Dr. Tao Hong

Personal Website:

Website

Education:

• Ph.D., (co-majors) Electrical Engineering and Operations Research, North Carolina State University, 2010
• M.S., (co-majors) Operations Research and Industrial Engineering, North Carolina State University, 2008
• M.S., Electrical Engineering, North Carolina State University, 2008
• B.Eng., Automation, Tsinghua University, 2005 

Classes:

Research:

• Energy forecasting
• Power systems operations and planning
• Renewable integration
• Risk management
• Energy trading
• Retail forecasting
• Revenue optimization
• Forecasting in heathcare, transportation, and sports

Research Grants:

• Delivery point level load and weather data analysis, sponsored by North Carolina Electric Membership Corporation, 2017 - present
• Short term load forecasting under data attacks, sponsored by US Department of Energy and Brookhaven National Laboratory, 2016 - present
• Short-term probabilistic load forecasting, sponsored by North Carolina Electric Membership Corporation, 2016
• Hierarchical load forecasting, sponsored by North Carolina Electric Membership Corporation, 2015
• Demand response forecasting using smart meter data, sponsored by Pacific Gas & Electric and DNV GL, 2014 - 2015
• Long term load forecasting case study, sponsored by US Department of Energy and National Association of Regulatory Utility Commissioners, 2014 - 2015

Selected Publications:

• Tao Hong, Jingrui Xie, and Jonathan Black, "Global Energy Forecasting Competition 2017: Hierarchical Probabilistic Load Forecasting," International Journal of Forecasting, vol. 35, no. 4, pp. 1389-1399, October-December, 2019.
• Yi Wang, Qixin Chen, Tao Hong, and Chongqing Kang, "Review of smart meter data analytics: applications, methodologies, and challenges," IEEE Transactions on Smart Grid, vol. 10, no. 3, pp. 3125-3148, May 2019.
• Tao Hong, David Wenzhong Gao, Tom Laing, Dale Kruchten, and Jorge Calzada, "Training energy data scientists: universities and industry need to work together to bridge the talent gap," IEEE Power and Energy Magazine, vol.16, no.3, pp 66-73, May-June 2018.
• Jonathan Black, Alex Hofmann, Tao Hong, Joseph Roberts, and Pu Wang, "Weather data for energy analytics: from modeling outages and reliability indices to simulating distributed photovoltaic fleets," IEEE Power and Energy Magazine, vol.16, no.3, pp 43-53, May-June 2018.
• Tao Hong and Shu Fan, "Probabilistic electric load forecasting: a tutorial review", International Journal of Forecasting, vol.32, no.3, pp 914-938, July-September, 2016
• Tao Hong, Pierre Pinson, Shu Fan, Hamidreza Zareipour, Alberto Troccoli and Rob J. Hyndman, "Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond", International Journal of Forecasting, vol.32, no.3, pp 896-913, July-September, 2016.
• Tao Hong, Pu Wang and Laura White, "Weather station selection for electric load forecasting", International Journal of Forecasting, vol.31, no.2, pp 286-295, April-June, 2015. 
• Tao Hong, Pierre Pinson and Shu Fan, "Global energy forecasting competition 2012", International Journal of Forecasting, vol.30, no.2, pp 357-363, April-June, 2014. 
• Tao Hong, Jason Wilson and Jingrui Xie, "Long term probabilistic load forecasting and normalization with hourly information", IEEE Transactions on Smart Grid, vol.5, no.1, pp.456-462, January, 2014

Honors & Awards:

• Charlotte Business Journal Energy Education Leader of the Year (2017)
• IEEE PES PSPI Technical Committee Prize Paper Award (2016)
• IEEE PES PSPI Technical Committee Working Group Recognition Award (2015)
• IEEE PES Technical Council Distinguished Service Award (2014) 

Professional Affiliations:

• Senior Member, Institute of Electrical and Electronics Engineers
• Director at Large, International Institute of Forecasters