CN115034060B

CN115034060B - Information physical system physical domain and network domain integrated coupling modeling method and device

Info

Publication number: CN115034060B
Application number: CN202210635058.8A
Authority: CN
Inventors: 李建科; 孙国强; 韩海腾; 陈静静; 罗珊; 黄蔓云; 臧海祥; 徐其威
Original assignee: Hohai University HHU; Army Engineering University of PLA
Current assignee: Hohai University HHU; Army Engineering University of PLA
Priority date: 2022-06-07
Filing date: 2022-06-07
Publication date: 2023-04-28
Anticipated expiration: 2042-06-07
Also published as: CN115034060A

Abstract

The invention discloses an information physical system physical domain and network domain integrated coupling modeling method and device, wherein the method divides a power grid information physical system into a network domain and a physical domain according to coupling logic, and specifically comprises the following steps: step 1: dividing a power system into a physical domain and a network domain, and firstly establishing a physical domain model comprising physical entity layer modeling and physical domain system modeling; step 2: establishing a network domain model comprising network domain element modeling and network domain system modeling, wherein the network domain system modeling covers communication network modeling and protection measurement and control network modeling; step 3: and (3) establishing an information system layer network model, and establishing an integrated coupling model by combining the physical domain model in the step (1) and the network domain model in the step (2). Based on the information physical system physical domain and network domain integrated coupling modeling method, a complex information physical system, such as a power system, can be finely described, and the stable operation meaning of the analysis information physical system is significant.

Description

Information physical system physical domain and network domain integrated coupling modeling method and device

Technical Field

The invention belongs to the field of power system information physical systems, and particularly relates to a physical domain and network domain integrated coupling modeling method and device.

Background

The concept of the information physical system (Cyber Physical System, CPS) was first elucidated as: "monitoring, control, integrated physical, biological and engineering systems implemented by a computing core: computing is embedded deep into each interconnected physical component or material; the computing core is an embedded system which needs real-time response; its behavior is an integrated fusion process of logical computation and physical behavior.

The concept of an information physical system is applied to the power industry, and a physical layer is a power network and comprises power primary equipment such as a generator, a load, a circuit breaker, a power transmission line and the like; the information layer is an electric power information network, and comprises various monitoring devices, control devices, computing devices, communication network devices and other electric power secondary devices and information transmission devices in the operation process, the monitoring devices (intelligent sensors, intelligent electric meters, remote measurement and control units and the like) of the electric power information network transmit operation state information (voltage, current, power, frequency and the like) of the electric power network to computing servers of all levels of regulation and control centers through the communication network, the servers generate reasonable control strategies according to the operation working conditions of the current system and instructions of a dispatcher, and send control instructions to all equipment terminals through the communication network again, and the equipment terminals execute corresponding operations according to the operation state information. The interconnection mode of the power information network and the power system is a hierarchical mode, namely, data is transmitted to a transformer substation through secondary equipment (such as a sensor) arranged on the primary power equipment, and the transformer substation is communicated with the layer of dispatching center after collecting and integrating the data, and uploads terminal data or downloads control signals. The main equipment of the power grid terminal layer comprises a generator set, a transformer substation and a circuit breaker; the main equipment of the dispatching center layer is a front-end processor system and a host computer system; the measurement and control equipment mainly comprises sensors (such as a current sensor and a voltage sensor), a remote measurement and control unit (RTU), a power Distribution Terminal Unit (DTU), a Feeder Terminal Unit (FTU) and a Distributed Control System (DCS); the data communication protocol comprises a transformer station data communication protocol, a telecontrol communication protocol, a computer data communication protocol and the like; the communication method mainly comprises optical fiber communication, power line carrier communication, wireless communication and the like.

Disclosure of Invention

The invention aims to overcome the defects in the prior art and provides an information physical system physical domain and network domain integrated coupling modeling method, which utilizes an association characteristic matrix to analyze the coupling relation between a physical domain and a network domain, establishes a power grid information physical system static model from the angle of a complex network, and establishes an information layer dynamic operation model and a physical layer dynamic operation model from the angles of information layer data transmission and physical layer electric energy transmission.

In order to achieve the above purpose, the invention is realized by adopting the following technical scheme:

in a first aspect, the present invention provides an information physical system physical domain and network domain integrated coupling modeling method, including the following steps:

step 1: establishing a physical domain model, including physical entity layer modeling and physical domain system modeling;

step 2: establishing a network domain model, comprising network domain element modeling and network domain system modeling, covering communication network modeling and protection measurement and control network modeling;

step 3: and establishing an information system layer network model and an integrated coupling model.

