Smart Investment Framework for Energy Resilience: A Case Study of a Campus Microgrid Research Facility

Abstract

Energy resilience is a vital consideration for ensuring the survivability of modern infrastructure systems. Achieving 100% resilience, however, is often impractical and economically burdensome. In this paper, we propose a smart investment framework that enables decision-makers to determine optimal investments in energy resilience based on available resources and desired levels of resilience. To illustrate the effectiveness of this framework, we present a case study of a campus microgrid research and testing facility. Using a real-time simulation approach conducted with Typhoon HIL, we evaluate the performance of the microgrid system over 24 hours following four historically significant hurricanes that have affected Louisiana in the past few years. The microgrid is designed to power local loads during outages, providing an effective solution for enhancing energy resilience. Real solar data collected from our 1.1 Megawatt (MW) solar facility on the University of Louisiana at Lafayette campus is integrated into the simulation, enabling a realistic evaluation of the system's performance under hurricane-induced disruptions. By employing the proposed smart investment framework, decision-makers can better identify and address resilience challenges. The framework facilitates informed investment decisions by considering available resources and aligning them with the desired level of resilience. This approach avoids over-investment in unnecessary redundancy while ensuring critical systems are adequately protected. Our research contributes to the field by demonstrating the practicality and benefits of a smart investment framework for energy resilience in a real-world scenario. The case study of the campus microgrid research facility provides valuable insights for decision-makers in similar contexts, highlighting the potential of this framework to guide resilient energy infrastructure planning and investment strategies.