| dc.description.abstract | With rapid growth in renewable energy development expected in the coming decades, it is crucial to ensure the clean energy transition does not perpetuate past injustices in infrastructure siting. In this thesis, I first contextualize historical renewable energy siting policies and patterns in the U.S., as well as current siting policies and debates. Then, I use a mixed-methods approach to characterize community sentiment towards large-scale renewable energy projects. First, I create a database of online narratives surrounding local renewable energy siting disputes using a large language model (LLM). This method analyzes online media, e.g., newspaper articles, public and legal proceedings, and social media, to quantify types of opposition sentiment. My analysis reveals that both wind and higher capacity projects are correlated with greater quantified measures of opposition, as scored by an LLM. To contextualize these national-level quantitative findings, I also conduct case studies of two ongoing siting disputes in California. I use interviews, focus groups, and participatory methods to better understand local context and analyze how recent state preemption of local siting authority affects public perceptions. Stakeholders focus on place-based factors overlooked in national analysis and express a desire for neutral joint fact-finding processes. Finally, I evaluate a university-based clinical model piloted at MIT for proactive stakeholder assessment and joint problem-solving to improve energy justice outcomes in renewable energy siting. Preliminary findings show the clinical approach increases participation of previously underrepresented groups, builds trust between stakeholders compared to a typical siting process, and expands experiential learning opportunities. Ultimately, this thesis suggests that a combination of large-scale empirical research paired with a site-specific clinical approach could enable a more equitable and efficient energy transition. | |
