With the improvement of intelligent, digital and informational degree for distribution network and the introduction of concept of micro-grid and distributed generation, smart distribution network has become a new trend in the future development of power grids . Smart distribution network is an extremely large and complex system with a large number of advanced sensing devices and distributed intelligent terminal equipment, such as FTU, TTU and other information equipment, which makes the smart distribution network show typical characteristics of cyber-physical system and form a new cyber physical model for smart distribution grid. A set of scientific, reasonable and comprehensive cyber-physical model for smart distribution grid provides theoretical and technical support for the realization of status assessment, fault diagnosis and prediction, reliability analysis and other fields of smart distribution network.
As the number of sensors and the size of information network in smart distribution network increase constantly, the impact of cyber system on the power grid is more prominent. On August 14, 2003, large portions of the Midwest and Northeast United States and Ontario, Canada, experienced an electric power blackout. An important reason was that the state estimation function was withdrawn; dispatchers lost their ability to perceive the real-time status of the power grid and failed to discover, assess and curb the spread of the fault. In 2001, El Paso Power Company from the United States had an electric power blackout; the cause was also protection malfunction due to abnormal communication delay. The company cut off a 345 kV line eventually . Therefore, it is the most critical and urgent to study the unified modeling of the power physical system and its cyber system.
2. Analysis of Cyber-Physical Model for Smart Distribution Grid
With the advance of smart grid, the available information resources and communication condition have undergone fundamental changes, the system structure is becoming more complex, and the network transmission of information brings challenges to fault identification, rationality and completeness of configuration, the fault type and operation of the power grid. Information flow becomes an indispensable link in the closed-loop chain of power flow. In this context, the coupling of power flow and information flow present the following characteristics: 1) the power flow is more closely coupled with the information flow, so that physical system and cyber system has become deeply integrated. 2) The dynamic process of the distribution network system is more complicated, and the requirement for real-time control is higher.
So, the cyber-physical model is a hot spot of many scholars, scholars have made some achievements according to the heterogeneity of system, time behavior of cyber system, cyber model and so on  . However, due to the heterogeneity of physical system and cyber system, the modeling of the physical layer and cyber layer is fragmented, and building a fusion model is very difficult. The method of hybrid system modeling is adopted in reference , which embodies the characteristics of cyber-physical system, but it cannot fully reflect the fusion of physical system and cyber system. So far there is no unified modeling method of cyber-physical system. Reference  gives a preliminary model framework of the cyber-physical system for power grid, which has some guiding significance for the development of power CPS model. In this section, the method and content of cyber-physical model are described in detail.
2.1. Content of Cyber-Physical Model
In cyber-physical system, the physical system is a continuous system and has a set of mature and complete quantitative analysis method of power modeling and simulation by employing calculus. The cyber system is a discrete system, and has a complete quantitative analysis method of information flow modeling and simulation through the event-driven mechanism of the finite state machine, such as OPNET (Optimized Network Engineering Tools). OPNET is a network simulation technology software package. It can accurately analyze the performance and behavior of complex network and can be inserted into standard or user-specified probe to collect data anywhere in the network model. The simulation data obtained through the probe can be displayed by graphics, data, or a third-party software package. However, the analysis method of power flow does not conform to the model of information flow and vice versa.
So, we propose to establish the coupling model in information flow simulation software to solve the quantitative analysis of cyber-physical model for smart distribution network. The content of cyber-physical model includes three parts:
1) Modeling of physical devices: In cyber-physical system, IED (Intelligent Electronic Device) is the carrier of power system operation. The IED consists of one or more processors. It can receive and transmit data from an external source or control an external source, and can also perform one or more logical contact tasks within the specified range of interfaces .
2) Modeling of information flow: At present, the operation function of distribution network system is based on information flow which includes three types: SV (Sampled Value), GOOSE (Generic Object Oriented Substation Event) and MMS (Manufacture Message Specification). The SV is a communication service for real-time transmission of digital sampling information, including voltage and current sampled value . The GOOSE is an object-oriented substation event, mainly used to achieve real-time information interaction between intelligent electronic equipment , including switch position information, trip signal, blocking signal, etc. MMS message belongs to the information flow between compartment and station level. The MMS network is the bridge between compartment and station level, including the calling and modification of relay protection setting value . The normal and fault conditions’ information flow in power system shows different dynamic characteristics, such as transmission law, which may lead to network fault or network blocking.
