A power information-physics coupling modeling method for new distribution systems

Abstract

The present invention discloses a method for modeling power information-physical coupling for a new distribution system, and relates to the technical field of modeling and simulation of distribution systems. The method uses a multi-tuple and adjacency matrix to perform matrix modeling on the physical layer, information layer, and coupling layer, and proposes a unified matrix modeling calculation method based on hybrid calculation; for different communication scenarios, the communication effect of the model under various scenarios is studied; based on the physical layer of the distribution system, the information layer of the communication network, and the coupling layer model and data communication of the coupling network, the delay and probability key data in the same-dimensional adjacency matrix are extracted, and a unified model is established, thereby realizing the unified modeling of power flow and information flow in the new distribution system. The present invention effectively improves the interaction effect between the various levels in the new distribution system under non-ideal communication conditions, and improves the real-time performance and reliability of the power information-physical coupling model of the new distribution system.

Description

Technical Field

[0001] The present invention relates to the technical field related to modeling and simulation of power distribution systems, and in particular to a power information-physical coupling modeling method for a new type of power distribution system. Background Art

[0002] The joint simulation of the new distribution system CPS mainly combines physical and digital technologies to create a new intelligent distribution environment and study the operation and control of the new distribution system under the influence of various communication factors. However, before the breakthrough in the theoretical research of power CPS, software simulation based on the prototype characteristics of the distribution system occupied a dominant position in the simulation, testing and verification support of theoretical and practical research. Therefore, it is necessary to establish a platform to simulate the multi-state and multi-fineness characteristics of CPS. Typical power system simulators use discrete steps to approximate continuous processes, while typical information system simulators use discrete state models to describe network behavior. So far, there is no unified software to simulate the two systems at the same time. In contrast, the joint simulation scheme first simulates the power and communication conditions separately, and then realizes data sharing and collaborative work through an interactive interface. This creates a combination of multiple simulators, allowing participants to interact, coordinate and cooperate with each other while retaining their own advantages. Its easy implementation and high reliability make collaborative simulation a feasible solution. This method integrates the communication model, coupling interface model and physical model into one model, reducing the difficulty of the handover between the communication system and the physical system. Based on the transformation of power flow and information flow, a coupling integrated joint simulation model is proposed, and the impact of different communication scenarios on the model is analyzed to verify the effectiveness of the model.

[0003] In summary, the information flow in the distribution system adopts a discrete state model, and the power flow adopts discrete steps to approximate the continuous process for simulation. Therefore, it is feasible to model the physical coupling of the power information system for the new distribution system. Summary of the invention

[0004] In view of the defects existing in the prior art, the present invention discloses a method for modeling power information-physical coupling for new distribution systems. The method is based on the characteristics of power CPS, and matrix modeling is performed with the physical layer, coupling layer and information layer in the new distribution system, and characteristic factors such as delay, interruption probability and error rate in the communication process are considered. At the same time, the delay composition of related communication scenarios is analyzed, and corresponding control effect improvement measures are proposed to reduce the interference of communication factors on the model, effectively overcome the message lag and error caused by communication delay, bit error rate and data congestion, and improve the real-time and reliability of the power information-physical coupling model of the new distribution system.

[0005] The present invention adopts the following technical solutions to solve the above technical problems:

[0006] A power information-physical coupling modeling method for a new distribution system includes the following contents:

[0007] In the form of multi-tuples and adjacency matrices, power data and communication data are selected to map equipment parameters and topological structures, and the power physical layer, information layer, and coupling layer of the new distribution system are modeled. The power data includes active power, reactive power, and voltage, and the communication data includes delay and bit error rate. The adjacency matrix is ​​used to reflect the information of interconnection between power nodes, power lines, and interdependent relationships, as well as the information transmitted between the communication network composed of communication nodes and their communication lines. The multi-tuple model further describes the power characteristics of power nodes, the communication characteristics of communication equipment, and the information collection and information transmission characteristics of coupling nodes.

[0008] According to the established power physical layer, information layer, and coupling layer models of the new distribution system, the communication related data in the same-dimensional adjacency matrix are extracted, and combined with the active and reactive data of the power nodes, a new distribution system power information-physical coupling model based on a unified matrix is ​​constructed.

