EAGER: SAI: New Decision Paradigms by Integrating Utility Theory into Infrastructure Investments

Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate human-centered fundamental and potentially transformative research that strengthens America’s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership.

To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering.

The aim of this project is to create a new framework for energy infrastructure investment decisions in the US by integrating more “macro” system-level sustainability analysis with more “micro” distributional preferences of stakeholders to generate more realistic, multi-level decision-making models. Decisions around energy system infrastructure investments involve numerous decision-makers and constituencies, each of which has their own interpretations and priorities.

Different stakeholder objectives can conflict, and even may change over time as decision-makers learn more about the implications of their chosen investment decisions. Infrastructure investments otherwise beneficial can also lead to poor distributional outcomes if marginalized groups are excluded from the benefits. This project investigates priorities and perceptions around distributions of outcomes and opportunities, examines how they may change with education, incorporates them into an energy infrastructure optimization model, and evaluates preferences for this model.

This framework is created by coupling an energy system optimization model with stakeholder elicitations, allowing stakeholders to determine and update acceptable tradeoffs between the environment, cost, and distributional outcomes for energy transition investment in the US. First, distributional preferences are elicited from the future engineering workforce along with an evaluation of how education can affect these preferences.

Second, these preferences are integrated into an energy micro-grid investment decision model (Maximize Energy Access Model). Third, a survey is administered to the local community to elicit community preferences and these preferences are integrated into the optimization models. Throughout this process, the differences between engineering students and community members are examined.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.