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1 | 1 | Solving climate change will require our globalized society to transition from |
2 | 2 | fossil fuel infrastructure to clean energy infrastructure. This transition must |
3 | 3 | also be done equitably and justly to prevent entrenching further injustices to |
4 | | -marginalized and vulnerable communities. To that end, this thesis develops the |
5 | | -first multi-objective energy system optimization framework, \texttt{Osier}, to |
6 | | -enhance the democratic engagement necessary for a just transition. Rather than |
7 | | -making projections about the future, \texttt{Osier} accomplishes this goal by |
8 | | -combining user-supplied energy demand data with technology-specific data (e.g., |
9 | | -emissions, land-use, cost) and delivers a set of co-optimal energy systems |
10 | | -(i.e., capacities for different energy generating technologies) that balance |
11 | | -competing priorities (e.g., emissions, cost, or land-use). Further, |
12 | | -\texttt{Osier} acknowledges structural uncertainty --- the existence of |
13 | | -unmodeled or \textit{unmodelable} objectives --- by extending the conventional |
14 | | -modeling-to-generate-alternatives approach into N-dimensional objective space. |
15 | | -This approach does not promise to model the unmodelable, rather it recognizes |
16 | | -that any presentation of ``optimal'' solutions will necessarily miss these |
17 | | -unmodelable priorities and that interesting solutions may be contained in a |
18 | | -models sub-optimal space. |
| 4 | +marginalized and vulnerable communities. Current energy planning tools optimize |
| 5 | +for a singular cost objective which challenges decision-makers' ability to |
| 6 | +balance competing priorities such as sustainability, employment, or land use. |
| 7 | +This thesis develops the first multi-objective energy system optimization |
| 8 | +framework, \texttt{Osier}, to enhance the democratic engagement necessary for a |
| 9 | +just transition. |
19 | 10 |
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20 | | -This thesis verified \texttt{Osier}'s suitability for energy modeling problems |
21 | | -with several \textit{in silico} experiments. The first set of experiments |
22 | | -establish \texttt{Osier}'s superiority at exploring decision space over the |
23 | | -mature \texttt{Temoa} framework. A second set of experiments demonstrates |
24 | | -\texttt{Osier} on relevant problems, such as deciding among many nuclear fuel |
25 | | -cycle options. Finally, this thesis presents the results of thirteen expert |
26 | | -interviews which support \texttt{Osier}'s utility for facilitating democratic |
27 | | -engagement between decision makers and their constituents, thereby attending |
28 | | -to issues related to procedural and recognition justice. |
| 11 | +\texttt{Osier} stores information about different energy technologies (e.g., |
| 12 | +wind, solar, nuclear), including their costs, emissions, and other data. Users |
| 13 | +provide energy demand data and define one or more goals for their energy system, |
| 14 | +such as minimizing cost, maximizing renewable energy, or minimizing land use. |
| 15 | +\texttt{Osier} then presents a set of co-optimal energy portfolios that |
| 16 | +prescribe how much of each technology should be built. Further, \texttt{Osier} |
| 17 | +recognizes that some objectives resist quantification. Rather than claiming to |
| 18 | +model the unmodelable, \texttt{Osier} samples near-optimal solution space using |
| 19 | +a novel algorithm developed herein. Together, these solution sets expose |
| 20 | +tradeoffs and allows communities, planners, and decision-makers to deliberate |
| 21 | +over priorities. Beyond planning, \texttt{Osier} serves as an accountability |
| 22 | +tool that allows communities or non-profit organizations to evaluate the |
| 23 | +alignment between implemented policies and stated values. By producing multiple |
| 24 | +solutions, \texttt{Osier} gives modelers and decision-makers the tools to |
| 25 | +meaningfully engage with public stakeholders and learn their preferences, |
| 26 | +thereby attending to issues of procedural and recognition justice. |
| 27 | + |
| 28 | +This thesis verified \texttt{Osier} through a set of benchmarking experiments, |
| 29 | +demonstrating comparable results for a least-cost optimization within 0.5\% of |
| 30 | +the mature modeling framework, \texttt{Temoa}. In addition to benchmarking |
| 31 | +exercises, this thesis applies \texttt{Osier} to two timely examples related to |
| 32 | +nuclear fuel cycle options and powering new data centers. Finally, this |
| 33 | +thesis presents results from thirteen expert interviews with Illinois energy planners which |
| 34 | +support \texttt{Osier}'s utility for enhancing democratic engagement by enabling |
| 35 | +stakeholders to explore tradeoffs and articulate their values, though structural |
| 36 | +barriers to energy modeling adoption at the municipal level persist. |
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