3) Modeling of communication protocol: The mode of information transmission has become digital and grown more networked, so power system has formulated a series of communication protocols and standards, these communication protocols and standards establish the communication rules and processes of modern power system, but the simulation platform of cyber system does not have the corresponding protocol model. Therefore, the communication protocol model based on smart distribution network system can accurately and completely describe the dynamic process of the cyber-physical system.
2.2. Method of Cyber-Physical Model for Distribution Network
3. Example of Cyber-Physical Model for Smart Distribution Grid
In this paper, the equipment model and information flow model of smart distribution network are constructed based on the OPNET simulation platform, which reflect the dynamic operating characteristics of the system. This paper also analyzes the dynamic characteristics of information flow of relay protection IED and switch.
3.1. Model of Smart Substation
Figure 1. Modeling method of information branch.
level. The interface node completes the mapping of the SV from the application layer to the data link layer. The data link node sends SV to the transmitter, the receiver sends SV to data link node. The data link node completes the mapping of SV from data link layer to application layer. The merging unit model of smart substation is shown in Figure 2.
2) Modeling of IED: Taking the relay protective IED as an example, the protective IED is similar to the merging unit in message header, protocol resolution and data transmission, but the application layer is different. The state transition of application layer is shown in Figure 3. The application layer of protective IED
Figure 2. Merging unit model of smart substation.
Figure 3. State transition of the application layer.
devices is initialized and then skips to idle state. SV messages are uploaded to the application layer through protocol parsing of physical and data link layer, which generates corresponding flow interruption, the status is transferred to parsing stage of SV, then takes out the relevant fields by protection algorithm from data packet, and the logic decision of protection action by combining the latest COOSE.
3.2. Assessment Method of Line Fault
The vulnerability of power system can be evaluated by N-1 method, which scan all possible line faults and analyze system’s each response. In cyber system, information failure may cause the system to generate improper control instructions, thereby affecting physical system.
Therefore, based on its influence on information network, information failure can be divided into two types: topology fault and line fault. There are four kinds of line fault in power system: transmission error, transmission delay, and transmission interrupt and transmission dislocation. Transmission delay is one of the most common faults in the actual site. As the name suggests, the failure causes a delay in the transmission of some data. For the information transmission branch ƒx, if the transmission of data sx occurs the delay of Δt, mapping operator of the branch mapping model increases by Δt.
3.3. Simulation Example
In this paper, the example is based on 110 kV communication network of a practical 110 kV smart substation. Building the exchange model of total net transmission scenario based on OPNET platform, this paper analyzes the action response of relay protection in line fault. The network topology is shown in Figure 4.
Referring to the previous section, the simulation mainly makes statistical analysis of the transmission delay of typical objects, such as Table 1.
When the line fault occurs, the maximum amplitude of the SV transmission delay reaches 80 s, although the transmission delay of SV is increased by different amplitudes compared with the steady state, but still in the message standard
Table 1. Line fault simulation results of 110 kV smart substation.
Figure 4. Topology of 110 kV communication network.
transmission delay. This is because the priority of GOOSE is higher than the SV. In the case of total net, the bandwidth is occupied, making the queue delay of SV in the switch increased.
The coupling and the interaction of power flow and information flow has become increasingly closely and important. Its emergency opens a new idea for the cyber-physical model for smart distribution grid. The cyber-physical model for smart distribution grid is a new research field; there are a lot of theoretical and technical problems to be solved. Through the analysis of coupling property of information flow and power flow, this paper introduces the content and method of cyber-physical model for smart distribution grid. Taking 110 kV typical substation as an example, we study the coupling mechanism and function of power flow and information flow, which provides guidance for cyber-physical model for smart distribution grid.
This work is supported by National Natural Science Foundation of China (51407076), the Natural Science Foundation of Hebei Province (F2014502050) and the Fundamental Re-search Funds for the Central Universities (2015ZD28).
 Yu, W.J., Xue, Y.S. and Luo, J.B. (2016)An UHV Grid Security and Stability Defense System: Considering The Risk of Power System Communication. IEEE Transactions on Smart Grid,7, 491-500. https://doi.org/10.1109/TSG.2015.2392100