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[Display omitted] • Novel method to estimate total technical potential for improving energy efficiency. • Bottom-up sector energy model used to characterize energy demands and opportunities. • Technology-explicit analysis framework used to estimate integrated energy savings. • Application to Canada's pulp & paper sector indicates major savings are possible. • Technical potential to reduce natural gas use by 95% and net electricity by 54% Industrial energy efficiency has long been recognized as a critical tool for energy management and emissions reduction and is increasingly considered to be an energy resource in its own right. However, the complexity of most industrial sectors creates barriers for modellers, companies, and policymakers in understanding and achieving the overall potential for efficiency-driven energy savings. To address this gap, we have developed a novel method that combines disaggregated bottom-up sector energy modelling with analysis of a comprehensive set of technology-explicit energy efficiency measures. This approach overcomes the deficiencies of top-down analyses and better represents the complexities of multi-measure efficiency investments compared to piecewise studies of individual measures. In this study, we demonstrated application of our method to the case of the Canadian pulp and paper sector. Our analysis shows that the sector can reduce its natural gas and electricity use by 95% and 41%, respectively, by adopting economical efficiency measures. This equates to 71 PJ of natural gas and 44 PJ of electricity saved annually and would result in cost savings of $81 per tonne of output sector-wide. Notably, we find that efficiency and fuel switching have the technical potential to reduce natural gas consumption by 98% across the sector. Taken together, the results provide quantitative evidence that energy efficiency is an underestimated resource for cost-effective energy savings in the Canadian pulp and paper sector. Our analysis framework can be applied to any industrial sector in any region to provide insights regarding energy conservation strategies and policy design. [ABSTRACT FROM AUTHOR]

The residential energy demand timing and magnitude are highly impacted by occupants' behaviors and activities. However, acquiring a reliable data source for these activities is a vital challenge, especially on an urban scale. In this context, this paper presents a stochastic bottom-up model for generating electrical loads for residential buildings in Canada. The proposed model is developed to investigate the impact of different household characteristics, appliance stock, and energy behaviors on the timing and magnitude of non-HVAC energy loads at individual or multiple houses. The proposed tool includes four main modules for generating stochastic profiles of occupancy, lighting demand, appliance load, and domestic hot water demand (DWH). The model is calibrated using the Canadian time use survey (TUS), energy use statistics, and appliance ownership surveys. The model is scalable and can be extended to serve various applications by adding new modules and data sources in the future. This paper presents the model development methodology, generated high-resolution load profiles, and validation in comparison with actual measurements. Finally, the model is used for studying the impact of household characteristics on total energy use. Future work will include incorporating this model into a comprehensive agent-based model for designing and testing effective demand response programs. • A stochastic load profile generator is developed for residential buildings. • Canadian TUS data is used to identify common patterns of activity schedules. • Stochastic profiles are developed for occupancy, lighting, appliances, and DWH. • The tool is demonstrated and validated using a case study. • The impact of household characteristics on total energy use is studied. [ABSTRACT FROM AUTHOR]

The Kraft process is an intensive user of capital, energy, water, and chemicals, and is particularly vulnerable in the present precarious economic situation. Therefore, Canadian Kraft pulp mills offer good potential for improvement, especially if the equipment and unit operations are diagnosed in details by means of specific key performance indicators (KPI). The characterization and performance analysis of equipment is a prerequisite to optimization. A thorough evaluation of the equipment performance must be done to assess the actual vs. the expected performance before proceeding to any kind of energy improvement project. A systematic methodology for equipment performance evaluation through key performance indicators (KPIs) is presented in Part I. New key performance indicators (KPIs) based on dimensional analysis as well as other conventional key performance indicators are used to efficiently analyze and diagnose the causes of inefficiencies of the equipment, and propose adequate remedial actions. The methodology has been applied to an Eastern Canadian Kraft mill and several improvement projects leading to 30% of energy savings are proposed, entailing a low investment cost and a payback of 1.1 a. [ABSTRACT FROM AUTHOR]

Permylene™ demonstration system (PDS), a membrane-based pilot unit for olefin/paraffin separation, is designed and fabricated by Imtex Membranes Corp. (Imtex). The PDS, equipped with pilot-scale Permylene™ elements, is capable of treating up to 3 kg/h of olefin/paraffin mixture. The PDS unit is installed in Imtex's testing lab in Mississauga, Ontario, Canada. Various plant-collected and lab-blended olefin/paraffin mixtures involving ethylene/ethane (C2), propylene/propane (C3), and butene/butane (C4) have been assessed on the unit. This paper is focused on the application of PDS for C3 separation, and a series of remarkable performances that have been achieved by the Permylene™ membrane and PDS unit. Propylene purity of over 98.5 vol% in the permeate/product stream has been reached over a wide range of propylene recovery rates, which could offer significant flexibility to meet various industrial operation conditions. Furthermore, the PDS unit demonstrates its stability and efficiency with 1200 hrs of continuous C3 permeation. Finally, a case study of recovering 90 % of propylene from 15,000 kg/h of C3 is performed to estimate energy consumption in commercial applications. The energy consumption of the Permylene™ process is calculated and compared with that of the distillation process. The result indicates that the energy consumption in PDS is extremely low, equal to only 8 % of that required in distillation. The study undeniably validates Permylene™'s remarkable capability for C3 separation, highlighting its potential as a viable and energy-efficient alternative to traditional distillation. [Display omitted] • The asymmetric membrane and solution replenishing overcome the instability. • This pilot unit is capable of treating up to 3 kg/h of olefin/paraffin mixture. • Propylene purity of 98.5 vol% is reached over a wide range of recovery rates. • Stable performance is shown in 1200 h of continuous C3 permeation. • The energy consumption in PDS equals 8 % of that required in distillation. [ABSTRACT FROM AUTHOR]

