Optimization of Sustainable Residential Heating and Cooling Systems

Abstract

Increased attention has been given to energy efficient, renewable energy systems for Heating, Ventilation and Air Conditioning (HVAC) in buildings as these often account for 40% or more of the total building energy consumption. Among them, Ground Source Heat Pumps (GSHP) are becoming increasingly attractive due to their reliability, low environmental impact and high efficiency when compared to conventional HVAC systems. However, their uptake has been limited due to the high initial cost involved in the drilling of boreholes for exchanging heat with the ground via HPDE (high density polyethileine) pipes. In addition, their system performance may also decline over long operating horizons if the annual heating and cooling loads are severely unbalanced. The application of hybrid ground source heat pump systems have therefore been proposed as an effective alternative approach that can mitigate these challenges and improve overall system performance.

Hybrid systems offset some percentage of the demand with the use of a supplemental source or a sink of heat. Solar thermal or conventional resistive heaters can be used as supplementary heat sources, thus forming a hybrid ground source heat pump system for heating-dominant climates. However, finding optimal design parameters when designing these systems is crucial to minimize the total life cycle cost and to improve overall system performance. In addition, due to their high initial cost, it is also important to conduct a feasibility study considering the full life cycle cost in comparison to conventional systems. Furthermore, the effect of local climatic conditions and economic structures on the system design and performance needs to be evaluated and understood to be able to select the most economical HVAC system for a given geographical location.

Implementing an intelligent control strategy can further improve the system performance by delivering the energy demanded efficiently. A significant percentage of the operational cost can be reduced by integrating the peak and off peak electricity prices into the controller. In addition, studies have shown that a substantial amount of cost and energy can be saved by incorporating weather and occupancy predictions into the controller. However, due to the uncertain nature of these variables, an effective controller must consider the uncertainties of the system dynamics.

This thesis explores optimisation of the system design for heating dominant climates while assessing their feasibility over conventional systems. The results suggest that optimally designed hybrid GSHP systems can achieve significant cost savings (up to 32%) compared to conventional heating and cooling systems. In addition, efficiency improvements in the operation of hybrid GSHP systems are also investigated to overcome the barriers associated with these systems and to make them a cost effective, attractive technology for building heating and cooling systems. The study demonstrated a considerable amount of operational cost reduction by incorporating uncertainty into the HVAC controller.