information network is considered, the reliability index of the breaker node interacting with the information network in the primary power system of the intelligent substation is shown in formula (8).
Step S4: and according to the reliability index of the primary power system, the reliability index of the information network and the interaction influence index of the primary power system and the information network, reliability evaluation is carried out on the intelligent substation.
Specifically, after the reliability index of the primary power system, the reliability index of the information network and the interaction influence index of the primary power system and the information network are obtained, the reliability of the intelligent substation can be evaluated according to the indexes.
In one embodiment, step S4 specifically includes: and taking the reliability index of the primary power system, the reliability index of the information network and the interaction influence index of the primary power system and the information network as input, and adopting a Monte Carlo simulation method to carry out reliability evaluation on the intelligent substation.
Specifically, the monte carlo simulation method is used in the present embodiment, and other methods may be used in other embodiments. As shown in fig. 2, an overall flowchart of the simulation performed by the monte carlo simulation method in step S4 is shown, where the reliability index of the intelligent substation is the reliability index of the primary power system and the reliability index of the information network, and step 3 may also obtain the interaction influence index of the primary power system and the information network by quantitatively analyzing the interaction influence of the primary power system and the information network of the intelligent substation.
In a specific implementation process, the condition that the intelligent substation normally works is set to be that outlet loads can normally supply power. Based on an electrical main wiring diagram of a transformer substation, a minimum path set for normal power supply of a load is established. And analyzing according to the minimum path set of the normal power supply of the electrical main wiring, and if any one equipment operation state in the minimum path set fails, the path fails. Fig. 8 is a diagram of a minimum road set of the electrical main wiring of the intelligent substation.
The invention uses the normal working probability P of the main wiringsThe reliability evaluation index is also called as the availability or power supply reliability of the main wiring as the target reliability evaluation index of the intelligent substation.
Figure BDA0002244809900000191
In the formula (20), S is a set of all operation states of the system; p is a radical ofiIs the probability that the system is in reliable operating state i.
Reliability assessment is carried out on the intelligent substation based on the Monte Carlo method, and after the interaction between the primary power system and the information network is considered in the intelligent substation, the reliability indexes of all devices and branches on the primary power system side are determined by a set Rp(Ap,i) And Rp[Bp(i,j)]Obtaining the reliability indexes of the equipment and the transmission line on the primary side of the electric power after the interaction between the primary system of the electric power and the information network is considered and inputting the data such as the structure of the electric power system according to the reliability indexes of the equipment and the transmission line on the primary system of the electric power of the intelligent substation,
taking D2-1 electrical main wiring diagram of FIG. 6 as an example, a minimum path set for normal power supply of each load point is established, the minimum path set is shown in FIG. 8, and the normal working probability P of the main wiring is taken assThe method is used as an intelligent substation reliability evaluation index. Fig. 9 shows a reliability evaluation flow, and the specific evaluation steps are as follows.
(1) Determining the operation conditions of each device and branch of the primary power network of the intelligent substation based on the non-sequential Monte Carlo sampling process;
(2) analyzing the topological structure of the electric main wiring network of the intelligent substation, solving the minimum path set of each load point, and judging whether the system works normally according to the power supply state of the load point;
(3) counting the evaluation result (wherein the evaluation result is failure or no failure), and calculating the corresponding target reliability index P according to the frequency of the abnormal operation state (failure) of the systems，
(4) Judgment of PsWhether the variance coefficient of (1) meets the sampling precision or not, and if not, repeating the steps 1) to 3); if yes, outputting the corresponding target reliability index Ps。
In the specific implementation process, the calculation process of the variance coefficient of the sample index in (3) is as follows:
defining U as the system's unavailability, xiVariables randomly drawn for system states at 0-1:
Figure BDA0002244809900000192
a. the estimated value of U can be found from the mean of the sampled values:
Figure BDA0002244809900000201
where N is the number of system state samples.
b: the sample variance is:
Figure BDA0002244809900000202
c: sample mean variance:
Figure BDA0002244809900000203
d: the coefficient of variance β for the sample is:
Figure BDA0002244809900000204
in order to research the influence of the interaction influence of the information network and the primary power system on the reliability evaluation result of the intelligent substation, the following three scenes are contrastively analyzed:
scene 1: considering that an information network is completely reliable and has good communication performance, and reliability evaluation is independently performed on a primary power system of the intelligent substation;
scene 2: considering that the measured information of the primary power system is normally input, and considering the reliability evaluation of the intelligent substation under the control influence of an information network on the primary power system;
scene 3: reliability evaluation of the intelligent substation under the interaction influence of the information-physical system is considered; the following table 8 was obtained according to the monte carlo simulation method:
table 8: reliability evaluation result
Figure BDA0002244809900000205
The table shows that the reliability evaluation results of the three types are reduced in sequence and are consistent with the actual situation.
Generally, the evaluation method provided by the invention has the following advantages or beneficial technical effects:
1. an information physical model of the intelligent substation is constructed, and the model can truly reflect the system structure of the intelligent substation;
2. reliability indexes of the intelligent substation communication equipment are analyzed based on an analytic hierarchy process, and actual operation conditions are better met;
3. the interaction influence of the primary power system and the information network of the intelligent substation is quantitatively analyzed according to the transmission process of the information service, and the analysis result is accurate and reliable;
4. based on a Monte Carlo simulation method, the interaction between the primary power system and the information network is considered, the reliability evaluation method of the intelligent substation is provided, and the evaluation result is more in line with the actual operation condition.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made in the embodiments of the present invention without departing from the spirit or scope of the embodiments of the invention. Thus, if such modifications and variations of the embodiments of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to encompass such modifications and variations.

