Impacts of rising air temperatures on electric transmission ampacity and peak electricity load in the United States

Abstract

Climate change may constrain future electricity supply adequacy by reducing electric transmission capacity and increasing electricity demand. The carrying capacity of electric power cables decreases as ambient air temperatures rise; similarly, during the summer peak period, electricity loads typically increase with hotter air temperatures due to increased air conditioning usage. As atmospheric carbon concentrations increase, higher ambient air temperatures may strain power infrastructure by simultaneously reducing transmission capacity and increasing peak electricity load. We estimate the impacts of rising ambient air temperatures on electric transmission ampacity and peak per-capita electricity load for 121 planning areas in the United States using downscaled global climate model projections. Together, these planning areas account for roughly 80% of current peak summertime load. We estimate climate-attributable capacity reductions to transmission lines by constructing thermal models of representative conductors, then forcing these models with future temperature projections to determine the percent change in rated ampacity. Next, we assess the impact of climate change on electricity load by using historical relationships between ambient temperature and utility-scale summertime peak load to estimate the extent to which climate change will incur additional peak load increases. We find that by mid-century (2040-2060), increases in ambient air temperature may reduce average summertime transmission capacity by 1.9%-5.8% relative to the 1990-2010 reference period. At the same time, peak per-capita summertime loads may rise by 4.2%-15% on average due to increases in ambient air temperature. In the absence of energy efficiency gains, demand-side management programs and transmission infrastructure upgrades, these load increases have the potential to upset current assumptions about future electricity supply adequacy. Glossary q c  Convective heat loss from conductor to air (W m -1 ) q r  Radiative heat loss from conductor to surroundings (W m -1 ) q s  Radiative heat transfer from sun to conductor (W m -1 ) q j  Resistive heating of the conductor (W m -1 )

The growing threat of heat disasters

“…These data highlight the vulnerability of power generation and transmission infrastruture to weather-related perturbances, particularly in the face of an anticipated increase in number and severity of extreme weather events (e.g. huricanes, heat waves) (Bartos et al 2016).…”

New York City Panel on Climate Change 2019 Report Chapter 7: Resilience Strategies for Critical Infrastructures and Their Interdependencies

“…Records of past heat wave events indicate that peak loads and blackouts can be related to these extreme heat events. The way overhead transmission and distribution systems are designed can affect vulnerability to sagging, which is related to air temperature and the ability to reduce heat effects (Bartos et al ., ).…”

New York City Panel on Climate Change 2019 Report Chapter 8: Indicators and Monitoring

“…These could be intermittent depending upon the length of the impacts; however, regardless of the time period, once the equipment is disabled, repairs will have to be made. r Extent to which overhead line sag contributes to decreased performance of electric transmission and distribution and the occurrence of outages where decreased performance cannot accommodate existing loads (Bartos et al, 2016) r Refinement of the SAIFI indicator to explicitly include climate change above what it currently includes as weather-related effects r Relevance of various input measures such as worker availability and the availability of materials to climate change in a way that can be related to output indicators 8.5.1 Case study 2: Energy Following the template of the first case study, we now turn to proposing an indicator for critical infrastructure in the energy sector in response to its established vulnerability to extreme weather events. Its characteristics include: Table 8.7, probably since as indicated above the indicators are not incorporating major storms in which customers lose power for more than 24 hours.…”