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A monitoring system was developed and implemented in the Archetype Sustainable House (ASH) of the Toronto and Region Conservation Authority (TRCA) for testing the performance of a gas-fired absorption heat pump various inlet temperatures at three different flowrates of glycol-water mixture, containing 50% propylene glycol. Results show that at 50% concentration of propylene glycol the output capacity of the GAHP is approximately 12–13 % lower than the specified capacity. Furthermore, at nominal flowrates in heating mode, the gas utilization efficiency (GUE), which is the ratio of heating (or cooling) output to the thermal energy input, stays above ‘1’ for outdoor temperatures down to –5 oC, implying that GAHP is more efficient than conventional heating equipment up to that point. Below –5 oC the GUE drops below ‘1’ and the GAHP acts like a conventional high efficiency boiler which means that GAHP is either better than or just as efficient as conventional heating equipment depending on the outdoor temperatures. However, the magnitude of energy savings achieved greatly depends on how frequently temperatures below –5 oC are encountered in a given heating season.

This preliminary study is part of a bigger cloud-based smart dual fuel switching system (SDFSS) for hybrid heating, ventilation and air conditioning (HVAC) systems. The SDFSS being developed enables flexible and cost-optimized control between the natural gas furnace and air source heat pump (ASHP), allowing simultaneous reduction in energy costs and greenhouse gas (GHG) emissions. To meet the optimal energy consumption requirements and satisfaction of the residents, the employment of smart sensors and software are broadly used. The data regarding the outdoor temperature plays the most crucial role in operating and controlling the SDFSS optimally. This study introduces a novel approach to obtaining the outdoor temperature that could potentially replace smart sensors with a data-driven model utilizing weather station data at time resolutions of 2 minutes and 1 hour. In this work, a computer program was implemented under Matlab R2018a software. This study found that the artificial neural network (ANN) model was able to predict the outdoor temperature within 0.95 R error in average, demonstrating ANN to be a powerful tool in predicting outdoor temperature. Thus, the model proposed can be confidently implemented as an alternative to temperature sensors in automated systems, in hybrid energy systems or other energy systems requiring accurate ambient temperature measurements.

This paper is intended to develop a detailed thermal and electrical model of a transparent backing Building Integrated Photovoltaic/Thermal (TBIPV/T) collector integrated to the roof. This model was used to assess the energy performance of a typical transparent PVT air collector. The energy balance equations were derived for glazing glass, the PV cells, glass back surface of the PV module, air flowing in the duct of TBIPV/T collector and back insulation surface. The energy equations were solved using FORTRAN. A new TRNSYS type was created for the transparent backing PVT system. This type is intended to function with multi-zone building model in TRNSYS, that means thermal interaction between the PV/T collector and the building was taken into account. The effect of different PVT system parameters such as PV cell packing factor, panel cover optical properties on thermal energy production and electricity generation were examined and discussed.

A test facility is designed and is under construction to experimentally verify the effect of thermal energy storage systems in overall performance of a coupled Building Integrated PhotoVoltaic / Thermal (BIPV/T) and Air Source Heat Pump (ASHP). This study shows how the loads for the test facility were adjusted by a regular size single family residential building. Moreover, the article explains different unique options of storing thermal energy in the test facility using the thermal mass of the building itself. Numerical models of Insulated Concrete Form (ICF) wall and Ventilated Concrete Slab (VCS) were developed using SolidWorks software’ Flow Simulation module and ANSYS Fluent software.