Energy is consumed every day at home as we perform simple tasks, such as watching television, washing dishes and heating/cooling home spaces during season of extreme weather conditions, using appliances, or turning on lights. Most often, the energy resources used in residential systems are obtained from natural gas, coal and oil. Moreover, climate change has increased awareness of a need for expendable, energy resources. As a result, carbon dioxide emissions are increasing and creating a negative effect on our environment and on our health. In fact, growing energy demands and limited natural resource might have negative impacts on our future. Therefore, saving energy is becoming an important issue in our society and it is receiving more attention from the research community. This thesis introduces a intelligent energy controller algorithm based on software agent approach that reduce the energy consumption at home for both heating and cooling spaces by considering the user’s occupancy, outdoor temperature and user’s preferences as input to the system. Thus the proposed approach takes into consideration the occupant’s preferred temperature, the occupied and unoccupied spaces, as well as the time spent in each area of the home. A Java based simulator has been implemented to simulate the algorithm for saving energy in heating and cooling systems. The results from the simulator are compared to the results of using HOT2000, which is Canada’s leading residential energy analysis and rating software developed by CanmetENERGY’s Housing, Buildings, Communities and Simulation (HBCS) group. We have calculated how much energy a home modelled will use under emulated conditions. The results showed that the implementation of the proposed energy controller algorithm can save up to 50% in energy consumption in homes dedicated to heating and cooling systems compared to the results obtained by using HOT2000.

Energy is consumed every day at home as we perform simple tasks, such as watching television, washing dishes and heating/cooling home spaces during season of extreme weather conditions, using appliances, or turning on lights. Most often, the energy resources used in residential systems are obtained from natural gas, coal and oil. Moreover, climate change has increased awareness of a need for expendable, energy resources. As a result, carbon dioxide emissions are increasing and creating a negative effect on our environment and on our health. In fact, growing energy demands and limited natural resource might have negative impacts on our future. Therefore, saving energy is becoming an important issue in our society and it is receiving more attention from the research community. This thesis introduces a intelligent energy controller algorithm based on software agent approach that reduce the energy consumption at home for both heating and cooling spaces by considering the user’s occupancy, outdoor temperature and user’s preferences as input to the system. Thus the proposed approach takes into consideration the occupant’s preferred temperature, the occupied and unoccupied spaces, as well as the time spent in each area of the home. A Java based simulator has been implemented to simulate the algorithm for saving energy in heating and cooling systems. The results from the simulator are compared to the results of using HOT2000, which is Canada’s leading residential energy analysis and rating software developed by CanmetENERGY’s Housing, Buildings, Communities and Simulation (HBCS) group. We have calculated how much energy a home modelled will use under emulated conditions. The results showed that the implementation of the proposed energy controller algorithm can save up to 50% in energy consumption in homes dedicated to heating and cooling systems compared to the results obtained by using HOT2000.

Energy is consumed every day at home as we perform simple tasks, such as watching television, washing dishes and heating/cooling home spaces during season of extreme weather conditions, using appliances, or turning on lights. Most often, the energy resources used in residential systems are obtained from natural gas, coal and oil. Moreover, climate change has increased awareness of a need for expendable, energy resources. As a result, carbon dioxide emissions are increasing and creating a negative effect on our environment and on our health. In fact, growing energy demands and limited natural resource might have negative impacts on our future. Therefore, saving energy is becoming an important issue in our society and it is receiving more attention from the research community. This thesis introduces a intelligent energy controller algorithm based on software agent approach that reduce the energy consumption at home for both heating and cooling spaces by considering the user’s occupancy, outdoor temperature and user’s preferences as input to the system. Thus the proposed approach takes into consideration the occupant’s preferred temperature, the occupied and unoccupied spaces, as well as the time spent in each area of the home. A Java based simulator has been implemented to simulate the algorithm for saving energy in heating and cooling systems. The results from the simulator are compared to the results of using HOT2000, which is Canada’s leading residential energy analysis and rating software developed by CanmetENERGY’s Housing, Buildings, Communities and Simulation (HBCS) group. We have calculated how much energy a home modelled will use under emulated conditions. The results showed that the implementation of the proposed energy controller algorithm can save up to 50% in energy consumption in homes dedicated to heating and cooling systems compared to the results obtained by using HOT2000.

