Infrastructure & Investment

Large power transformers (LPTs) are critical yet increasingly vulnerable components of the power grid. More frequent and intense heat waves or high temperatures can degrade their operational lifetime and thereby increase the premature failure risk. Without adequate preparedness, a widespread situation would ultimately lead to prolonged grid disruption and incur excessive economic costs. In this study, we investigate the impact of climate warming and corresponding shifts in heat waves on a selected LPT located in the Northeast corridor of the United States. We apply an analogue method, which detects the occurrence of heat waves based on the salient, associated large-scale atmospheric conditions (“composites”), to assess the risk of future change in heat wave occurrence. Compared with the more conventional approach that relies on climate model-simulated daily maximum temperature, the analogue method produces model medians of late twentieth-century heat wave frequency that are more consistent with observation and have stronger inter-model consensus. Under the future climate warming scenarios, multi-model medians of both model daily maximum temperature and the analogue method indicate strong decadal increases in heat wave frequency by the end of the 21st century, but the analogue method improves model consensus considerably. We perform a preliminary assessment on the decrease of transformer lifetime with temperature increase. Future work will focus on using more advanced algorithms to quantify the impact of more frequent heat waves on the transformer’s expected lifetime and associated additional costs. The improved inter-model consensus of the analogue method is viewed as a promising step toward providing actionable information for a more stable, reliable, and environmentally responsible national grid.

Urban planners face challenges in water infrastructure development decisions due to short-term variation in water availability and demand, long-term uncertainty in climate and population growth, and differing perspectives on the value of water. This paper classifies these multiple uncertainties and develops a decision framework that combines simulation for probabilistic uncertainty, scenario analysis for deep uncertainty, and multistage decision analysis for uncertainties reduced over time with additional information. This framework is applied to a case from Melbourne, Australia, where a drought from 1997 to 2009 prompted investment in a $5 billion desalination plant completed in 2012 after the drought ended. The results show opportunities for significant reduction in capital investment using flexible design. Building no infrastructure is best in most simulations. However, in 10% of simulations, building no infrastructure leads to regret of greater than $10 billion compared with a small, flexible desalination plant. Scenario analysis for deep uncertainties underlines the significant impact of assumptions about the future and also on value judgments about the cost of water scarcity in evaluating infrastructure performance.

From 1997 to 2009, Melbourne, Australia experienced what was ultimately called the Millennium Drought, the worst drought on record in the island continent. To compensate, the city’s water planners invested about $3 billion in 2007 in a 150-million-cubic-meter (MCM)/year reverse osmosis desalination plant. At the time, the plant was one of the largest of its kind in the world.

A recent study estimates that about 1.6 million people in China die each year—roughly 4,000 a day—from heart, lung and stroke disorders due to poor air quality. Most of the nation’s lethal air pollution, including headline-grabbing toxins such as fine particulate matter (PM2.5) and ground-level ozone (O3), is produced in its coal-dominated energy and industrial sectors.

China Project

A new MIT study called "Mobility of the Future" is under way with the goals of understanding how developments in technology, fuel, infrastructure, policy and consumer preference will impact the transportation sector. To support the study, the EPPA model will be used to assess how the vehicle fleet and fuel mix will evolve in response to various transportation, energy and climate policy scenarios, and the likely costs of different policy options.

Pages

Subscribe to Infrastructure & Investment