Regional Energy Demand Responses To Climate Change: Methodology And Application To The Commonwealth Of Massachusetts

By A. Amato, Matthias Ruth, P. Kirshen, James Horwitz. 2005

245 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Management Science and Operations Research, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/b9df1fc705e823e7a85c64cd5d510989208e840f

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In Global and Planetary Change

Page Kyle

In Renewable Energy, Sustainability and the Environment

Citations in the corpus

Analyzing the impact of weather variables on monthly electricity demand (2005, background): “Arguably between 14 and 17 , there is a dead zone/balance point in which the electricity consumption can be considered largely unresponsive to the temperature [12].”
Indications for a changing electricity demand pattern: The temperature dependence of electricity demand in the Netherlands (2009, background): “Most studies investigating this relation assume a fixed balance temperature (Sailor and Mun ˜ oz, 1997; Sailor, 2001; Amato et al., 2005; Crowley and Joutz, 2005; Hadley et al., 2006; Ruth and Lin, 2006), mostly at 181C.”
Understanding the spectrum of residential energy consumption: A quantile regression approach (2010, unknown): “Increasing interest in the relationships between energy consumption, climate, land use and transportation is evidenced by recent work (e.g. Ewing and Rong 2008; Amato et al., 2005; Barnes et al., 2005).”
Effects of long-term climate change on global building energy expenditures (2018, background): “This group includes studies exploring future demand for electricity and heating fuels in Massachusetts (Amato et al., 2005), electricity consumption in eight tute of Science and Technology ty. f Geological and Atmospheric icle under the CC BY license (http://c U.S. states (Sailor, 2001), cooling…”
The non-linear link between electricity consumption and temperature in Europe: A threshold panel approach (2008, background): “2A notable exception is the study by Amato et al. (2005), choosing the threshold value producing the highest coefficient of determination in the regression including HDD and CDD variables.”