As one of the main contributors to greenhouse gas emissions, the electricity sector is anticipated to go through the following transitions in order to meet deep decarbonization targets for a sustainable future: 1) on the supply side, the electric grid is increasing its reliance on renewable generation, such as wind and solar; 2) on the demand side, heating is shifting from direct burning of fuel on site to electric, namely heat pumps. This dissertation evaluates the benefits of selected methods to alleviate pressing challenges associated with the electricity sector transitions on both the supply side and the demand side. First, on the supply side, the benefits of renewable generation forecasting coupled with storage are evaluated for an electric grid with high wind energy penetration and load following generation served by fossil fuels. A time series based forecasting method is found to have high forecasting accuracy and low computational costs. This methodology is applied to a real world situation in Sao Vicente, an island with 30% current wind energy penetration. The simulation results show that coupling forecasting and energy storage would further increase the wind penetration up to 38% without additional installation of wind turbines. Second, on the demand side, the benefits of demand side management using heat pumps enabled by the inherent thermal storage of the building envelope are evaluated during extreme cold events when the electric demand peaks and the wind power is often highly fluctuating. A second order thermal model is developed to thoroughly characterize the thermal inertia and leakage of the building envelope and quantify the amount of flexibility the building envelope is able to provide. This methodology is applied to five historical extreme cold events in New York City and the simulation results show that the requirements for short term ramping due to high wind variability are greatly reduced through the sequential controls of the heat pumps.
This dissertation also studies the implications of the electricity sector transitions on the residential sector with regard to costs, energy, missions, and policy. Four representative residential city blocks located in three different climate regions of the United States are analyzed using fine spatial and temporal real historical consumption and weather data. Residential blocks in different climate regions have different weather patterns, demand profiles, and local renewable resources. Future energy scenarios with electric heating at high renewable penetration levels are modeled and compared for the representative residential city blocks. Detailed costs comparisons are evaluated for various technological interventions including 1) air source and ground source heat pumps; 2) battery and thermal storage; and 3) wind and solar generation. This dissertation finds that 1) the optimal wind and solar generation mix varies with location and amount of storage and 2) battery storage is more cost effective than thermal storage, ground source heat pumps, and overbuilt renewable generation. In addition, optimal pathways to deep decarbonization for these representative residential city blocks are proposed and compared. Strategic actions are identified for the homes and suggestions are discussed for policy makers and local utilities. This dissertation through its methodologies and analysis enables home owners and policy makers to make cost assessments in achieving the goals of deep decarbonization.
Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-dx7f-qf05 |
Date | January 2019 |
Creators | Yuan, Shengxi |
Source Sets | Columbia University |
Language | English |
Detected Language | English |
Type | Theses |
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