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• 1. [Article] A Combined Energy and Geoengineering Optimization Model (CEAGOM) for Climate Policy Analysis

  One of the greatest challenges that will face humanity in the 21st century is the issue of climate change brought about by emissions of greenhouse gases. Energy use is one of the primary sources of greenhouse ...

  Citation × Citation Citation Abstract Copy Title: A Combined Energy and Geoengineering Optimization Model (CEAGOM) for Climate Policy Analysis Author: Anasis, John George Year: 2015 One of the greatest challenges that will face humanity in the 21st century is the issue of climate change brought about by emissions of greenhouse gases. Energy use is one of the primary sources of greenhouse gas emissions. However, it is also one of the most important contributors to improved human welfare over the past two centuries and will continue to be so for years to come. This quandary has led a number of researchers to suggest that geoengineering may be required in order to allow for continued use of fossil fuels while at the same time mitigating the effects of the associated greenhouse gas emissions on the global climate. The goal of this research was to develop a model that would allow decision-makers and policy analysts to assess the optimal mix of energy and geoengineering resources needed to meet global or regional energy demand at the lowest cost while accounting for appropriate emissions, greenhouse gas concentration, or temperature rise constraints. The resulting software model is called the Combined Energy and Geoengineering Optimization Model (CEAGOM). CEAGOM was then used to analyze the recently announced U.S.-China emissions agreement and to assess what the optimal global energy resource mix might be over the course of the 21st century, including the associated potential need for geoengineering. These analyses yielded optimal mixes of energy and geoengineering resources that could be used to inform regional and global energy and climate management strategies. Title: A Combined Energy and Geoengineering Optimization Model (CEAGOM) for Climate Policy Analysis Author: Anasis, John George Year: 2015 One of the greatest challenges that will face humanity in the 21st century is the issue of climate change brought about by emissions of greenhouse gases. Energy use is one of the primary sources of greenhouse gas emissions. However, it is also one of the most important contributors to improved human welfare over the past two centuries and will continue to be so for years to come. This quandary has led a number of researchers to suggest that geoengineering may be required in order to allow for continued use of fossil fuels while at the same time mitigating the effects of the associated greenhouse gas emissions on the global climate. The goal of this research was to develop a model that would allow decision-makers and policy analysts to assess the optimal mix of energy and geoengineering resources needed to meet global or regional energy demand at the lowest cost while accounting for appropriate emissions, greenhouse gas concentration, or temperature rise constraints. The resulting software model is called the Combined Energy and Geoengineering Optimization Model (CEAGOM). CEAGOM was then used to analyze the recently announced U.S.-China emissions agreement and to assess what the optimal global energy resource mix might be over the course of the 21st century, including the associated potential need for geoengineering. These analyses yielded optimal mixes of energy and geoengineering resources that could be used to inform regional and global energy and climate management strategies. Close

• 2. [Article] The Investigation and Optimization of a Two-Heat-Pump System Incorporating Thermal Storage for Shaping Residential Heating Load

  Portland General Electric has proposed coupling one or more water tanks with two heat pumps in order to perform load-shifting in residential customer heating and cooling applications. By using the water ...

  Citation × Citation Citation Abstract Copy Title: The Investigation and Optimization of a Two-Heat-Pump System Incorporating Thermal Storage for Shaping Residential Heating Load Author: Barrett, Emily Lord Year: 2016 Portland General Electric has proposed coupling one or more water tanks with two heat pumps in order to perform load-shifting in residential customer heating and cooling applications. By using the water tanks as a thermal storage unit, this project attempts to partially decouple energy consumption from generation to provide peak demand reduction and to better facilitate the integration of variable renewable energy resources. A scoping study was performed to evaluate the potential impact of this project if implemented in single family homes in Portland, Oregon. This study revealed that the system could provide meaningful savings in the cost of electricity to both the customer and utility. Additionally, an optimization algorithm was developed to dictate system operation and to maximize gains to the utility. Evolutionary algorithms were explored in an attempt to increase the effectiveness of the algorithm's search in limited computation time. Ultimately, an evolution strategy was selected as the most suitable based on tests run in winter and spring months. A genetic algorithm was then developed to handle fixed-speed heat pump operation for compatibility with an alpha-system prototype that has been developed by the research team. Title: The Investigation and Optimization of a Two-Heat-Pump System Incorporating Thermal Storage for Shaping Residential Heating Load Author: Barrett, Emily Lord Year: 2016 Portland General Electric has proposed coupling one or more water tanks with two heat pumps in order to perform load-shifting in residential customer heating and cooling applications. By using the water tanks as a thermal storage unit, this project attempts to partially decouple energy consumption from generation to provide peak demand reduction and to better facilitate the integration of variable renewable energy resources. A scoping study was performed to evaluate the potential impact of this project if implemented in single family homes in Portland, Oregon. This study revealed that the system could provide meaningful savings in the cost of electricity to both the customer and utility. Additionally, an optimization algorithm was developed to dictate system operation and to maximize gains to the utility. Evolutionary algorithms were explored in an attempt to increase the effectiveness of the algorithm's search in limited computation time. Ultimately, an evolution strategy was selected as the most suitable based on tests run in winter and spring months. A genetic algorithm was then developed to handle fixed-speed heat pump operation for compatibility with an alpha-system prototype that has been developed by the research team. Close