As the importance of eco-friendly transportation increases, providing an efficient approach for marine vessel operation is essential. Methods for status monitoring with consideration to the weather condition and forecasting with the use of in-service data from ships requires accurate and complete models for predicting the energy efficiency of a ship. The models need to effectively process all the operational data in real-time. This paper presents models that can predict fuel consumption using in-service data collected from a passenger ship. Statistical and domain-knowledge methods were used to select the proper input variables for the models. These methods prevent over-fitting, missing data, and multicollinearity while providing practical applicability. Prediction models that were investigated include multiple linear regression (MLR), decision tree approach (DT), an artificial neural network (ANN), and ensemble methods. The best predictive performance was from a model developed using the XGboost technique which is a boosting ensemble approach. Our code is available on GitHub at https://github.com/pagand/model%5foptimze%5fvessel/tree/OE for future research. • Comparison of fuel consumption models for west coast Canada vessel • Feature engineering utilized domain knowledge to identify key variables • Parametric and non-parametric models used for prediction model development • Evaluation included running time, mean error, and future step prediction error. [ABSTRACT FROM AUTHOR]

Abstract: Prince Edward Island (PEI) is the smallest province in Canada measuring about 5700 km2 in area with a population of around 130,000 people. Small family farm operation is part of the Island's way of life. However, the dairy industry in North America is undergoing significant structural change. Statistics show a significant decline in the small dairy farms industry, while the number of large operations has been increasing. Advantages for large operations include purchasing energy in large quantities with better price margins and the inherent economy of scale created by such breaks. One strategy for small-scale farms to become competitive is to reduce their energy-related operational costs and greenhouse gas emissions. This can be achieved through taking energy efficiency steps, reducing overall energy consumption and generating energy through renewable energy resources and technologies. This paper uses a case study of a small dairy farm in Oyster Bed Bridge, PEI to gain insight into the direct use of energy within small dairy farms. An energy audit methodology is used to determine the energy intensity of the farm as well as energy efficiency opportunities. The paper also assesses the feasibility of meeting part of the energy demand of the farm with renewable energy generation. Energy efficiency recommendations for the case study farm include lighting retrofitting and regular maintenance of refrigeration condenser units. Renewable energy generation findings include the potential use of an anaerobic digester or a 25 kW wind turbine to generate the majority of the operation's energy. [Copyright &y& Elsevier]

Policy-makers are investigating ways to reduce greenhouse gas emissions of the transportation sector. Many government agencies have studied the effects of pavement type and characteristics on fuel consumption. Such models, valid for a particular set of simulation conditions, suggest that rigid pavements perform better than flexible pavements. However, it is unclear how this type of model can be applied at the scale of a realistic road network. This paper proposes a statistical approach to assess the relative importance of pavement type and characteristics on fuel consumption of heavy vehicle traffic by considering the specificities of meteorological conditions, heavy vehicles, and driver behaviours. A case study in Canada showed that the potential advantage of using rigid pavements was offset by cold climate effects and the consideration of a realistic statistical payload distribution. Road roughness accounted on average for 1.1% of total fuel consumption, with an increased value of 1.9% in January. [ABSTRACT FROM AUTHOR]

In a zero energy home annual energy consumption is equal to the annual energy production using one or more available renewable energy resources. In St John’s, Newfoundland wind is the readily available renewable energy resource. The average annual wind speed in St John’s is 6.7 m/s. This paper presents a feasibility study of a wind energy conversion system based zero energy home in Newfoundland. This study is based on year round recorded wind speed data, solar data and power-consumed data in a typical R-2000 house in Newfoundland. National Renewable Energy Laboratory’s software HOMER is used to select an optimum energy system. A detailed analysis, description and expected performance of the system are presented in this paper. This investigation indicates feasibility of a wind energy system based zero energy homes in Newfoundland. [Copyright &y& Elsevier]

This paper presents a case study of a recently built high-performance Canadian social housing building with the aim of comparing the expected and measured energy consumptions and to identify the parameters affecting the most the energy need. A monitoring system compiles at a 10-min frequency information related to the energy use and the thermal conditions observed in the building and its HVAC system. The building has the particularity of comprising two symmetric sections made of different timber structure systems. No significant differences of energy consumption were detected between the two parts of the buildings. However, a large variance was observed when comparing each dwelling individually regardless of their structures. The orientation of the dwelling also exhibited a minimal influence compared to these variations, suggesting that occupant behavior is the dominant factor explaining dwelling-to-dwelling variability and is thus critical for understanding energy use in residential buildings. Regression analysis showed that specific occupant actions, such as opening windows in winter or using electrical appliances, have a great impact on the energy balance of the apartments. In 2016, the performance gap between measured and expected total energy demand of the building was 74%. With the use of the large dataset coming from the building, it was possible to determine the causes behind this large gap for the reference building. [ABSTRACT FROM AUTHOR]

