CN115034060A

CN115034060A - Integrated coupling modeling method and device for physical domain and network domain of information physical system

Info

Publication number: CN115034060A
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: 2022-09-09
Anticipated expiration: 2042-06-07
Also published as: CN115034060B

Abstract

The invention discloses a method and a device for identifying and simulating paraplegia caused by weak links of an cyber physical system.

Description

Integrated coupling modeling method and device for physical domain and network domain of information physical system

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 Cyber Physical System (CPS) was first stated as: "realize monitoring, control, integrated physical, biological and engineering systems through the computational core: computing is embedded deeply 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 ".

Applying the concept of an information physical system to the power industry, wherein a physical layer is a power grid and comprises power primary equipment such as a generator, a load, a breaker, a power transmission line and the like; the information layer is an electric power information network, and comprises various monitoring devices, control devices, secondary electric power devices such as computing devices and communication network 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 the operation state information (voltage, current, power, frequency and the like) of the electric power network to computing servers of various levels of regulation and control centers through the communication network, the servers generate reasonable control strategies according to the operation conditions of the current system and the instructions of a dispatcher, and send the control instructions to equipment terminals through the communication network again, and the equipment terminals execute corresponding operations according to the control instructions. The interconnection mode of the power information network and the power system is a hierarchical mode, namely, data are transmitted to a transformer substation through secondary equipment (such as a sensor) installed on primary power equipment, the transformer substation collects and aggregates the data and then communicates with a dispatching center of the layer, and terminal data are uploaded or control signals are downloaded. The main equipment on the power grid terminal level comprises a generator set, a transformer substation and a line breaker; the main equipment of the dispatching center layer is a front-end processor system and a host 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 substation data communication protocol, a telecontrol communication protocol, a computer data communication protocol and the like; the communication method mainly includes 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 integrated coupling modeling method for a physical domain and a network domain of an information physical system.

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

in a first aspect, the invention provides an integrated coupling modeling method for a physical domain and a network domain of an information physical system, which comprises 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, including network domain element modeling and network domain system modeling, covering communication network modeling and protection measurement and control network modeling;

and 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

A generator: the generator model is described by a fourth-order differential equation under a local d-q coordinate system:

wherein i is the generator node number; delta is a turning angle; omega, omega ₀ Rotor speed and rated rotor speed, respectively; e _fd Is the internal magnetic field voltage; e.g. of the type _q 、e _d Terminal voltages of q-axis and d-axis, respectively; e' _q 、e′ _d Transient voltages of the q-axis and d-axis, respectively; i.e. i _q 、i _d Currents of the q-axis and d-axis, respectively; k is _D Is a damping coefficient; t is _m 、T _e Mechanical torque and electrical air gap torque, respectively; t' _q0 、T′ _d0 Is the open circuit time constant; x is a radical of a fluorine atom _q 、x _d Synchronous reactance for the q-axis and d-axis respectively; x' _q 、x′ _d The transient reactances of the q-axis and d-axis, respectively.

Photovoltaic cell: the photovoltaic power generation device is composed of series-parallel resistors, diodes and a photo-generated current source. I is _ph Is a photo-generated current, R _s Is a series equivalent resistance, R _sh Is a shunt resistor. The relation between the output voltage and the current of the photovoltaic array is as follows:

wherein A is an ideal factor of the diode; boltzmann constant k 1.38 x 10 ^-23 J/K; the charge q of the electron is 1.6 × 10 ^-19 C; theta is the temperature; r _sh And R _s Parallel and series resistors.

(2) Branch road side element model

A 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 to be Y. From kirchhoff's voltage-current law, one can derive:

the current transfer formula can thus be derived:

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

the current transmission formula can be obtained by the following steps:

phase shifter: according to the equivalent circuit model of the phase shifter, the following results can be obtained:

the current transmission formula can be obtained by the following steps:

therefore, the admittance model is:

(3) load side element model

RL series load: when calculating and analyzing the power system, the general characteristics of the load group presented to the external system are generally concerned, so that an overall load model needs to be established. Among the various loads, load circuits in which RL are connected in series are the most common. According to the ac circuit theory, a static model of the load can be obtained:

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

load of asynchronous motor: the asynchronous motor has a large proportion 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 program, a mechanical transient model is generally adopted:

in the formula G _Σ Is the conductance as seen from the motor port. Slip s ═ ω _s -ω _r )/ω _s ＝1-ω _r /f。

