In Canada 15% of greenhouse gas (GHG) emissions are produced by the residential sector’s energy demand. The majority of the energy demand is space heating which is primarily met with natural gas combustion. Motivation exists to reduce GHG emissions due to their contribution to climate change. Integrated Community Energy Harvesting (ICE-Harvest) systems seek to integrate thermal and electrical energy production, storage, redistribution, and consumption in a way that reduces GHG emissions. Borehole thermal energy storage (BTES) is implemented in ICE-Harvest systems as seasonal thermal energy storage. This thesis presents a novel model of BTES thermal response with reduced complexity to aid in early siting, design, optimization, and control systems development work for ICE-Harvest systems. The reduced model can be used to approximate periodic steady state BTES thermal response. The model provides information on average ground storage volume temperature, outlet fluid temperature, heat exchanger fluid to storage volume heat transfer rate, storage volume top loss heat transfer rate, storage volume side and bottom loss heat transfer rate, and annual thermal energy storage efficiency which aids system modelling efforts for BTES in solar thermal and ICE-Harvest systems. The reduced model is formed from a solution of the thermal energy balance equations for the BTES ground storage volume and heat exchanger fluid with simplified operating conditions for a yearly BTES charging and discharging cycle. Ground storage volume temperature is lumped as a single value. Heat transfer rates between the storage volume and the heat exchanger fluid and the storage volume and its surroundings are modelled with periodic steady state thermal resistance values for the charging and discharging timesteps. A TRNSYS DST simulation of BTES is validated against measurements from a BTES installation and TRNSYS DST is used to generate the periodic steady state thermal resistance values the reduced model requires. The periodic steady state thermal resistance values of BTES charging and discharging are dependent on BTES design parameters (spacing between boreholes, number of boreholes, borehole depth, and storage volume size) and ground thermal properties (thermal capacity and thermal conductivity) which is presented in a series of parameter sweeps with respect to a reference simulation. The reduced model predicts periodic steady state average storage volume temperature with a RMSD of 0.96°C for charging and 1.3°C for discharging when compared to the TRNSYS DST reference simulation. The reduced model predicts the periodic steady state heat exchanger total energy transfer within 1.8% for the charging timestep and 2.8% for the discharging timestep when compared to the TRNSYS DST reference simulation. The reduced model’s periodic steady state thermal resistance values are demonstrated to be independent of heat exchanger fluid inlet temperature except for the side and bottom loss thermal resistance during discharging. The reduced model cannot replicate the change in heat transfer direction that occurs during BTES discharging when the temperature of the storage volume decreases below the temperature of the surrounding ground, however, the magnitude of the energy transfer that would occur is negligible compared to the magnitude of the BTES heat exchanger total energy transfer. / Thesis / Master of Applied Science (MASc)

This thesis's main objective is to conduct a comparison study between measured values and simulated results of a demonstrator, of the intelligent home energy management (iHEM) project. The comparison helps to validate the simulation. TRNSYS software is used for the design. In this study, only the thermal energy side of the project is considered. In which system-level (both domestic hot water (DHW), space heating (SH)) and component level (solar collector, gas boiler) are considered as the parameters to compare. An attempt is made to optimize both system-level and component-level simulation outputs with measured values by adopting measured boundary conditions as simulation inputs.During the comparison, the DHW loop simulation design is modified. The measured data were given as input files for simulation, replacing the estimated values used before. This is done to optimize the simulation output with measured data. In the space heating loop (SH), the simulated building model’s parameters were changed to optimize the SH demand. After the system-level validation and optimization, the component level comparison is carried out. For this, the simulation output of solar thermal collectors and gas boiler are compared with measured values. The solar collector loop in the simulation is modified to optimize the simulated results. The seasonal and yearly efficiencies of the collector have been calculated. Solar supply fraction and gas boiler supply fraction is also determined. For the comparison, graphs are plotted for three different weeks, representing the spring, summer, and winter months of 2018.The final optimized simulation output of DHW demand is 7% less than the measured value. Even after optimizing the Space heating loop (SH), the simulated building demand is 17% more heat than the demonstrator building. The simulation's solar collector output is optimized close to the measured values. The simulated gas boiler produces 19% more than the demonstrator system to meet excess SH demand in the simulation (including losses). The overall yearly collector efficiency calculated for measured and simulated values are 58% and 50%, respectively. The estimated solar collector supply fraction and gas boiler supply fraction is 26%, 76% for measured, and 23%, 81% for simulation, respectively.

This thesis's main objective is to conduct a comparison study between measured values and simulated results of a demonstrator, of the intelligent home energy management (iHEM) project. The comparison helps to validate the simulation. TRNSYS software is used for the design. In this study, only the thermal energy side of the project is considered. In which system-level (both domestic hot water (DHW), space heating (SH)) and component level (solar collector, gas boiler) are considered as the parameters to compare. An attempt is made to optimize both system-level and component-level simulation outputs with measured values by adopting measured boundary conditions as simulation inputs.During the comparison, the DHW loop simulation design is modified. The measured data were given as input files for simulation, replacing the estimated values used before. This is done to optimize the simulation output with measured data. In the space heating loop (SH), the simulated building model’s parameters were changed to optimize the SH demand. After the system-level validation and optimization, the component level comparison is carried out. For this, the simulation output of solar thermal collectors and gas boiler are compared with measured values. The solar collector loop in the simulation is modified to optimize the simulated results. The seasonal and yearly efficiencies of the collector have been calculated. Solar supply fraction and gas boiler supply fraction is also determined. For the comparison, graphs are plotted for three different weeks, representing the spring, summer, and winter months of 2018.The final optimized simulation output of DHW demand is 7% less than the measured value. Even after optimizing the Space heating loop (SH), the simulated building demand is 17% more heat than the demonstrator building. The simulation's solar collector output is optimized close to the measured values. The simulated gas boiler produces 19% more than the demonstrator system to meet excess SH demand in the simulation (including losses). The overall yearly collector efficiency calculated for measured and simulated values are 58% and 50%, respectively. The estimated solar collector supply fraction and gas bo