Intelligent Grids and Systems

3M Smart Grid: Connected, Efficient and Sustainable Energy

Research Interests:

  • Intelligent control in power engineering applications
  • Artificial neural networks for prediction and forecast of renewable energy generation.
  • Neural network architecture, training algorithms, and comparisons of neural networks with traditional AI models.

Patents:

  • Shuhui Li, Donald C. Wunsch, and Michael Fairbank, “Vector Control of Grid-Connected Power Electronic Converter using Artificial Neural Networks,” Filed: Attorney Docket No. 10025-080PV1.
  • Shuhui Li, Michael Fairbank, Xingang Fu, Donald Wunsch, and Eduardo Alonso, “Systems, Methods and Devices for Vector Control of Permanent Magnet Synchronous Machines using Artificial Neural Networks,” Filed: Attorney Docket No. 10025-090PV1.
  • Shuhui Li, Dong Zhang, and Min Sun, “Smart and Real-Time Demand Response Mechanism and System for Residential Energy Consumers,” Filed: Approved by The University of Alabama on Sep. 17, 2013.

Related publications and papers:

Journals:

  • Dong Zhang and Shuhui Li, “Integrating PowerWorld and MatLab for Optimal Dispatch and Unit Commitment Study of Competitive Electric Power Markets,” American Journal of Engineering and Applied Sciences, Vol. 8, Issue 3, pp. 291-301, 2015.
  • Xingang Fu, Shuhui Li, Michael Fairbank, Donald C. Wunsch, Eduardo Alonso, “Training Recurrent Neural Networks With Levenberg–Marquardt Backpropagation for Optimal Control of a Grid-Connected Converter,” IEEE Transactions on Neural Networks and Learning Systems, Vol. 26, Issue 9, pp. 1900-1912, Aug. 2015.
  • Yanyu Zhang, P. Zheng, Shuhui Li, Chuanzhi Zang and Hepeng Li, ” A Novel Multi-Objective Optimization Algorithm for Home Energy Management System in Smart Grid,” Mathematical Problems in Engineering, http://dx.doi.org/10.1155/2015/807527, 2015.
  • Dao Lam, Shuhui Li, and Donald C. Wunsch, “Hidden Markov Model with Information Criteria Clusting and Extreme Learning Machine Regression for Wind Forecasting,” Journal of Computer Science and Cybernetics, Vol. 30, No. 4, pp. 361-376, 2015.
  • Shuhui Li, Michael Fairbank, Cameron Johnson, Donald C. Wunsch, Eduardo Alonso, and Julio Proano, “Artificial Neural Networks for Control of a Grid-Connected Rectifier/Inverter under Disturbance, Dynamic and Power Converter Switching Conditions”, IEEE Transactions on Neural Networks and Learning Systems, Vol. 25, No. 4, April 2014, pp. 738-750.
  • Shuhui Li, Dong Zhang, Adam B. Roget and Zheng ONeill, “Integrating Building Energy Simulation and Dynamic Price for Demand Response Study,” IEEE Transactions on Smart Grid, Vol. 5, Issue 2, March 2014, pp. 779-788.
  • Shuhui Li, Ke Bao, Xingang Fu, and Huiying Zheng, “Energy Management and Control of Electric Vehicle Charging Stations,” Electric Power Components and Systems (Taylor & Francis), Vol. 42, No. 3-4, pp. 339-347, 2014.
  • Dong Zhang, Shuhui Li, Peng Zeng, and Chuanzhi Zang, “Optimal Microgrid Control and Power Flow Study with Different Bidding Policies by Using PowerWorld Simulator,” IEEE Transactions on Sustainable Energy, Vol. 5, Issue 1, Jan. 2014, pp. 282-292.
  • Michael Fairbank, Shuhui Li, Xingang Fu, Eduardo Alonso, and Donald C. Wunsch, “An Adaptive Recurrent Neural-Network Controller using a Stabilization Matrix and Predictive Inputs to Solve the Tracking Problem under Disturbances,” Neural Networks (Elsevier), Vol. 49, Jan. 2014, pp. 74-86.
  • Dong Zhang and Shuhui Li, “Optimal Dispatch of Competitive Power Markets by using PowerWorld Simulator,” International Journal of Emerging Electric Power Systems, Vol. 14, Issue 6, Dec. 2013, pp. 535-547.
  • Jing Liu, Yang Xiao, Shuhui Li, Wei Liang, and C. L. Philip Chen, “Cyber Security and Privacy Issues in Smart Grids,” IEEE Communications Surveys & Tutorials, Vol. 14, Issue 4, 2012, pp. 981-997.
  • R. Challoo, P. Rao, S. Ozcelik, L. Challoo, and Shuhui Li, “Navigation Control and Path Mapping of a Mobile Robot using Artificial Immune Systems, ” International Journal of Robotics and Automation, Vol. 1, Issue 1, May 2010, ISSN: 2180-1312.
  • Shuhui Li, Don C. Wunsch, Edgar O’Hair, and Michael G. Giesselmann,”Comparative Analysis of Regression and Artificial Neural Network Models for Wind Turbine Power Curve Estimation “, Transactions of the ASME, Journal of Solar Energy Engineering, November, 2001.
  • Shuhui Li, Don C. Wunsch, Edgar O’Hair, and Michael G. Giesselmann, “Using neural network to estimate wind turbine power generation”, IEEE Transactions on Energy Conversion, Vol. 16, No. 3, September 2001.

