Reliable and environmentally sustainable production and consumption of electricity are a major concern in cities experiencing climate extremes. This research plan outlines a framework that addresses the influence of extreme heat and drought on electricity production and consumption. Different from regional- or national-level management, electricity management in densely populated cities during extreme heat and drought events poses unique challenges due to elevated electricity needs and localized characteristics such as urban heat islands. The proposed study will investigate the impact of extreme climate scenarios on modern city-scale power systems and the inherent uncertainties in such analyses. The study will also suggest robust power generation decision-making strategies during these climate extremes.
A framework for the analysis of urban electricity demands and required generation in the face of climate extreme scenarios relies, first, on modeling and data studies of the scenarios themselves. In a first task, historical data on heat and drought, the urban heat island effect, regional climate models, and urban canopy parameterizations at fine spatial scales will be employed to develop an ensemble of heat/drought climate scenarios that inherently account for uncertainties. At city scale, electricity consumption data, geospatial data, building energy modeling, and demand-side management are next considered and included in an uncertainty quantification setting to describe urban energy consumption, with a focus on periods of extreme heat and drought. Uncertainty in electricity supply because of stresses on different generation modes is considered by examining (i) variable thermoelectric power generation and attendant issues, such as lack of cooling water due to often coincident drought and extreme heat periods; and (ii) variability in renewable energy generation via wind and solar power due to extreme climate scenarios related in different ways to the power curve for wind turbines or photovoltaic panel efficiency for solar power. Considering uncertainties in efficiency and output of different energy generation types, robust power dispatch strategies will also be considered using data-driven optimization methods. Two case studies using the cities of Des Moines and Austin will be
selected where the framework that incorporates the tasks above is invoked in various analyses