Thesis-1997-Ren.pdf (6.63 MB)
Optimal predictive control of thermal storage in hollow core ventilated slab systems
thesis
posted on 2013-06-10, 13:48 authored by Mei J. RenThe energy crisis together with greater environmental awareness, has increased interest
in the construction of low energy buildings. Fabric thermal storage systems
provide a promising approach for reducing building energy use and cost, and consequently,
the emission of environmental pollutants. Hollow core ventilated slab
systems are a form of fabric thermal storage system that, through the coupling of
the ventilation air with the mass of the slab, are effective in utilizing the building
fabric as a thermal store. However, the benefit of such systems can only be realized
through the effective control of the thermal storage. This thesis investigates an
optimum control strategy for the hollow core ventilated slab systems, that reduces
the energy cost of the system without prejudicing the building occupants thermal
comfort.
The controller uses the predicted ambient temperature and solar radiation, together
with a model of the building, to predict the energy costs of the system
and the thermal comfort conditions in the occupied space. The optimum control
strategy is identified by exercising the model with a numerical optimization
method, such that the energy costs are minimized without violating the building
occupant's thermal comfort. The thesis describes the use of an Auto Regressive
Moving Average model to predict the ambient conditions for the next 24 hours.
A building dynamic lumped parameter thermal network model, is also described,
together with its validation. The implementation of a Genetic Algorithm search
method for optimizing the control strategy is described, and its performance in
finding an optimum solution analysed.
The characteristics of the optimum schedule of control setpoints are investigated
for each season, from which a simplified time-stage control strategy is derived. The
effects of weather prediction errors on the optimum control strategy are investigated
and the performance of the optimum controller is analysed and compared
to a conventional rule-based control strategy. The on-line implementation of the
optimal predictive controller would require the accurate estimation of parameters
for modelling the building, which could form part of future work.
History
School
- Architecture, Building and Civil Engineering
Publisher
© Mei Juan RenPublication date
1997Notes
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough UniversityEThOS Persistent ID
uk.bl.ethos.389774Language
- en