A Distributed Computing Platform Supporting Power System Security Knowledge Discovery Based on Online Simulation

Power systems are generating masses of data, including measurement and simulation data. To operate and control power systems more effectively, this paper establishes a distributed platform to store, read, and compute massive amounts of data. Our distributed computing platform can support online simulation based power system security knowledge discovery through big data analysis. First, a framework for a distributed computing platform is designed. Then, distributed algorithms are developed, including a distributed massive sampling simulation method and a distributed feature selection method. Next, the software platform and hardware platform for the distributed computing platform are established. Finally, the platform is applied to the Guangdong Province Power System in China to evaluate its accuracy and efficiency. The simulation results show that the distributed computing platform can improve computing efficiency and perform better than a centralized platform.

[1]  J. Rodgers,et al.  Thirteen ways to look at the correlation coefficient , 1988 .

[2]  Roberto Battiti,et al.  Using mutual information for selecting features in supervised neural net learning , 1994, IEEE Trans. Neural Networks.

[3]  Moon,et al.  Estimation of mutual information using kernel density estimators. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[4]  M. Aganagic,et al.  Security constrained economic dispatch using nonlinear Dantzig-Wolfe decomposition , 1997 .

[5]  Huan Liu,et al.  Feature Selection for Classification , 1997, Intell. Data Anal..

[6]  T. E. Dy-Liacco Enhancing power system security control , 1997 .

[7]  Louis Wehenkel Machine-Learning Approaches to Power-System Security Assessment , 1997, IEEE Expert.

[8]  Marija D. Ilic,et al.  Transmission capacity in power networks , 1998 .

[9]  Louis Wehenkel,et al.  Emergency control and its strategies , 1999 .

[10]  B. J. Cory,et al.  A study of the homogeneous algorithm for dynamic economic dispatch with network constraints and transmission losses , 2000 .

[11]  Holger R. Maier,et al.  Critical Values of a Kernel Density-based Mutual Information Estimator , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

[12]  Feng Zhao,et al.  PGFB: A hybrid feature selection method based on mutual information , 2010, 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery.

[13]  Thomas J. Overbye,et al.  An Authenticated Control Framework for Distributed Voltage Support on the Smart Grid , 2010, IEEE Transactions on Smart Grid.

[14]  Alexandru Iosup,et al.  Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing , 2011, IEEE Transactions on Parallel and Distributed Systems.

[15]  Miao He,et al.  Robust Online Dynamic Security Assessment Using Adaptive Ensemble Decision-Tree Learning , 2013, IEEE Transactions on Power Systems.

[16]  Bin Wang,et al.  Power system online security operational trend analysis and simulation results , 2013, 2013 IEEE Power & Energy Society General Meeting.

[17]  Zhe Chen,et al.  A Systematic Approach for Dynamic Security Assessment and the Corresponding Preventive Control Scheme Based on Decision Trees , 2014, IEEE Transactions on Power Systems.

[18]  Zhi Gang Zhang,et al.  Simple Application of Variance Reduction Techniques in Monte Carlo and Missile Simulation , 2014 .

[19]  Sudip Misra,et al.  Cloud Computing Applications for Smart Grid: A Survey , 2015, IEEE Transactions on Parallel and Distributed Systems.

[20]  Kenji Tanaka,et al.  Conceptual Study for Open Energy Systems: Distributed Energy Network Using Interconnected DC Nanogrids , 2015, IEEE Transactions on Smart Grid.

[21]  Venkata Dinavahi,et al.  Extended Kalman Filter-Based Parallel Dynamic State Estimation , 2016, IEEE Transactions on Smart Grid.

[22]  Ding Li,et al.  Distributed Smart-Home Decision-Making in a Hierarchical Interactive Smart Grid Architecture , 2015, IEEE Transactions on Parallel and Distributed Systems.

[23]  Feng Zhao,et al.  Automatic Learning of Fine Operating Rules for Online Power System Security Control , 2016, IEEE Transactions on Neural Networks and Learning Systems.