Medium-term electricity load forecasting and climate change in arid cities

Abstract

Electric utilities need to consider how potential changes in climate patterns will affect their peak loads. This study incorporates weather and socio-economic variables into a medium-term load forecasting model to consider potential climate change effects on the challenging summer peak season for utilities in the arid southwestern US. Our ‘average hourly load by month’ model shows marked improvement over a purely autoregressive approach to load forecasting used by some electric utilities. In light of climate change, electric utilities and society can benefit from minimizing inaccuracies in load predictions. Decision-making based on more climate-sensitive forecasts will reduce the water and carbon footprint of electric utilities and improve their investment strategies for renewable energy technologies.

Keywords:

• electricity load
• climate change
• forecast

Acknowledgements

The authors appreciate insightful comments and suggestions provided by Satheesh Aradhyula and Gary Thompson. We acknowledge our research colleagues with the Climate Assessment for the Southwest program at the University of Arizona. This work was supported by that project through the National Oceanic and Atmospheric Administration's Climate Program Office (NOAA), grant NA16GP2578. The statements, findings, conclusions, and recommendations are our own and do not necessarily reflect the views of NOAA, US Department of Commerce, or the US Government Climate Program. We also thank TEP and AZMET for providing the necessary electricity load and weather data.