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

the electromagnetic torque and the mechanical torque are respectively:

T _M ＝T′ _M0 [(1-s)f] ^β

in the formula (I), the compound is shown in the specification,

f is port voltage, current and frequency respectively; omega _r Is the rotor speed; r _s Is a stator resistor; x, X' are steady-state and transient reactances, respectively; t' _d0 、T _J Respectively a rotor winding time constant and an inertia time constant; t is _E 、T _M Electromagnetic torque and mechanical torque, respectively; β 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 relationship of the power grid can 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 Is the sum of the admittance of each branch connected to node i, its non-diagonal element (mutual admittance) Y _ij Admittance y for the branch between node i and node j _ij Negative values of (c). Therefore, a calculation formula of the self-admittance and the mutual admittance of the node admittance matrix can be obtained:

Y _ij ＝Y _ji ＝-y _ij

in the formula, y _i0 Admittance to ground for node i; y is _ij Admittance for the branch 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 the tidal current distribution of a physical power grid, is represented as instantaneous balance of power in the system, and can be described by a node voltage equation and a node power equation. Node voltage equation: a node voltage equation is adopted in the power flow calculation of the power system to reflect the relation between the node voltage in the system and the injection current of the node.

Let the voltages at nodes i and j be represented as

And

the admittance of the lines i-j is denoted y _ij Then the current I in this line flows from node I to node j _ij Can be expressed as:

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

in the formula (I), the compound is shown in the specification,

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

The matrix form of the node voltage equation is:

node power equation: in power system load flow calculation, node injection power of a load and a generator is known, and the node injection power is not influenced by a node voltage. Therefore, under the condition that the node injection power is unchanged, the injection current of the node is changed along with the change of the node voltage, and the node injection power equation can be expressed as follows:

wherein

Is the complex power of the node, I ^* Representing current

Conjugation of (1). By making Y _ij ＝G _ij +jB _ij ，

The above equation can be expanded in polar coordinates:

in the formula, theta _ij ＝θ _i -θ _j The phase angle difference between the head and tail ends of the branches i-j is shown. After arrangement, an equation of active power and reactive power under a polar coordinate can be obtained:

further, the method for modeling the network domain element comprises the following steps:

(1) protection measurement and control node modeling

The 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: the first is the functional relationship between information input and output (information processing function), and the second is the information processing performance in the information processing and transmission processes.

The functional characteristics of the protection measurement and control node are described by adopting a tuple, which is shown as the following formula:

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

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

(2) Communication network element modeling

A communication node: the state quantities in the physical system and the information system are uniformly abstracted into communication nodes, and the communication nodes comprise measurement values, system state quantities, control instructions and the like.

Communication branch: a path of data transmission in a communication network is abstracted into a communication branch (cyberbranch), wherein a head end node and a tail end node of the communication branch are input data and output data respectively, and a branch characteristic equation is a mapping operator between the input data and the output data.

The communication nodes and communication branches need to be able to describe the information processing performance. 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 power grid CPS is analyzed, the communication interruption can be represented by a state of 0-1 to determine whether the interruption is caused. However, when the influence of the communication interruption on the reliability of the power grid CPS is analyzed, the communication interruption needs to be described as a communication interruption probability or communication reliability. Therefore, the communication performance of the communication branch is described by adopting the multi-element group, and elements in the multi-element group can be expanded according to the application requirements of the power grid CPS. Such as the tuple shown below:

C _ij ＝[P _B,ij ,P _M,ij ,…]

wherein P is _B,ij ，P _M,ij Respectively representing the interruption probability and the correct information transmission probability between the node i and the node j.

(3) Information network element modeling

An 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 a relevant instruction according to the information input. Through this process, the information layer and the information physical coupling layer are tightly coupled.

An information hub: in the control system, the data output of some modules will be collected into a total information pool, which will be used as the data source of other modules. Such modules are defined as "information hubs". The information concentrator is a virtual node, exists at the interface position of a communication network and an information network, and does not correspond to any information function in an actual system. But the network data interface is two network data interfaces, so that the modules are mutually coupled through information interaction to form a complete network domain. For example, all measurement results in the substation are integrated in the station-level control center, and only a part of the data is uploaded to the master control center.

