• Energy Research

Abstract A double pass photovoltaic thermal-solar air heater (PVT-SAH) system integrated with heat pipes was developed with the aim of using it for applications that require high-temperature air. A dynamic model was first developed and validated to predict the electrical and thermal performance of the PVT-SAH system with heat pipes and inform an analysis of economic benefits. A life-cycle saving method was employed, and an uncertainty analysis was included to investigate the economic performance of the proposed system in comparison with the performance of a benchmark design. The optimal designs for maximising electrical and thermal efficiencies of the new PVT-SAH system were obtained for several system lengths through a multi-objective design optimisation strategy. The PVT-SAH systems with heat pipes had higher capital construction costs than the benchmark designs but can still offer an annualised life cycle saving that ranged from A$925 to A$4606 and a payback time between 5.7 and 16.8 years. The PVT-SAH system with heat pipes was also found to deliver more efficient cooling effect to the PV panel and improve the temperature uniformity of the PV panel. The temperature variation along the length of the PV panel for the proposed system and for the benchmark design was 9.4 °C and 21 °C respectively. In addition, the maximum thermal efficiency of the PVT-SAH with heat pipes was 69.2% compared to 61.7% for benchmark design.

Abstract: Natural ventilation can be used in residential buildings in several Australian climatic zones and well-designed windows have the potential to facilitate indoor thermal comfort by allowing occupants to control volumetric outdoor airflow and indoor air velocities. Top-hung window is one of the most popular window types in Australia. This paper investigates the effect of the attributes of top-hung windows (i.e. window length, aspect ratio, height above the ground, window opening angle and the fly screen porosity) and outdoor air conditions (i.e. outdoor air temperature, wind speed and direction) on indoor thermal comfort during cross ventilation using CFD simulations. The Taguchi method was used to design the simulation scenarios and analysis of variance was used to determine the most significant factors influencing thermal comfort optimisation so as to reduce the number of CFD simulation cases. For the range of parameters considered and a particular case study building, results show that outdoor air temperature, window height and window opening angle are the most important factors influencing indoor thermal comfort in this room. The optimal window configurations for indoor thermal comfort of the case study building are also identified using a signal-to-noise ratio analysis.

Microencapsulated phase change materials (MEPCM) could be used for energy saving applications in buildings due to their relatively high energy storage capacities at constant temperature, which could passively reduce peak cooling loads in summer. In this study, poly(methyl methacrylate-co-methacrylic acid) (PMMA-MAA) was used as a shell material to fabricate MEPCM by crosslinking methyl methacrylate (MMA) and methacrylic acid (MAA) through in-situ suspension-like polymerization method. The effects of initiator weight percentage and the ratio of shell monomers for the preparation of MEPCM were also investigated. The experimental results showed that the best MEPCM sample was achieved with a shell monomer weight ratio of 80% MMA : 20% MAA and thermal initiator of 1 wt%. Differential scanning calorimetric (DSC) analysis also showed a latent heat value for the best sample as 170 kJ/kg with a melting temperature of 23.68°C which makes these materials suitable for application in residential buildings. Meanwhile, the core material contents and encapsulation efficiencies were calculated according to the measured results of the DSC. Finally the thermogravimetric (TG) analysis on the samples showed very good thermal stability behaviours ranging between 162.3°C and 204.4°C and therefore satisfies the environmental requirements for most applications.

Editorial to proceedings of Improving Residential Energy Efficiency International Conference, IREE 2017, 16-17 February 2017, Wollongong, Australia

We used outdoor test cells during a hot humid period to analyse the surface temperatures behind the following four types of green walls: a felt layer wall; a planter boxes wall; a direct climbing plants wall, and; an indirect climbing plants wall. We compared these temperatures with temperatures of a bare wall and we found that all four types of green facades were able to maintain lower temperatures than the bare wall, and that the felt layer and planter boxes wall had lower temperatures than the other walls for the majority of the study period. In particular, the daily average and peak surface temperatures behind the felt layer wall were by 1.9°C–4.8°C and by 7.1°C–13.4°C respectively lower than the bare wall. We undertook a significance analysis and produced Pearson coefficients to better understand the relationship between average daily weather conditions and the surface temperatures on all five test cells. We noted that the average daily solar radiation flux did not affect the surface temperatures behind the planter boxes and felt layer walls, but the daily average ambient air temperature was significantly correlated with the average and peak surface temperatures behind all four green facades. Finally, we concluded that the cooling potential of the felt layer and the planter boxes walls increases with higher amounts of solar radiation and higher ambient temperatures. In addition, from the analysis of the diurnal temperature variations and the time series trends we illustrated that the temperatures behind the felt layer and planter boxes walls fluctuated less than the other walls, which lead to a slower rate of surface temperature reductions during a cooler day than the other wall types of the study.

Abstract Ground source heat pump (GSHP) systems have attracted wide attention in developing energy-efficient buildings. Considering the high upfront cost of GSHP systems, appropriate design and control optimization are essential to enhancing their energy efficiency and reducing the payback period. Since there are many variables influencing the performance of GSHP systems, the commonly used rule-based approaches cannot ensure that the system is designed and operated in an optimal manner. This paper presents an overview of recent advances and development in optimal design and control of GSHP systems, aiming to provide some concluding remarks and recommendations for future research in this direction. The general optimization problems for optimal design and control of GSHP systems are first presented. Sensitivity analysis to determine the major variables to formulate the optimization problems is then discussed. Furthermore, recent progress in optimal design and control of GSHP systems is reviewed. The results showed that an increasing number of single-objective and multi-objective design optimization strategies for GSHP systems have been developed, which seems more robust than commonly used rule-based design approaches. It was shown that optimal control can provide a better operating performance of GSHP systems as compared to rule-based control methods. The majority of studies used a model-based approach to formulate the control problem and model predictive control could play an essential role in renewable integrated GSHP systems. However, studies on optimal control of GSHP systems are insufficient and development of energy-efficient control strategies and evaluation of their control reliability, effectiveness and long-term performance are needed.

Abstract This paper presents a model-based optimal control strategy for ground source heat pump systems with integrated solar photovoltaic thermal collectors (GSHP-PVT). The control strategy was formulated using simplified adaptive models and a genetic algorithm (GA) to identify energy efficient control settings for GSHP-PVT systems. The simplified adaptive models were used to predict the system energy performance under various working conditions and control settings, and the model parameters were continuously updated using the recursive least squares (RLS) estimation technique with exponential forgetting. The performances of the adaptive models and the control strategy were evaluated based on a virtual simulation system representing a GSHP-PVT system for residential applications. The performance of the major adaptive models was also validated using the experimental data. The results showed that the simplified adaptive models used were able to provide acceptable energy performance prediction. The optimal control strategy can save energy consumption by 7.8%, 7.1% and 7.5%, and increase electricity generation by 4.4%, 6.2% and 5.1%, during the whole cooling, heating and transition periods considered, respectively, in comparison to a conventional control strategy. The findings obtained from this study could be potentially used to drive the development of advanced control strategies suitable for real-time applications.