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ghMulti-Level Approach for Model-Based Predictive Control (MPC) in Buildings: A Preliminary Overview
Abstract
Model-based predictive control (MPC) has
emerged in recent years as a promising approach to
building operation. MPC uses models of the
system(s) under control -and knowledge about future
disturbances- to select an optimal set of actions.
Despite its advantages, implementing MPC in a
building can be quite challenging. This is largely due
to the difficulty of dealing with a detailed simulation
model that may contain hundreds or thousands of
variables. Simple models offer a potential solution;
however, a coarser representation of the entire
building is not suitable for local scales (e.g., a zone).
This paper presents an overview of a strategy to
address this problem. Optimization problems are
formulated by using models focusing on different
control levels (building, zone, rooms, etc.), while
enabling communication between them. This method
allows for simpler models, facilitates programming
and provides insight on building operation.
Preliminary results, corresponding
Citation
Candanedo, J. A.; Dehkordi, V. R. (2013). ghMulti-Level Approach for Model-Based Predictive Control (MPC) in Buildings: A Preliminary Overview. Energy Systems Laboratory (http://esl.tamu.edu); Texas A&M University (http://www.tamu.edu). Available electronically from https : / /hdl .handle .net /1969 .1 /151420.