Unit commitment for systems with significant wind penetration

Aidan Tuohy, Peter Meibom, Eleanor Denny () and Mark O'Malley

MPRA Paper from University Library of Munich, