Mary Ann Piette

Publications

Viewing 25 of 241 publications

2021

Wang, Zhe, Tianzhen Hong, Han Li, and Mary Ann Piette. "Predicting city-scale daily electricity consumption using data-driven models." Advances in Applied Energy 2 (2021) 100025.

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Dalton, Patrick, Mary Ann Piette, Paul De Martini, Fritz Kahrl, Jeremy Twitchell, and Andrew D Mills. "Western States Training Webinars on Integrated Distribution System Planning." 2021.

Announcement and Trainer Bios

Integration, Management, and Control of Supply-Side DER

Demand Flexibility Technology, New Programs and Emerging Policies

Grid Modernization and Resilience Planning

Grid Modernization Investment Economics

Planning for Energy Storage

Storage for Integration and Hybrid Power Plants

Agenda for Western States Roundtable: Policy and Regulatory Issues for Utility Investments in Grid Modernization

2020

Liu, Jingjing, Rongxin Yin, Marco Pritoni, Mary Ann Piette, and Monica Neukomm. "Developing and Evaluating Metrics for Demand Flexibility in Buildings: Comparing Simulations and Field Data." ACEEE Summer Study. 2020.

Clark, Callie, Anand Prakash, Marco Pritoni, Margarita Kloss, Pranav Gupta, Bruce Nordman, and Mary Ann Piette. "Harvesting the low-hanging fruit of high energy savings -- Virtual Occupancy using Wi-Fi Data." ACEEE Summer Study. Virtual, 2020.

Singh, Reshma, Anand Prakash, Mary Ann Piette, and Shreya Agarwal. "A Community Energy Operations and Planning System: Concept, Use cases, Metrics, and Benefits." The American Council for an Energy-Efficient Economy. 2020.

Gerke, Brian F, Giulia Gallo, Sarah Josephine Smith, Jingjing Liu, Shuba V Raghavan, Peter Schwartz, Mary Ann Piette, Rongxin Yin, and Sofia Stensson. The California Demand Response Potential Study, Phase 3: Final Report on the Shift Resource through 2030. 2020.

Gerke, Brian F, Cong Zhang, Andrew Satchwell, Samanvitha Murthy, Mary Ann Piette, Elaina Present, Eric Wilson, Andrew Speake, and Rajendra Adhikari. "Modeling the Interaction Between Energy Efficiency and Demand Response on Regional Grid Scales." ACEEE 2020 Summer Study on Energy Efficiency in Buildings. ACEEE, 2020.

ACEEE Proceedings PDF

Yoon, Nari, Leslie K Norford, Ali Malkawi, Holly Samuelson, and Mary Ann Piette. "Dynamic metrics of natural ventilation cooling effectiveness for interactive modeling." Building and Environment 180.106994 (2020).

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Malik, Jeetika, Ronita Bardhan, Tianzhen Hong, and Mary Ann Piette. "Contextualising adaptive comfort behaviour within low-income housing of Mumbai, India." Building and Environment 177 (2020) 106877.

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Yoon, Nari, Mary Ann Piette, Jung Min Han, Wentao Wu, and Ali Malkawi. "Optimization of Window Positions for Wind-Driven Natural Ventilation Performance." Energies 13.10 (2020) 2464.

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Wang, Zhe, Tianzhen Hong, and Mary Ann Piette. "Building thermal load prediction through shallow machine learning and deep learning." Applied Energy 263 (2020) 114683.

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Satchwell, Andrew, Peter Cappers, Jeff Deason, Sydney Forrester, Natalie Mims Frick, Brian F Gerke, and Mary Ann Piette. A Conceptual Framework to Describe Energy Efficiency and Demand Response Interactions. 2020.

2017

Page, Janie, Rongxin Yin, Mary Ann Piette, and Richard E Brown. Exploration of PG&E AutoDR Incentive Options. 2017.

pge_incentive_options_2001330.pdf

Granderson, Jessica, Guanjing Lin, David Blum, Shankar Earni, Janie Page, and Mary Ann Piette. Optimizing Operational Efficiency: Integrating Energy Information Systems and Model-Based Diagnostics. 2017.

2019

Piette, Mary Ann, Reshma Singh, and Anand Prakash. "Evaluation of the Need for and Design of a City Energy Operations System." Proceedings of the 1st ACM International Workshop on Urban Building Energy Sensing, Controls, Big Data Analysis, and Visualization - UrbSys’19. New York, New York, USA: ACM Press, 2019.

Yin, Rongxin, Girish Ghatikar, and Mary Ann Piette. Big-Data Analytics for Electric Grid and Demand-Side Management. 2019.

Singh, Reshma, Baptiste Ravache, and Mary Ann Piette. Energy Modeling in Urban Districts: Forecast of multi-sector Energy Use and GHG Emissions. 2019.

Wang, Zhe, Tianzhen Hong, and Mary Ann Piette. "Predicting plug loads with occupant count data through a deep learning approach." Energy 181 (2019) 29–42.

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Wang, Zhe, Tianzhen Hong, Mary Ann Piette, and Marco Pritoni. "Inferring occupant counts from Wi-Fi data in buildings through machine learning." Building and Environment 158 (2019) 281–294.

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Wang, Zhe, Tianzhen Hong, and Mary Ann Piette. "Data fusion in predicting internal heat gains for office buildings through a deep learning approach." Applied Energy 240 (2019) 386–398.

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Blum, David, K Arendt, Lisa Rivalin, Mary Ann Piette, Michael Wetter, and C.T Veje. "Practical factors of envelope model setup and their effects on the performance of model predictive control for building heating, ventilating, and air conditioning systems." Applied Energy 236 (2019) 410–425.

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Granderson, Jessica, Guanjing Lin, David Blum, Janie Page, Michael Spears, and Mary Ann Piette. "Integrating diagnostics and model-based optimization." Energy and Buildings 182 (2019) 187–195.

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1996

Koomey, Jonathan G, Mary Ann Piette, Michael Cramer, and Joseph H Eto. "Efficiency improvements in US office equipment." Energy Policy 24.12 (1996) 1101–1110.

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2011

Granderson, Jessica, Mary Ann Piette, Ben Rosenblum, R Lily Hu, Daniel Harris, Paul A Mathew, Phillip N Price, Geoffrey C Bell, Srinivas Katipamula, and Michael Brambley. Energy Information Handbook: Applications for Energy-Efficient Building Operations. Berkeley: Lawrence Berkeley National Laboratory, 2011.