[0009] Furthermore, the power information adjacency matrix is ​​as follows:

[0010] The multi-group model of power nodes is as follows:

[0011] v i =[K,S]

[0012] In the formula, K represents the type of this power node, and typical physical equipment in the distribution network cluster, such as power stations, substations, and controllable power points, are selected as the main characterization types; S represents the parameters of this power node when it is put into operation.

[0013] The power line edge set is as follows:

[0014] E={e1,e2,e3,...,e n}

[0015] In the formula, each element e1, e2, e3, ..., e n Represents each power line.

[0016] The power information model in the form of adjacency matrix is ​​as follows:

[0017]

[0018] In the formula, the diagonal elements are the multi-element model of the power nodes; the off-diagonal elements represent the connection relationship between nodes, and the element values ​​1 / 0 represent whether there is / is not a power line connected between the nodes.

[0019] Furthermore, the information layer adjacency matrix is ​​as follows:

[0020] The set of communication nodes in the information layer is as follows:

[0021] D={d1,d2,d3,...,d n}

[0022] In the formula, each element d1, d2, d3, ..., d n Represents each communication node.

[0023] The communication node multi-group model is as follows:

[0024] d i =[A(S),U(t),K W ]

[0025] Where A(S) represents the processing and control algorithm that should be adopted after the physical layer device information S is collected and uploaded to the information layer communication node; U(t) represents the average delay of processing data; K W Represents the bit error rate of the communication node processing data.

[0026] The communication link edge set is as follows:

[0027] C={c1,c2,c3,...,c n}

[0028] In the formula, each element c1, c2, c3, ..., c n Represents each communication link.

[0029] Among them, the unified multi-group modeling of the information flow transmission process is as follows:

[0030] c=[U C ,K B ,K F ]

[0031] Where U C represents the channel delay; K B represents the probability of channel interruption; K F Represents the bit error rate of the channel.

[0032] The communication network model in the form of an information layer adjacency matrix is ​​as follows:

[0033]

[0034] In the formula, the diagonal elements are communication nodes; the off-diagonal elements describe the communication links between communication nodes. When there is no direct communication connection between two nodes, the element c = [0], which is equivalent to an empty tuple.

[0035] Furthermore, the device interaction relationship model in the information layer and the physical layer is as follows:

[0036] r=[UR ,R B ,R F ]

[0037] Where r represents the channel performance; U R represents the delay of information collection and processing; R B represents the probability of data transmission interruption; R F Represents the error rate of information transmission.

[0038] The coupled interface model in diagonal network matrix form is as follows:

[0039]

[0040] Where the diagonal elements are coupling nodes.

[0041] Furthermore, considering the communication delay, communication congestion, and communication delay scenarios in the modeling, the communication improvement measures for different communication scenarios include: using better terminal equipment to reduce the acquisition and measurement delay; improving the network bandwidth level to improve communication congestion; setting up an error data screening program to timely remove error data;

[0042] The improvement measures for small error data are as follows:

[0043]

[0044] In the formula, x k-1 is the data received last time, x k is the new data received this time. k )=1, then the data x k It is judged as erroneous data and cleared immediately. k Use the last received data x k-1 replace.

[0045] Furthermore, the process of establishing the power information-physical coupling model of the new distribution system based on the unified matrix is ​​divided into: the process of uploading power data by the new distribution system, the process of issuing instructions by the new distribution system, and the establishment of the information-physical coupling simulation model matrix of the new distribution system.

[0046] The process of uploading power data is as follows:

[0047] The power layer data information matrix is ​​defined as G0, then the data matrix R received by the acquisition and sensing equipment in the coupling layer is rec Also G0.

[0048] The data matrix received by the communication device in the information layer, which contains power information and collected sensor information, is:

[0049]

[0050] In the formula, Stands for hybrid computing.

[0051] The process of issuing instructions is as follows:

[0052] The information layer control information matrix is ​​defined as H adj , then the data matrix R received by the information transmission device in the coupling layer send Also H adj .