Further, the method for modeling the physical entity layer network model comprises the following steps:

(1) Power supply side element model

And (3) a generator: the generator model is described by a fourth-order differential equation in a local d-q coordinate system:

Wherein i is the number of the generator node; delta is the corner; omega, omega ₀ Rotor speed and rated rotor speed respectively; e (E) _fd Is the internal magnetic field voltage; e, e _q 、e _d Terminal voltages of q axis and d axis respectively; e' _q 、e′ _d Transient voltages of q-axis and d-axis respectively; i.e _q 、i _d Currents of q-axis and d-axis, respectively; k (K) _D Is a damping coefficient; t (T) _m 、T _e Respectively isMechanical torque and electrical air gap torque; t'. _q0 、T′ _d0 Is an open circuit time constant; x is x _q 、x _d Synchronous reactance of q axis and d axis respectively; x's' _q 、x′ _d The transient reactance of the q-axis and d-axis, respectively.

And (2) a photovoltaic cell: the device consists of a series-parallel resistor, a diode and a photo-generated current source. I _ph For generating current, R _s Is equivalent resistance in series, R _sh Is a shunt resistor. The output voltage and current relationship of the photovoltaic array is as follows:

wherein A is the ideal factor of the diode; boltzmann constant k=1.38×10 ^-23 J/K; the charge quantity q=1.6×10 of electrons ^-19 C, performing operation; θ is temperature; r is R _sh And R is _s Are parallel and series resistances.

(2) Branch side element model

The power line: the power line generally adopts a pi-type equivalent circuit model, and the total impedance of the line is assumed to be Z, and the total admittance is assumed to be Y. The kirchhoff voltage-current law can be obtained by:

the current transfer formula can thus be derived:

a transformer: by constructing a transformer equivalent model, the method can be obtained according to kirchhoff's law:

From this, the current transfer formula can be obtained:

phase shifter: from the phase shifter equivalent circuit model, it is possible to obtain:

from this, the current transfer formula can be obtained:

the admittance model is therefore:

(3) Load side element model

RL series load: in performing power system calculations and analyses, the general nature of the load group as presented to the external system is of general concern, and thus an overall load model needs to be built. Among various loads, a load circuit in which RL is connected in series is most common. According to the alternating current circuit theory, a static model of the load can be obtained:

with current as a state variable, the dynamic model of the load is as follows:

asynchronous motor load: the asynchronous motor occupies a large specific gravity in the load and is the most important dynamic component in the load, so that the establishment of a mathematical model of the asynchronous motor is particularly important.

In a general power system calculation procedure, a mechanical transient model is generally adopted:

g in _Σ Is the conductance looking into the motor port. Slip s= (ω) _s -ω _r )/ω _s ＝1-ω _r /f。

The state equation of the mechanical transient model is first order, i.e. only the rotor motion equation is considered:

the electromagnetic torque and the mechanical torque are respectively:

T _M ＝T′ _M0 [(1-s)f] ^β

in the method, in the process of the invention,

f is the port voltage, current and frequency, respectively; omega _r The rotor speed; r is R _s Is a stator resistor; x, X' are steady-state and transient reactance, respectively; t'. _d0 、T _J Respectively a rotor winding time constant and an inertia time constant; t (T) _E 、T _M Electromagnetic torque and mechanical torque, respectively; beta is a mechanical torque coefficient, and each of the above amounts is a per unit value.

Further, the method for modeling the physical domain system model comprises the following steps:

(1) Power grid topology modeling

In the physical domain, the system topology of the power network may be described by a node admittance matrix. The order of the node admittance matrix is equivalent to the number of individual nodes of the network. Its diagonal element (self admittance) Y _ii For each connected with node iSum of branch admittances, off-diagonal element (transadmittance) Y _ij For branch admittance y between node i and node j _ij Negative values of (a). From this, the calculation formula of the node admittance matrix self admittance and the mutual admittance can be obtained:

Y _ij ＝Y _ji ＝-y _ij

wherein y is _i0 Admittance to ground for node i; y is _ij Is the branch admittance between node i and node j. The node admittance matrix Y of the n-node system is:

(2) Power grid energy flow modeling

The energy flow distribution is physical power grid power flow distribution, shows instantaneous balance of power in the system, and can be described by a node voltage equation and a node power equation. Node voltage equation: node voltage equations are used in power system flow calculation to reflect the relationship between node voltages and node injection currents in the system.