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

(1) communication network modeling

A communication network comprising m communication nodes is modeled based on the communication network element model presented in the previous section. 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 a formula:

in the formula, C _ij ＝[T _ij ,P _B,ij ,P _M,ij ]If i ≠ j, ij denotes a communication node, and if i ≠ j, ij denotes a communication branch. When there is no direct connection between communication node i and node j, C _ij ＝[0,0,0]。

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

and modeling the protection measurement and control network comprising k protection measurement and control nodes based on the protection measurement and control model provided in the previous section. Because there is no coupling relation between the 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 a multi-element group of the protection measurement and control nodes, and the protection measurement and control network communication network adjacent matrix S can be completed only by being matched with a communication network.

(3) Modeling of protection measurement and control communication network

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

using expandable tuples S-C _ij ＝[S-C _TP,ij ,S-C _T,ij ,S-C _PB,ij ,…]To describe the association between a communication node and a protection measurement and control layer node, S-C _TP,ij ，S-C _T,ij ，S-C _PB,ij And respectively indicating 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 adjacency matrix S is adopted to describe the topology and the 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 the protection measurement and control node, and if i ≠ j, ij represents the protection measurement and control channel. When the protection measurement and control node i and the node j have logical direct connection (direct information exchange), S _ij The performance of the protection measurement and control channel is expressed and obtained 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 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 correlation characteristic matrix (P-S or S-P) and a protection measurement and control-information correlation characteristic matrix (S-I or I-S) which are respectively used for describing the correlation relationship between the information physical coupling network and the physical entity layer and the information layer, thereby communicating the physical entity layer, the information physical coupling layer and the information system layer to form a complete network domain and physical domain layered coupling model. The method comprises the steps of 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 property matrix (P-S): the matrix is an n multiplied by k matrix, and matrix elements represent the incidence relation between a physical entity 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 tuples P-S _ij ＝[P-S _TP,ij ,P-S _PB,ij ,…]To describe the association relationship between the physical node and the node of the protection measurement and control layer, P-S _TP,ij The topological association relation between the physical node i and the protection measurement and control node j is represented by 0-1; P-S _PB,ij Indicating the reliability of the interaction, e.g. the probability of the control command being executed correctly. If the protection measurement and control node has no direct interaction relation with the physical node, the element at the corresponding position is 0.

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

using expandable 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 relation between the physical node i and the protection measurement and control node j is represented by 0-1; S-P _PB,ij Indicating the reliability of the interaction, e.g. the probability of the control command being executed correctly. If the protection measurement and control node has no direct interaction relation with the physical node, the element of the corresponding position is 0.

Protection measurement and control-information correlation characteristic matrix (S-I): the matrix is a k multiplied by l order matrix, the matrix elements represent the characteristic that the real-time analysis result is uploaded to a decision unit of an information system layer by the protection measurement and control, and the matrix elements mainly describe the incidence relation between a protection measurement and control network and an information layer in the process of inputting information into the decision unit.

With extended tuples S-I _ij ＝[S-I _TP,ij ,S-I _PB,ij ,…]To describe the association between the communication nodes and the nodes of the protection measurement and control layer, S-I _TP,ij The method comprises the steps that a topological incidence relation between a physical node i and a protection measurement and control node j is represented, and can be represented by 0-1; S-I _PB,ij Indicating the reliability of the interaction, e.g. the probability of the control command being executed correctly. If the protection measurement and control node and the physical node are not connectedAnd if the relationship is direct, the element at the corresponding position is 0.

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

By expanding 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 relation between the physical node i and the protection measurement and control node j is represented by 0-1; I-S _PB,ij Indicating the reliability of the interaction, e.g. the probability of the control command being executed correctly. If the protection measurement and control node has no direct interaction relation with the physical node, the element of the corresponding position is 0.

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

a 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;

a network domain modeling module: the method is used for establishing a network domain model, comprises network domain element modeling and network domain system modeling, and comprises communication network modeling and protection measurement and control network modeling;

an integrated modeling module: 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 integrated coupling modeling apparatus for a physical domain and a network domain of an cyber-physical system, 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 following beneficial effects: based on the integrated coupling modeling method of the physical domain and the network domain of the information physical system, provided by the invention, the refined modeling of elements and systems of the physical domain and the network domain is realized, the coupling relation in and among all the parts is measured by utilizing a correlation characteristic matrix method, a static model of the information physical system of the power grid is established from the perspective of a complex network, and a dynamic operation model of an information layer and a dynamic operation model of a physical layer are established from the perspective of data transmission of the information layer and electric energy transmission of the physical layer, so that the complicated information physical system, such as an electric power system, can be finely described, and the integrated coupling modeling method has great significance for analyzing the stable operation of the information physical system.