[0053] The data matrix received by the power actuator in the physical layer, which contains adjustment control instructions and information transmission, is:

[0054]

[0055] Furthermore, the new power distribution system cyber-physical coupling simulation model can be represented by a matrix containing the above process:

[0056]

[0057] Furthermore, the information-physical coupling simulation model of the new distribution system includes an electric power-physical system simulation module, an information-communication system simulation module, and a control system simulation module, wherein the electric power-physical system simulation module includes modeling of an electric power system model, a control unit model, a sensor unit model, and a data interaction network interface module; the information-communication system simulation module includes a simulation interface module, a communication delay module, a communication congestion module, and a communication error module; the control system simulation module includes a data receiving and sending module, a data detection module, and a decision-making control module.

[0058] Furthermore, the information-physical coupling simulation model of the new distribution system includes an electric power physical system simulation module, an information communication system simulation module, and a control system simulation module, wherein the electric power physical system simulation module is used to establish models of the electric power physical layer, the information layer, and the coupling layer, and includes an electric power system model, a control unit model, a sensor unit model, and a data interaction network interface module; the information communication system simulation module acquires communication data for improving different communication scenarios, and includes a simulation interface module, a communication delay module, a communication congestion module, and a communication error module; the control system simulation module executes information transmission and feedback, and includes a data receiving and sending module, a data detection module, and a decision control module.

[0059] Furthermore, the power physical system simulation module is used to obtain power data and communication data information, map equipment parameters and topology structures, and then model the power physical layer, information layer and coupling layer in the new power system.

[0060] Furthermore, the information communication system simulation module adopts three communication improvement measures for three different communication scenarios:

[0061] For communication delay scenarios, terminal equipment is used to reduce collection and measurement delays; for communication congestion scenarios, the network bandwidth level is increased to improve communication congestion; for communication error scenarios, an error data screening program is set up to eliminate error data in a timely manner.

[0062] Furthermore, the control system simulation module performs the following tasks: the new distribution system uploads the power data and the new distribution system issues instructions.

[0063] Compared with the prior art, the present invention has the following beneficial effects:

[0064] 1. The present invention performs matrix modeling on the physical layer, coupling layer and information layer in the new power distribution system, taking into account characteristic factors such as delay, interruption probability and error rate in the communication process.

[0065] 2. The present invention can overcome the message lag and error effects caused by communication delay, bit error rate and data congestion.

[0066] 3. The present invention integrates the communication model, coupling interface model and physical model into the same model, thereby reducing the difficulty of the handover between the communication system and the physical system.

[0067] 4. The present invention improves the real-time performance and reliability of the power information-physical coupling model of the new distribution system. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 is a flow chart of Embodiment 1 of the present invention;

[0069] Figure 2 is a structural diagram of a simulation model of the first embodiment of the present invention;

[0070] Figure 3 1 is a comparison diagram of the active output control effect of DG without considering the influence of communication and considering the influence of communication delay according to the first embodiment of the present invention;

[0071] Figure 4 1 is a comparison diagram of the voltage control effect of DG without considering the influence of communication and considering the influence of communication delay in the first embodiment of the present invention;

[0072] Figure 5 This is a comparison diagram of the active output control effect of DG before and after communication congestion improvement in Embodiment 1 of the present invention;

[0073] Figure 6 This is a comparison diagram of DG active output control effects before and after improvement of communication large bit error data of a power information-physical coupling modeling method for a new distribution system according to a first embodiment of the present invention. DETAILED DESCRIPTION

[0074] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clearly understood, the present invention is described in detail below in conjunction with the accompanying drawings of the embodiments of the present invention and the first implementation case. It should be understood that the specific implementation case described herein is only a part of the embodiments of the present invention, which is used to explain the present invention and is not used to limit the invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0075] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and specific embodiments:

[0076] Embodiment 1

[0077] like Figure 1 As shown in FIG. 1 , a power information-physical coupling modeling method for a new distribution system includes the following contents:

[0078] In the form of multi-tuples and adjacency matrices, power data and communication data are selected to map equipment parameters and topological structures, and the power physical layer, information layer, and coupling layer of the new distribution system are modeled. The power data includes active power, reactive power, and voltage, and the communication data includes delay and bit error rate. The adjacency matrix is ​​used to reflect the information of interconnection between power nodes, power lines, and interdependent relationships, as well as the information transmitted between the communication network composed of communication nodes and their communication lines. The multi-tuple model further describes the power characteristics of power nodes, the communication characteristics of communication equipment, and the information collection and information transmission characteristics of coupling nodes.

