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Cognitive Radio Network for the Smart Grid: Experimental System Architecture, Control, Algorithm, Security and Microgrid

Cognitive Radio Network for the Smart Grid: Experimental System Architecture, Control, Algorithm, Security and Microgrid Testbed. Yujie Tang Supervisor: Professor J. W. Mark March 1 st , 2012. Outline. 1. Introduction. 2. Communication testbeds for Smart Grid.

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Cognitive Radio Network for the Smart Grid: Experimental System Architecture, Control, Algorithm, Security and Microgrid

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  1. Cognitive Radio Network for the Smart Grid: Experimental System Architecture, Control, Algorithm, Security and Microgrid Testbed Yujie Tang Supervisor: Professor J. W. Mark March 1st, 2012

  2. Outline 1. Introduction 2. Communication testbeds for Smart Grid 3. Host computer with graphics processing 4. Microgridtestbeds for Smart Grid 5. Conclusion

  3. Outline 1. Introduction 2. Communication testbeds for Smart Grid 3. Host computer with graphics processing 4. Microgridtestbeds for Smart Grid 5. Conclusion

  4. Introduction • Smart Grid: In a nutshell, smart grid amounts to providing an Internet Protocol (IP) address to every device that is connected to the electricity grid. • Advantages of smart grid: • Reducing blackouts • Promoting renewable energy usage • Give families more control over their energy diet • Secure Communications in Smart Grid • Physical layer and cybersecurity • Latency for time-sensitive data (CR)

  5. Introduction • Related work • Using Cognitive Radio in the Smart Grid in [1]-[3] • Building a Cognitive Radio network testbed at TTU, [4]: the overall picture of this project [1]. R. Qiu, “A cognitive radio network testbed,” Proposal to Office of Naval Research (ONR), Sep. 2010, currently funded. [2]. R. C. Qiu, “Cognitive radio and smart grid,” presented at the IEEE Chapter, Huntsville, AL, Feb. 18, 2010 [Online]. Available: http://iweb.tntech.edu/rqiu/publications.htm [3]. R. C. Qiu, “Smart grid research at TTU,” Argonne National Laboratory, Feb. 2010 [Online]. Available: http://iweb.tntech.edu/rqiu/publications.htm [4]. R. C. Qiu, Z. Chen, N. Guo, Y. Song, P. Zhang, H. Li, and L. Lai, “Towards a real-time cognitive radio network testbed: architecture, hardware platform, and application to smart grid,” in Proc. 5th IEEE Workshop Netw. Technol. Software-Defined Radio White Space, Jun. 2010.

  6. Introduction • Main Contributions • The application of Cognitive Radio to the Smart Grid being addressed systemically • Applying a complex independent component analysis (ICA) technique, in combination with robust principle component analysis (PCA) algorithm • Microgrid testbed: include various distributed energy resources, different power loads or appliances and control modules • Layered and hybrid control strategy

  7. Outline 1. Introduction 2. Communication testbeds for Smart Grid 3. Host computer with graphics processing 4. Microgridtestbeds for Smart Grid 5. Conclusion

  8. Communication testbed for SG • Hardware platforms for CRN • Virginia Tech developed a testbed for CRN with 48 nodes. • Each node consists of an Intel Xeon processor-based high-performance sever, a USRP2 and a custom developed radiofrequency (RF) daughterboard • It is not a low-power processing platform • It is not capable of mobility • Four kinds of hardware platforms

  9. Communication testbed for SG • Universal Software Radio Peripheral 2 (USRP2) • Consists of a motherboard and one or more selectable RF daughterboard • Works with GNU radio • Has random response delay and needs multicore CPU

  10. Communication testbed for SG • Small Form Factor Software Defined Radio Development Platform (SFF SDR DP) • Digital processing module, data conversion module and RF module • Moved easily and full-duplex communications • Not easy to update and response time delay

  11. Communication testbed for SG • Wireless Open-Access Research Platform Development Platform (WARP) • An FPGA (Xilinx Virtex-4 FX100 FPGA) board and one to four radio boards • A SFF independent hardware platform, physical and MAC • Can not implement full-duplex communications

  12. Communication testbed for SG • Microsoft Research Software Radio (Sora Platform) • A radio control board (RBC) and a selectable RF board, works with a multicore host computer • A high-throughput interface • Speedup trick is not easy, full-duplex is challenging and lacks mobility

  13. Communication testbed for SG • Proposed Testbed for CRN and SG • Performing time-critical tasks in the FPGA and split MAC design with host and FPGA implementations • Ample power and upgradable • Minimum response time delay • Full-duplex communications • Proposed motherboard, functional architecture and network testbeds

