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This study was conducted to assess the techno-economic feasibility of converting the Canadian housing stock (CHS) into net/near zero energy buildings by introducing and integrating high efficient and renewable/alternative energy technologies in new construction and existing houses. Performance assessment of energy retrofit and renewable/alternative energy technologies in existing houses in regional and national scale is necessary to devise feasible strategies and incentive measures. The Canadian Hybrid Residential End-Use Energy and GHG Emissions model (CHREM) that utilizes a bottom-up modeling approach is used to investigate the techno-economic feasibility of air to water heat pump retrofit in the Canadian housing stock. The proposed energy retrofit includes an air to water heat pump, auxiliary boiler, thermal storage tank, hydronic heat delivery and domestic hot water (DHW) heating. Energy savings, GHG emission changes and economic feasibility of the air source heat pump retrofit are considered in this study. Results show that there is a potential to reduce 36% of energy consumption and 23% of GHG emissions of the CHS if all eligible houses undertake the retrofit. Economic analysis indicates that the feasibility of air to water heat pump systems is strongly affected by the current status of primary energy use for electricity generation and space and DHW heating as well as energy prices and economic conditions. Legislation, economic incentives and education for homeowners are necessary to enhance the penetration level of air to water heat pump retrofits in the CHS.

An improved understanding of the consumption patterns, end-uses, and temporal variations of electrical loads in houses is warranted because a significant fraction of a society's total electricity consumption occurs within residential buildings. In general, there is a lack of high-temporal-resolution data describing occupant electrical consumption that are available to researchers in this field. To address this, new measurements were performed and combined with data emanating from an earlier study to provide a database of annual measurements for 23 houses at a 1-min resolution that characterizes whole-house, non-HVAC, air conditioner, and furnace fan electrical draws, as well as the draw patterns of some major appliances. All houses were located in Ottawa, Canada. The non-HVAC measurements of this 23-house sample were shown to be in agreement with published estimates for the housing stock. The furnace fan was found to be the most significant end-use. These high-temporal-resolution data of electrical demands in houses can be used by researchers to increase the fidelity of building performance simulation analyses of different micro-generation technologies in residential buildings.

Fuel cells with nominal outputs of approximately 1kW AC are emerging as a prime-mover of a micro-cogeneration system potentially well-suited to compete, on an energy basis, with conventional methods for satisfying occupant electrical and thermal demands in a residential application. As the energy benefits of these systems can be incremental when compared to efficient conventional methods, it is especially important to consider the uncertainties of the models on which simulation results are based. However, researchers have yet to take this aspect into account.This article makes a contribution by demonstrating how these model uncertainties may be propagated to the simulation results of a micro-cogeneration system for comparison to a reference scenario using a case study. This case study compares the energy performance of a fuel-cell based micro-cogeneration system serving only domestic hot water demands to an efficient reference scenario where the conventional methods for providing electrical and thermal demands are considered to be a central gas-fired combined-cycle plant and a condensing tankless water heater respectively. The simulation results demonstrated that if model uncertainties were ignored, it would have been possible to demonstrate that the considered micro-cogeneration system was more efficient than the reference scenario for average consumption levels of domestic hot water. However, when model uncertainties were considered, the efficiency of the considered micro-cogeneration system could not reliably exceed that of the reference scenario by serving the domestic hot water needs of a single-family home.

Techno-economic impact of retrofitting houses in the Canadian housing stock with PV and BIPV/T systems is evaluated using the Canadian Hybrid End-use Energy and Emission Model. Houses with south, south-east and south-west facing roofs are considered eligible for the retrofit since solar irradiation is maximum on south facing surfaces in the northern hemisphere. The PV system is used to produce electricity and supply the electrical demand of the house, with the excess electricity sold to the grid in a net-metering arrangement. The BIPV/T system produces electricity as well as thermal energy to supply the electrical as well as the thermal demands for space and domestic hot water heating. The PV system consists of PV panels installed on the available roof surface while the BIPV/T system adds a heat pump, thermal storage tank, auxiliary heater, domestic hot water heating equipment and hydronic heat delivery system, and replaces the existing heating system in eligible houses. The study predicts the energy savings, GHG emission reductions and tolerable capital costs for regions across Canada. Results indicate that the PV system retrofit yields 3% energy savings and 5% GHG emission reduction, while the BIPV/T system yields 18% energy savings and 17% GHG emission reduction in the Canadian housing stock. While the annual electricity use slightly increases, the fossil fuel use of the eligible houses substant