[0079] According to the established power physical layer, information layer, and coupling layer models of the new distribution system, the communication related data in the same-dimensional adjacency matrix are extracted, and combined with the active and reactive data of the power nodes, a new distribution system power information-physical coupling model based on a unified matrix is ​​constructed.

[0080] Furthermore, the power information adjacency matrix is ​​as follows:

[0081] A multivariate model is used to describe the characteristics of power nodes:

[0082] v i =[K,S]

[0083] In the formula, K represents the type of this power node, and typical physical equipment in the distribution network cluster, such as power stations, substations, and controllable power points, are selected as the main characterization types; S represents the parameters of this power node when it is put into operation, such as capacity, active power, reactive power, and voltage, etc., and specific scenarios are analyzed specifically.

[0084] For the electrically connected power lines, they can also be abstracted as edge sets E in graph theory:

[0085] E={e1,e2,e3,...,e n}

[0086] In the formula, each element e1, e2, e3, ..., e n Represents each power line.

[0087] The adjacency matrix is ​​used to reflect the comprehensive topological relationship of the cluster power network, including the interconnection information of power nodes, power lines and mutual dependencies in the cluster.

[0088] A power network with n power nodes and their branch electrical connections is modeled, namely the power information adjacency matrix G.

[0089]

[0090] In the formula, the diagonal elements are the multi-element model of the power nodes; the off-diagonal elements represent the connection relationship between nodes, and the element e ij The value 1 / 0 represents whether there is a power line connection between nodes i and j.

[0091] Multitudes are used to model the characteristics of communication nodes and communication links of information equipment, and adjacency matrices are used to model the topology of communication networks:

[0092] The communication nodes in the information layer are represented by a set D:

[0093] D={d1,d2,d3,...,d n}

[0094] In the formula, each element d1, d2, d3, ..., d n Represents each communication node.

[0095] According to the common communication characteristics of network communication equipment, data processing algorithms, delays and bit error rates are selected to model the multi-tuple of communication nodes.

[0096] d i =[A(S),U(t),K W ]

[0097] Where A(S) represents the processing and control algorithm that should be adopted after the physical layer device information S is collected and uploaded to the information layer communication node; U(t) represents the average delay of processing data; K W Represents the bit error rate of the communication node processing data.

[0098] For the communication links used for information connection in the information layer, they can also be represented by a link edge set C:

[0099] C={c1,c2,c3,...,c n}

[0100] In the formula, each element c1, c2, c3, ..., c n Represents each communication link.

[0101] The above information flow transmission process is modeled as a unified multi-group:

[0102] c=[U C ,K B ,K F ]

[0103] Where U C represents the channel delay; K B represents the probability of channel interruption; K F Represents the bit error rate of the channel.

[0104] Based on the communication node and line model established above, for a communication network consisting of n communication nodes and their communication lines, the communication network model in the form of an adjacency matrix is ​​as follows:

[0105]

[0106] In the formula, the diagonal elements are communication nodes; the off-diagonal elements describe the communication links between communication nodes. When there is no direct communication connection between two nodes, the element c = [0], which is equivalent to an empty tuple.

[0107] Furthermore, the coupling layer modeling method includes the following contents:

[0108] The measurement, control and execution functions of secondary equipment are described by multi-tuples, and the interaction relationship between equipment in the information layer and the physical layer is modeled by diagonal matrix mapping.

[0109] r=[U R ,R B ,R F ]

[0110] Where r represents the channel performance; U R represents the delay of information collection and processing; R B represents the probability of data transmission interruption; R F Represents the error rate of information transmission.

[0111] Assuming that there are n power nodes that need to interact with an equal number of communication nodes, a coupling interface diagonal network matrix containing n coupling nodes is required, as shown below:

[0112]

[0113] Where the diagonal elements are coupling nodes.

[0114] Furthermore, considering the communication delay, communication congestion, and communication delay scenarios in the modeling, the communication improvement measures for different communication scenarios include: using better terminal equipment to reduce the acquisition and measurement delay; improving the network bandwidth level to improve communication congestion; setting up an error data screening program to timely remove error data;

[0115] The improvement measures for small error data are as follows:

[0116] Improvement measures for small error data:

[0117]

[0118] In the formula, x k-1 is the data received last time, x k is the new data received this time. k )=1, then the data x k It is judged as erroneous data and cleared immediately. k Use the last received data x k-1 replace.