Let the voltages at nodes i and j be represented as

And->

Admittance of line i-j is denoted y _ij The current I flowing from node I to node j in this line _ij Can be expressed as:

assuming that there are n nodes directly connected to node i, there are based on kirchhoff's current law:

in the method, in the process of the invention,

-y _ij ＝Y _ij therefore, the above formula can be written as +.>

The node voltage equation is in matrix form:

node power equation: in power system flow calculations, the node injection power of the load and generator is generally known and is not affected by the node terminal voltage. Thus, in the case where the node injection power is unchanged, the node injection current is changed with the change of the node voltage, and then the node injection power equation can be expressed as:

wherein the method comprises the steps of

For the complex power of the node, I ^* Indicating current +.>

Is a conjugate of (c). By letting Y _ij ＝G _ij +jB _ij ，/>

The above can be expanded in polar coordinates:

in θ _ij ＝θ _i -θ _j Is the phase angle difference at the head end and the tail end of the branch i-j. The sum of active power under polar coordinates can be obtained after finishingEquation for reactive power:

further, the method of modeling a network domain element includes:

(1) Protection measurement and control node modeling

Modeling of the protection measurement and control node needs to reflect the influence of the protection measurement and control node on the power grid, namely, the characteristics of two aspects can be reflected: the function relation (information processing function) of information input and output, and the information processing performance in the information processing and transmission process.

The functional characteristics of the protection measurement and control node are described by adopting a plurality of groups, and the formula is as follows:

S _ii ＝[F _ii (a _input ),P _ii (F _ii ),…]

wherein F is _ii (a _input ) P is an information processing algorithm _ii (F _ii ) The correct probability is processed for the information.

(2) Communication network element modeling

Communication node: we abstract the state quantities in physical and information systems collectively as "communication nodes," which include measured values, system state quantities, control instructions, etc.

Communication branch: we abstract the path of data transmission in a communication network as a "communication branch" (cyberbranch), whose head and end nodes are respectively input and output data, and whose branch characteristic equation is a mapping operator between input and output.

The communication nodes and communication branches need to be able to describe information processing capabilities. Meanwhile, different communication performances have different expression forms due to different analysis requirements of the power grid, for example, when the influence of communication interruption on the real-time operation of the CPS of the power grid is analyzed, the communication interruption can be represented by a 0-1 state to show whether the interruption occurs. However, when analyzing the effect of a communication outage on the reliability of the power grid CPS, the communication outage needs to be described as a communication outage probability or a communication reliability. Therefore, the communication performance of the communication branch is described by adopting a multi-element group, and elements in the multi-element group can be expanded according to the CPS application requirements of the power grid. A multi-tuple of the formula:

C _ij ＝[P _B,ij ,P _M,ij ,…]

Wherein P is _B,ij ，P _M,ij The interrupt probability and the information transmission correct probability between the i node and the j node are respectively represented.

(3) Information network element modeling

Information node: the information network is a virtual network formed by abstracting functions of different power control applications, and nodes in the information network represent information functions such as state estimation, voltage control, safety and stability control and the like. The functional unit of the control application of the information system takes the information processing result of the protection measurement and control layer as information input, and generates related instructions according to the information input. Through this process, the information layer and the information physical coupling layer are tightly coupled.

Information hub: in the control system, the data output of some modules is gathered into a total information pool, which is used as the data source of other modules. Such modules are defined as "information hubs". An information hub is a virtual node that exists at the interface location of the communication network and the information network and does not correspond to any information function in the actual system. But it is two network data interfaces, so that each module is mutually coupled through information interaction to form a complete network domain. For example, all measurements within a substation may be integrated at a substation level control center, where only a portion of the data may be uploaded to the overall control center.

Further, the modeling method of the network domain system model comprises the following steps:

(1) Communication network modeling

Based on the communication network element model mentioned in the previous section, a communication network comprising m communication nodes is modeled. The topology and the characteristics of the communication network are expressed by adopting a communication network adjacency matrix C, and the structural definition of the matrix C is shown as the formula:

wherein C is _ij ＝[T _ij ,P _B,ij ,P _M,ij ]If i=j, ij represents a communication node, and if i+.j, ij represents a communication branch. C when there is no direct connection between communication node i and node j _ij ＝[0,0,0]。

(2) Modeling a protection measurement and control node network:

based on the protection measurement and control model provided in the previous section, modeling is carried out on a protection measurement and control network comprising k protection measurement and control nodes. Because there is no coupling relation between pure protection measurement and control, the incidence matrix diag (S) forming the protection measurement and control node network model is a diagonal matrix:

the diagonal elements of the matrix are multiple groups of protection measurement and control nodes, and the protection measurement and control network communication network adjacent matrix S can be completed by matching with a communication network.

