A case study on regional impacts of climate change: peak loads on the power grid in Rochester, New York

Scott Constable (), Jason Hamilton () and Thomas Pfaff ()

Journal of Environmental Studies and Sciences, 2013, vol. 3, issue 1, 15-20

Abstract: Understanding the effects of climate change and determining appropriate mitigation and adaptation measures comprise a paradigmatic example of an issue that crosses traditional disciplinary boundaries and requires communication and collaboration across many fields of study. For example, it is well documented that power consumption in the USA increases drastically when summer temperatures spike (Wong et al., IEEE Trans Powere Syst 25:480–488, 2010 ). As people resort to air conditioning to curb the heat, the strain on the power grid can become overwhelming, occasionally leading to blackouts. This is already a serious issue in some areas of the USA. However, it is unclear to what extent future climate scenarios will increase electrical demand in any particular area and whether this will lead to increased risk of blackouts from excessive electrical demand. To illustrate the powerful potential for interdisciplinary collaboration between departments of mathematics and environmental studies and sciences, we use predictions of peak electrical load and the likelihood of resultant blackouts in Rochester, NY under the IPCC A2 climate change scenario as a case study. Using publicly available climate simulations and regional climate data, coupled with simple mathematical modeling of extreme events (generalized extreme value distributions), we develop a planning tool for predicting regional power demand. In this case, our model forecasts that a given extreme peak load which now occurs only once every 20 years, will occur annually by around 2050. This information is crucial for planning our future electrical power needs. Copyright AESS 2013

Keywords: Interdisciplinary collaboration; Climate change; Electricity grid; Generalized extreme value distribution; Peak load; Simulation (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/s13412-012-0097-5

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