[0119] Furthermore, the process of establishing the power information-physical coupling model of the new distribution system based on the unified matrix is ​​divided into: the process of uploading power data by the new distribution system, the process of issuing instructions by the new distribution system, and the establishment of the information-physical coupling simulation model matrix of the new distribution system:

[0120] The process of uploading power data, that is, the process of converting power flow into information flow when the physical layer data is transmitted to the information layer, is as follows:

[0121] The power layer data information matrix is ​​defined as G0, then the data matrix R received by the acquisition and sensing equipment in the coupling layer is rec Also G0.

[0122] R rec =G0

[0123] The communication device in the information layer receives the data matrix H containing power information and collected sensor information. rec for:

[0124]

[0125] In the formula, Stands for hybrid computing.

[0126] The process of issuing instructions, that is, the process of converting information flow into power flow when the message of the information layer is sent to the physical layer, is as follows:

[0127] The information layer control information matrix is ​​defined as H adj , then the data matrix R received by the information transmission device in the coupling layer send Also H adj .

[0128] R send =H adj

[0129] The power execution device in the physical layer receives the data matrix G containing adjustment control instructions and information transmission. rec for:

[0130]

[0131] The new power distribution system information-physical coupling simulation model can be represented by a matrix W containing the above process, and its structure can be defined as follows:

[0132]

[0133] Furthermore, the information-physical coupling simulation model of the new distribution system includes an electric power physical system simulation module, an information communication system simulation module, and a control system simulation module, wherein the electric power physical system simulation module is used to establish models of the electric power physical layer, the information layer, and the coupling layer, and includes an electric power system model, a control unit model, a sensor unit model, and a data interaction network interface module; the information communication system simulation module acquires communication data for improving different communication scenarios, and includes a simulation interface module, a communication delay module, a communication congestion module, and a communication error module; the control system simulation module executes information transmission and feedback, and includes a data receiving and sending module, a data detection module, and a decision control module.

[0134] Furthermore, the power physical system simulation module is used to obtain power data and communication data information, map equipment parameters and topology structures, and then model the power physical layer, information layer and coupling layer in the new power system.

[0135] Furthermore, the information communication system simulation module adopts three communication improvement measures for three different communication scenarios:

[0136] For communication delay scenarios, terminal equipment is used to reduce collection and measurement delays; for communication congestion scenarios, the network bandwidth level is increased to improve communication congestion; for communication error scenarios, an error data screening program is set up to eliminate error data in a timely manner.

[0137] Furthermore, the control system simulation module performs the following tasks: the new distribution system uploads the power data and the new distribution system issues instructions.

[0138] The physical information simulation model of the power distribution network in this implementation case is as follows Figure 2 As shown in the figure, the system consists of 6 communication nodes and 6 distributed power sources. The specific parameters of the 6 DGs are shown in Table 1. Considering the high reliability of optical fiber communication, it is believed that the delay of optical signals in optical fiber communication is 5μs / km. The delay of short-distance carrier communication mainly considers the influence of the frequency band of the communication line. The data transmission rates of the high-frequency band and the low-frequency band are 0.1Mb / s and 20Mb / s respectively. In the simulation model, the d1-d3 line uses a high-frequency band carrier, the d6-d4 line uses a low-frequency band carrier, and the remaining lines use optical fiber. The average delay of RTU data collection is 100ms.

[0139] Table 1 DG capacity

[0140]

[0141] Table 2 Distance between DG installation points

[0142]

[0143] According to the power information-physics coupling modeling method proposed in the present invention, the simulation of Case 1 is carried out in MATLAB.

[0144] like Figure 3 , Figure 4 As shown in the figure, the system has two control actions at 0.1s and 0.4s respectively. In the communication scenario with transmission delay, the action delay of DG20 is about 0.01-0.02s. Without considering the influence of communication and considering the influence of delay, there is little difference between the active output and bus voltage control of DG20. It is just that the delayed communication lags slightly behind the ideal communication scenario in action time, which still meets the system real-time and reliability requirements.