[Display omitted] • Post-plasma constriction of a CO 2 microwave plasma enhances conversion and energy efficiency. • Increased performance is the result of enhanced molecular transport from the plasma region. • 3D CFD simulations showed that the constriction encourages product retention, which results in increased performance. Transforming CO 2 into value-added chemicals is crucial to realizing a carbon–neutral economy, and plasma-based conversion, a Power-2-X technology, offers a promising route to realizing an efficient and scalable process. This paper investigates the effects of post-plasma placement of a converging–diverging nozzle in a vortex-stabilized 2.45 GHz CO 2 microwave plasma reactor to increase energy efficiency and conversion. The CDN leads to a 21 % relative increase in energy efficiency (31 %) and CO 2 conversion (13 %) at high flow rates and near-atmospheric conditions. The most significant performance improvement was seen at low flow rates and sub-atmospheric pressure (300 mbar), where energy efficiency was 23 % and conversion was 28 %, a 71 % relative increase over conditions without the CDN. Using CFD simulations, we found that the CDN produces a change in the flow geometry, leading to a confined temperature profile at the height of the plasma, and forced extraction of CO to the post-CDN region. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel system for production and storage of H 2 with net-zero carbon emissions is developed. • High-temperature fuel cells and biogas upgrading unit are efficiently integrated. • Waste heat of the fuel cells is recovered in the Cu-Cl unit for hydrogen production. • Integrated process can generate 108 kmol/h liquid hydrogen and 18.88 MW power. • A hybrid method of the GA and artificial intelligence tools is applied for optimization. Global energy consumption has been exponentially increasing, leading to the depletion of conventional energy sources and a considerable increase in greenhouse gas emissions. The exploitation of sustainable energy sources and the development of innovative methods for mitigation of CO 2 emissions is necessary. Hydrogen (H 2) as a versatile and green fuel can be produced and stored in liquid form using sustainable energy sources through innovative methods. In this paper, a novel optimal hybrid structure is proposed for hydrogen production and storage with net-zero CO 2 emissions. A high-temperature fuel cell is utilized to reduce CO 2 emissions and supply the heat and power needed to produce and liquefy hydrogen. The hybrid configuration employs an electro-thermochemical unit for hydrogen production, molten carbonate fuel cells, a hydrogen liquefaction process, and a biogas upgrading by water scrubbing. A robust combination of meta-heuristic algorithms and artificial intelligence is developed to optimize the investment return period and energy/exergy efficiencies. The fuzzy Bellman-Zadeh, LINMAP, and TOPSIS techniques are also used to make decisions in multi-objective optimization. This innovative configuration generates 108 kmol/h liquid hydrogen, 18.88 MW power, 54 kmol/h oxygen, and 3258 kmol/h hot water. Pinch, sensitivity, exergy, and economic assessments are implemented to evaluate the performance of the hybrid structure. The thermal and exergy efficiencies of the proposed configuration are obtained to be 78.21 % and 64.83 %, respectively. The greatest portions of destructed exergy are resulted from the fuel cells-gas turbine hybrid system (63.63 %), electro-thermochemical unit (25.96 %), and biogas upgrading technology (6.23 %). The returns period on investment, the prime price of electricity, and the net benefit are computed as 4.854 years, 0.0420 US$/kWh, and 15.73 million US$/years, respectively, based on the energy potentials of Newfoundland and Labrador, Canada. [ABSTRACT FROM AUTHOR]

This paper presents the design analysis of a solar heat pumpusing cool thermal storage. The integrated concept uses cool storage (sensible or ice-based) as a short-term (i.e. days, weeks) storage for solar energy in winter and cooling energy in the summer. Annual TRNSYS simulations are performed in four Canadian regions to identify the potential of ice storage and unglazed solar collectors. Results show that combiningthese two technologies can reduce mechanical system energy use by 17% - 28% compared to a cold-climate air-water heat pump. Unglazed collectors demonstrated potential in areas with milder winters. [ABSTRACT FROM AUTHOR]

This is an empirical study on the causal relationship between sustainable economic welfare growth and energy consumption for Canada, France, Germany, Italy, Japan, UK and the USA using a multivariate panel framework with variables such as employment, capital, energy consumption and R&D. The short and long run relationships are compared with those produced from the commonly known so far, energy-GDP (Gross Domestic Product) growth relationship. Results mainly show that in the long-run, G7 economies can reduce energy consumption without compromising sustainable economic welfare. In the short-run though, both GDP and economic welfare are very much dependent on energy consumption for their materialization of growth, sustainable or not. The current paper follows the tendency of New Economics that shift their focus therein and propagate the use of sustainable welfare in place of the criticized GDP. The calculation of the Index for Sustainable Economic Welfare (ISEW) reveals that UK, closely followed by USA, have the largest gap (on average 52% and 50% respectively) between their GDP and sustainable economic welfare. Japan is experiencing a steadily widening gap, while Canada is the most sustainable country among G7. [ABSTRACT FROM AUTHOR]