Claims (8)

1. An intelligent substation reliability assessment method based on an information physical fusion model is characterized by comprising the following steps:
step S1: constructing an information physical fusion model of the intelligent substation, wherein the information physical fusion model comprises a power primary system and an information network;
step S2: determining the reliability index of the primary power system and the reliability index of the information network;
step S3: determining an interaction influence index of the primary power system and the information network according to the interaction between the primary power system and the information network;
step S4: according to the reliability index of the primary power system, the reliability index of the information network and the interaction influence index of the primary power system and the information network, reliability evaluation is carried out on the intelligent substation;
wherein, the primary power system includes primary power devices and a power transmission line, the information network includes a communication link and a communication device, and step S2 specifically includes:
step S2.1: determining the reliability index of the primary power system according to the availability of the primary power equipment and the availability of the power transmission line;
step S2.2: determining a reliability index of the information network according to the availability of the communication link, the reliability of the transmission data, the availability of the communication equipment and the importance of the communication equipment to the transmission of the communication service;
step S2.2 specifically includes:
step S2.2.1: determining a reliability index R of the communication link according to the availability of the communication link and the credibility of the transmission datac(Bc,k)：
Rc(Bc,k)＝Rc[Bc(i',j')]＝Ai',j'·(1-D) (3)
Where k denotes the kth communication link, Rc[Bc(i',j')]Representing a slave communication device Ac,i'To communication device Ac,j'Branch B ofc(i ', j'); subscript c denotes an information side, i 'and j' denote numbers of communication devices;d represents the error rate of the transmitted data in the communication link, Ai',j'Which indicates the availability of the link or links,
Figure FDA0003235376570000011
λi',j'and ui',j'Respectively representing communication links Bc(i ', j') failure rate, repair rate, MTBR and MTBF respectively representing communication link Bc(i ', j') an average repair interval time and an average fault interval time;
step S2.2.2: determining the reliability index R of the communication equipment according to the availability of the communication equipment and the importance of the communication equipment to the communication service transmissionc(Ac,i')：
Figure FDA0003235376570000021
Wherein λ ise,i'Representing the equivalent failure rate of the communication device to the system reliability,
Figure FDA0003235376570000025
the method is used for representing the importance of communication equipment to communication service transmission and is determined by adopting an analytic hierarchy process
Figure FDA0003235376570000022
Value of (A)i'Is the failure rate of the communication device; u. ofi'I' represents the number of the communication device as the repair rate of the communication device;
step S2.2.3: and taking the reliability index of the communication link and the reliability index of the communication equipment as the reliability index of the information network.
2. The method according to claim 1, wherein step S1 specifically comprises:
step S1.1: for the primary power system, a first network model with the power transmission line as a branch and the power equipment as a node is established;
step S1.2: establishing a second network model with a communication link as a branch and communication equipment as a node in the information network;
step S1.3: and constructing an information physical fusion model of the intelligent substation based on the constructed first network model, the constructed second network model and the interaction between the power equipment in the primary power system and the communication equipment in the information network.
3. The method according to claim 1, characterized in that step S2.1 comprises in particular:
step S2.1.1: determining a reliability index R of the primary electric power equipment according to the availability of the primary electric power equipmentp(Ap,i)：
Figure FDA0003235376570000023
Wherein λ isiIndicating an electric primary appliance Ap,iFailure rate of uiFor powering primary equipment Ap,iThe repair rate of (1), MTBR, represents the power primary equipment Ap,iMean time between repairs, MTBF stands for power primary ap,iMean time between failures of (1);
