Volume 50

Systems-level Methodology for Optimizing Urban Infrastructure Energy Resilience Jingyuan Shen, Xi Wang, Abdulrahman H Alorabi, Takahiro Yoshida, Akito Murayama, Perry Pei-Ju Yang

Abstract

Urban population growth and extreme weather events challenge the balance of energy supply and demand, stressing power grids and leading to higher prices and potential blackouts. Addressing these challenges requires sustainable and resilient energy systems. This research aims to develop a methodology to optimize urban infrastructure energy resilience by integrating urban-scale building energy modeling (UBEM) with smart grid technologies. The methodology encompasses building energy analysis, renewable energy optimization, and systems-level integration. Using the Toyosu area of Tokyo as a case study, the research examines a normal baseline with 2023 historical weather data and an extreme weather scenario with future climate datasets. Each case contains 11 input variables and 4 output variables, with 6 input variables used in UBEM to generate the load profile. The study employs the REopt tool to identify optimal combinations of renewable energy and storage technologies. Simulation results demonstrate the feasibility of the proposed methodology, providing insights into enhancing urban energy system resilience and achieving sustainability goals. The proposed methodology allows for a more robust and dynamic response to fluctuations in energy demand and supply that is particularly critical during extreme weather events which are becoming more frequent due to climate change.

Keywords Urban building energy modeling, smart grid, design of experiment, digital twins, energy resilience