Drawings

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

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

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

fig. 4 is a coupling model for integrating a physical domain and a network domain.

Detailed Description

The first embodiment is as follows:

the embodiment provides an integrated coupling modeling method for a physical domain and a network domain of an information physical system, which comprises the steps of carrying out fine modeling on elements and systems of the physical domain and the network domain, measuring coupling relations inside and among all the parts by using a correlation characteristic matrix method, building a static model of the information physical system of a power grid from the perspective of a complex network, and building a dynamic operation model of an information layer and a dynamic operation model of a physical layer from the perspective of data transmission of the information layer and electric energy transmission of the physical layer.

The integrated coupling modeling method for the physical domain and the network domain of the information physical system 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 generator node number; delta is a corner; omega, omega ₀ Rotor speed and rated rotor speed, respectively; e _fd Is the internal magnetic field voltage; e.g. of the type _q 、e _d Terminal voltages of q-axis and d-axis, respectively; e' _q 、e′ _d Transient voltages of the q-axis and d-axis, respectively; i.e. i _q 、i _d Currents of the q-axis and d-axis, respectively; k _D Is a damping coefficient; t is _m 、T _e Mechanical torque and electrical air gap torque, respectively; t' _q0 、T′ _d0 Is the open circuit time constant; x is the number of _q 、x _d Synchronous reactance for q-axis and d-axis respectively; x' _q 、x′ _d The transient reactances of the q-axis and d-axis, respectively.

wherein A is an ideal factor of the diode; boltzmann constant k 1.38 x 10 ^-23 J/K; the charge q of the electron is 1.6 × 10 ^-19 C; theta is(ii) a temperature; r is _sh And R _s Parallel and series resistors.

(2) Model of branch road side element

A 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 to be Y. From kirchhoff's voltage-current law one can derive:

the current transfer formula can thus be derived:

the current transmission formula can be obtained by the following steps:

the current transmission formula can be obtained by the following steps:

therefore, the admittance model is:

(3) load side element model

the electromagnetic torque and the mechanical torque are respectively:

T _M ＝T′ _MM0 [(1-s)f] ^β

in the formula (I), the compound is shown in the specification,

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

Modeling a physical domain system model:

(1) power grid topology modeling

In the physical domain, the system topology relationship of the power grid can be described by a node admittance matrix. The order of the node admittance matrix is equal to the number of independent nodes of the network. Its diagonal element (self-admittance) Y _ii Is the sum of the admittance of the branches connected to node i, its non-diagonal elements (transadmittance) Y _ij Admittance y for the branch between node i and node j _ij Negative values of (c). Therefore, a calculation formula of the self-admittance and the mutual admittance of the node admittance matrix can be obtained:

Y _ij ＝Y _ji ＝-y _ij

in the formula, y _i0 Admittance to ground for node i; y is _ij Admittance for the branch between node i and node j. node of n-node systemThe admittance matrix Y is:

(2) power grid energy flow modeling

Let the voltages at nodes i and j be represented as

And

the admittance of the line i-j is denoted y _ij Then current I in this line flows from node I to node j _ij Can be expressed as:

in the formula (I), the compound is shown in the specification,

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

The matrix form of the node voltage equation is then:

wherein

Is the complex power of the node, I ^* Representing current

And (3) conjugation. By making Y _ij ＝G _ij +jB _ij ，

The above equation can be expanded in polar coordinates:

in the formula, theta _ij ＝θ _i -θ _j Is the phase angle difference between the head and tail ends of the branch i-j. After arrangement, an equation of active power and reactive power under a polar coordinate 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

Communication branch: the path of data transmission in a communication network is abstracted into a communication branch (cyberbranch), wherein the head end node and the tail end node of the communication branch are input data and output data respectively, and the characteristic equation of the branch is a mapping operator between the input data and the output data.

The communication nodes and communication branches need to be able to describe the information processing performance. 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 power grid CPS is analyzed, the communication interruption can be represented by a state of '0-1' to determine whether the interruption is caused. However, when the influence of the communication interruption on the reliability of the power grid CPS is analyzed, the communication interruption needs to be described as a communication interruption probability or communication reliability. Therefore, the communication performance of the communication branch is described by adopting the multi-element group, and elements in the multi-element group can be expanded according to the application requirements of the power grid CPS. Such as the multiplet shown below:

C _ij ＝[P _B,ij ,P _M,ij ,…]

(3) Information network element modeling

An 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. And 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 a related instruction according to the information input. Through this process, the information layer and the information physical coupling layer are tightly coupled.