[0145] Figure 5 The change of DG active power before and after the communication congestion is improved is shown. It can be seen that the whole system based on the power information physical coupling modeling method proposed by the present invention can improve the delay by 50% compared with the congested communication scenario, the congestion is greatly alleviated, and the active output curve of DG20 is gradually smoothed, meeting the real-time and reliability requirements of the system.

[0146] Figure 6 The DG active power changes before and after the communication error is improved are shown. The power information physical coupling modeling method proposed in the present invention can immediately determine that DG20 has received the error data, clean up the data in time, and use the previous communication data for transition, so that the system can restore real-time performance and reliability.

[0147] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A power information-physical coupling modeling method for a new power distribution system, characterized in that: Includes the following: In the form of multi-tuples and adjacency matrices, power data and communication data are selected to map equipment parameters and topological structures, and the power physical layer, information layer, and coupling layer of the new distribution system are modeled. The power data includes active power, reactive power, and voltage, and the communication data includes delay and bit error rate. The adjacency matrix is ​​used to reflect the information of interconnection between power nodes, power lines, and interdependent relationships, as well as the information transmitted between the communication network composed of communication nodes and their communication lines. The multi-tuple model further describes the power characteristics of power nodes, the communication characteristics of communication equipment, and the information collection and information transmission characteristics of coupling nodes. According to the established power physical layer, information layer, and coupling layer models of the new distribution system, the communication-related data in the same-dimensional adjacency matrix are extracted, and combined with the active and reactive data of the power nodes, a new power information-physical coupling model of the distribution system based on a unified matrix is ​​constructed; The method also includes communication improvement measures for different communication scenarios, specifically including: for communication delay scenarios, using terminal equipment to reduce acquisition and measurement delays; for communication congestion scenarios, improving network bandwidth levels to improve communication congestion; for communication error scenarios, setting an error data screening program to timely remove error data; The improvement measures for small error data are as follows: In the formula, x k-1 is the data received last time, x k is the new data received this time, when y(x k )=1, then the data x k It is judged as erroneous data and cleared immediately. k Use the last received data x k-1 replace.

2. According to claim 1, a power information-physical coupling modeling method for a new power distribution system is characterized in that: The modeling methods of the power physical layer and information layer of the new power distribution system are as follows: The power physical layer is modeled as follows: The power nodes, power links and power networks of the physical layer of the new power distribution system are modeled in the form of multi-tuples and adjacency matrices: A multivariate model is used to describe the characteristics of power nodes: v i =[K,S] In the formula, K represents the type of this power node, and typical physical equipment in the distribution network cluster, such as power stations, substations, and controllable power points, are selected as the main characterization types; S represents the parameters of this power node when it is put into operation; For the electrically connected power lines, they can also be abstracted as edge sets E in graph theory: And={e1,e2,e3,...,e n } In the formula, each element e1, e2, e3, ..., e n Represents each power line; The adjacency matrix is ​​used to reflect the comprehensive topological relationship of the cluster power network, including the interconnection information of power nodes, power lines and mutual dependencies in the cluster; Model a power network with n power nodes and their branch electrical connections, namely, the power information adjacency matrix G; In the formula, the diagonal elements are the multi-element model of the power nodes; the off-diagonal elements represent the connection relationship between nodes, and the element e in The value 1 / 0 represents whether there is / is not a power line connected between nodes i and n; The information layer is modeled as follows: Multitudes are used to model the characteristics of communication nodes and communication links of information equipment, and adjacency matrices are used to model the topology of communication networks: The communication nodes in the information layer are represented by a set D: <h2 style=";text-align:left;direction:ltr">D = {d1,d2,d3,...,d<h2 style=";text-align:left;direction:ltr"> n <h2 style=";text-align:left;direction:ltr">} In the formula, each element d1, d2, d3, ..., d n Represents each communication node; According to the common communication characteristics of network communication equipment, data processing algorithms, delays and bit error rates are selected to model the multi-tuple of communication nodes; d i =[A(S),U(t),K W ] Where A(S) represents the processing and control algorithm that should be adopted after the physical layer device information S is collected and uploaded to the information layer communication node; U(t) represents the average delay of processing data; K W Represents the bit error rate of the communication node processing data results; For the communication links used for information connection in the information layer, they can also be represented by a link edge set C: C={c1,c2,c3,...,c n } In the formula, each element c1, c2, c3, ..., c n Represents each communication link; The above information flow transmission process is modeled as a unified multi-group: c=[U C ,K B ,K F ] Where U C represents the channel delay; K B represents the probability of channel interruption; K F Represents the bit error rate of the channel; Based on the communication node and line model established above, for a communication network consisting of n communication nodes and their communication lines, the communication network model in the form of an adjacency matrix is ​​as follows: In the formula, the diagonal elements are communication nodes; the off-diagonal elements describe the communication links between communication nodes. When there is no direct communication connection between two nodes, the element c ni =[0], equivalent to an empty tuple.

