Stanislaw, LaurenSeatle, MadeleineMcPherson, Madeleine2024-03-282024-03-282024Stanislaw, L., Seatle, M., & McPherson, M. (2024). Quantifying the value of building demand response: Introducing a cross-sectoral model framework to optimize demand response scheduling. Energy Reports, 11, 2111-2126. https://doi.org/10.1016/j.egyr.2024.01.063https://doi.org/10.1016/j.egyr.2024.01.063https://hdl.handle.net/1828/16319The authors would like to thank Mohammad Miri, Jack Pawlyna, and Harold Stanislaw for insightful feedback during the manuscript editing process.Co-optimization of demand-side electrification and supply-side variable renewable energy integration in electricity systems can lead to dramatically reduced emissions due to synergies between the two sectors. However, few models exist that represent both sectors in sufficient operational detail. To bridge this gap, this paper proposes a novel framework for transferring information from a building stock model to an electricity system model. First, demand response (DR) events are simulated within a model of building stock energy use. Then, the energy characteristics of these events are used to inform a series of constraints within the electricity system model. At the same time, hourly electricity use predictions from the building stock are also incorporated into the total demand met by the electricity system. This allows the electricity system model to determine the grid-optimal times for the building stock to enact DR. To demonstrate the utility of this framework, a case study into the effects of building efficiency increases, DR, and variable renewable capacity expansion in the city of Regina, Saskatchewan is performed, and various ways to reduce the costs and emissions associated with electricity use in Regina are compared.enAttribution 4.0 Internationalurban building energy modelingelectricity system modelcross-sectoral model integrationdemand responseArticleDepartment of Civil Engineering