The development of a smart grid and communication co-simulator

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1 The development of a smart grid and communication co-simulator W H Lau, Simon Shum, Ryan Lam, Henry Chung, Norman C F Tse and L L Lai Centre for Smart Energy Conversion and Utilization Research City University of Hong Kong State Grid Energy Research Institute, China Abstract 1 - Facing the ever increasing demand of energy and the forthcoming shortage of energy resources, renewable energy generation becomes important in power generation. With the integration of various distributed energy resources, a smart grid is created. For the traditional power grid system, the control is usually based on a dedicated communication system. With the smart grid, all control and data may be exchanged through a public communication network. The unavoidable latency could cause desirable effects to the grid reliability and hence a software system for simulating these situations becomes essential. This paper presents some important considerations for developing a co-simulation software that incorporates a power system software simulator and a communication network simulator. The framework design of the co-simulator and preliminary results are given in this paper. 1. Introduction Facing the urgent need of reducing the greenhouse gas emission and increasing the efficiency of electricity utilization, traditional power delivery network is unable to cope with the new requirement. Renewable energy resources like solar PV panels and wind turbines are being integrated into the power grid network. In addition, the installation of roof-top PV panels and small wind turbines becomes popular in residential households. These additional energy sources become distributed energy sources and they will inject energy into the power grid. For the existing power grid systems, almost all of them are designed to delivery electricity to consumers. However, the renewable energy sources cause the power flow in the grid no longer in one direction since surplus electricity from them may flow into the power grid. The integration of renewable energy sources could cause undesirable effects This research is supported by the Centre for Smart Energy Conversion and Utilization Research, City University of Hong Kong to the power grid. The renewable energy resources connected to the power grid results in a more advanced and complex power grid smart grid. For the traditional power grid system, the control is usually achieved through a dedicated communication system, typical one is the SCADA (Supervisory Control And Data Acquisition) framework. With smart grid, the control and co-ordination of various stakeholders creates a complicated scenario. New distributed energy sources can be introduced as required and they must communicate with the central control system in form of Plug and Play manner. All these new installations must communicate with the central control station such that their operation conditions and status can be monitored and analyzed so as to avoid disaster happening. The intermittent nature of renewable energy sources and changing power demand pattern has a profound impact on the smart grid. The success of the smart grid relies on an advanced communication infrastructure with support for security and real-time communication. The design and co-ordination of both the power grid network and communication network requires extensive study. In the last few years, efforts have been focused on developing co-simulation of smart grid and communication network in order to study and examine the operational aspects of the entire system [1-6]. However, these co-simulations only focus on specific components and with a limited scope of study. A more comprehensive co-simulation software package is not yet available. Nevertheless, the complexity of the entire smart grid poses a great challenge to the design of such a comprehensive software package. In this paper, some important aspects of the co-simulation software will be discussed and an illustration of using PSCAD and to form a simple framework of the co-simulator will be given. 2. Co-simulator requirement The key components of co-simulator include a power system simulator and a communication

