Key Variables in Determining Energy Shaving Capacity of Buildings during Demand Response Events

Author:

Yu Xinran1ORCID,Ergan Semiha2

Affiliation:

1. Ph.D. Candidate, Dept. of Civil and Urban Engineering, New York Univ., 6 Metrotech Center, Brooklyn, NY 11201 (corresponding author). ORCID: .

2. Assistant Professor, Dept. of Civil and Urban Engineering, New York Univ., 6 Metrotech Center, Brooklyn, NY 11201.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Strategy and Management,Industrial relations,Building and Construction,Civil and Structural Engineering

Reference41 articles.

1. Demand side flexibility: Potentials and building performance implications

2. Chen T. and C. Guestrin. 2016. “XGBoost: A scalable tree boosting system.” In Proc. 22nd ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining 785–794. New York: Association for Computing Machinery.

3. Cigler J. D. Gyalistras J. Široky V. Tiet and L. Ferkl. 2013. “Beyond theory: The challenge of implementing model predictive control in buildings.” In Proc. 11th REHVA World Congress CLIMA. Prague Czech Republic: Federation of European Heating Ventilation and Air Condition Association.

4. Energy plus: Energy simulation program;Crawley D. B.;ASHRAE J.,2000

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