Collaborative Research: SAI-P: Institutional Design Innovation for Power System Reliability as the Grid Decarbonizes

Project: Research

Project Details

Description

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 electricity system within the U.S. is undergoing rapid changes. It is incorporating higher levels of wind and solar energy sources, responding to more variable demand, and preparing for large climate and weather uncertainties. Yet, decisions about resource procurement, investment, and contingency planning are often made with limited information about tradeoffs between resource costs and reliability risks or the unequal impacts of power grid reliability across communities and social settings. This SAI planning project examines how the transition to a reliable future electric grid can be made more efficient, sustainable, and equitable. It considers how the engineering metrics and models for resource adequacy are embedded in decision-making practices and relationships between organizations. The project focuses on the co-design of resource adequacy approaches, with partnerships involving industry actors, regulators and electric grid stakeholders in a region of the country where the relationships between power reliability, affordability, and sustainability are at the forefront of legislative and regulatory agendas. This SAI planning project establishes an integrated framework, a set of transformative concepts and analytical tools, and an interdisciplinary collaborative team to further a fundamental rethinking of approaches for power grid reliability. The project develops a new framework for power-grid resource adequacy assessment by focusing on two long-term research questions. One is a consideration of how institutional design choices and rules structuring governance arrangements enable or constrain learning and innovation. The other focuses on how quantitative and predictive modeling of resource adequacy and power shutoff contingencies can better incorporate differences across spatial and social settings in assumptions and attitudes about risks, costs, fairness, environmental impacts, and climate change mitigation. The planning activity combines stakeholder-engaged conceptualization and data collection, semi-structured interviews, pilot testing of analytical tools and approaches to uncertainty in coupled human-technical systems, and team building activities. These efforts provide a foundation for research on resource adequacy using new concepts for understanding institutional design choices in electricity system governance, novel analytical tools for characterizing the risks and uncertainties posed by rapid technological and climate change, and new metrics and modeling tools for assessing the affordability, reliability, sustainability, and equity of decisions.This award is supported by the Directorate for Social, Behavioral, and Economic (SBE) Sciences and the Directorate for Engineering.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.
StatusFinished
Effective start/end date15/09/2231/08/24

Funding

  • National Science Foundation: $78,872.00

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