The fossil fuel-driven transport sector has been one of the major contributors to CO 2 emission across the world keeping it on the energy policy agenda for the past three decades. Canada ranks second in gasoline consumption among OECD countries and Canadian gasoline expenditure share has been increasing since the 1990s. Fuel efficiency policies aim to decrease gasoline consumption; however, the effect can be mitigated by changes in consumer behavior such as traveling more distances — a rebound effect. Thus, the effectiveness of fuel efficiency policy is dependent on the magnitude of the rebound effect. In this paper, we estimate the rebound effect for personal transportation in Canada using data from the household spending survey for the period 1997–2009. The model includes a system of expenditure share equations for gasoline, other energy goods, and non-energy goods specified by AIDS and QUAIDS models and estimated by the nonlinear SUR method. Our estimation results show a rather high average rebound effect of 82–88% but with significant heterogeneity across income groups, provinces, and gasoline prices. Specifically, the rebound effect ranges from 63 to 96% across income groups and provinces and increases with gasoline prices. [ABSTRACT FROM AUTHOR]

• Hybrid of different intelligent models of load forecasting using clustering techniques are proposed. • Different combinations of Kalman filtering (KF), Wavelet and artificial neural network (WNN and ANN) schemes are used. • Six different models are proposed based on the clustering techniques. • The proposed work is validated by using different dataset for two different locations in Egypt and Canada. Smart grid is one of the most important topics to be covered with the increasing penetration of renewable energy in the power system grid to improve grid energy efficiency by managing the relationship between the demand and the generation. Load forecasting is playing a crucial role in this process as well as the output power generation from different renewable energy resources. The accuracy of the forecasting models is very important to deal with the new energy generation and consumption. Conventional approaches used in the literature work done for load forecasting can not handle the requirements of new generation of renewable energy and their uncertainties. This paper is proposing a novel technique for short-term load forecasting based on hybrid of different models and using clustering techniques to improve the overall system performance and quality. These models involve different combinations of Kalman filtering (KF), Wavelet and Artificial Neural Network (WNN and ANN) schemes. Six different models are proposed based on the clustering techniques. Simulations proved higher performance of the proposed models. The data used is commercial data, so it is scaled in this paper. The proposed work is validated by using different dataset for two different locations in Egypt and Canada. [ABSTRACT FROM AUTHOR]

Typically the effect of thermal bridges on the energy performance of buildings is taken into account by implementing an average U-value in 1D whole building energy simulation program, which is referred to as the equivalent U-value method. This treatment accounts for the effect of thermal bridges on the overall thermal transmittance of envelope details, while their thermal inertia effect is ignored. In this paper, the dynamic effect of balcony slab as thermal bridges on the energy performance of a high-rise residential building is investigated by comparing the annual space conditioning loads obtained by the equivalent U-value method to that obtained from 3D dynamic modeling of the balcony junctions implemented in WUFI Plus program. The simulation results show that the equivalent U-value method underestimates the annual heating loads by 2.8–4.4% for the building as-designed. With the increase of balcony portion and better insulated walls, the difference in annual space heating loads modeled using these two methods is increased to 8.6–15.2%. With the implementation of balcony thermal break the annual heating loads are reduced by 8.8–25.7% and the difference between these two modeling methods is also reduced to 1.9–11.5% for the cases investigated. [ABSTRACT FROM AUTHOR]

In terms of energy resources, Canada is an important player on the world scene. However, the energy systems of the Canadian provinces and territories are much diversified and a national energy strategy is missing in order to optimize the management of energy systems. The objective of this paper is twofold. First, we introduce TIMES-Canada, a new multi-regional energy model that has been developed using the most advanced TIMES optimization modeling framework, while keeping a very high level of details in the database (5000 specific technologies; 400 commodities) compared with other Canadian energy models. Second, we define and analyze possible futures for the Canadian integrated energy system on a 2050 horizon, under five different baselines: a Reference scenario as well as four alternate scenarios corresponding to different oil prices (Low and High) and socio-economic growth trends (Slow and Fast). In our Reference scenario, we show that the Canadian final energy consumption is expected to increase by 43% between 2007 and 2050. The Fast scenario leads to the maximum increase compared with the Reference scenario (21% in 2050). In all scenarios, oil products will continue to dominate on the long term, although in a decreasing proportion over time (from 43% in 2007 to 29% in 2050) in favor of electricity (31% of the additional demand in 2050) and biomass/biofuels. Regarding the corresponding optimal energy production paths, we illustrate two main trends: (1) a gradual replacement of onshore conventional oil & gas sources by unconventional and offshore sources (oil sands is expected to represent half of the production in 2050), and (2) a significant penetration of renewables in the electricity mix is shown after 2035 due to increases in oil import prices and decreases in renewable technology costs. The development and calibration of such a detailed technology-rich model represent an important contribution for Canada: TIMES-Canada is the only optimization model covering in details the large diversity of provincial energy systems on a long term horizon. [ABSTRACT FROM AUTHOR]

This paper investigates the fuel efficiency of commercial hybrid electric vehicles (HEVs) and compares their performance with respect to standard gasoline vehicles in the context of cold Canadian urban environments. The effect of different factors on fuel efficiency is studied including road driving conditions (link type, city size), temperature, speed, cold-starts and eco-driving training. For this study, fuel consumption data at the link level in real-world conditions was used from a sample of 74 instrumented vehicles. From the study fleet, 21 vehicles were HEVs. Among other results, the beneficial fuel efficiency merits of hybrid vehicles were demonstrated with respect to gasoline cars, in particular at low speeds and in urban (city) environments. After controlling for other factors, sedan HEVs were 28% more efficient than sedan gasoline vehicles. However, the low temperatures (below 0 °C) observed regularly during winter season in the study cities were identified as a detrimental factor to fuel economy. In winter, the fuel efficiency of HEVs decrease about 20% with respect to summer. Other factors such as eco-driving training, city size, cold start and vehicle type were also found to be statistically significant. [ABSTRACT FROM AUTHOR]

