Model Predictive Control Prototyping and Validation for a Large Central Cooling System

Title: Model Predictive Control Prototyping and Validation for a Large Central Cooling System
Creator: Heidari, Rahmat; Braslavsky, Julio H.
Relation: 18th IFAC Workshop on Control Applications of Optimization CAO 2022. 18th IFAC Workshop on Control Applications of Optimization CAO 2022 Proceedings [presented in IFAC-PapersOnLine, Vol. 55 No.16] (Gif sur Yvette, France 18-22 July, 2022) p. 338-343
Publisher Link: http://dx.doi.org/10.1016/j.ifacol.2022.09.047
Publisher: Elsevier
Resource Type: conference paper
Date: 2022
Description: In this paper we present an application of Model Predictive Control (MPC) to a commercial building cooling system. The MPC models are a combination of white, grey and black box models derived from the experimental dataset and ensure energy and mass conservation is the system. Individual equipment models are validated against the actual measurements to ensure they accurately represent the physical system. A comparison of MPC performance to that of a business-as-usual operation scenario indicates up to 25% savings in operating costs with MPC.
Subject: modelling for control optimisation; industrial applications of optimal control; building automation; real-time algorithms; scheduling; programming
Identifier: http://hdl.handle.net/1959.13/1492194
Identifier: uon:53270
Identifier: ISSN:2405-8963
Language: eng
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