An information hub: in the control system, the data output of some modules will be collected into a total information pool, which will be used as the data source of other modules. Such modules are defined as "message hubs". The information concentrator is a virtual node, exists at the interface position of a communication network and an information network, and does not correspond to any information function in an actual system. But the network data interface is two network data interfaces, so that the modules are mutually coupled through information interaction to form a complete network domain. For example, all measurement results in the substation are integrated in the station-level control center, and only a part of the data is uploaded to the master control center.

Modeling a network domain system model:

(1) communication network modeling

in the formula, C _ij ＝[T _ij ,P _B,ij ,P _M,ij ]If i ≠ j, ij denotes a communication node, and if i ≠ j, ij denotes a communication branch. When there is no direct connection between communication node i and node j，C _ij ＝[0,0,0]。

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

(3) Modeling of protection measurement and control communication network

Modeling of the protection measurement and control-communication gateway: the protection measurement and control network is a control network based on a communication network, so a protection measurement and control network model must be established based on the communication network model. Therefore, the incidence relation between the protection measurement and control network and the communication network is modeled. And describing the uploading process of the acquired information by adopting a protection measurement and control-communication network incidence matrix S-C, and corresponding to the incidence relation (measurement system) between the information acquisition protection measurement and control node and the communication node. And describing an instruction issuing process by using C-S, wherein the C-S corresponds to an association relation (a relay protection system) between a communication node and the execution of operation protection measurement and control. The two matrixes are not necessarily completely symmetrical matrixes, but the modeling mode is similar, and S-C is taken as an example below, and the structure of the S-C is defined as follows:

using expandable tuples S-C _ij ＝[S-C _TP,ij ,S-C _T,ij ,S-C _PB,ij ,…]To describe the association between a communication node and a protection measurement and control layer node, S-C _TP,ij ，S-C _T,ij ，S-C _PB,ij Respectively indicating whether the communication node i and the protection measurement and control node j are directly connected, the transmission interruption probability and the information transmission are positiveAnd (6) determining the rate.

Specifically, step 3 includes the following:

using scalable tuples P-S _ij ＝[P-S _TP,ij ,P-S _PB,ij ,…]To describe the association relationship between the physical node and the node of the protection measurement and control layer, P-S _TP,ij The topological association relation between the physical node i and the protection measurement and control node j is represented by 0-1; P-S _PB,ij Indicating the reliability of the interaction, e.g. the probability of the control command being executed correctly. If the protection measurement and control node has no direct interaction relation with the physical node, the element of the corresponding position is 0.

employing extensible 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 method comprises the steps that a topological incidence relation between a physical node i and a protection measurement and control node j is represented, and can be represented by 0-1; S-P _PB,ij Indicating the reliability of the interaction, e.g. the probability of the control command being executed correctly. If the protection measurement and control node has no direct interaction relation with the physical node, the element of 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, the matrix elements represent the characteristic that the protection measurement and control uploads the real-time analysis result to a decision unit of an information system layer, and the matrix elements mainly describe the incidence relation between a protection measurement and control network and an information layer in the process of inputting information into the decision unit.

With extended tuples S-I _ij ＝[S-I _TP,ij ,S-I _PB,ij ,…]To describe the association between the communication nodes and the nodes of the protection measurement and control layer, S-I _TP,ij The topological association relation between the physical node i and the protection measurement and control node j is represented by 0-1; S-I _PB,ij Indicating the reliability of the interaction, e.g. the probability of the control command being executed correctly. If the protection measurement and control node has no direct interaction relation with the physical node, the element at the corresponding position is 0.

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

This embodiment takes a specific integrated hybrid calculation of a physical domain and a network domain as an example, and introduces the present invention:

when the power system operates, the energy flow distribution of the physical power grid determines the operating state of the physical system. After an information system (control center application) is introduced, each measuring terminal converts some selected physical state quantities into corresponding virtual signals, a secondary-side information system generates final control signals after multi-level transmission, conversion and calculation based on the information, and a system control terminal converts the final control signals into changes of physical states (such as switching of switches, load changes and the like), so that energy flow distribution of a physical power grid is influenced, and a new operating state is generated. Thus, the process of interaction of an informational node with a physical node may be viewed as a "physical-informational-physical" process.