3. The method for power information-physical coupling modeling for a new power distribution system according to claim 1, characterized in that: The coupling layer modeling method is as follows: The measurement, control and execution functions of secondary equipment are described by multi-tuples, and the interaction relationship between equipment in the information layer and the physical layer is modeled by diagonal matrix mapping; r=[U R ,R B ,R F ] Where r represents the channel performance; U R represents the delay of information collection and processing; R B Represents the probability of data transmission interruption; R F Represents the error rate of information transmission; Assuming that there are n power nodes that need to interact with an equal number of communication nodes, a coupling interface diagonal network matrix containing n coupling nodes is required, as shown below: Where the diagonal elements are coupling nodes.

4. The method for power information-physical coupling modeling for a new power distribution system according to claim 1, characterized in that: The process of establishing the power information-physical coupling model of the new distribution system based on the unified matrix is ​​divided into: the process of uploading power data by the new distribution system, the process of issuing instructions by the new distribution system, and the establishment of the information-physical coupling simulation model matrix of the new distribution system; The process of uploading power data is as follows: The power layer data information matrix is ​​defined as G0, then the data matrix R received by the acquisition and sensing equipment in the coupling layer is rec Also G0; R rec =G0 The communication device in the information layer receives the data matrix H containing power information and collected sensor information. rec for: In the formula, stands for hybrid computing; The process of issuing instructions is as follows: The information layer control information matrix is ​​defined as H adj , then the data matrix R received by the information transmission device in the coupling layer send Also H adj ; R send =H adj The power execution device in the physical layer receives the data matrix G containing adjustment control instructions and information transmission. rec for: The new power distribution system information-physical coupling simulation model can be represented by a matrix W containing the above process, and its structure can be defined as follows:

5. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, which is used to execute the method described in any one of claims 1 to 4 when the computer program is executed, so as to realize the process of power information-physical coupling modeling of a novel power distribution system.

6. A power information-physical coupling modeling device for a new power distribution system, which is used to implement a power information-physical coupling modeling method for a new power distribution system according to any one of claims 1 to 4, characterized in that: It includes an electric power physical system simulation module, an information communication system simulation module, and a control system simulation module, wherein the electric power physical system simulation module is used for establishing models of the electric power physical layer, the information layer, and the coupling layer, and includes an electric power system model, a control unit model, a sensor unit model, and a data interaction network interface module; the information communication system simulation module acquires communication data for improving different communication scenarios, and includes a simulation interface module, a communication delay module, a communication congestion module, and a communication error module; the control system simulation module executes information transmission and feedback, and includes a data receiving and sending module, a data detection module, and a decision control module.

7. The power information-physical coupling modeling device for a new power distribution system according to claim 6, characterized in that: The power physical system simulation module is used to acquire power data and communication data information, map device parameters and topology, and then model the power physical layer, information layer and coupling layer in the new power system.

8. The power information-physical coupling modeling device for a new power distribution system according to claim 6, characterized in that: The information communication system simulation module adopts three communication improvement measures for three different communication scenarios: For communication delay scenarios, terminal equipment is used to reduce collection and measurement delays; for communication congestion scenarios, the network bandwidth level is increased to improve communication congestion; for communication error scenarios, an error data screening program is set up to eliminate error data in a timely manner.

9. The power information-physical coupling modeling device for a new power distribution system according to claim 6, characterized in that: The control system simulation module performs the following tasks: the new power distribution system uploads power data and the new power distribution system issues instructions.

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