2 network simulator and these two simulators must exchange data for realizing the real-time action. For the power system simulator, it is required to cover the following topics: i. Reliability ii. Load flow iii. Fault analysis iv. Protection v. Transient stability vi. Optimal dispatch of generating units (unit commitment) vii. Transmission (optimal power flow) viii. Reactive power planning ix. System impact due to clean energy For the communicate network simulator, it needs to cover different network connection and data transmission protocols as listed in the following: i. LAN ii. WAN iii. WiFi iv. GSM v. 3G vi. LTE vii. WiMax viii. ZigBee ix. TCP/IP x. UTP Since it is rather complicated and not economical to develop a co-simulator from scratch, all research reported in the literature are based on existing software packages. However, the challenging issue is on the bridging between two software packages with different operation nature as well as data exchange among themselves. For the design of the power system simulator, it is generally modeled as continuous system. On the other hand, the design of the communication network simulator is modeled as a discrete system. The most critical issue on designing a co-simulator is to resolve the interface between the two software packages. A framework is required for facilitating the data exchange and time synchronization between the two different software packages running in different machines. In particular, the time synchronization is extremely important since catastrophic events may occur if data packet containing control signals are delayed or even lost. A co-simulation engine is required to ensure time synchronization for both simulators and decision making for various events occurring in the smart grid. With this co-simulator, the automatic generation and load control over a wide area can be simulated with detailed power system and communication network models. The responsiveness of the smart grid to undesirable events can be well studied and analyzed. The results generated will provide a clear picture of the influences to the smart grid operation due to communication system and network traffic. However, it is clear that the development of a comprehensive co-simulator is not a simple task. 3. Software implementation Both open sources and commercial tools are available for power system and communication network simulation. To name a few, the power system simulators include but not limited to Modelica [1,7], PSLF [3], PSS/E [8], GE-PSLF [9], MATLAB [5,6] and PSCAD/EMTSDC [10,11]. For communication network simulators, the most popular ones are NS2 (open source developed by UC Berkley) [1-3], OMNet [5,7] and [12,13]. 3.1 Power system simulator The modeling of power system is in general described by continuous functions. In computer simulation, this will be turned into a sampled system since the system will be evaluated at regular interval, nevertheless, it is still regarded as a continuous system. In our co-simulator design, PSCAD/EMTDC is adopted for the power system simulation. Users can define their component models for the simulations and PSCAD/EMTDC also provides two subroutines, DSDYN and DSOUT, to interface with other software package. This is an important aspect since the simulation needs to be stop and new control parameters have to be entered for responding to a particular event for resuming simulation. The DSDYN and DSOUT subroutines allow user to define the smart grid in a flexible manner. They provide accessibility for control and monitoring of system variables and enable both the control of input variables and the monitoring of output variables all within the same time step. The flow chart shown in Figure 1 illustrates the application of DSDYN and DSOUT. These two subroutines allow simulation to be stopped and resumed with new parameters which facilitates the operation alteration for event handling.

3 Esys Interface for data exchanging with external system, for example a co-simulation engine in our case, as shown in Figure 2. Simulation Models Simulation Kernel Esys Interface Co-Simulation Engine Figure 1. Interface routines DSYN and DSOUT 3.2 Communication network simulator The use of public network is unavoidable in smart grid. The distributed nature of the renewable energy sources and mobile loads (EV) require the components to be connected to the nearest communication network access point, Wi-Fi, LAN, WAN, even via wireless connection through 2G/3G. The latency delay of the data sent by a grid component reaching another component varies depending on the routing path and network traffic. The reliability of the smart grid heavy relies on the co-ordination among all grid connected components. If the delay is too long to hinder fast action, undesirable situation would occur. is chosen for network simulation tool for our co-simulator development. Users can use the modeler to define the transmission protocols and network architecture/infrastructure including wired and wireless networks for simulating the latency, network traffic and QoS (Quality of Service). The latency can be statistically measured and the responsiveness of the smart grid can be studied. also provides a function called Figure 2. Esys Interface function 3.3 Co-simulation engine The core component of the co-simulator is the co-simulation engine. The co-simulation engine is responsible for steering the entire operation of the simulation. It should be noted that the two simulators may be run in two different machines and the timelines are different. One important function is to perform time synchronization between the two simulators. Another important function is for making decision for event handling. Tools like MATLAB/Simulink have been used for the implementation. However, using C or C++ to develop the engine is more flexible and an agent based design will also be adopted so as to cater for different events. The scale of the co-simulation engine depends on the functionalities requirement. 3.4 Example of event handling In normal operation, PSCAD/EMTDC generates status information of various grid components and they may communicate with control system at a regular interval. However, if an unexpected event occurs, grid component will send data to central control for decision making or receiving command from central control to perform certain tasks. These unexpected events are asynchronous to the simulation timeline for both simulators running in different machines. Therefore the transmission and reception of data through the communication network are discrete events. The scenarios are illustrated in the following Figure 3. In case 1, a grid component sends data to central control resided in co-simulation

