PNNL

Abstract

As extreme weather-related grid outages become more frequent, customers are vulnerable to significant economic losses and non-energy impacts,such as increased mortality rates, property damages, due to service disruption. Although, several resilience enhancement approaches have investigated in existing literature, one of key barriers towards adoption has been the lack of a framework for holistically analyzing the operational and economic performance of such approaches. Towards addressing that gap, this work introduces a techno-economic analysis framework for evaluating the performance of resilience enhancement mechanisms and their value proposition from different stakeholder perspectives. This proposed framework integrates a physics-based grid response modeling and co-simulation approach with a valuation methodology incorporating energy and non-energy impacts to comprehensively evaluate various resilience enhancement mechanisms. The framework is implemented for a realistic use-case that emulates the grid response of Texas during the winter storm Uri in mid-February 2021 and its efficacy is demonstrated through a techno-economic analysis of two alternative resilience enhancement approaches as compared to legacy outage management schemes. The two approaches, explored in this work, includes a data-driven rolling outage mechanism that selectively serve customers in a sequential fashion based on adaptive curtailment requirements and a transactive energy (TE) based allocation scheme that offer a certain level of allocation to all customers for serving their essential loads during periods of scarcity while facilitating preference-based trading of their allocation. The results indicate that both the rolling outage and TE scenarios performed well, improving the energy utilization and thermal comfort for customers compared to the controlled outage case. Moreover, the TEPA case outperformed the rolling outage mechanism in terms of efficient energy utilization, considering customer preferences, and reducing power interruption costs.