(3) Protection measurement and control communication network modeling

Protection measurement and control-communication gateway joint modeling: the protection measurement and control network is a control network based on a communication network, so that a protection measurement and control network model must be established based on the communication network model. The association between the protection measurement and control network and the communication network is modeled. And describing the information collection uploading process by adopting a protection measurement and control-communication network incidence matrix S-C, and corresponding to the incidence relation (measurement system) between the information collection protection measurement and control node and the communication node. C-S is used for describing the instruction issuing process, and the association relation (relay protection system) between the corresponding communication node and the execution operation protection measurement and control is adopted. The two are not necessarily completely symmetrical matrixes, but the modeling mode is similar, taking S-C as an example, and the structure is defined as follows:

Using extensible tuples S-C _ij ＝[S-C _TP,ij ,S-C _T,ij ,S-C _PB,ij ,…]To describe the association relationship between the communication node and the protection measurement and control layer node, S-C _TP,ij ，S-C _T,ij ，S-C _PB,ij And respectively representing whether the communication node i and the protection measurement and control node j are directly connected, the transmission interruption probability and the information transmission accuracy.

Modeling a protection measurement and control communication network: for a protection measurement and control network comprising k protection measurement and control nodes, a protection measurement and control communication network adjacent matrix S is adopted to describe the topology and characteristics of the protection measurement and control network, and the structure of the matrix S is defined as follows:

wherein S is _ij ＝[F(a _input ),T _ij ,P _B,ij ,…]If i=j, ij represents a protection measurement and control node, and if i+.j, ij represents a protection measurement and control channel. When the protection measurement and control node i and the node j are logically and directly connected (direct information exchange), S _ij The performance of the protection measurement and control channel is represented by a protection measurement and control node network model (diag (S)), a protection measurement and control-communication network association model (S-C or C-S) and a communication network model (C) through a certain hybrid calculation algorithm. S is carried out when no logic direct connection exists between the protection measurement and control node i and the node j _ij ＝[0,0,0]。

Further, step 3 comprises the following:

and establishing a physical-protection measurement and control associated characteristic matrix (P-S or S-P) and a protection measurement and control-information associated characteristic matrix (S-I or I-S) which are respectively used for describing the association relation between the information physical coupling network and the physical entity layer and the information layer, so that the physical entity layer, the information physical coupling layer and the information system layer are communicated to form a complete network domain and a physical domain layered coupling model. And establishing the following association characteristic matrix for a power grid CPS network comprising n physical nodes, m communication nodes, k protection measurement and control nodes and l information application nodes.

Physical-protection measurement and control correlation characteristic matrix (P-S): the matrix is an n multiplied by k order matrix, and matrix elements represent the association relationship between physical entities and a protection measurement and control network in the information acquisition process. The physical-protection measurement and control correlation characteristic matrix (P-S) is defined as follows:

using scalable multi-element P-S _ij ＝[P-S _TP,ij ,P-S _PB,ij ,…]To describe the association relationship between the physical node and the protection measurement and control layer node, P-S _TP,ij The topological association relationship between the physical node i and the protection measurement and control node j can be represented by 0-1; P-S _PB,ij Indicating the reliability of the interaction, such as the probability of the control command executing correctly. If no direct interaction relation exists between the protection measurement and control node and the physical node, the element at the corresponding position is 0.

Protection measurement and control-physical association characteristic matrix (S-P): the matrix is a k multiplied by n order matrix, and matrix elements represent the association relation between the protection measurement and control network and the physical entity in the command execution process. The definition process of the protection measurement and control-physical association characteristic matrix (S-P) is as follows:

using scalable tuples S-P _ij ＝[S-P _TP,ij ,S-P _PB,ij ,…]To describe the association relationship between the communication node and the protection measurement and control layer node, S-P _TP,ij The topological association relationship between the physical node i and the protection measurement and control node j can be represented by 0-1; S-P _PB,ij Indicating the reliability of the interaction, such as the probability of the control command executing correctly. If no direct interaction relation exists between the protection measurement and control node and the physical node, the element at the corresponding position is 0.