Energy is consumed every day at home as we perform simple tasks, such as watching television, washing dishes and heating/cooling home spaces during season of extreme weather conditions, using appliances, or turning on lights. Most often, the energy resources used in residential systems are obtained from natural gas, coal and oil. Moreover, climate change has increased awareness of a need for expendable, energy resources. As a result, carbon dioxide emissions are increasing and creating a negative effect on our environment and on our health. In fact, growing energy demands and limited natural resource might have negative impacts on our future. Therefore, saving energy is becoming an important issue in our society and it is receiving more attention from the research community. This thesis introduces a intelligent energy controller algorithm based on software agent approach that reduce the energy consumption at home for both heating and cooling spaces by considering the user’s occupancy, outdoor temperature and user’s preferences as input to the system. Thus the proposed approach takes into consideration the occupant’s preferred temperature, the occupied and unoccupied spaces, as well as the time spent in each area of the home. A Java based simulator has been implemented to simulate the algorithm for saving energy in heating and cooling systems. The results from the simulator are compared to the results of using HOT2000, which is Canada’s leading residential energy analysis and rating software developed by CanmetENERGY’s Housing, Buildings, Communities and Simulation (HBCS) group. We have calculated how much energy a home modelled will use under emulated conditions. The results showed that the implementation of the proposed energy controller algorithm can save up to 50% in energy consumption in homes dedicated to heating and cooling systems compared to the results obtained by using HOT2000.

Today’s carbon constrained world with its increasing demand for cheap energy and a fossil fuel intensive fleet of power producers is making carbon capture and storage (CCS) desirable. Several CCS technologies are under investigation by various research and development groups globally. One of the more promising technologies is oxy-fuel combustion, since it produces a CO2 rich flue gas which requires minor processing to meet storage condition requirements. In this study the economics of an advanced super critical oxy-coal power plant burning lignite, simulated in-house was assessed. A robust and user-friendly financial tool box has been developed with commonly acceptable default parameter settings. Capital, operation and maintenance costs were estimated along with corresponding levelized cost of electricity and CO2 avoidance costs calculated using the detailed financial model developed. A levelized cost of electricity of 131 $/MWhrnet along with a levelized CO2 avoidance cost of 64 $/tonne was estimated for an ASC oxy-coal power plant with CO2 capture. Also a levelized cost of electricity of 83 $/MWhrnet was estimated for an ASC air-fired coal power plant without CO2 capture capabilities as the base plant. The price of electricity was observed to increase from 83 $/MWhrnet to 131 $/MWhrnet translating into a 57% increase. The sensitivity of the overall economics of the process was assessed to several parameters. The overall economics was found sensitive to the choice chemical engineering plant cost index (CEPCI), capacity factor, size of power plant, debt ratio, fuel price, interest rate, and construction duration.

Today???s carbon constrained world with its increasing demand for cheap energy and a fossil fuel intensive fleet of power producers is making carbon capture and storage (CCS) desirable. Several CCS technologies are under investigation by various research and development groups globally. One of the more promising technologies is oxy-fuel combustion, since it produces a CO2 rich flue gas which requires minor processing to meet storage condition requirements. In this study the economics of an advanced super critical oxy-coal power plant burning lignite, simulated in-house was assessed. A robust and user-friendly financial tool box has been developed with commonly acceptable default parameter settings. Capital, operation and maintenance costs were estimated along with corresponding levelized cost of electricity and CO2 avoidance costs calculated using the detailed financial model developed. A levelized cost of electricity of 131 $/MWhrnet along with a levelized CO2 avoidance cost of 64 $/tonne was estimated for an ASC oxy-coal power plant with CO2 capture. Also a levelized cost of electricity of 83 $/MWhrnet was estimated for an ASC air-fired coal power plant without CO2 capture capabilities as the base plant. The price of electricity was observed to increase from 83 $/MWhrnet to 131 $/MWhrnet translating into a 57% increase. The sensitivity of the overall economics of the process was assessed to several parameters. The overall economics was found sensitive to the choice chemical engineering plant cost index (CEPCI), capacity factor, size of power plant, debt ratio, fuel price, interest rate, and construction duration.

