Yang Et al.: Getting to Yes: The Sustainable Energy Modeling Project (SEMPro) Model of Infrastructure Siting

Zining Yang, Mark Abdollahian, Hal Nelson, Brett Close

We present the results of the Sustainable Energy Modeling Project (SEMPro), a three year research project to develop a new, agent-based, predictive analytics model of the energy infrastructure siting in the techno-social space. The citizen module of SEMPro simulates attitudinal and behavioral diffusion of support and opposition to new energy infrastructure projects with large negative externalities. Using a Southern California high voltage transmission line as a case study, the model integrates project engineering and institutional factors with GIS data on land use attributes and residential demographics in an agent based modeling framework. Communication between utilities, nongovernmental organizations (NGOs) and citizen agents result in messages being sent to the project’s regulators as well as the formation of community based organizations who either support or oppose the project. The simulations show that the distance that citizen agents are able to talk across (talkspan) has a large negative impact on the number of CBOs that form. As citizens are able to communicate and exchange political opinions across greater distances with more neighbors, the emergence of social cohesion and collective action declines precipitously and individual expression increases.

We also find that CBO formation and the number of NGO messages have a positive impact on the number of citizen comments submitted as a part of the Environmental Impact Statement process. As expected, utility messages modestly influence the preferences of citizen agents, but have the counterintuitive effect of increasing the number of citizen opposition messages as citizens are turned off by the stronger utility messaging. We believe that SEMPro can serve as an exploratory platform for ideas about issue framing for a successful policy dialogues, scenarios analysis to explore key political, environmental, and regulatory uncertainty, and can identify which solutions resonate with underserved communities.

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