Forecasting Impact
Forecasting Impact is a monthly podcast that aims to disseminate the science and practice of forecasting alongside prominent academics and practitioners in the field. Our vision is to grow the forecasting community, foster collaboration between academia and industry, and promote scientific forecasting and good practice. We’ll discuss a variety of topics in economics, supply chain, energy, AI, data analytics, healthcare, and more.
Podcast Team: Dr. Mahdi Abolghasemi, Dr. Sevvandi Kandanaarachchi, Michał Chojnowski, Dr Laila Akhlaghi, George Boretos, Mariana Menchero, Dr. Faranak Golestaneh, Arian Sultan Khan.
Future guests: if you have something interesting on forecasting to share with our audiences, please send an email to forecastingimpact@gmail.com
Forecasting Impact
Tao Hong, on Energy Forecasting
In this episode, we talk to Prof. Tao Hong, a Distinguished Professor at the University of North Carolina at Charlotte. Tao provides his insights on the future of energy forecasting research, and why we need to focus on reproducibility. He discusses the Global Energy Forecasting competitions, and what we have learned from them. He also sheds light o n the importance of industry and academic collaboration, and a business model that he has implemented successfully.
He recommends the following reading for interested readers who want to go deep into forecasting and, specifically, energy forecasting:
Books
- Forecasting Principles and Practice, by Rob Hyndman, and George Athanasopoulos
- Matrix Analysis and Applied Linear Algebra by Carl D Meyer
Paper
- Probabilistic electric load forecasting: A tutorial review, T Hong, S Fan, International Journal of Forecasting, V 32 (3), 2016.