@misc{debb9a70b426472382fd6a9463b97f35,
title = "Adapting Existing Energy Models for Resilience Analysis",
abstract = "Resilience is a topic receiving much attention in relation to energy systems, with particular attention being paid to the supply of electricity. As a result of the growing interest in energy sector resilience, research communities have proposed a plethora of candidate resilience indicators and metrics, most of which remain immature at different scales and segments within the energy system. A necessary focus of the research community lies in implementing, testing, and validating resilience metrics and analysis approaches in energy sector models, which will be invaluable for informing resilience planning and investment decisions. Recognizing these challenges that need to be addressed, we explore how to effectively integrate resilience considerations into energy sector models and tools. The overarching goal of the effort was to evaluate the data needs, methodologies, and outcomes—including consequences and/or changes in investment or operational decisions due to avoided consequences—based on resilience analysis in a range of existing tools. In particular, we selected five models originally built at NREL to explore non-resilience energy research questions to implement and exercise resilience metrics and analysis approaches. To demonstrate the importance of perspective, we selected models that represent different segments of the energy sector, geographic scales, and modeling approaches. A second important aspect of our effort was the development of generalized power interruption scenarios. These scenarios were intended to help establish a framework for simulating the effects of real-world threats in terms of their impacts on system components and, in turn, power interruption.",
keywords = "metrics, modeling, resilience",
author = "Caitlin Murphy and Eliza Hotchkiss and Kate Anderson and Clayton Barrows and Stuart Cohen and Sourabh Dalvi and Nick Laws and Jeff Maguire and Gord Stephen and Eric Wilson",
year = "2020",
language = "American English",
series = "Presented at the INFORMS 2020 Annual Virtual Meeting, 12 November 2020",
type = "Other",
}