Future Western U.S. Building Electricity Consumption in Response to Climate and Population Drivers: A Comparative Study of the Impact of Model Structure
Casey D. Burleyson 1*, Gokul C. Iyer 1, Mohamad I. Hejazi 1, Sonny Kim 1, Page Kyle 1, Jennie S. Rice 1, Amanda D. Smith 1, Z. Todd Taylor 1, Nathalie Voisin 1, and YuLong Xie 1
1 Pacific Northwest National Laboratory, Richland, WA
* corresponding author: casey.burleyson@pnnl.gov
Projections of building electricity consumption are used in multiple fields and for a variety of purposes, from energy utility investment decisions to global climate assessments. Existing approaches to modeling building electricity consumption span a range of structural methodologies, spatial resolutions, and temporal scales, potentially leading to divergent projections. This paper compares how two models with different structures and resolutions respond to a common set of population and climate drivers in the western U.S. The BEND model simulates hourly residential and commercial building electricity consumption at the county scale by weighting the results of simulations of thousands of representative buildings. In contrast, the projected electricity demand in GCAM-USA is determined for each state, year, sector (residential/commercial), and service (e.g., heating, cooling, and others), based on population, income, technology, energy prices, and average annual climate. This paper aggregates the two models’ results to a common resolution: annual residential and commercial building electricity consumption by state. Both models show similar responses to future projected population change and climate change, with population change having the larger impact between the two. Differences are primarily due to how the models capture changes in the aggregate energy efficiency of the building stock as it evolves over time.
Burleyson, C.D., G.C. Iyer, M.I. Hejazi, S. Kim, P. Kyle, J.S. Rice, A.D. Smith, Z.T. Taylor, N. Voisin, and Y. Xie, 2020: Future western U.S. building electricity consumption in response to climate and population drivers: A comparative study of the impact of model structure. Energy, 208, 118312, https://doi.org/10.1016/j.energy.2020.118312.
Burleyson, C.D., P. Kyle, Z.T. Taylor, and Y. Xie (2020). Supporting code for Burleyson et al. 2020 [Code]. Zenodo. https://doi.org/10.5281/zenodo.3978578.
Burleyson, C.D., G.C. Iyer, M.I. Hejazi, S. Kim, P. Kyle, J.S. Rice, A.D. Smith, Z.T. Taylor, N. Voisin, and Y. Xie (2020). Supporting data for Burleyson et al. 2020 [Data set]. DataHub. https://doi.org/10.25584/data.2020-06.1320/1634287.
| Model | Version | Repository Link |
|---|---|---|
| GCAM-USA 1 | v5.0 | https://github.com/pkyle/gcam-core/tree/gpk/paper/gcam-usa-bend |
| GCAM-USA 2 | v5.0 | https://github.com/pkyle/gcam-core/tree/gpk/paper/gcam-usa-bend-cal2005 |
| BEND * | v0 | https://github.com/IMMM-SFA/BEND-V0 |
1 GCAM-USA projection simulations
2 GCAM-USA historical calibration simulations
* The BEND model is currently undergoing a major revision. The version of the model used in this publication has been archived and is available upon request.