The dynamics of United Kingdom regional energy demand

Smyth, M. J.

doi:10.1002/(sici)1099-114x(199602)20:2<93::aid-er221>3.0.co;2-z

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…Already in 1996, Smyth stated that the regional dimension of energy demand had not been given enough attention. Aydinalp et al .…”

Section: Introductionmentioning

confidence: 99%

“… have investigated the effects of the geographic location on load and energy requirements of residential buildings in Saudi Arabia. Smyth has estimated price and income elasticities of regional energy demand in Scotland, Northern Ireland and the UK. Recent studies in load profile simulation focus on integrating renewable energy supply into distribution grids , cogeneration , micro‐CHP and mixed energy distribution systems, that is, incorporating more than one carrier .…”

Section: Introductionmentioning

confidence: 99%

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Simulation of disaggregated load profiles and development of a proxy microgrid for modelling purposes

Zeyringer

Andrews

Schmid

et al. 2014

Int. J. Energy Res.

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SUMMARYThe deployment of small-scale renewable energy technologies affects the electricity grid depending on the local resource potential as well as on the regional composition of consumers. Spatially explicit renewable energy supply data and spatially disaggregated load profiles of consumers are usually not available to modellers. These data are, however, necessary to better account for the particularities of electricity systems with high levels of distributed renewable production. We present a methodology to estimate the load profile for the distribution grid of household and commercial consumers at 1 km pixel resolution for Austria. Consequently, we combine statistical data on the distribution of electricity consumers with standardized load profiles. Additionally, we present a model that allows allocating theoretical transformers to pixels allowing constructing proxy microgrids. We validate the load generation methodology for three different days and seasons. Hence, we use recently measured load profiles from the federal state of Vorarlberg. The proxy microgrids are validated using data on transformer locations from the federal state of Upper Austria. The modelling approach allows reproducing the historically measured load profiles and the number and location of transformers in the distribution grid with reasonable accuracy. The validation results show that about 80-91% of the variance of the modelled demand data can be explained by the variance of the measured data. In addition, about 78% of the transformer locations can be replicated.

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“…Already in 1996, Smyth stated that the regional dimension of energy demand had not been given enough attention. Aydinalp et al .…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Simulation of disaggregated load profiles and development of a proxy microgrid for modelling purposes

Zeyringer

Andrews

Schmid

et al. 2014

Int. J. Energy Res.

View full text Add to dashboard Cite

show abstract

“…Other studies modelled the energy consumption of the different economic sectors (e.g. industrial, commercial, and residential) within a country (Smyth 1996, Eltony & Hosque 1997. Co-integration techniques for establishing long-and short-term energy demand relationships with climate factors have also been performed (Bard & Nasr 2001).…”

Section: Introductionmentioning

confidence: 99%

Trends in energy load demand for Athens, Greece: weather and non-weather related factors

Giannakopoulos

Psiloglou²

2006

Clim. Res.

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This study examines the characteristics of energy demand for the Greater Athens area in Greece, and explores its relationship with variations in temperature. Energy demand in Athens varies both seasonally and from year to year. The latter shows an increasing trend, which is associated mainly with economic, social and demographic factors. The former is controlled by prevailing weather fluctuations and also by factors unrelated to weather effects (weekend and holiday effects). Weekends and public holidays always appear to have much lower values of energy demand than weekdays. Analysis of our data series has indicated that the relation between energy demand and temperature is non-linear and that the optimum ambient temperature for low levels of energy demand is 22°C. This temperature was also used as the base temperature for the calculation of heating and cooling degree-days. The sensitivity of energy load to air temperature is greater during the cold period of the year. Under a changing climate, regional models predict a warming for Athens by the 21st century that will be associated with a decrease in demand during the milder and shorter winter period and with an increase in demand during the hotter and longer summer period.KEY WORDS: Degree-days · Energy demand trends · Ambient temperature · Climate change Resale or republication not permitted without written consent of the publisher

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On the relationship between electrical energy consumption and climate factors in Lebanon: co-integration and error-correction models

Badr¹,

Nasr²

2001

Int. J. Energy Res.

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The dynamics of United Kingdom regional energy demand

Cited by 3 publications

References 6 publications

Simulation of disaggregated load profiles and development of a proxy microgrid for modelling purposes

Simulation of disaggregated load profiles and development of a proxy microgrid for modelling purposes

Trends in energy load demand for Athens, Greece: weather and non-weather related factors

On the relationship between electrical energy consumption and climate factors in Lebanon: co-integration and error-correction models

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