Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond

B-Tier
Journal: International Journal of Forecasting
Year: 2016
Volume: 32
Issue: 3
Pages: 896-913

Authors (6)

Hong, Tao (University of North Carolina a...) Pinson, Pierre (not in RePEc) Fan, Shu (not in RePEc) Zareipour, Hamidreza (not in RePEc) Troccoli, Alberto (not in RePEc) Hyndman, Rob J. (Monash University)

Score contribution per author:

0.335 = (α=2.01 / 6 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

The energy industry has been going through a significant modernization process over the last decade. Its infrastructure is being upgraded rapidly. The supply, demand and prices are becoming more volatile and less predictable than ever before. Even its business model is being challenged fundamentally. In this competitive and dynamic environment, many decision-making processes rely on probabilistic forecasts to quantify the uncertain future. Although most of the papers in the energy forecasting literature focus on point or single-valued forecasts, the research interest in probabilistic energy forecasting research has taken off rapidly in recent years. In this paper, we summarize the recent research progress on probabilistic energy forecasting. A major portion of the paper is devoted to introducing the Global Energy Forecasting Competition 2014 (GEFCom2014), a probabilistic energy forecasting competition with four tracks on load, price, wind and solar forecasting, which attracted 581 participants from 61 countries. We conclude the paper with 12 predictions for the next decade of energy forecasting.

Technical Details

RePEc Handle
repec:eee:intfor:v:32:y:2016:i:3:p:896-913
Journal Field
Econometrics
Author Count
6
Added to Database
2026-02-02