The performance of buildings participating in demand response (DR) programs is usually evaluated with baseline models, which predict what electric demand would have been if a DR event had not been called. Different baseline models produce different results. Moreover, modelers implementing the same baseline model often make different model implementation choices producing different results. Using real data from a DR program in CA and a regression-based baseline model, which relates building demand to time of week, outdoor air temperature, and building operational mode, we analyze the effect of model implementation choices on DR shed estimates. Results indicate strong sensitivities to the outdoor air temperature data source and bad data filtration methods, with standard deviations of differences in shed estimates of ≈20–30 kW, and weaker sensitivities to demand/temperature data resolution, data alignment, and methods for determining when buildings are occupied, with standard deviations of differences in shed estimates of ≈2–5 kW.
How Baseline Model Implementation Choices Affect Demand Response Assessments
Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING: INCLUDING WIND ENERGY AND BUILDING ENERGY CONSERVATION. Manuscript received June 6, 2014; final manuscript received August 22, 2014; published online September 30, 2014. Assoc. Editor: Gregor P. Henze. The United States Government retains, and by accepting the article for publication, the publisher acknowledges that the United States Government retains, a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for United States government purposes.
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Addy, N. J., Kiliccote, S., Callaway, D. S., and Mathieu, J. L. (September 30, 2014). "How Baseline Model Implementation Choices Affect Demand Response Assessments." ASME. J. Sol. Energy Eng. April 2015; 137(2): 021008. https://doi.org/10.1115/1.4028478
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