How probabilistic electricity demand forecasts can expedite universal access to reliable electricty
This paper highlights an area of research that promises value for infrastructure investment decision-making
Abstract
The global community is projected to fail in achieving the United Nation’s goal of universal access to affordable, reliable, sustainable and modern electricity by 2030. This is ultimately due to inadequate levels of investment. Efforts to right-size infrastructure investments promise improved efficiency: right-sized infrastructure yields more connections with better reliability for every dollar invested. Because of this, geographic information systems, electrification planning models, and methods for characterizing electricity supply and demand have received growing attention as ways to support improved investment decision-making at scale.
In this paper, we highlight an underrepresented and complementary area of research that promises significant value for infrastructure investment decision-making: probabilistic electricity demand forecasting.
This research is part of the Energy and Economic Growth (EGG) Programme.
Citation
Stephen J. Lee, Dhruv Suri, Priyanshi Somani, Christopher L. Dean, Jason Pacheco, Robert Stoner, Ignacio J. Perez-Arriaga, John W. Fisher III, Jay Taneja (2021) How probabilistic electricity demand forecasts can expedite universal access to reliable electricty. Energy and Economic Growth (EGG) Programme.
Link
How probabilistic electricity demand forecasts can expedite universal access to reliable electricty