Task 3.1

Develop community-centric and location-based metrics.

Research driven by Dr. Shi, Dr. Dadgostari, Dr. Spangler, Dr. Hu, and Dr. Sullivan.

By focusing on creating key metrics for climate-aware resilience in energy systems, this task addresses service reliability, environmental resilience, energy burden and equity, and adaptability

Task 3.2

Model interactions and impact dynamics.

Researchers include Dr. Shi, Dr. Zhang, Dr. Cui, Dr. Dadgostari, and Dr. Spangler.

This task aims to develop impact assessment models for energy systems, utilizing baselines and metrics from Task 3.1 to analyze “what-if” scenarios. Then using an algorithm that is designed to estimate resilience levels across multiple scales, from individual households to entire communities.

Task 3.3

Develop a framework for climate-adaptive multi-timescale infrastructure optimization for renewable energy systems.

Researchers for this task are Dr. Wang, Dr. Dadgostari, Dr. Shi, Dr. Spangler, and Dr. Zhang.

This task develops a hierarchical optimization model to manage uncertainties from climate change and weather extremes by focusing on renewable energy infrastructure planning,

Task 3.4

Model community-centric load restoration in the aftermath of power outages.

Researchers are Dr. Zhang, Dr. Spangler, Dr. Hu, Dr. Haggerty, and Dr. Wang.

This task aims to develop models for load restoration in communities following power outages, filling critical gaps in current smart grid technologies. It addresses two main challenges: the under-researched area of resilience infrastructure at the community level, and the tendency of existing restoration models to overlook the needs of low-income communities