D
David Blum
Researcher at Lawrence Berkeley National Laboratory
Publications - 39
Citations - 772
David Blum is an academic researcher from Lawrence Berkeley National Laboratory. The author has contributed to research in topics: HVAC & Model predictive control. The author has an hindex of 10, co-authored 27 publications receiving 307 citations. Previous affiliations of David Blum include Centers for Disease Control and Prevention & Massachusetts Institute of Technology.
Papers
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Journal ArticleDOI
All you need to know about model predictive control for buildings
Ján Drgoňa,Ján Drgoňa,Javier Arroyo,Iago Cupeiro Figueroa,David Blum,Krzysztof Arendt,Donghun Kim,Donghun Kim,Enric Perarnau Ollé,Juraj Oravec,Michael Wetter,Draguna Vrabie,Lieve Helsen +12 more
TL;DR: This paper provides a unified framework for model predictive building control technology with focus on the real-world applications and presents the essential components of a practical implementation of MPC such as different control architectures and nuances of communication infrastructures within supervisory control and data acquisition (SCADA) systems.
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Practical factors of envelope model setup and their effects on the performance of model predictive control for building heating, ventilating, and air conditioning systems
TL;DR: It is found that a difference of up to 20% in cooling cost for the cases studied can occur between the best performing model and the worst performing model, and the primary factors attributing to this were model structure and initial parameter guesses during parameter estimation of the model.
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Opportunity Cost Quantification for Ancillary Services Provided by Heating, Ventilating, and Air-Conditioning Systems
TL;DR: It is found that marginal ancillary service opportunity costs vary over time and that properly adjusting energy consumption at an hour of interest can reduce the total opportunity cost of providing ancillaillary services.
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Field demonstration and implementation analysis of model predictive control in an office HVAC system
TL;DR: In this article , an open-source, Modelica-based tool-chain that automatically generates optimal control, parameter estimation, and state estimation problems aimed at facilitating MPC implementation is presented.
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Technologies and Magnitude of Ancillary Services Provided by Commercial Buildings
TL;DR: This paper reviews available technologies and necessary control strategies for HVAC systems in commercial buildings to provide ancillary services, and develops physically-based scaling metrics for building thermal storage technologies accessible through HvAC systems.