2016
DOI: 10.1088/1748-9326/11/12/124025
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Quantifying the increasing sensitivity of power systems to climate variability

Abstract: Large quantities of weather-dependent renewable energy generation are expected in power systems under climate change mitigation policies, yet little attention has been given to the impact of long term climate variability. By combining state-of-the-art multi-decadal meteorological records with a parsimonious representation of a power system, this study characterises the impact of year-to-year climate variability on multiple aspects of the power system of Great Britain (including coal, gas and nuclear generation… Show more

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Cited by 107 publications
(99 citation statements)
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“…Note that in some countries the total load data may include a contribution from embedded renewable generation, which should be noted in the interpretation of results. This approach is very similar to that used in previous studies (Bloomfield et al ., , ) and validates well against observations on daily timescales with R 2 > 0.86 for all countries, and an average root mean square error (RMSE) of 7% of the national‐aggregate demand in all cases. For full details of the regression co‐efficients and corresponding skill scores, see Supporting Information File S1.…”
Section: Methodsmentioning
confidence: 97%
“…Note that in some countries the total load data may include a contribution from embedded renewable generation, which should be noted in the interpretation of results. This approach is very similar to that used in previous studies (Bloomfield et al ., , ) and validates well against observations on daily timescales with R 2 > 0.86 for all countries, and an average root mean square error (RMSE) of 7% of the national‐aggregate demand in all cases. For full details of the regression co‐efficients and corresponding skill scores, see Supporting Information File S1.…”
Section: Methodsmentioning
confidence: 97%
“…Bloomfield et al [38] model a simplified British power system across several decades but only consider wind power, neglecting the increasingly important role of PV; Pfenninger [31] examines the inter-annual variability of both wind and PV over 25 years in a UK power system model. However, none of these studies consider the influence of weather on power demand.…”
Section: Introductionmentioning
confidence: 99%
“…It is thus necessary to consider indicators such as the variability and synchronicity of generation in addition to total energy yields Bruckner et al, 2014;Bloomfield et al, 2016). Several validated time series of renewable generation based on reanalysis data are available to assess the power system operation Staffell and Pfenninger, 2016;Gonzalez Aparcio et al, 2016).…”
Section: Introductionmentioning
confidence: 99%