Modeling natural gas price volatility: The case of the UK gas market

Scholtens, Bert; Goor, H. van

doi:10.1016/j.energy.2014.05.016

Cited by 43 publications

(18 citation statements)

References 33 publications

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“…Previous studies have found a near-linear, negative relationship between temperature and electricity and gas demand in the UK (Hor et al 2005, Bessec and Fouquau 2008, Psiloglou et al 2009, Summerfield et al 2015. Energy demand is shown to vary across a range of timescales, with clear daily, weekly and annual cycles (Taylor and Buizza 2003, Taylor 2010, van Goor and Scholtens 2014. In addition, UK electricity demand exhibits a long term trend (Hor et al 2005).…”

Section: Introductionmentioning

confidence: 93%

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The role of temperature in the variability and extremes of electricity and gas demand in Great Britain

Thornton

Hoskins

Scaife

2016

Environ. Res. Lett.

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The daily relationship of electricity and gas demand with temperature in Great Britain is analysed from 1975 to 2013 and 1996 to 2013 respectively. The annual mean and annual cycle amplitude of electricity demand exhibit low frequency variability. This low frequency variability is thought to be predominantly driven by socio-economic changes rather than temperature variation. Once this variability is removed, both daily electricity and gas demand have a strong anti-correlation with temperature (r elec =−0.90 , r gas =−0.94). However these correlations are inflated by the changing demand-temperature relationship during spring and autumn. Once the annual cycles of temperature and demand are removed, the correlations are =r 0.60 elec and =r 0.83 gas . Winter then has the strongest demand-temperature relationship, during which a 1°C reduction in daily temperature typically gives a ∼1% increase in daily electricity demand and a 3%-4% increase in gas demand. Extreme demand periods are assessed using detrended daily temperature observations from 1772. The 1 in 20 year peak day electricity and gas demand estimates are, respectively, 15% (range 14%-16%) and 46% (range 44%-49%) above their average winter day demand during the last decade. The risk of demand exceeding recent extreme events, such as during the winter of 2009/2010, is also quantified.

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Section: Introductionmentioning

confidence: 93%

“…Predicting electricity and gas demand is important for ensuring there is sufficient supply to meet demand. This is particularly important during extreme demand periods, when the risk of energy shortages and whole sale energy prices rise (National Grid 2014, van Goor andScholtens 2014).…”

Section: Introductionmentioning

confidence: 99%

The role of temperature in the variability and extremes of electricity and gas demand in Great Britain

Thornton

Hoskins

Scaife

2016

Environ. Res. Lett.

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“…Mean-reverting OU models have been also reported in the literature to adequately approximate the spot prices after extracting the deterministic components [22,23]. However, the deterministic component at a low scale is not as easy observable in the gas as in the electricity prices.…”

Section: Gas Price Modelmentioning

confidence: 96%

“…Gas prices are daily, and this makes it difficult to observe characteristic patterns as those shown in the electricity price. Therefore, we resorted in this case to differently extract the deterministic part by obtaining for each day the mean price over the last ten years [22]. The OU values obtained for gas price are shown in Table 1 (Gas price).…”

Section: Gas Price Modelmentioning

confidence: 99%

Joint cost of energy under an optimal economic policy of hybrid power systems subject to uncertainty

Díaz

Planas

Andreu

et al. 2015

Energy

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“…Wang and Wu [6] forecasted energy market volatility by using multivariate and univariate GARCH-class models. Goor and Scholtens [7] applied GARCH models in the UK gas market. Kanamura [8] proposed a new volatility model model for energy prices using the supply-demand relationship.…”

Section: Introductionmentioning

confidence: 99%

Will the Steam Coal Price Rebound under the New Economy Normalcy in China?

2016

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Abstract:The steam coal price in China has been continuously decreasing since the second half of 2012. Constant low price of coal will accelerate the development of thermal power, cause more serious air pollution problems, and bring adverse influence to China's energy reformation in the future. Therefore, analyzing the factors underlying the phenomenon of the decreasing steam coal price is significant. In this study, we first qualitatively analyze five main factors, namely, economy, supply, demand, substitutes, and port stocks. On the basis of the relationships among these five factors, we obtain the causality diagram and the system flow diagram of coal price for further quantitative research. Then, we conduct an empirical analysis using the system dynamics (SD) method and determine the simulated price from 2012 to 2017. Finally, we discuss the running results and come to the conclusion that the steam coal price will continue to decrease under the combined actions of the five main factors and it will not rebound in the near future.

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Modeling natural gas price volatility: The case of the UK gas market

Cited by 43 publications

References 33 publications

The role of temperature in the variability and extremes of electricity and gas demand in Great Britain

The role of temperature in the variability and extremes of electricity and gas demand in Great Britain

Joint cost of energy under an optimal economic policy of hybrid power systems subject to uncertainty

Will the Steam Coal Price Rebound under the New Economy Normalcy in China?

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