Day-Ahead Electricity Demand Forecasting Competition: Post-COVID Paradigm

The COVID-19 related shutdowns have made significant impacts on the electric grid operation worldwide. The global electrical demand plummeted around the planet in 2020 continuing into 2021. Moreover, demand shape has been profoundly altered as a result of industry shutdowns, business closures, and people working from home. In view of such massive electric demand changes, energy forecasting systems struggle to provide an accurate demand prediction, exposing operators to technical and financial risks, and further reinforcing the adverse economic impacts of the pandemic. In this context, the IEEE DataPort Day-Ahead Electricity Demand Forecasting Competition: Post-COVID Paradigm was organized to support the development and dissemination state-of-the-art load forecasting techniques that can mitigate the adverse impact of pandemic-related demand uncertainties. This paper presents the findings of this competition from the technical and organizational perspectives. The competition structure and participation statistics are provided, and the winning methods are summarized. Furthermore, the competition dataset and problem formulation is discussed in detail. Finally, the dataset is published along with this paper for reproducibility and further research.

Automated summary

The COVID-19 related shutdowns have had significant impacts on electric grid operations globally, leading to a dramatic decrease in electricity demand and a shift in demand patterns. Existing energy forecasting systems struggle to accurately predict these demand changes, exposing operators to risks and worsening the economic impact of the pandemic. Therefore, organizing the "IEEE DataPort Day-Ahead Electricity Demand Forecasting Competition: Post-COVID Paradigm" to promote the development and dissemination of advanced load forecasting techniques is of great importance.