Abstract: Canada''s Arctic environment is rich in hydrocarbon resources. As international attention turns to the Arctic to meet global energy demands there is increased recognition of the need to advance upstream impact assessment and decision-making to plan for energy development. There have been several applications of strategic environmental assessment (SEA) over the past decade in the international offshore energy sector; however, SEA remains underdeveloped offshore in comparison to project-based environmental impact assessment and unchartered territory in Canada''s Arctic. This paper examines stakeholder perceptions of the opportunities and risks of advancing SEA for offshore energy planning and development in Canada''s Beaufort Sea. Results indicate a number of perceived opportunities for SEA, including improved regulatory efficiency, better regional baselines and planning practices, an opportunity to assess cumulative effects, more meaningful project-based assessment, and greater certainty for industry stakeholders. At the same time there are a number of perceived risks, including foregoing anticipated development opportunities, the loss of flexibility in decision making, adding another layer of bureaucracy, and the added uncertainties of a novel approach. The implications of these findings for advancing SEA in the offshore energy sector are discussed. [Copyright &y& Elsevier]

Abstract: This paper presents an assessment of two solar assisted heat pump systems integrated into an air distribution system in three different 210 m2 single detached residential houses in Montreal, Canada. The housing types considered are a 1980''s house, an energy efficient house and a “net zero ready” house. The advanced heat pump systems considered in the analysis focused on coupling solar energy on the evaporator side of an air source and water source heat pumps to improve performance compared to a standard air source heat pump and provide an alternative to a costly ground source heat pump system. The annual energy consumption and utility cost of the solar assisted heat pump systems were compared to a market available air source heat pump, a ground source heat pump system as well as the typical reference housing heating and cooling system. The results predicted that a solar assisted air source heat pump has a comparable capital cost to a ground source heat pump system in all housing types and the highest energy savings for a “net zero ready” house of 34% compared to the base case. The solar assisted water source heat pump did not yield interesting results, as the solar assisted air source heat pump demonstrated improved energy savings and lower capital costs in all housing types considered. Comparing the 20 year life cycle costs of the solar assisted heat pump systems to the base case, only in the 1980''s housing archetype did the solar assisted air source heat pump system demonstrate a lower life cycle cost than the base case. A standard air source heat pump yielded the lowest life cycle cost in the 1980''s and energy efficient house considered and the reference base case system had the lowest life cycle cost in the net zero ready house considered. [Copyright &y& Elsevier]

Abstract: The energy consumption and fossil CO2 emissions from the Canadian vegetable greenhouse industry were assessed using greenhouse statistics from 2002 to 2007. The fossil CO2 emissions were compared to the fossil CO2 emitted during transport of an equal weight of food by truck and by airplane from two horticultural production centers in the southern USA to four locations in Canada. The calculations in this paper for Canadian greenhouse energy use for heating were verified against farm energy use survey data collected from greenhouse operators in 1996. Allowing for extrapolations to 1996 from the 2002 to 2007 period, the survey data were underestimated by 12%. Since the survey data were not corrected for possible household energy use by greenhouse operators, some underestimation in the heat energy calculations was expected. The fossil CO2 emissions from Canadian greenhouses were 0.35Tg. This estimate is about twice as high as the diesel fuel CO2 emissions required to truck the same weight of vegetables from south to north, but only slightly less than half the CO2 emissions to ship the same vegetables by air. Quebec greenhouse crops had the lowest CO2 emission intensity and the least difference with trucking CO2 emissions, while BC greenhouse crops had the highest CO2 emission intensity and the most difference with trucking CO2 emissions. The study revealed some potential CO2 mitigation practices including alternative fuels such as straw pellets or wood chips, non-recycle-able combustible urban waste and biogas from city waste treatment facilities or manure storage systems. Mitigation of heat energy loss could involve insulating heating lines within greenhouses and doorway designs that minimize the time and area open to the outside air. In order to reduce the CO2 emission intensity, research should aim at a higher ratio of yield to fossil energy use, rather than simply trying to maximize greenhouse yields. [Copyright &y& Elsevier]

Abstract: In Canada, off-grid power production is significant, with more than 200,000 people living in about 300 remote communities scattered across Yukon, the Northwest Territories, Nunavut, and other islands. Most of these isolated sites rely on diesel to generate electricity. The operation of these remote isolated grids run on a deficit in the order of hundreds of millions of dollars yearly and must therefore be subsidized by the government. Low and high penetration wind–diesel hybrid systems (WDS) have been experimented to reduce diesel consumption. In a previous article, we explored the re-engineering of current diesel power plants with the introduction of high penetration wind systems using compressed air energy storage (CAES). This is a viable alternative to increase the overall percentage of renewable energy and reduce the cost of electricity, to increase the diesel engine lifetime and efficiency and to decrease their fuel consumption and GHG emissions. In this paper, we present the operative principle of this hybrid system, its economic benefits and advantages. Finally, we apply this concept in the case of a Canadian Nordic village to demonstrate the real energetic, ecological and economic potential of this system. [Copyright &y& Elsevier]