Protection measurement and control-information association characteristic matrix (S-I): the matrix is a k multiplied by l order matrix, matrix elements represent the characteristics of a decision unit for uploading real-time analysis results to an information system layer by protection measurement and control, and mainly describe the association relationship between a protection measurement and control network and the information layer in the process of inputting information into the decision unit.

By expanding the tuples S-I _ij ＝[S-I _TP,ij ,S-I _PB,ij ,…]To describe the association relationship between the communication node and the protection measurement and control layer node, S-I _TP,ij The topological association relationship between the physical node i and the protection measurement and control node j can be represented by 0-1; S-I _PB,ij Indicating the reliability of the interaction, such as the probability of the control command executing correctly. If no direct interaction relation exists between the protection measurement and control node and the physical node, the element at the corresponding position is 0.

Information-protection measurement and control correlation characteristic matrix (I-S): the matrix is an l multiplied by k order matrix, matrix elements represent the characteristic that a decision unit issues a control instruction to the protection measurement and control equipment, and mainly describe the incidence relation between the information system layer and the protection measurement and control network and the information system layer in the issuing process when the information system layer applies the control instruction.

With extended tuples I-S _ij ＝[I-S _TP,ij ,I-S _PB,ij ,…]To describe the association relationship between the communication node and the protection measurement and control layer node, I-S _TP,ij The topological association relationship between the physical node i and the protection measurement and control node j can be represented by 0-1; I-S _PB,ij Indicating the reliability of the interaction, such as the probability of the control command executing correctly. If no direct interaction relation exists between the protection measurement and control node and the physical node, the element at the corresponding position is 0.

In a second aspect, the present invention provides an information physical system physical domain and network domain integrated coupling modeling apparatus, the apparatus comprising:

physical domain modeling module: the method is used for establishing a physical domain model and comprises physical entity layer modeling and physical domain system modeling;

network domain modeling module: the network domain modeling method comprises the steps of establishing a network domain model, including network domain element modeling and network domain system modeling, covering communication network modeling and protection measurement and control network modeling;

and the integrated modeling module is as follows: the method is used for establishing an information system layer network model and an integrated coupling model.

In a third aspect, the present invention provides an information physical system physical domain and network domain integrated coupling modeling apparatus, which is characterized by comprising a processor and a storage medium;

the storage medium is used for storing instructions;

the processor is configured to operate in accordance with the instructions to perform the steps of the method of the first aspect.

Compared with the prior art, the invention has the beneficial effects that: based on the information physical system physical domain and network domain integrated coupling modeling method, the coupling relation inside and among all parts is measured by the method of the correlation characteristic matrix through the fine modeling of the physical domain, network domain elements and systems, a static model of the power grid information physical system is established from the angle of a complex network, and an information layer dynamic operation model and a physical layer dynamic operation model are established from the angle of information layer data transmission and physical layer electric energy transmission, so that the complex information physical system, such as an electric power system, can be finely described, and the stable operation significance of analyzing the information physical system is great.

Drawings

FIG. 1 is a flow chart of the physical domain and network domain integrated coupling modeling method of the present invention;

FIG. 2 is a hierarchy of a physical domain and network domain coupling model;

FIG. 3 is a physical domain and network domain coupled system information-energy flow hybrid model;

fig. 4 is a physical domain and network domain integration coupling model.

Detailed Description

Embodiment one:

the embodiment provides an information physical system physical domain and network domain integrated coupling modeling method, which is characterized in that the coupling relation inside and among all parts is measured by utilizing a method of an association characteristic matrix through the refined modeling of physical domain and network domain elements and systems, a power grid information physical system static model is established from the angle of a complex network, and an information layer dynamic operation model and a physical layer dynamic operation model are established from the angles of information layer data transmission and physical layer electric energy transmission.

The physical domain and network domain integrated coupling modeling method of the information physical system of the embodiment comprises the following steps:

Specifically, step 1 includes the following:

modeling a physical entity layer network model:

(1) Power supply side element model

wherein i is the number of the generator node; delta is the corner; omega, omega ₀ Rotor speed and rated rotor speed respectively; e (E) _fd Is the internal magnetic field voltage; e, e _q 、e _d Terminal voltages of q axis and d axis respectively; e' _q 、e′ _d Transient voltages of q-axis and d-axis respectively; i.e _q 、i _d Currents of q-axis and d-axis, respectively; k (K) _D Is a damping coefficient; t (T) _m 、T _e Respectively a mechanical torque and an electrical air gap torque; t'. _q0 、T′ _d0 Is an open circuit time constant; x is x _q 、x _d Synchronous reactance of q axis and d axis respectively; x's' _q 、x′ _d The transient reactance of the q-axis and d-axis, respectively.

