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ghMulti-Level Approach for Model-Based Predictive Control (MPC) in Buildings: A Preliminary Overview
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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
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