Abstract: The use of solar passive strategies such as new solar control coatings on windows for buildings with large glazed areas, have recently become important and helpful tools, mainly because these developments help to reduce heat gains and/or losses through transparent materials, diminishing energy loads, and improving the environment inside buildings. This paper shows an assessment of the thermal performance for an office on top of a building with four different configurations of window glass, and their influence on the indoor conditions. The window glass configurations are: clear glass, glass-film (SnS–CuxS solar control coating), double-glass-film, and double clear glass. The simulations were carried out using weather data from Mexico City and Ottawa, which are a good representation of two extreme weather conditions, in order to assess the thermal behaviour inside offices, such as energy loads, costs for air conditioning, and the influence of interior heat transfer coefficient correlations. The results indicate that the glass-film proves to be the less appropriate configuration due to the high temperatures reached on the film surface, which has an impact on the air temperatures inside the office and contributes to increase the energy consumption. In general, the double glass-film configuration results to be adequate for both climates, nevertheless it shows a better performance for Ottawa than Mexico City, where a simple double clear glass would work the same way. [ABSTRACT FROM AUTHOR]

Abstract: Energy sources such as oil, natural gas, and coal currently account for around 80% of the world’s primary energy consumption. Despite significant investments in renewable energy and energy efficiency, that Canada and others are making, the International Energy Agency (IEA) has forecast that as the global economy continues to grow, fossil fuels will continue to dominate the world’s energy supply for decades. Reconciling the world’s ongoing reliance on fossil fuels with the need to reduce greenhouse gas (GHG) emissions is then one of our greatest challenges. Canada is taking this challenge seriously with climate change policies that include enhancing our global leadership in advancing one of the most promising technologies for reducing GHG emissions from fossil fuel use: Carbon capture and storage (CCS). CCS is only one of several technologies that must be deployed and is not a ‘silver-bullet’ for meeting Canada’s target of reducing its GHG emissions by 17% from 2005 levels by 2020. Yet, CCS is one of the only technologies currently available for making emissions reductions from large-scale fossil fuel usage–and, thus, will be a critical component of the technology puzzle for Canada to meet its emissions reduction objectives. Canada has a number of key sectors where the deployment of CCS is needed and there are opportunities to advance the technology. These include coal-fired electricity plants, the oil sands, and natural gas processing (e.g. from the new development of shale gas) -though the opportunity and demand for advancing CCS technology also exists in other sectors such as chemicals, fertilizer, steel making, and cement. Federal and provincial governments in Canada are making substantial investments in CCS, committing upwards of $3 billion in public funding towards seven large-scale fully-integrated CCS demonstration projects. The federal ecoENERGY Technology Initiative announced $151 million for the initial engineering and/or pilot stages of seven potential demonstration projects in 2008. The 2009 federal budget created Clean Energy Fund, which included $610 million for CCS demonstrations. The Provinces of Alberta, Saskatchewan, and British Columbia have also committed funding for demonstrations, in particular $2 billion by Alberta. This public funding will leverage additional investment from industry, for projects that will each capture and store on the order of 1 million tonnes of CO2 per year, coming on-line starting in 2015 or sooner. This paper will provide an overview of Canada’s actions on advancing CCS deployment, with a focus on the CCS demonstration program and current R&D activities in Canada. [Copyright &y& Elsevier]

Abstract: This paper puts forward an integrated approach, based on logarithmic mean divisia index (LMDI) – an index decomposition analysis (IDA) method, an artificial neural network (ANN) and a data envelopment analysis (DEA) for the analysis of total energy efficiency and optimization in an industrial sector. The energy efficiency assessment and the optimization of the proposed model use LMDI to decompose energy consumption into activity, structural and intensity indicators, which serve as inputs to the ANN. The ANN model is verified and validated by performing a linear regression comparison between the specifically measured energy consumption and the corresponding predicted energy consumption. The proposed approach utilizes the measure-specific, super-efficient DEA model for sensitivity analysis to determine the critical measured energy consumption and its optimization reductions. The proposed method is validated by its application to determine the efficiency computation and an analysis of historical data as well as the prediction and optimization capability of the Canadian industrial sector. [Copyright &y& Elsevier]

Abstract: Despite much optimistic language on commercial websites, little data is available on actual performance of hydrokinetic turbines. This paper summarises the findings of a series of tests on several Darrieus type cross flow hydrokinetic turbines (HKTs). Although this type of hydrokinetic turbine (HKT) has some advantages over axial flow turbines, fixed pitch Darrieus HKTs also have some drawbacks, including inability to self-start under load, low efficiency and shaking. Variable pitch has been suggested to increase starting torque and efficiency, ducts to increase power output and helical blades to produce smooth torque. To assess each of these modifications, tests were conducted in Australia and Canada on HKTs with fixed and variable pitch straight blades, fixed helical blades, with and without a slatted diffuser, by mounting each turbine in front of a barge and motoring through still water at speeds ranging from less than 1 m/s up to 5 m/s. The diffuser increased the power output by a factor of 3 in one configuration but considerably less in others. A reason for this finding is suggested. The maximum coefficient of performance Cp of the fixed pitch straight blade and helical turbines without a diffuser ranged from about 0.25 at 1.5 m/s down to less than 0.1 at 5 m/s, while Cp for those with a diffuser ranged from about 0.45 down to about 0.3. Fixed blade turbines, both straight and helical, exhibited low starting torque, while variable pitch turbines started easily. Considerable differences in Cp were observed for the same turbine configuration at different speeds. The turbine with fixed pitch, straight blades was found to shake violently due to cyclical hydrodynamic forces on blades, while the helical and variable pitch turbines did not shake excessively. These findings suggest that variable pitch cross flow HKTs should be further investigated. [Copyright &y& Elsevier]

