Modeling the Impact of Summer Temperatures on National Electricity Consumption

Comte, Douglas M. Le; Warren, Henry E.

doi:10.1175/1520-0450(1981)020<1415:mtiost>2.0.co;2

Cited by 68 publications

(27 citation statements)

References 1 publication

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“…The link between climatic variables and energy use has been widely documented and utilized to explain energy consumption and to assist energy suppliers with short-term planning (Quayle and Diaz, 1979;Le Comte and Warren, 1981;Warren and LeDuc, 1981;Downton et al, 1988;Badri, 1992;Lehman, 1994;Lam, 1998;Yan, 1998;Morris, 1999;Pardo et al, 2002). However, to date few analyses address the longer-term implications of climate change for energy use patterns and investment decisions.…”

Section: Energy Demand Sensitivity To Climate and Climate Changementioning

confidence: 99%

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

et al. 2005

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Climate is a major determinant of energy demand. Changes in climate may alter energy demand as well as energy demand patterns. This study investigates the implications of climate change for energy demand under the hypothesis that impacts are scale dependent due to region-specific climatic variables, infrastructure, socioeconomic, and energy use profiles.In this analysis we explore regional energy demand responses to climate change by assessing temperature-sensitive energy demand in the Commonwealth of Massachusetts. The study employs a two-step estimation and modeling procedure. The first step evaluates the historic temperature sensitivity of residential and commercial demand for electricity and heating fuels, using a degree-day methodology. We find that when controlling for socioeconomic factors, degree-day variables have significant explanatory power in describing historic changes in residential and commercial energy demands. In the second step, we assess potential future energy demand responses to scenarios of climate change. Model results are based on alternative climate scenarios that were specifically derived for the region on the basis of local climatological data, coupled with regional information from available global climate models. We find notable changes with respect to overall energy consumption by, and energy mix of the residential and commercial sectors in the region. On the basis of our findings, we identify several methodological issues relevant to the development of climate change impact assessments of energy demand.

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Section: Energy Demand Sensitivity To Climate and Climate Changementioning

confidence: 99%

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

et al. 2005

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“…The most impressive phenomenon is the urban thermo-effect, which refers to thermal environment changes within the area due to the alteration of energy balance (Oke, 1982(Oke, , 1988. The urban thermoeffect may cause the Urban Heat Island phenomenon during which the temperature of an urban area becomes higher than that of the surrounding rural area, resulting in a high rate of heat-related diseases and mortality (Kalkstein, 1993;Semenza et al, 1996;Kalkstein and Greene, 1997;Smoyer, 1998), high consumption of energy for air conditioning (Le Comte and Warren, 1981;Santamouris et al, 2001), and air pollution (Aikawa et al, 2006;Sarrat et al, 2006;Noyes et al, 2009).…”

Section: Introductionmentioning

confidence: 87%

Urban climate change: A comprehensive ecological analysis of the thermo-effects of major Chinese cities

Huang

Wang

Shi

2010

Ecological Complexity

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“…The relationship is different for working and nonworking days, as heating and cooling systems equipment and operation are very different in workplaces from private residences (Smith, 2000); it also changes with the time of the year (Hyde & Hodnett, 1997). There is a dynamic effect, as the load at t does not depend solely on the temperature at t, but also on the temperatures on the previous days (Le Comte & Warren, 1981). Exhaustion effects may appear because of the limited capacity of existing electricity appliances, so there is no further increase in electricity consumption when the temperature exceeds some saturation level (Henley & Peirson, 1997).…”

Section: Temperature Effectsmentioning

confidence: 99%

Forecasting the electricity load from one day to one week ahead for the Spanish system operator

Cancelo¹,

Espasa²,

Grafe³

2008

International Journal of Forecasting

143

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This paper discusses the building process and models used by Red Eléctrica de España (REE), the Spanish system operator, in short term electricity load forecasting. REE's forecasting system consists of one daily model and 24 hourly models with a common structure. There are two types of forecasts of special interest to REE, several days ahead predictions for daily data, and one day ahead hourly forecasts. Accordingly, the forecast accuracy is assessed in terms of their errors. To do this, we analyse historical, real time forecasting errors for daily and hourly data for the year 2006, and report the forecasting performance by day of the week, time of the year and type of day. Other aspects of the prediction problem, like the influence of the errors in predicting the temperature on forecasting the load several days ahead, or the need for an adequate treatment of special days, are also investigated.

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Modeling the Impact of Summer Temperatures on National Electricity Consumption

Cited by 68 publications

References 1 publication

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

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

Urban climate change: A comprehensive ecological analysis of the thermo-effects of major Chinese cities

Forecasting the electricity load from one day to one week ahead for the Spanish system operator

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