  14. Communication testbed for SG • Mortherboard for Hardware Platforms

  15. Communication testbed for SG • Functional architecture for the nodes • Network testbed

  16. Communication testbed for SG • Security of the network testbed • The data sent out by the nodes should be encrypted, to prevent unauthorized users from intercepting the data over the air (cryptographic algorithms) • The reconfigurable FPGAs in the network testbed should have the capability of protecting themselves from being invaded or tampered (an open question)

  17. Outline 1. Introduction 2. Communication testbeds for Smart Grid 3. Host computer with graphics processing 4. Microgridtestbeds for Smart Grid 5. Conclusion

  18. Host computer with GPU • GPGPU: the various cores of a graphics processor unit (GPU) can be utilized for general purpose parallel computing • CUDA: both a hardware and software architecture by Nvidia • Allows GPUs to run programs written by C, C++, Fortran, etc • CULA is a linear algebra library which utilize to Nvidia CUDA architecture for computational acceleration • CULA offers more functions than GPUmat

  19. Outline 1. Introduction 2. Communication testbeds for Smart Grid 3. Host computer with graphics processing 4. Microgridtestbeds for Smart Grid 5. Conclusion

  20. Microgrid testbeds for SG • Microgrid: a localized grouping of electrical sources and loads • Contains distributed generators or distributed energy sources • Increase the local reliability, reduce the power loss, maintain the local power voltage and enhance power utilization and efficiency • Microgrid testbeds • Integrated renewable or distributed energy sources, less exchange of power • Intelligent communications and efficiency power dispatch • Battery and inverter technology, such as plug-in vehicles and energy storage

  21. Smart houses, microgrid central controller, main electrical power grid, one common energy storage and common secondary power sources • Controller together with smart meters: operation, maintenance, administration and provisioning of microgrid • Action theory can be explored in the microgrid central controller to determine the trading price and the trading quantity of energy Fig. Microgrid testbeds for SG

  22. Microgrid testbeds for SG • Control strategy • Layered and hybrid • Different subproblems solved by different functions (different control layer and different control modules) • Requirement: loading balancing, electrical generation, the limitation and efficiency of storage • The function of knowledge representation and reasoning (means the representaion of knowledge in a manner that helps in inferencing from knowledge) • A presentation of related knowledge • A cognition loop using artificial intelligence • Heuristic algorithm for the distributed control or noncooperative control • Game theory in a complex system

  23. Microgrid testbeds for SG • Take one control problem in the single smart house as an example Fig. The total cost affected by the capacity of energy storage

  24. Microgrid testbeds for SG • Security consideration • For information flow– date confidentiality, data authenticity, data integrity, data freshness, data privacy, public key infrastructure, trusted computing , attack detection, attack survivability, intelligent monitoring, cybersecurity, and so on • For energy flow– autonomous recovery is the main security consideration • Deal with the optimization issue with uncertainty • Robust optimization: the performance is stable with the bounded errors • Stochastic optimization: guarantee the performance in average for the uncertainty information

  25. Microgrid testbeds for SG • Kernel GLRT for malicious data attack [5] Y. Liu, M. K. Reiter, and P. Ning, “False data injection attacks against state estimation in electric power grids,” in Proc. 16th Conf. Comput. Commun. Security, 2009, pp. 21–32. [6] O. Kosut, L. Jia, R. J. Thomas, and L. Tong, “On malicious data attacks on power system state estimation,” in Proc. Universities Power Eng. Conf. (UPEC), 2010, pp. 1–6. [7] O. Kosut, L. Jia, R. Thomas, and L. Tong, “Malicious data attacks on smart grid state estimation: Attack strategies and countermeasures,” in Proc. 1st IEEE Int. Conf. Smart Grid Commun., Gaithersburg, MD, Oct. 2010, pp. 220–225. • ICA for recovery of smart meter transmission in the presence of strong interference

  26. Outline 1. Introduction 2. Communication testbeds for Smart Grid 3. Host computer with graphics processing 4. Microgridtestbeds for Smart Grid 5. Conclusion

  27. Conclusion • The big picture is to sense, communicate, compute and control • This paper is the first to systematically investigate the new idea of using the next generation wireless technology, cognitive radio network, for the SG • System architecture,algorithms and hardware testbed are studied in detail • A microgrid testbed is proposed • Control strategies and security considerations are discussed

  28. Q & A Thank you!

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