Abstract: Private and public sectors own and operate an array of office buildings that consume energy and contribute to the emission of greenhouse gases (GHG). Energy demands can be reduced by applying energy retrofit measures (ERMs) to existing buildings. The choice of ERMs involves evaluation of applicability, energy end uses and cost of application versus energy savings. This paper describes a methodology developed to screen office buildings for their current level of energy consumption and potential for retrofit application. Selection of an optimal set of ERMs is influenced by climate, occupancy, heating and cooling systems, envelope properties and building geometry. When assessing the implications of applying ERMs to a large building stock it is vital to screen the complete building set for optimal retrofit opportunities. This can be accomplished by characterizing office building stock into a manageable set of archetypes and simulating building operation using energy simulation software. Using regression analyses, a model was developed for estimating the energy consumption. Present value analysis was used to optimize the evaluation of the various ERMs. The methodology developed can be used to simplify the ranking of buildings for retrofit; to select and combine ERMs, and to plan energy and GHG reduction activities. [ABSTRACT FROM AUTHOR]

This paper summarizes greenhouse gas (GHG) emissions measurements obtained during several recent studies conducted by Environment Canada, Emissions Research and Measurement Division (ERMD). A variety of heavy-duty vehicles and engines operating on a range of different fuels including diesel, biodiesel, compressed natural gas (CNG), hythane (20% hydrogen, 80% CNG), and liquefied natural gas (LNG), and with different advanced aftertreatment technologies were studied by chassis dynamometer testing, engine dynamometer testing or on-road testing. Distance-based emission rates of CO2, CH4, and N2O are reported. Fuel consumption calculated by carbon balance from measured emissions is also reported. The measurement results show, for heavy-duty diesel vehicles without aftertreatment, that while CO2 emissions dominate, CH4 emissions account for between 0% and 0.11% and N2O emissions account for between 0.16% and 0.27% of the CO2-equivalent GHG emissions. Both of the aftertreatment technologies (diesel oxidation catalyst and active regeneration diesel particle filter) studied increased N2O emissions compared to engine out emissions while CH4 emissions remain essentially unchanged. No effect on tailpipe GHG emissions was found with the use of up to 20% biodiesel when the engine was equipped with an oxidation catalyst. Biodiesel use did show some reductions in tailpipe GHG emissions as compared to ULSD without aftertreatment and with the use of a diesel particle filter. Natural gas and hythane also offer decreased GHG emissions (10–20%) at the tailpipe when compared with diesel. Emission factors (gL−1 fuel) for CH4 and N2O are suggested for heavy-duty vehicles fueled with diesel-based fuels and natural gas. These emission factors are substantially lower than those recommended for use by IPCC methodologies for developing national inventories. [Copyright &y& Elsevier]

Abstract: This paper presents new forms of urban renewable energy, in particular, the integration of solar and wind power into the industrial and commercial buildings with flat roofs which populate a city''s downtown core. This combination of renewable energy passively adapts to pre-existing structures and exploits them to their full advantage. The working prototypes presented aim to introduce an element of multi-functionality to building-integrated photovoltaics (BIPV), creating systems which produce energy while meeting required needs and desirable features of urban buildings. We also explore the combination of wind energy and various energy efficiency initiatives with BIPV designs. Our energy efficiency initiatives include a new method of generating the perception of natural sunlight from artificial light and brainwave controlled lighting that dims automatically when occupants’ concentration is lowered. These efforts result in an environment that celebrates the existential notion of self-empowerment through reducing energy consumption and having control over one''s own energy production. Our discussion follows into market considerations of our BIPV designs and how project costs are lowered and space is conserved, assets when designing for urban locations. The test site for the development of urban renewable energy is the Existential Technology Research Center (ETRC), located in downtown Toronto, Canada. [Copyright &y& Elsevier]

Given that human behavior is increasingly recognized to play an essential role in building energy use, the validity of occupant-related assumptions in the building code and in the energy performance modeling tools used for demonstrating code compliance is a central concern. This paper investigates the current occupant-related assumptions in the National Building Code (NBC) of Canada compared to new and emerging data sources, along with their potential energy and design impacts. Six parameters were selected: setpoint temperatures, domestic hot water (DHW) use, appliances lighting and plug (ALP) loads, internal heat gains, mechanical ventilation, and the number of occupants. For each parameter, available data sources were compared against the NBC assumptions. Our analysis indicates that several code assumptions are substantially different from findings in recent measurement-based studies. For the temperature setpoints, the mean heating and cooling setpoints are approximately 1.5 °C cooler than the current NBC specification (21 °C and 25 °C, respectively). For DHW, the total daily volume is highly dependent on the number of occupants; hence, the current assumption of NBC (225 L/day) may not reflect the typical current use. Moreover, the hourly schedule for DHW use specified by NBC is significantly different than all data sources found (primarily in the timing and magnitude of morning and evening peaks in usage). For internal heat gains, the available data suggests a similar profile as NBC, except for that absence of a morning peak. Therefore, the findings presented in this study illustrate a need for revising the current building standards/codes. • A comprehensive review of new and emerging occupant-related data in Canada. • Occupant-related assumptions in NBC varies from the new available datasets. • Thermostat data from over 13,000 homes across Canada were analyzed. • The total daily volume of DHW use is highly dependent on the number of occupants. • A daily ALP loads profile from multiple sources was developed. [ABSTRACT FROM AUTHOR]

