DocumentCode :
1630610
Title :
Challenges in quantifying wind generation´s contribution to securing peak demand
Author :
Zachary, S. ; Dent, C.J. ; Brayshaw, D.J.
Author_Institution :
Sch. of Math. & Comput. Sci., Heriot-Watt Univ., Edinburgh, UK
fYear :
2011
Firstpage :
1
Lastpage :
8
Abstract :
Wind generation´s contribution to supporting peak electricity demand is one of the key questions in wind integration studies. Differently from conventional units, the available outputs of different wind farms cannot be approximated as being statistically independent, and hence near-zero wind output is possible across an entire power system. This paper will review the risk model structures currently used to assess wind´s capacity value, along with discussion of the resulting data requirements. A central theme is the benefits from performing statistical estimation of the joint distribution for demand and available wind capacity, focusing attention on uncertainties due to limited histories of wind and demand data; examination of Great Britain data from the last 25 years shows that the data requirements are greater than generally thought. A discussion is therefore presented into how analysis of the types of weather system which have historically driven extreme electricity demands can help to deliver robust insights into wind´s contribution to supporting demand, even in the face of such data limitations. The role of the form of the probability distribution for available conventional capacity in driving wind capacity credit results is also discussed.
Keywords :
demand side management; risk management; statistical distributions; wind power plants; joint distribution; near-zero wind output; peak electricity demand; power system; risk model structure; statistical estimation; weather system; wind capacity credit; wind capacity value assessment; wind farms; wind generation contribution; wind integration; Availability; Capacity planning; Educational institutions; Probability distribution; Time series analysis; Wind; Power system modeling; Power system reliability; Wind power generation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting, 2011 IEEE
Conference_Location :
San Diego, CA
ISSN :
1944-9925
Print_ISBN :
978-1-4577-1000-1
Electronic_ISBN :
1944-9925
Type :
conf
DOI :
10.1109/PES.2011.6039572
Filename :
6039572
Link To Document :
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