The influence of the information system on the physical grid can be regarded as being achieved by the information flow. Therefore, to analyze the information-physical coupling characteristics of the system, the core is to discuss the interaction between the information flow and the physical energy flow, i.e. to solve the information-energy flow distribution of the whole system by blending.

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 preceding section, and the power flow calculation is described in a unified manner 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 interference variable, and t is a time scale corresponding to each control period of the system. And Y is an admittance matrix, and describes the connection mode and the switch state of each element of the system and the parameters of the network element.

b. Information flow calculation model

The information flow distribution describes the operating state of the secondary side information system. For example, in the directional information flow model established by the user, information flows are mapped (information transmission, information processing and information pool) by different modules from a protection measurement and control node and finally flow to the information node. Thus, the flow of information in the system can be viewed as a mapping of information from inode y to other nodes. The information of the information node and other nodes is recorded as z ═ z respectively ₁ ...z _n ] ^T And w ═ w ₁ ...w _n ] ^T Then the information flow model can be expressed as:

c. energy-information flow calculation model

The link realizes the conversion from a physical state to a virtual signal, corresponds to a state perception link in an actual system, namely measures corresponding quantity according to a control requirement from a compliance variable x, and converts the quantity into the control requirementThe virtual signal is taken as an information source of a future information system and is recorded 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

This link corresponds to the control link of the actual system, i.e. the information z of the information node is mapped into the actual control quantity u of the protection measurement and control node, which can be described as:

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 incidence characteristic matrix is established aiming at the information uploading and issuing processes.

The modeling analysis calculation flow comprises the following steps: firstly, establishing C and S according to real-time data or empirical data _ES ，S _SS ，S _MS A P-S, S-I matrix; based on C, S _ES ，S _SS ，S _MS The matrix is used for searching a signal transmission path by adopting a hybrid calculation method aiming at the communication transmission accuracy, and considering the influence of the communication transmission accuracy on protection measurement and control to form an S matrix; and thirdly, forming a P-I or I-P matrix by adopting a hybrid calculation method according to the S, P-S and S-I matrix, and further analyzing the influence of the P-I or I-P matrix on the CPS of the power grid.

For the measurement information uploading process, the power grid weak link can be quickly evaluated by applying the communication transmission hybrid calculation model framework based on the incidence characteristic matrix provided in the section.

Table 1 channel reliability parameter set-up

And establishing an incidence 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 information transmission modes, communication service types, bit error rates and the like. The communication stability of each node finally obtained by calculating the transmission matrix reliability model constructed in this section is 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 can be seen from the above analysis that, when the channel reliability is used as a research object, the edge nodes have worse reliability and lower attack difficulty and cost when the same-level channel reliability is the same.

Example two:

the embodiment of the invention also provides an integrated coupling modeling device for the physical domain and the network domain of the cyber-physical system, which comprises the following components:

The apparatus of the present embodiment can be used to implement the method described in the first embodiment.

Example three:

the embodiment of the invention also provides an integrated coupling modeling device of the physical domain and the network domain of the cyber-physical system, 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.

As will be appreciated by one skilled in the art, 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 flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams 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 above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.

Claims

1. An integrated coupling modeling method for a physical domain and a network domain 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, including physical entity layer modeling and physical domain system modeling;

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

and 3, 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).

2. The integrated coupling modeling method for the physical domain and the network domain of the cyber-physical system according to claim 1, wherein: the physical entity layer network model modeling method comprises the following steps:

(1) power supply side element model

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

photovoltaic cell: by series-parallel resistor, diode and photo-generated currentSource composition; i is _ph Is a photo-generated current, R _s Is a series equivalent resistance, R _sh Is a bypass resistor; the relation between the output voltage and the current of the photovoltaic array is as follows:

wherein A is an ideal factor of the diode; boltzmann constant k 1.38 x 10 ^-23 J/K; the charge q of the electron is 1.6 × 10 ^-19 C; theta is the temperature; r _sh And R _s Parallel and series resistors;

(2) branch road side element model

A power line: the power line adopts a pi-type equivalent circuit model, the total impedance of the line is Z, and the total admittance is Y; obtaining a current transmission formula:

a transformer: the transformer equivalent model is obtained according to kirchhoff's law:

the current transmission formula is obtained:

phase shifter: the equivalent circuit of the phase shifter is obtained according to kirchhoff's law:

the current transmission formula is obtained:

therefore, the admittance model is:

(3) load side element model

RL series load: obtaining a static model of the load:

load of asynchronous motor: a mechanical transient model is adopted:

in the formula G _Σ Is the conductance as seen from the motor port; slip s ═ ω _s -ω _r )/ω _s ＝1-ω _r /f；

the electromagnetic torque and the mechanical torque are respectively:

T _M ＝T′ _M0 [(1-s)f] ^β

in the formula (I), the compound is shown in the specification,

3. The integrated coupling modeling method for the physical domain and the network domain of the cyber-physical system according to claim 1, wherein: the method for modeling the physical domain system model comprises the following steps:

(1) power grid topology modeling

In a physical domain, describing a system topological relation of a power grid by using a node admittance matrix; the order of the node admittance matrix is equal to the number of independent nodes of the network; its diagonal element (self-admittance) Y _ii Is the sum of the admittance of each branch connected to node i, its non-diagonal element (mutual admittance) Y _ij Admittance y for the branch between node i and node j _ij A negative value of (d); thereby obtaining a calculation formula of the self-admittance and the mutual admittance of the node admittance matrix:

Y _ij ＝Y _ji ＝-y _ij

in the formula, y _i0 As node i pairAdmittance of the ground; y is _ij Admittance of a branch 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 the tidal current distribution of a physical power grid, is expressed as instantaneous balance of power in a system and is described by a node voltage equation and a node power equation; node voltage equation: in the power flow calculation of the power system, a node voltage equation is adopted to reflect the relationship between the node voltage in the system and the injection current of the node;

let the voltages at nodes i and j be denoted as

And

the admittance of the lines i-j is denoted y _ij Then the current I in this line flows from node I to node j _ij Expressed as:

if n nodes directly connected to the node i are provided, based on kirchhoff's current law:

in the formula (I), the compound is shown in the specification,

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

The matrix form of the node voltage equation is:

node power equation: in power system load flow calculation, node injection power of a load and a generator is known, and the node injection power is not influenced by a node end voltage; therefore, under the condition that the node injection power is not changed, the injection current of the node is changed along with the change of the node voltage, and the node injection power equation can be expressed as follows:

wherein

Is the complex power of the node, I ^* Representing current

Conjugation of (1); by making Y _ij ＝G _ij +jB _ij ，

The above formula is expanded under polar coordinates:

in the formula, theta _ij ＝θ _i -θ _j The phase angle difference of the head end and the tail end of the branch i-j is obtained; after arrangement, an equation of active power and reactive power under a polar coordinate can be obtained:

4. the integrated coupling modeling method for the physical domain and the network domain of the cyber-physical system according to claim 1, wherein: the method for modeling the network domain element comprises the following steps:

(1) modeling a protection measurement and control node to obtain a protection measurement and control model:

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

wherein, F _ii (a _input ) For information processing algorithms, P _ii (F _ii ) Processing the correct probability for the information;

(2) modeling a communication network element to obtain a communication network element model:

a communication node: uniformly abstracting state quantities in a physical system and an information system into communication nodes, wherein the communication nodes comprise measurement values, system state quantities and control instructions;

communication branch: abstracting a data transmission path in a communication network into a communication branch (cyber branch), wherein the head end node and the tail end node of the communication branch are input data and output data respectively, and a branch characteristic equation is a mapping operator between input and output;

the communication performance of the communication branch is described by adopting the multi-element group, elements in the multi-element group can be expanded according to the application requirements of the CPS of the power grid, and the multi-element group is shown as the following formula:

C _ij ＝[P _B,ij ,P _M,ij ,…]

wherein P is _B,ij ，P _M,ij Respectively representing the interrupt probability and the correct information transmission probability between the node i and the node j;

(3) information network element modeling

An information node: 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 a relevant instruction according to the information input; the information layer and the information physical coupling layer are tightly coupled through the process;

an information hub: the information concentrator is a virtual node, exists at the interface position of a communication network and an information network, and does not correspond to any information function in an actual system; but the two network data interfaces are adopted, so that the modules are mutually coupled through information interaction to form a complete network domain; for example, all measurement results in the substation are integrated in the station-level control center, and only a part of the data is uploaded to the master control center.