4 engine at t 0 and receives command in t 1. The delay involves the turn-around delay through the network and the processing time for the central control to make decision. It is in no way that the delay will be aligned with the simulated time step of the power system simulator. Same as in Case 2, central control determines that Grid Component 2 needs to perform certain function in responding to the operating conditions of Grid Component 1. The delay will not in line with the power system simulator. network used in the system is a simple T1 trunk with MBits/s. Power System Model EMTDC Case 1 t 0 Grid Component Co-Sim Engine (CSE) t 1 EMTDC Grid Component 1 t 0 Co-Sim Engine (CSE) Case 2 Comm. Network Model Grid Component 2 t 1 Figure 3. Event handling of the co-simulation engine 3.5 Time synchronization One important responsibility of the co-simulation engine is to perform time synchronization for both simulators to achieve co-simulation. One approach is to adopt a global scheduler to generate a global event list as shown in Figure 4. By referencing to the same timeline, the PSCAD/EMTDC will stop after one round of simulation and the CSE will check for event. The PSCAD/EMTDC will resume operation after serving an event as shown in the following figure. However, this approach is inefficient since enormous overhead will be spent on passing control among various components and the co-simulation engine. More efficient approach needs to be developed. 4. Simulations A preliminary design of the con-simulator has been implemented and a simple event is used to illustrate its functionality. The power system model and communication network model are shown in Figure 5. The communication Figure 5. Power system and Communication Network models for the simulation A load is powered by two generators from Bus 1 and Bus 2 through Line 2, with Line 1 open. An artificial fault of short-circuiting Line 2 to ground will cause Breaker 2 to open and Breaker 1 to close bringing the power supply switched to Line 1. The line voltage and real power fluctuation of 3 buses are shown in Figure 6. The corresponding frequencies of the two generators are shown in Figure 7. The behaviors of various components are clearly illustrated during the changeover period. From the simulator, the measured latency through the network is sec. for completing the changeover. This simple demonstration confirms the successful communication between PSCAD/EMTDC and.

5 Stands for one round of simulation of the power grid dynamic Event Stands for a communication network event PSCAD/ EMTDC simulator t simulator Event 1 Event 2 Event 3 Event 4 Event 5 Event 6 Figure 4. Time synchronization of the co-simulation engine Figure 6.Voltage waveforms of the 3 buses and real power of the generator and load Figure 7.Frequencies of the two generators

6 5. Conclusion With the future development of smart grid, it is import to have a tool to simulate it operational behavior for realizing a reliable design. In this paper, the design aspects of a co-simulator incorporating power system and communication network simulators have been discussed. In addition, a framework design based on PSCAD/EMTDC and has been successfully implemented. The data and control signal can be exchanged between two simulators and the latency of the communication network is successfully measured. Future effort will be focused on introducing more grid components to the co-simulator so that a comprehensive study of a smart grid becomes feasible. 6. Reference [1] V. Liberatore and A. Al-Hammouri, Smart grid communication and co-simulation, IEEE Energytech, pp. 1-5, 2011 [2] Tim Godfrey et al, Modeling Smart Grid Application with co-simulation, Proc. of 1 st IEEE Int. Conf. on SmartGridComm, pp , 2010 [3] Hua Lin et al, Power system and communication network co-simulation for smart grid applications, Proc. of the IEEE PES Innovative Smart Grid Technologies, pp. 1-6, 2011 [4] D. Anderson et al., A Virtual Smart Grid, IEEE Power and Energy Magazine, pp.49-57, Feb [5] K. Mets et al, Integrated simulation of power and communication networks for smart grid applications, Proc. of the IEEE 16 th Int. Workshop on CAMAD, pp , 2011 [6] Filip Andren et al, Framework for Co-Ordinated Simulation of Power Networks and Components in Smart Grids Using Common Communication Protocols, Proc. of the IEEE 37 th Annual Conference on IECON, pp , 2011 [8] Ahmad Farid Bin Abidin et al, A New Power Swing Detection Scheme for Distance Relay Operation, Proc. of the Int. J. of Energy, pp. 9-16, Issue 1, Vol. 3, 2009 [9] N. Lu. and A. Qiao, Composite Load Model Evaluation, PNNL-16916, Pacific Northwest National Laboratory, Richland, WA., 2007 [10] F. Delfino et al, A control algorithm for the maximum power point tracking and the reactive power injection from grid-connected PV systems, Proc. of the IEEE Power and Energy Society General Meeting, pp. 1-7, 2010 [11] Mu Wei and Zhe Chen, Intelligent control on wind farm, Proc. of the IEEE PES ISGT Europe, pp. 1-6, 2010 [12] Milan Bartl et al, Integration of Real Network Components into Modeler Co-simulation Process, WSEAS Trans. on Communications, pp , Vol. 9, 2010 [13] Xiaoyang Tong, The Co-simulation Extending for Wide-area Communication Networks in Power System Asia-Pacific Power and Energy Engineering Conference (APPEEC), pp. 1-4, 2010