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Implementation of real-time model predictive heating control for a factory building using ANN-based lumped modelling approach.
- Source :
- Journal of Building Performance Simulation; Mar2023, Vol. 16 Issue 2, p163-178, 16p
- Publication Year :
- 2023
-
Abstract
- It is important to control the heating system by following real-time demand, while considering the dynamic changes and non-uniform distributions of indoor environments. This paper presents a model predictive control (MPC) scheme for predicting indoor air temperatures at multiple points in a large factory building that consists of large irregular spaces and heat-generating equipment. Instead of using a full-blown dynamic simulation model (e.g. EnergyPlus), the authors developed a lumped simulation model. This model can accurately predict the temperatures and is, therefore, used for the optimal on/off control of 61 unit heaters installed in the factory building. Based on the MPC, energy savings of 56.3% were realized over three weeks, and the indoor air temperatures were maintained within a comfortable range. It is highlighted in the paper that this MPC approach based on the minimalistic lumped model can accurately predict indoor thermal behaviour and save significant energy. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19401493
- Volume :
- 16
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Journal of Building Performance Simulation
- Publication Type :
- Academic Journal
- Accession number :
- 161935888
- Full Text :
- https://doi.org/10.1080/19401493.2022.2125581