And (2) a photovoltaic cell: by serial-parallel connectionThe resistor, the diode and the photo-generated current source. I _ph For generating current, R _s Is equivalent resistance in series, R _sh Is a shunt resistor. The output voltage and current relationship of the photovoltaic array is as follows:

/>

(2) Branch side element model

the current transfer formula can thus be derived:

from this, the current transfer formula can be obtained:

from this, the current transfer formula can be obtained:

the admittance model is therefore:

(3) Load side element model

with current as a state variable, the dynamic model of the load is as follows:

the electromagnetic torque and the mechanical torque are respectively:

T _M ＝T′ _MM0 [(1-s)f] ^β

in the method, in the process of the invention,

Modeling a physical domain system model:

(1) Power grid topology modeling

In the physical domain, the system topology of the power network may be described by a node admittance matrix. The order of the node admittance matrix is equivalent to the number of individual nodes of the network. Its diagonal element (self admittance) Y _ii The sum of the admittances of the branches connected with the node i is the off-diagonal element (transadmittance) Y thereof _ij For branch admittance y between node i and node j _ij Negative values of (a). From this, the calculation formula of the node admittance matrix self admittance and the mutual admittance can be obtained:

Y _ij ＝Y _ji ＝-y _ij

(2) Power grid energy flow modeling

Let the voltages at nodes i and j be represented as

And->

in the method, in the process of the invention,

-y _ij ＝Y _ij therefore, the above formula can be written as +.>

The node voltage equation is in matrix form:

/>

Wherein the method comprises the steps of

For the complex power of the node, I ^* Indicating current +.>

Is a conjugate of (c). By letting Y _ij ＝G _ij +jB _ij ，/>

The above can be expanded in polar coordinates:

in θ _ij ＝θ _i -θ _j Is the phase angle difference at the head end and the tail end of the branch i-j. After finishing, the equation of active power and reactive power under polar coordinates can be obtained:

specifically, step 2 includes the following:

network domain element modeling

(1) Protection measurement and control node modeling

S _ii ＝[F _ii (a _input ),P _ii (F _ii ),…]

(2) Communication network element modeling

C _ij ＝[P _B,ij ,P _M,ij ,…]

(3) Information network element modeling

Modeling a network domain system model:

(1) Communication network modeling

wherein C is _ij ＝[T _ij ,P _B,ij ,P _M,ij ]If i=j, ij represents a communication node,if i+.j, ij denotes the communication branch. C when there is no direct connection between communication node i and node j _ij ＝[0,0,0]。

(2) Modeling a protection measurement and control node network:

(3) Protection measurement and control communication network modeling

using extensible tuples S-C _ij ＝[S-C _TP,ij ,S-C _T,ij ,S-C _PB,ij ,…]To describe the association relationship between the communication node and the protection measurement and control layer node, S-C _TP,ij ，S-C _T,ij ，S-C _PB,ij Respectively represent a communication node i and a protection measurement and control nodej is direct connection, transmission interruption probability and information transmission accuracy.

Specifically, step 3 includes the following:

In this embodiment, the specific physical domain and network domain integrated hybrid computation is taken as an example, and the present invention is described:

When the power system operates, the energy flow distribution of the physical power grid determines the operation state of the physical system. After an information system (control center application) is introduced, each measuring terminal converts some selected physical state quantity into corresponding virtual signals, the information system on the secondary side generates final control signals after multistage transmission, conversion and calculation based on the information, and the system control terminal converts the information system into physical state changes (such as switching of a switch, load changes and the like) so as to influence the energy flow distribution of a physical power grid and then generate a new running state. Thus, the interaction process of an information node with a physical node can be regarded as a "physical-information-physical" process.