5. The integrated coupling modeling method for the physical domain and the network domain of the cyber-physical system according to claim 4, wherein: the method for modeling the network domain system model comprises the following steps:

(1) communication network modeling

Modeling a communication network comprising m communication nodes based on the communication network element model; 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 a formula:

in the formula, C _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; when there is no direct connection between communication node i and node j, C _ij ＝[0,0,0]；

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

based on the protection measurement and control model, modeling is carried out on the protection measurement and control network comprising k protection measurement and control nodes, and an incidence matrix diag (S) for forming a protection measurement and control node network model is a diagonal matrix:

the diagonal elements of the matrix are a multi-element group of protection measurement and control nodes, and the protection measurement and control network communication network adjacent matrix S can be completed only by matching with a communication network;

(3) protection measurement and control communication network modeling

Modeling of the protection measurement and control-communication gateway: describing an uploading process of the acquired information by adopting a protection measurement and control-communication network incidence matrix S-C, and corresponding to the incidence relation between the information acquisition protection measurement and control node and the communication node, namely a measurement system; the C-S is used for describing the instruction issuing process, and the corresponding communication node and the incidence relation of the execution operation protection measurement and control are defined as follows:

using expandable tuples S-C _ij ＝[S-C _TP,ij ,S-C _T,ij ,S-C _PB,ij ,…]To describe the association between a communication node and a protection measurement and control layer node, S-C _TP,ij ，S-C _T,ij ，S-C _PB,ij Respectively indicating 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;

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; s when the protection measurement and control node i is logically directly connected with the node j _ij The performance of the protection measurement and control channel is expressed and is obtained by a protection measurement and control node network model, a protection measurement and control-communication network association model and a communication network model through a certain hybrid calculation algorithm; s when no logic direct connection exists between the protection measurement and control node i and the node j _ij ＝[0,0,0]。

6. The integrated coupling modeling method for the physical domain and the network domain of the cyber-physical system according to claim 1, wherein: the physical domain and network domain integrated model established in the step 3 is as follows:

establishing a physical-protection measurement and control incidence characteristic matrix and a protection measurement and control-information incidence characteristic matrix which are respectively used for describing incidence relations among the physical coupling network, 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 physical domain layered coupling model; establishing a following incidence 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: the matrix is an n multiplied by k matrix, and matrix elements represent the incidence relation between a physical entity 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 tuples P-S _ij ＝[P-S _TP,ij ,P-S _PB,ij ,…]To describe the association relationship between the physical node and the node of the protection measurement and control layer, P-S _TP,ij The topological association relation between the physical node i and the protection measurement and control node j is represented by 0-1; P-S _PB,ij Indicating interaction reliability, such as the probability of correct execution of the control command; if the protection measurement and control node has no direct interaction relation with the physical node, the element of the corresponding position is 0;

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

using expandable 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 relation between the physical node i and the protection measurement and control node j is represented by 0-1; S-P _PB,ij Indicating interaction reliability, such as the probability of correct execution of the control command; if the protection measurement and control node has no direct interaction relation with the physical node, the element of the corresponding position is 0;

protection measurement and control-information association characteristic matrix: the matrix is a k multiplied by l order matrix, the matrix elements represent the characteristic that the protection measurement and control uploads the real-time analysis result to a decision unit of an information system layer, and the matrix elements mainly describe the incidence relation between a protection measurement and control network and an information layer in the process of inputting information into the decision unit;

using extended tuples S-I _ij ＝[S-I _TP,ij ,S-I _PB,ij ,…]To describe the association between the communication nodes and the nodes of the protection measurement and control layer, S-I _TP,ij The topological association relation between the physical node i and the protection measurement and control node j is represented by 0-1; S-I _PB,ij Indicating interaction reliability, such as the probability of correct execution of the control command; if the protection measurement and control node has no direct interaction relation with the physical node, the element at the corresponding position is 0;

information-protection measurement and control correlation property matrix: the matrix is an l x k order matrix, the matrix elements represent the characteristic that a decision unit issues a control command to the protection measurement and control equipment, and the matrix elements mainly describe the incidence relation between the generation of the control command applied by the information system layer and the protection measurement and control network and the information system layer in the issuing process;

by expanding 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 relation between the physical node i and the protection measurement and control node j is represented by 0-1; I-S _PB,ij Indicating interaction reliability, such as the probability of correct execution of the control command; if the protection measurement and control node has no direct interaction relation with the physical node, the element at the corresponding position is 0.

7. An integrated coupling modeling device for a physical domain and a network domain of an cyber-physical system, the device comprising:

8. An integrated coupling modeling device for a physical domain and a network domain of an information physical system 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 according to any one of claims 1 to 6.