The techno-economic feasibility of retrofitting existing Canadian houses with solar assisted heat pump (SAHP) is investigated. The SAHP architecture is adopted from previous studies conducted for the Canadian climate. The system utilizes two thermal storage tanks to store excess solar energy for use later in the day. The control strategy is defined in order to prioritise the use of solar energy for space and domestic hot water heating purposes. Due to economic and technical constraints a series of eligibility criteria are introduced for a house to qualify for the retrofit. A model was built in ESP-r and the retrofit was introduced into all eligible houses in the Canadian Hybrid Residential End-Use Energy and GHG Emissions model. Simulations were conducted for an entire year to estimate the annual energy savings, and GHG emission reductions. Results show that the SAHP system performance is strongly affected by climatic conditions, auxiliary energy sources and fuel mixture for electricity generation. Energy consumption and GHG emission of the Canadian housing stock can be reduced by about 20% if all eligible houses receive the SAHP system retrofit. Economic analysis indicates that the incentive measures will likely be necessary to promote the SAHP system in the Canadian residential market.

The design and analysis of community-scale energy systems and incentives is a non-trivial task. The challenge of such undertakings is the well-documented uncertainty of building occupant behaviours. This is especially true in the residential sector, where occupants are given more freedom of activity compared to work environments. Further complicating matters is the dearth of available measured data. Building performance simulation tools are one approach to community energy analysis, however such tools often lack realistic models for occupant-driven demands, such as appliance and lighting (AL) loads. For community-scale analysis, such AL models must also be able to capture the temporal and inter-dwelling variation to achieve realistic estimates of aggregate electrical demand. This work adapts the existing Centre for Renewable Energy Systems Technology (CREST) residential energy model to simulate Canadian residential AL demands. The focus of the analysis is to determine if the daily, seasonal, and inter-dwelling variation of AL demands estimated by the CREST model is realistic. An in-sample validation is conducted on the model using 22 high-resolution measured AL demand profiles from dwellings located in Ottawa, Canada. The adapted CREST model is shown to broadly capture the variation of AL demand variations observed in the measured data, however seasonal variation in daily AL demand behaviour was found to be under-estimated by the model. The average and variance of daily load factors was found to be similar between measured and modelled. The model was found to under-predict the daily coincidence factors of aggregated demands, although the variance of coincident factors was shown to be similar between measured and modelled. A stochastic baseload input developed for t

Large amounts of south facing windows can help reduce heating demand in the winter and shoulder seasons by allowing high levels of solar radiation to enter the building. One problem that may arise from large areas of south facing glazing is overheating of the adjacent rooms, even during winter in a cold climate. Cooling of the floors may provide a means to prevent overheating in such a situation. Cooling a floor prevents solar gains absorbed by the floor from being transferred to the space by convection or infrared radiation. This cooling can be achieved with the use of water pipes in the floor. The heat removed can be upgraded to a higher temperature with a heat pump, and then may be stored in a thermal storage tank for space heating and domestic hot water heating. This paper shows preliminary simulation results of such a system for a house in Ottawa, Canada. The house contains a much larger south facing window area than is typical. In periods of overheating, the solar gains are absorbed by the floor cover and collected by the cold pipes in the floor. The heat is upgraded by a heat pump and stored in a hot storage tank. Preliminary modelling results show that, with the use of a large thermal storage tank (2 m3), space heating and domestic hot water demand with this type of system may be reduced by as much as 24%, when compared with a more conventional house.

Solar thermal systems have been identified as a viable solution to meeting domestic thermal energy needs due to their low temperature operating conditions. The complication of these systems is that solar availability and demand side loads are often mismatched. This is especially true for solar space heating systems, where demand is a maximum in winter when solar potential is the lowest. By using a long-term thermal storage, useful gains in the summer may be carried over to the heating season. There are numerous simulation tools capable of studying such solar thermal systems and building-side demands, however each tool possesses both strengths and shortcomings. This paper outlines the strengths of two modelling tools, TRNSYS and ESP-r, through a new co-simulator in order to evaluate the potential contributions of a seasonal solar thermal system at a single-house scale.

The pursuit of innovative architectural designs and the development of novel and integrated energy conversion, storage, and distribution technologies presents a challenge for existing building performance simulation (BPS) tools. No single BPS tool offers sufficient capabilities and the flexibility to resolve all the possible design variants of interest. The development of a co-simulation bet

Published validation tests developed within major research projects have been an invaluable aid to program developers to check on their programs. This paper sets out how selected ASHRAE Standard 140-2004 and European CEN standards validation tests have been incorporated into the ESP-r simulation program so that they can be easily run by users and also discusses some of the issues associated with compliance checking. Embedding the tests within a simulation program allows program developers to check routinely whether updates to the simulation program have led to signif­icant changes in predictions and to run sensitivity tests to check on the impact of alternative algorithms. Importantly, it also allows other users to undertake the tests to check that their installation is correct and to give them, and their clients, confi­dence in results.