The impact of an information system on a physical grid can be considered to be achieved by information flow. Thus, to analyze the information-physical coupling characteristics of a system, it is at the heart to discuss the interaction of information flow and physical energy flow, i.e. to perform a hybrid solution on the information-energy flow distribution of the whole system.

a. Energy flow calculation model

The energy flow distribution, i.e. the power flow distribution of the physical network, has been analyzed in detail in the previous section, and the power flow calculation is now described in detail as follows:

f(x(t+1),u(t),d(t),Y)＝0 (48)

Wherein x is a compliance variable, u is a control variable, d is an uncontrollable disturbance variable, t is a time scale, and corresponds to each control period of the system. Y is an admittance matrix, describing the connection mode and the switching state of each element of the system and the parameters of network elements.

b. Information flow calculation model

The information flow distribution describes the operational state of the secondary-side information system. In the directional information flow model established by us, the information flow is finally flowed to the information node by protecting the measurement and control node through the information mapping (information transmission, information processing and information pool) of different modules. Thus, the information flow in the system can be seen as an information mapping from the information node y to other nodes. Information of the information recording node and other nodes is z= [ z ] ₁ ...z _n ] ^T Sum w= [ w ₁ ...w _n ] ^T The information flow model may be expressed as:

c. energy-information flow calculation model

The link realizes the conversion from physical state to virtual signal, and corresponds to the state sensing link in the actual system, i.e. the corresponding quantity is measured from the compliance variable x according to the control requirement and converted into the virtual signal as the future information systemInformation source, denoted as y= [ y ] ₁ …y _m ] ^T . The process can be described as:

y(N)＝H _y ·x(N) (50)

d. information-energy flow calculation model

The link corresponds to the control link of the actual system, namely, the information z of the information node is mapped into the actual control quantity u of the protection measurement and control node, and can be described as follows:

u(N)＝E _u ·z(N) (51)

for a power grid with n physical nodes, m communication nodes, k protection measurement and control nodes and l information nodes, a data processing hybrid calculation model based on an association characteristic matrix is established aiming at the information uploading and issuing process.

The modeling analysis and calculation flow is as follows: (1) establishing C, S according to real-time data or experience data _ES ，S _SS ，S _MS P-S, S-I matrix; (2) based on C, S _ES ，S _SS ，S _MS The matrix adopts a mixing calculation method aiming at the communication transmission accuracy to search the signal transmission path, and the influence of the communication transmission accuracy on the protection measurement and control is considered to form an S matrix; (3) according to the S, P-S and S-I matrixes, a P-I or I-P matrix is formed by adopting a hybrid calculation method, and then the influence of the P-I or I-P matrix on the CPS of the power grid is analyzed.

And for the measurement information uploading process, the communication transmission hybrid calculation model framework based on the association characteristic matrix provided in the section is applied, so that the weak link of the power grid can be rapidly evaluated.

Table 1 channel reliability parameter settings

And establishing an association matrix of each layer of network, and assuming that the reliability of each channel in the same network is the same. The reliability of the communication link needs to comprehensively consider the information transmission mode, the communication service type, the error rate and the like. The communication stability of each final node can be obtained by calculating the transmission matrix reliability model constructed in this section as shown in table 2:

Table 2 IEEE 9 node transmission stability calculation results

Node sequence number	Stability parameter
		1	99.64％
2	99.88％
		3	99.14％
4	99.38％
		5	99.60％
6	96.36％
		7	98.75％
8	97.65％
		9	99.96％

It is obvious from the above analysis that when the channel reliability is the same as the research object, the reliability of the edge node is worse, and the corresponding attack difficulty and cost are lower.

Embodiment two:

the embodiment of the invention also provides an information physical system physical domain and network domain integrated coupling modeling device, which comprises:

The apparatus of this embodiment may be used to implement the method described in embodiment one.

Embodiment III:

the embodiment of the invention also provides an information physical system physical domain and network domain integrated coupling modeling device, which comprises a processor and a storage medium;

the storage medium is used for storing instructions;

The processor is configured to operate in accordance with the instructions to perform the steps of the method of embodiment one.

It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The foregoing is merely a preferred embodiment of the present invention, and it should be noted that modifications and variations could be made by those skilled in the art without departing from the technical principles of the present invention, and such modifications and variations should also be regarded as being within the scope of the invention.

