Given ever-evolving climate trends, incorporating climate data into electric grid infrastructure planning processes is essential to ensure we are planning our power systems for the future we face, not for historical conditions. However, organizational inertia, the complexity of electric grid planning processes, and the high levels of uncertainty present in climate data hinders planners’ ability to effectively integrate climate information and make informed decisions regarding infrastructure investment. Emerging research in decision-making under deep uncertainty (DMDU) in the context of infrastructure planning offers insights on how to improve climate awareness in electric power systems planning despite the complexity of the electricity sector and high uncertainties in local climate impacts. Our work aims to decipher the DMDU literature, extrapolate relevant ideas, and apply them to the electric grid planning process.

Pulling from existing research related to climate impacts on grid infrastructure, decisions made in grid planning, and decision-making in the face of uncertainty, we will discuss emerging best-practices and offer a series of recommendations for applying DMDU frameworks to the electricity sector. We will (1) explore different types of uncertainty in electric grid infrastructure planning and how they may affect the decision-making process; (2) offer actions decision-makers can take to embrace uncertainty, thus leading to a more robust and potentially adaptive plan; and (3) demonstrate how DMDU frameworks can help resolve tension between conflicting policy objectives through an iterative multi-stakeholder engagement process.

More specifically, we will discuss how ideas of exploratory modeling, adaptive planning, and decision support can be applied to grid planning. We consider options for action—such as updating rules of thumb for component inspections and incorporating scenarios that account for new types of electricity demand and consumer behavior into planning models—in the context of adaptive and risk-aware planning. By demonstrating applicability of DMDU methods in grid planning and providing action-oriented recommendations, we hope to inform how infrastructure planners may develop robust climate adaptation and resilient plans given climate data uncertainties.