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The water footprint of urban energy systems| Concepts, methods and applications for assessing electricity supply risk factors

<p> This dissertation adds to the body of knowledge of the <i>water-energy nexus</i> in four measurable ways. First, a water withdrawal footprint of energy supply (WWFES) to cities was developed, and placed it in the context of other water footprints defined in the literature. The WWFES provides a novel way to quantify direct and indirect water requirements to satisfy urban energy demand. The magnitude of the WWFES for Denver, Colorado was found to be 381 liters/person/day and 66% as large as all direct water uses in the city combined (mean estimate). This finding is relevant to urban sustainability planning as it shows significant water conservation may be achieved through energy efficiency and energy conservation. </p><p> Next, we demonstrate the robustness of the WWFES method for a rapidly developing city (Delhi) with unique energy requirements, energy infrastructure and data availability compared to the initial test case (Denver). Data collected for the Indian power sector enabled exploration of spatial- and temporal-variability of electricity supply to cities and the associated dynamic WWFES. Integrating over both space and time for one year, we estimate the water requirements of electricity production alone to be 36% as large as municipal water supply for Delhi, compared to 16% for Denver. In both cases, this highlights that electricity supply, like municipal supply, can be at risk during drought or other hydrological extremes, corroborated by interviews with industry experts. </p><p> The third and fourth contributions of this dissertation are to place water-related constraints to power generation in the context of other system risks using both social science methods and data-driven statistical analysis. For the former, a survey was administered to electricity infrastructure operators serving Delhi with three objectives: (1) identify and rank system risks to power supply reliability based on industry perceptions of risk; (2) identify and rank current and future service provision priorities; and (3) collect social network data regarding interaction between infrastructure operators. For the latter, an empirical study of electricity supply reliability in Northern India was conducted in a hierarchical modeling framework to assess the contribution of structural, environmental and supply-chain constraints to grid reliability. Model results indicate the WWFES is a statistically significant predictor of power supply reliability in Northern India when we control for structural, climate and supply-chain covariates. These results highlight the importance of the WWFES when evaluating risks to, and reliability of, trans-boundary energy systems.</p>

Identiferoai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:3621820
Date26 July 2014
CreatorsCohen, Elliot J.
PublisherUniversity of Colorado at Denver
Source SetsProQuest.com
LanguageEnglish
Detected LanguageEnglish
Typethesis

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