Claims

1. A physical domain and network domain integrated coupling modeling method of an information physical system is characterized in that: the method comprises the following steps:

step 1: dividing a power system into a physical domain and a network domain, and firstly establishing a physical domain model comprising physical entity layer modeling and physical domain system modeling;

step 2: establishing a network domain model comprising network domain element modeling and network domain system modeling, wherein the network domain system modeling covers communication network modeling and protection measurement and control network modeling;

step 3: establishing an information system layer network model, and establishing an integrated coupling model by combining the physical domain model in the step 1 and the network domain model in the step 2;

the physical domain and network domain integrated model established in the step 3 is as follows:

establishing a physical-protection measurement and control associated characteristic matrix and a protection measurement and control-information associated characteristic matrix which are respectively used for describing the associated relation between an information physical coupling network and a physical entity layer and an information layer, so as to connect the physical entity layer, the information physical coupling layer and an information system layer together to form a complete network domain and a physical domain layered coupling model; establishing the following association characteristic matrix for a power grid CPS network comprising n physical nodes, m communication nodes, k protection measurement and control nodes and l information application nodes;

Physical-protection measurement and control association characteristic matrix: the matrix is an n multiplied by k order matrix, and matrix elements represent the association relationship between physical entities and a protection measurement and control network in the information acquisition process; the physical-protection measurement and control association characteristic matrix P-S is defined as follows:

using scalable multi-element P-S _ij ＝[P-S _TP,ij ,P-S _PB,ij ,…]To describe the association relationship between the physical node and the protection measurement and control layer node, P-S _TP,ij The topological association relationship between the physical node i and the protection measurement and control node j can be represented by 0-1; P-S _PB,ij Indicating interaction reliability, such as the probability of control commands executing correctly; if there is no direct interaction between the protection measurement and control node and the physical node,then the element of the corresponding position is 0;

protection measurement and control-physical association characteristic matrix: the matrix is a k multiplied by n order matrix, and matrix elements represent the association relation between a protection measurement and control network and a physical entity in the command execution process; the definition process of the protection measurement and control-physical association characteristic matrix S-P is as follows:

using scalable tuples S-P _ij ＝[S-P _TP,ij ,S-P _PB,ij ,…]To describe the association relationship between the communication node and the protection measurement and control layer node, S-P _TP,ij The topological association relationship between the physical node i and the protection measurement and control node j can be represented by 0-1; S-P _PB,ij Indicating interaction reliability, such as the probability of control commands executing correctly; if no direct interaction relation exists between the protection measurement and control node and the physical node, the element at the corresponding position is 0;

Protection measurement and control-information association characteristic matrix: the matrix is a k multiplied by l order matrix, matrix elements represent the characteristics of a decision unit for uploading real-time analysis results to an information system layer by protection measurement and control, and mainly describe the association relationship between a protection measurement and control network and the information layer in the process of inputting information into the decision unit;

by expanding the tuples S-I _ij ＝[S-I _TP,ij ,S-I _PB,ij ,…]To describe the association relationship between the communication node and the protection measurement and control layer node, S-I _TP,ij The topological association relationship between the physical node i and the protection measurement and control node j can be represented by 0-1; S-I _PB,ij Indicating interaction reliability, such as the probability of control commands executing correctly; if no direct interaction relation exists between the protection measurement and control node and the physical node, the element at the corresponding position is 0;

information-protection measurement and control association characteristic matrix: the matrix is an l multiplied by k order matrix, matrix elements represent the characteristic that a decision unit issues a control instruction to the protection measurement and control equipment, and mainly describe the incidence relation between the information system layer and the protection measurement and control network and the information system layer in the issuing process when the information system layer applies the control instruction;

with extended tuples I-S _ij ＝[I-S _TP,ij ,I-S _PB,ij ,…]To describe the association relationship between the communication node and the protection measurement and control layer node, I-S _TP,ij The topological association relationship between the physical node i and the protection measurement and control node j can be represented by 0-1; I-S _PB,ij Indicating interaction reliability, such as the probability of control commands executing correctly; if no direct interaction relation exists between the protection measurement and control node and the physical node, the element at the corresponding position is 0.

2. An information physical system physical domain and network domain integrated coupling modeling device, characterized in that the device comprises:

and the integrated modeling module is as follows: the method comprises the steps of establishing an information system layer network model and an integrated coupling model;

the physical domain and network domain integrated model is built as follows:

using scalable multi-element P-S _ij ＝[P-S _TP,ij ,P-S _PB,ij ,…]To describe the association relationship between the physical node and the protection measurement and control layer node, P-S _TP,ij The topological association relationship between the physical node i and the protection measurement and control node j can be represented by 0-1; P-S _PB,ij Indicating interaction reliability, such as the probability of control commands executing correctly; if no direct interaction relation exists between the protection measurement and control node and the physical node, the element at the corresponding position is 0;

3. The integrated coupling modeling device for the physical domain and the network domain of the information physical system is characterized by comprising a processor and a storage medium;

the storage medium is used for storing instructions;

the processor is operative according to the instructions to perform the steps of the method of claim 1.