International Journal of Forecasting
Special Issue on Probabilistic Energy Forecasting
In today's competitive and dynamic environment, more and more decision making processes in the energy industry are relying on probabilistic forecasts. The applications of probabilistic energy forecasts spread across planning and operations of the entire energy value chain. We are seeking papers from researchers working on the areas of probabilistic energy forecasting. "Energy forecasting" refers to "forecasting in the energy industry", which includes but is not limited to forecasting supply, demand and price of electricity, gas, water, and renewable energy resources. The probabilistic forecasts can take various forms, e.g., from quantile to full density forecasts, probabilistic forecasts for multi-categorical variables or functional data.
The potential topics include:
- Accounting for complex and uncertain inputs, such as weather and economy, in energy forecasting;
- Probabilistic energy forecasting for specific decision-making processes, such as energy trading, market operations, system planning and operations, and financial planning;
- Evaluation and verification of probabilistic energy forecasts, especially in the multivariate case
- Ensemble probabilistic energy forecasts and approaches to calibration
- Normalization of energy supply, demand and price.
If you are interested in contributing a paper to this special issue, please submit a one-page extended abstract with a cover letter to both editors for an initial review. Authors of selected abstracts will be invited to submit full papers to the International Journal of Forecasting. In addition, winners of the Global Energy Forecasting Competition 2014 (www.gefcom.org) will be invited to contribute to this special issue as well.
The proposed schedule is listed below:
- Abstract due: Jan 31st, 2014
- Initial review due: Mar 31st, 2014
- Full paper due: July 31st, 2014
- Notification of first round decision: Oct 31st, 2014
- Notification of final decisions: Mar 31st, 2015
Prof. Tao Hong, University of North Carolina at Charlotte, USA (firstname.lastname@example.org)
Prof. Pierre Pinson, Technical University of Denmark, Denmark (email@example.com)
Hi! I realize that I am too late for your call for papers, but I thought I would send you a link to a poster session I did at the Univ of Minnesota Institute for Mathematics and Its Applications ten years ago. Over the past fifteen years, I have developed a well articulated methodology for doing probabilistic forecasts of electricity prices in the US markets. The poster pertained to a method I developed and still use for modeling weather as part of my power price modeling.ReplyDelete
Go to the third citation down where it mentions "James B. Carson (RisQuant Energy)".