• A retrofit selection strategy employing economic and environmental decision criteria was proposed. • Building energy retrofits were evaluated through a life cycle thinking approach. • Retrofits with operational emissions savings may not be beneficial when considering life cycle impacts. • Energy mix and the heating system of the house greatly impact the effectiveness. • Retrofit selection changes with stakeholder priorities on environment and economics. Improving the energy performance of buildings has been a much-discussed topic over the past few decades. With the current focus on climate change mitigation, emissions reduction has also come to the forefront of this discussion. Retrofitting is an option to improve the energy and emissions performance of buildings. However, in the residential building stock, retrofit planning for existing buildings faces many complexities due to variations in climatic conditions and macro-environment as well as the presence of multiple stakeholder groups. Thus, in identifying solutions, it is necessary to take a holistic perspective that covers these different dimensions. In this paper, commonly used building energy retrofits were evaluated through a life cycle thinking approach. The performance of various retrofit options applicable for single family detached housing were evaluated using the HOT2000 energy simulation software package under the varying climatic conditions and energy supply scenarios across Canada. The retrofits were evaluated in terms of the additional investment, energy use and cost reduction achieved over the life cycle, and life cycle emissions reduction. The findings indicate that the provincial energy mix and the heating system of the house (i.e. electric or natural gas) play a major role in determining the effectiveness of a retrofit, and this "effectiveness" changes at different stakeholder levels. However, not all retrofits that reduce emissions make economic sense and vice versa when life cycle thinking comes into play. The findings will be useful for building owners and occupants as well as for policy developers and other decision makers interested in demand side management. [ABSTRACT FROM AUTHOR]

Occupant behavior in residential buildings has a direct impact on the effectiveness of energy-saving measures. In order to realize a buildings' carbon mitigation targets, the impact of individual occupancy profiles needs to be integrated with building simulation models. This paper introduces a decision support framework as a potential solution to make energy performance upgrade choices based on different occupancy profiles. This framework has been demonstrated through a case study of two single-family detached homes in Canada, which were highly instrumented with sensors for monitoring energy input and output. The case studies represented two common occupancy profiles-(1) a family of four (consisting of 2 working adults and 2 teenagers); and (2) a retired couple. Firstly, calibrated energy models were developed by using one-year energy use data collected through an intrusive load monitoring technique. Secondly, energy upgrade combinations were considered for each profile and tested for additional investment, payback period and greenhouse gas (GHG) emissions. Lastly, the most suitable combination of energy upgrade for each profile was ranked using a multi-criteria decision-making method (e.g., TOPSIS). Results indicated that the retired couple used more energy than the family of four and required energy upgrades with usually higher payback periods to achieve the same level of GHG emission reduction. The results of this research are timely for energy policymaking and developing best management practices, which need to be implemented along with the deployment of more stringent building standards and codes. • A scenario-based framework was developed for residential homes energy upgrades. • It considers occupant behavior and preference in selecting energy upgrades. • Field data is used to represent energy use of a family of four and a stay-at-home retired couple. • Energy upgrades are same under pro-economic choices for two profiles. • Energy upgrades vary under pro-environmental scenarios for two profiles. [ABSTRACT FROM AUTHOR]

• Majority of the approaches developed to improve the performance of CDN utilize the CDN utility as a key metric to evaluate their effectiveness. • CDN utility does not take into account the utilization of CDN resources. • CDN utilization has a direct impact on the energy consumption of CDN resources and can be utilized as a tool to implement energy-aware policies in CDN environment. • Hence, CDN utilization should be considered as an important metric to evaluate the performance of CDN policy. The exponential increase in the Internet of Things (IoT) has drastically augmented the need for computing and storage resources. IoT devices generate massive data that requires to be efficiently stored and disseminated for further processing and decision making. Given this, Content Distribution Networks (CDN) play a vital role to store and serve contents through geographically distributed surrogate servers in an IoT environment. Thanks to the explosive rise in IoT devices, CDN installations are also significantly increasing, hence, consuming a substantial amount of energy. The dynamic energy consumption of CDN resources is proportional to their utilization. Therefore, it is very crucial to design and develop utilization aware policies and strategies for sustainable content distribution. In the literature, different approaches have been proposed to improve the CDN performance by improving CDN utility in terms of security, authentication, and confidentiality, etc. Whereas, these works largely neglect the efficient utilization of CDN resources. In this perspective, this paper investigates the fact that CDN utility does not reflect the utilization of CDN resources. For this purpose, a comprehensive analysis is performed by comparing both metrics - CDN utility and CDN utilization, under various CDN scenarios. The results show that CDN utilization exhibits lower values even if the CDN utility is showing promising results. Hence, we recommend to consider utilization as a major metric to evaluate the performance of a CDN policy. [ABSTRACT FROM AUTHOR]