Integrating physical and data-driven perspectives on building energy performance : a tale of two cities
Abstract/Contents
- Abstract
- Cities are the epicenters of our everyday lives. As they account for over 75% of primary energy consumption and 80% of all greenhouse gas emissions globally, the need to decarbonize the urban built environment is becoming increasingly dire. It is well-established that with a better understanding of how and when buildings consume energy, "low-hanging" solutions in the form of building retrofits can provide key energy, environmental, and economic improvements to cities. Fortunately, rapid growth in sensing technologies and smart city initiatives has led to a windfall of structured and unstructured data streams increasingly available to describe building energy consumption. Despite this broad availability of information describing our cities, we lack tools capable of making sense of this data. But when combined with interpretable visualization and computational techniques, they can produce once hidden insights to improve urban building energy performance. Thus, the overarching motivation for this dissertation is to propose new strategies that leverage emerging data sources to empower urban sustainability stakeholders to make informed decisions regarding their energy systems and built environments. To do so, this work introduces computational tools for two types of cities: data-rich and data-sparse cities. The first context area of study -- data-rich cities -- explores the capability of using high-fidelity data streams to predict building energy consumption while considering the impacts of the surrounding urban context. And the second area -- data-sparse cities -- looks to utilize limited observational and sensor data to evaluate how building design decisions influence the onset of heat stress and the demand for energy-intensive space cooling. Despite the unique energy challenges facing every city, creating interpretable, data-driven solutions can inform the future planning of the built environment to improve energy efficiency and human well-being. The results and methods I introduce in this dissertation contribute theoretical and practical knowledge to decision makers determining the energy sustainability future of our world.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2021; ©2021 |
| Publication date | 2021; 2021 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Nutkiewicz, Alexandra Ilana |
|---|---|
| Degree supervisor | Jain, Rishee |
| Thesis advisor | Jain, Rishee |
| Thesis advisor | Fischer, Martin A |
| Thesis advisor | Gorle, Catherine |
| Degree committee member | Fischer, Martin A |
| Degree committee member | Gorle, Catherine |
| Associated with | Stanford University, Civil & Environmental Engineering Department |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Alexandra I. Nutkiewicz. |
|---|---|
| Note | Submitted to the Civil & Environmental Engineering Department. |
| Thesis | Thesis Ph.D. Stanford University 2021. |
| Location | https://purl.stanford.edu/nm585pw3295 |
Access conditions
- Copyright
- © 2021 by Alexandra Ilana Nutkiewicz
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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