Working Group on Energy Forecasting and Analytics
IEEE Working Group on Energy Forecasting and Analytics
Scopes:
–Energy forecasting:
-Forecasting objectives: load, renewable energy, price; individual consumer load, demand response, EV charging load, net load, wind power ramp; power, gas, heat, and cooling demands; reserve capacity, risk, network congestion;
-Forecasting algorithms: traditional regression, advanced machine learning, deep learning, transfer learning, ensemble learning, robust forecasting;
-Forecasting outputs: point forecasting, probabilistic forecasting, hierarchical forecasting, cost-oriented forecasting;
-Forecasting evaluation: Alternative loss functions for different forecasting objectives and different applications.
–Energy Analytics:
-Data preprocessing: outlier detection, data cleansing, feature selection, data compression;
-Behavior modeling: load profiling, energy theft detection, renewable energy spatiotemporal correlation analysis, pattern recognition, sensitivity analysis, load or renewable energy simulation;
-Applications: demand response implementation, data-driven pricing, bidding, and trading, topology identification, outage and risk management, privacy concerns.
–Officers
-Chair: Dr.Jethro Browell, University of Glasgow
-Vice-chair: Dr. Yi Wang, ETH Zurich, Switherland
-Secretary:
-Past-chair:
Prof. Hamid Zareipour, University of Calgary, Canada (Secretary: 2012 – 2016; Vice Chair: 2016-2019)
Prof. Tao Hong, University of North Carolina at Charlotte, US (Chair: 2011-2019)
-Past Officers: Dr. Shu Fan, Monash University (Vice Chair: 2011-2016)
Past activities:
http://www.eeyiwang.com/WGEF.html
Recent Activities:
- IEEE PESGM 2020 Panel session on “Machine Learning Applications to Energy Forecasting and Analytics”
- Participation in the ERPI webinar 2020, where Prof. Hamidreza Zareipour talked about the EPRI Customer Research Program. There is a load forecasting interest group and about 400 people attended this meeting with a focus on long-term load forecasting.
- Review paper: T. Hong, P. Pinson, Y. Wang, R. Weron, D. Yang and H. Zareipour, “Energy Forecasting: A Review and Outlook,” in IEEE Open Access Journal of Power and Energy, vol. 7, pp. 376-388, 2020. (Best Paper of the IEEE OAJPE for 2021)
- Day-Ahead Electricity Demand Forecasting Competition: Post-COVID paradigm (https://ieee-dataport.org/competitions/day-ahead-electricity-demand-forecasting-post-covid-paradigm)
- IEEE OAJPE special section on “COVID-19 Impact on Electrical Grid Operation: Analysis and Mitigation” and competition paper
- IEEE TSTE special section on “Advances in Renewable Energy Forecasting: Predictability, Business Models and Applications in the Power Industry.”
- ICHQP2022 conference Special Session on “Forecasting and Analytics for Power Quality Problems.”
Future Plan:
- IEEE PESGM 2022 Panel session on “Utilisation of probabilistic energy forecasts in power system operation”
- IEEE PESGM 2022 Tutorial on “Probabilistic Energy Forecasting: Methodologies, Implementations, and Applications”
- Sustainable Energy, Grids and Networks, Special issue on “Forecast production and end-use for efficient management of energy systems”
- Host energy forecasting competition (net load, multi-energy etc.)