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|Title: ||Going with the wind: temporal characteristics of potential wind curtailment in Ireland in 2020 and opportunities for demand response|
|Authors: ||McKenna, Eoghan|
|Keywords: ||Demand response|
|Issue Date: ||2015|
|Citation: ||MCKENNA, E., GRUNEWALD, P. and THOMSON, M., 2015. Going with the wind: temporal characteristics of potential wind curtailment in Ireland in 2020 and opportunities for demand response. IET Renewable Power Generation, 9 (1), pp. 66-77.|
|Abstract: ||The Republic of Ireland and Northern Ireland have ambitious targets for 40% of electricity to be supplied by
renewables by 2020, with the majority expected to be supplied by wind power. There is, however, already a significant
amount of wind power being turned down, or ‘curtailed’, and this is expected to grow as wind penetrations increase. A
model-based approach is taken to estimate curtailment using high-resolution wind speed and demand data covering four
years, with a particular focus on the temporal characteristics of curtailment and factors that affect it. The model is validated
using actual wind output and curtailment data from 2011. The results for 2020 are consistent with previously published
estimates, and indicate curtailment levels ranging from 5.6 to 8.5% depending on assumptions examined in this study.
Curtailment is found to occur predominantly at night, and to exhibit stochastic variability related to wind output. To
accommodate high penetrations of wind power, the findings highlight the value of flexible demand over relatively long timeperiods.
The model’s output data have been made publicly available for free for further investigation.|
|Description: ||This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/ The dataset 'Wind curtailment estimates for Irish power system in 2020' accompanying the paper is also available to download with this record.|
|Sponsor: ||This work was supported by the Engineering and Physical Sciences Research Council, UK, within the HiDEF Supergen project [ grant number EP/G031681/1], the Transformation of the Top and Tail of Energy Networks project [grant number EP/I031707/1], and the Realising Transition Pathways project [grant number EP/K005316/1]. The authors gratefully acknowledge data from the UK Meteorological Office, the National Centers for Environmental Prediction, Eirgrid Group, and the Irish Single Electricity Market Operator.|
|Appears in Collections:||Data Sets and Software (Mechanical, Electrical and Manufacturing Engineering)|
Published Articles (Mechanical, Electrical and Manufacturing Engineering)
Data Sets and Software (CREST)
Published Articles (CREST)
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