Hydrocracking and hydrotreating are bitumen upgrading technologies designed to enhance fuel quality by decreasing its density, viscosity, boiling point and heteroatom content via hydrogen addition. The aim of this thesis is to model and simulate an upgrading and integrated gasification combined cycle then to evaluate the feasibility of integrating slurry hydrocracking, trickle-bed hydrotreating and residue gasification using the Aspen HYSYS® simulation software. The close-coupling of the bitumen upgrading facilities with gasification should lead to a hydrogen, steam and power self-sufficient upgrading facility with CO2 capture. Hydrocracker residue is first withdrawn from a 100,000 BPD Athabasca bitumen upgrading facility, characterized via ultimate analysis and then fed to a gasification unit where it produces hydrogen that is partially recycled to the hydrocracker and hydrotreaters and partially burned for power production in a high hydrogen combined cycle unit. The integrated design is simulated for a base case of 90% carbon capture utilizing a monoethanolamine (MEA) solvent, and compared to 65% and no carbon capture scenarios. The hydrogen production of the gasification process is evaluated in terms of hydrocracker residue and auxiliary petroleum coke feeds. The power production is determined for various carbon capture cases and for an optimal hydrocracking operation. Hence, the feasibility of the integration of the upgrading process and the IGCC resides in meeting the hydrogen demand of the upgrading facility while producing enough steam and electricity for a power and energy self-sufficient operation, regardless of the extent of carbon capture.

Hydrocracking and hydrotreating are bitumen upgrading technologies designed to enhance fuel quality by decreasing its density, viscosity, boiling point and heteroatom content via hydrogen addition. The aim of this thesis is to model and simulate an upgrading and integrated gasification combined cycle then to evaluate the feasibility of integrating slurry hydrocracking, trickle-bed hydrotreating and residue gasification using the Aspen HYSYS® simulation software. The close-coupling of the bitumen upgrading facilities with gasification should lead to a hydrogen, steam and power self-sufficient upgrading facility with CO2 capture. Hydrocracker residue is first withdrawn from a 100,000 BPD Athabasca bitumen upgrading facility, characterized via ultimate analysis and then fed to a gasification unit where it produces hydrogen that is partially recycled to the hydrocracker and hydrotreaters and partially burned for power production in a high hydrogen combined cycle unit. The integrated design is simulated for a base case of 90% carbon capture utilizing a monoethanolamine (MEA) solvent, and compared to 65% and no carbon capture scenarios. The hydrogen production of the gasification process is evaluated in terms of hydrocracker residue and auxiliary petroleum coke feeds. The power production is determined for various carbon capture cases and for an optimal hydrocracking operation. Hence, the feasibility of the integration of the upgrading process and the IGCC resides in meeting the hydrogen demand of the upgrading facility while producing enough steam and electricity for a power and energy self-sufficient operation, regardless of the extent of carbon capture.

Hydrocracking and hydrotreating are bitumen upgrading technologies designed to enhance fuel quality by decreasing its density, viscosity, boiling point and heteroatom content via hydrogen addition. The aim of this thesis is to model and simulate an upgrading and integrated gasification combined cycle then to evaluate the feasibility of integrating slurry hydrocracking, trickle-bed hydrotreating and residue gasification using the Aspen HYSYS® simulation software. The close-coupling of the bitumen upgrading facilities with gasification should lead to a hydrogen, steam and power self-sufficient upgrading facility with CO2 capture. Hydrocracker residue is first withdrawn from a 100,000 BPD Athabasca bitumen upgrading facility, characterized via ultimate analysis and then fed to a gasification unit where it produces hydrogen that is partially recycled to the hydrocracker and hydrotreaters and partially burned for power production in a high hydrogen combined cycle unit. The integrated design is simulated for a base case of 90% carbon capture utilizing a monoethanolamine (MEA) solvent, and compared to 65% and no carbon capture scenarios. The hydrogen production of the gasification process is evaluated in terms of hydrocracker residue and auxiliary petroleum coke feeds. The power production is determined for various carbon capture cases and for an optimal hydrocracking operation. Hence, the feasibility of the integration of the upgrading process and the IGCC resides in meeting the hydrogen demand of the upgrading facility while producing enough steam and electricity for a power and energy self-sufficient operation, regardless of the extent of carbon capture.