step S2.1.2: determining the reliability index R of the transmission line according to the availability of the transmission linep[Bp(i,j)]：
Figure FDA0003235376570000024
In the formula (2), Rp[Bp(i,j)]Representing a slave power primary appliance Ap,iTo the electric primary equipment Ap,jTransmission line Bp(i, j) reliability index, λi,jIs the failure rate of the transmission line, ui,jThe repair rate of the transmission line; subscript p represents the grid side, i and j represent the numbers of the electric primary devices;
step S2.1.3: and taking the reliability index of the primary power equipment and the reliability index of the power transmission line as the reliability index of the primary power system.
4. The method according to claim 1, wherein step S3 specifically comprises:
step S3.1: determining a transmission path of data flow between an information network and a power primary system;
step S3.2: calculating the reliability index of each data stream;
step S3.3: and obtaining the interactive influence index of the primary power system and the information network according to the reliability index of each data stream.
5. The method according to claim 4, characterized in that step S3.2 is embodied to calculate the reliability index of the data stream according to equation (5):
R[L(i',j')]＝f(Ac，1,Ac，2,...,Ac,i',Bc,1,Bc,2,...,Bc,k)
＝Rc(Ac,1)Rc(Ac,2)...Rc(Ac,i')·Rc(Bc,1)Rc(Bc,2)...Rc(Bc,k) (5)
in the formula (5), R [ L (i ', j')]Representing a data stream transmission reliability index, Ac,i'Representing the communication node, B, through which the data stream transmission path passesc,kRepresenting the communication link through which the data stream transmission path passes.
6. The method according to claim 4, wherein the transmission path of the data stream includes an SAV message transmission path and a GOOSE message transmission path, and step S3.3 specifically includes:
according to the SAV message transmission reliability index and the GOOSE message transmission reliability index, calculating an interaction influence index R of the primary power system and the information networkp(Ap,i')'：
Rp(Ap,i')'＝Rp(Ap,i')Rg[L(i',j')]Rs[L(i',j')] (6)
Wherein R isp(Ap,i') Representing an index of reliability, R, of primary electric devices in an electric primary system interacting with an information networks[L(i',j')]Representing a corresponding SAV message transmission reliability index, Rg[L(i',j')]And expressing the GOOSE message transmission reliability index.
7. The method of claim 6, wherein the method further comprises: optimizing SAV message transmission reliability index by adopting measurement information deviation rate, and further optimizing interaction influence index R of primary power system and information networkp(Ap,i') Optimizing to obtain optimized interactive influence index, wherein the optimized SAV message transmission reliability index is Rs[L(i',j')]'：
Rs[L(i',j')]'＝(1-ξr)Rs[L(i',j')] (7)
Wherein ξrThe deviation rate of the measurement information is represented and used for representing the deviation occurrence probability of the measurement information transmitted to the merging unit and the original measurement information;
the optimized interactive influence index is Rp(Ap,i')”：
Rp(Ap,i')”＝Rp(Ap,i')Rg[L(i',j')]Rs[L(i',j')]' (8)
Wherein R iss[L(i',j')]' is calculated by equation (7).
8. The method according to claim 1, wherein step S4 specifically comprises: and taking the reliability index of the primary power system, the reliability index of the information network and the interaction influence index of the primary power system and the information network as input, and adopting a Monte Carlo simulation method to carry out reliability evaluation on the intelligent substation.
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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013023178A1 (en) * 2011-08-11 2013-02-14 The Trustees Of Columbia University In The City Of New York Adaptive stochastic controller for dynamic treatment of cyber-physical systems
CN106329518A (en) * 2016-09-06 2017-01-11 中国科学院信息工程研究所 Grid CPS (cyber-physical system) interactive modeling method

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013023178A1 (en) * 2011-08-11 2013-02-14 The Trustees Of Columbia University In The City Of New York Adaptive stochastic controller for dynamic treatment of cyber-physical systems
CN106329518A (en) * 2016-09-06 2017-01-11 中国科学院信息工程研究所 Grid CPS (cyber-physical system) interactive modeling method

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
Reliability Modeling and Analysis of IEC61850 Based Substation Protection Systems;Hangtian Lei等;《IEEE Transactions on smart grid》;20140930;第5卷(第5期);2195-2201 *
基于信息物理接口矩阵的IEC61850变电站自动化系统可靠性分析;李勇等;《电力自动化设备》;20190131;第39卷(第1期);84-88 *
配电网信息物理系统可靠性评估关键技术探讨;蒋卓臻等;《电力自动化设备》;20171231;第37卷(第12期);30-42 *

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