Model-based predictive control of an ice storage device in a building cooling system

2013 ◽  
Vol 111 ◽  
pp. 1032-1045 ◽  
Author(s):  
J.A. Candanedo ◽  
V.R. Dehkordi ◽  
M. Stylianou
2019 ◽  
Vol 11 (1) ◽  
pp. 101-104
Author(s):  
Tamás Kardos ◽  
Dénes Nimród Kutasi

Abstract This paper presents the application of two model-based predictive control (MPC) algorithms on the cooling system of an office building. The two strategies discussed are a simple MPC, and an adaptive MPC algorithm connected to a model predictor. The cooling method used represents the air-conditioning unit of an HVAC system. The temperature of the building’s three rooms is controlled with fan coil units, based on the reference temperature and with different constraints applied. Furthermore, the building model is affected by dynamically changing interior and exterior heat sources, which we introduced into the controller as disturbances.


Author(s):  
Vahid R. Dehkordi ◽  
José A. Candanedo

This paper presents a model predictive control (MPC) algorithm designed for the cooling system of a small commercial building under a time-dependent electricity price profile. The proposed approach includes a problem formulation in terms of cooling power, a variable-length prediction horizon and the consideration of the equipment duty cycle as a constraint in the optimization algorithm. The cooling system is equipped with an ice bank for thermal energy storage. A simple linear building thermal model is used to calculate the required amount of cooling power to maintain thermal comfort. The MPC algorithm uses this information to find the optimal operating points for the chiller and the ice bank to minimize the electric energy cost. The results of the MPC algorithm are compared against those of the reactive rule-based control algorithm currently in use in the building.


2021 ◽  
Author(s):  
Mahboubeh Ahmadipour ◽  
Mojtaba Barkhordari-Yazdi ◽  
Saeid R. Seydnejad

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