Book chapters:

  • Shuhui Li and Tim Haskew, “Intelligent Control of PWM Converter for Grid Integration of Variable Speed Wind Turbines,” Smart Systems Engineering: Computational Intelligence in Architecting Engineering Systems, AMSE Press, November 2008.
  • R. Challoo, R. Kalwakuntla, S. Ozcelik, and Shuhui Li, “Face Detection in Color Images Using Artificial Neural Networks,” Smart Systems Engineering: Computational Intelligence in Architecting Engineering Systems, AMSE Press, November 2008.
  • R. Challoo, G. Pavuluri, and Shuhui Li, “Real_time Intelligent Control of A DC Motor,” accepted in Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME Press, November 2006.
  • R. Challoo, P. Mehendale, Shuhui Li, and R. McLauchlan “Adaptive Neuro-Fuzzy Control of a Spring-Mass Damper System,” in Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME Press, November 2004.
  • Robert McLauchlan, Rajab Challoo, Shuhui Li, S. Iqbal Omar, and Ligong Wang, “Intelligent Control of a Robot Arm to Avoid an Obstacle”, in Smart Engineering Systems: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME Press, November 2001.
  • Shuhui Li, Edgar O’Hair, Michael G. Giesselmann, and Don C. Wunsch, “Comparative analysis of regression and neural network models for wind power”, in Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining and Rough Sets, ASME Press, November 1998, (ANNIE’98).

Conferences:

  • Shuhui Li, Michael Fairbank, Xingang Fu, Donald C. Wunsch, and Eduardo Alonso, “Vector Control of Permanent Magnet Synchronous Motor using Adaptive Recurrent Neural Networks”, Proceedings of 2013 International Joint Conference on Neural Network, Dallas, August 3-8, 2013. Poster presentation.
  • Shuhui Li and Dong Zhang, “A Comparison Study of Demand Response using Optimal and Heuristic Algorithms”,  Proceedings of 2013 IEEE Power & Energy Society General Meeting, Vancouver, British Columbia, Canada, 21-25 July, 2013.
  • Dong Zhang and Shuhui Li, “Solving Optimal Dispatch Problem for a Competitive Wholesale Power Market by using PowerWorld Simulator”, Proceedings of  2013 IEEE Power & Energy Society General Meeting, Vancouver, Canada, 21-25 July, 2013.
  • Shuhui Li, Michael Fairbank, Donald C. Wunsch, and Eduardo Alonso, “Vector Control of a Grid-Connected Rectifier/Inverter Using an Artificial Neural Network”, Proceedings of 2012 International Joint Conference on Neural Network, Brisbane Australia, June 2012. Poster presentation.
  • Shuhui Li, “Wind Power Prediction Using Recurrent Multilayer Perceptron Neural Networks”, in the Proceeding of 2003 IEEE Power Engineering Society General Meeting, Toronto, Canada, July 13-17, 2003.
  • Shuhui Li, “Comparative Analysis of Backpropagation and Extended Kalman Filter in Pattern and Batch Forms for Training Neural Networks”, in 2001 International Joint Conference on Neural Network, Washington, D.C., July 15-19 2001.
  • Shuhui Li, Don C. Wunsch, Edgar O’Hair, and Michael G. Giesselmann, ” Wind Turbine Power Estimation by Neural Networks With Kalman Filter Training on a SIMD Parallel Machine Neural network for wind power with compressing function”, in International Joint Conference on Neural Networks, Washington, D.C., July 1999.
  • Shuhui Li, Edgar O’Hair, and Michael G. Giesselmann, “Using neural networks to predict wind power generation”, in Proceedings of the ASME International Solar Energy Conference, Washington, D.C., ASME 1997, pp. 415-420.
  • Shuhui Li, Don C. Wunsch, Edgar O’Hair, and Michael G. Giesselmann, “Neural network for wind power with compressing function”, IEEE International Conference on Neural Network, Houston, June 1997, pp. 115-120.