Hybrid model predictive control of residential heating, ventilation and air conditioning systems with on-site energy generation and storage

Driven by population growth and our insatiable need for energy, there is an ever increasing trend in worldwide energy consumption and cost. Therefore, sustainability in the energy sector has become one of the most important international strategic issues. One approach to mitigating this trend is to reduce energy consumption in the built environment, which contributes significantly to overall world energy demand. A substantial reduction in consumption of fossil fuels can be achieved by increasing building energy efficiency, as well as integrating on-site renewable electrical and thermal energy generation, and energy storage. Such solutions are becoming more and more cost effective, and readily available for straightforward implementation in both new and existing buildings. This thesis presents the design, implementation and testing of an innovative solarassisted residential Heating, Ventilation and Air Conditioning (HVAC) system developed for the Team UOW ‘Illawarra Flame’ Solar Decathlon house and the design, development and implementation of a Hybrid Model Predictive Control (HMPC) strategy to optimise its operational performance. This novel yet practical modelling and control approach has wide spread application in the optimisation of HVAC and integrated renewable energy systems. The Illawarra Flame house was the winning entry to the Solar Decathlon China 2013 competition, and its HVAC system included an airbased Photovoltaic-Thermal (PVT) collector and a Phase Change Material (PCM) thermal store integrated with a reverse-cycle heat pump, in a ducted air distribution system.