Mary Ann Piette

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Sila KiliccoteLBNL, SLAC, Google, eIQ Mobility, Breakthrough Energy VenturesVerified email at kiliccote.com
Tianzhen HongSenior Scientist, FIBPSA, FASHRAE, Lawrence Berkeley National LabVerified email at lbl.gov
Bruce NordmanResearch Scientist, Lawrence Berkeley National LaboratoryVerified email at lbl.gov
Rongxin YinUC Berkeley/Lawrence Berkeley National LabVerified email at lbl.gov
Philip HavesLawrence Berkeley National LaboratoryVerified email at lbl.gov
Richard BrownLawrence Berkeley National LaboratoryVerified email at lbl.gov
Michael WetterLBNL, Berkeley, CAVerified email at lbl.gov
Sang Hoon LeeSenior Scientific Engineering Associate, Lawrence Berkeley National LaboratoryVerified email at lbl.gov
Evan MillsSenior Scientist (retired)Verified email at lbl.gov
Michael D. SohnLawrence Berkeley National LaboratoryVerified email at lbl.gov
Sarah C. Taylor-LangeLawrence Berkeley National LaboratoryVerified email at lbl.gov
Jonathan KoomeyPresident, Koomey AnalyticsVerified email at koomey.com
Kaoru KawamotoProfessor, Data Science División, Shiga University, JapanVerified email at osakagas.co.jp
Stephen SelkowitzLawrence Berkeley National LabVerified email at lbl.gov
Johanna MathieuAssociate Professor of Electrical Engineering and Computer Science, University of MichiganVerified email at umich.edu
David E. ClaridgeTexas A&M UniversityVerified email at tamu.edu
Steven LanziseraLawrence Berkeley National LaboratoryVerified email at lbl.gov
James E. BraunPurdue UniversityVerified email at purdue.edu
Frank OlkenFrank Olken Consulting

Mary Ann Piette

LBNL

Verified email at lbl.gov


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Quantifying changes in building electricity use, with application to demand response JL Mathieu, PN Price, S Kiliccote, MA Piette IEEE Transactions on Smart Grid 2 (3), 507-518, 2011	435	2011
Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis Y Chen, T Hong, MA Piette Applied Energy 205, 323-335, 2017	407	2017
Building thermal load prediction through shallow machine learning and deep learning Z Wang, T Hong, MA Piette Applied Energy 263, 114683, 2020	371	2020
Introduction to Commercial Building Control Strategies and Techniques for Demand Response--Appendices N Motegi	311	2007
Energy flexibility of residential buildings: A systematic review of characterization and quantification methods and applications H Li, Z Wang, T Hong, MA Piette Advances in Applied Energy 3, 100054, 2021	283	2021
Analysis of an information monitoring and diagnostic system to improve building operations MA Piette, SK Kinney, P Haves Energy and Buildings 33 (8), 783-791, 2001	277	2001
Electricity used by office equipment and network equipment in the US K Kawamoto, JG Koomey, B Nordman, RE Brown, MA Piette, M Ting, ... Energy 27 (3), 255-269, 2002	266*	2002
Study on Auto-DR and pre-cooling of commercial buildings with thermal mass in California R Yin, P Xu, MA Piette, S Kiliccote Energy and Buildings 42 (7), 967-975, 2010	239	2010
Commercial building energy saver: An energy retrofit analysis toolkit T Hong, MA Piette, Y Chen, SH Lee, SC Taylor-Lange, R Zhang, K Sun, ... Applied Energy 159, 298-309, 2015	218	2015
Peak demand reduction from pre-cooling with zone temperature reset in an office building P Xu, P Haves, MA Piette, J Braun	184	2004
CityBES: A web-based platform to support city-scale building energy efficiency T Hong, Y Chen, SH Lee, MA Piette Urban Computing 14, 2016, 2016	183	2016
The cost-effectiveness of commercial-buildings commissioning E Mills, H Friedman, T Powell, N Bourassa, D Claridge, T Haasl, MA Piette LBNL-56637, 2004	167	2004
Statistical analysis of baseline load models for non-residential buildings K Coughlin, MA Piette, C Goldman, S Kiliccote Energy and Buildings 41 (4), 374-381, 2009	165	2009
Energy retrofit analysis toolkits for commercial buildings: A review SH Lee, T Hong, MA Piette, SC Taylor-Lange Energy 89, 1087-1100, 2015	161	2015
Demand response opportunities and enabling technologies for data centers: Findings from field studies G Ghatikar	157	2012
Machine to machine (M2M) technology in demand responsive commercial buildings DS Watson, MA Piette, O Sezgen, N Motegi Handbook of Web Based Energy Information and Control Systems, 429-446, 2020	156	2020
Robust on-line fault detection diagnosis for HVAC components based on nonlinear state estimation techniques M Bonvini, MD Sohn, J Granderson, M Wetter, MA Piette Applied Energy 124, 156-166, 2014	147	2014
Estimating demand response load impacts: Evaluation of baseline load models for non-residential buildings in California K Coughlin, MA Piette, C Goldman, S Kiliccote	139	2008
Open automated demand response communications specification (Version 1.0) MA Piette	133	2009
Development and evaluation of fully automated demand response in large facilities MA Piette, O Sezgen, DS Watson, N Motegi, C Shockman, L Ten Hope	132	2004

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