Ten questions concerning data-driven modelling and forecasting of operational energy demand at building and urban scale

Abstract

Buildings account for over a third of end energy demand in many countries worldwide. Modelling this demand accurately marks the first step in producing forecasts that can help optimize energy efficiency as well as ensure stable grid operation, a growing concern with the electrification of heating and transportation demand and proliferation of renewable energy sources. These changes, for instance through large scale deployment of rooftop solar PV systems also mean that urban electricity demand is in a constant state of flux. To address these issues, a very large number of research papers have appeared in recent literature which propose or test different building and urban energy demand or load forecasting techniques, often with conflicting results. Meanwhile, in the same period, the broader field of forecasting has also witnessed tremendous development due to greater data availability, growth in computing power, and algorithmic innovations. As a result, there is little clarity in the energy demand forecasting field on best practices, especially in relation to the creation, evaluation, and utilization of these forecast models. This ten questions paper addresses this shortcoming and provides answers to the most important questions that researchers and practitioners alike need to ask themselves before creating their own demand forecaster, be it at the building or urban level. In addition to summarizing current best practices, the paper also provides an overview of some of the most important challenges related to energy demand forecasting and a principled framework to address them. Additionally, two companion notebooks provide an in-depth tutorial form introduction to load forecasting at both building and urban scale.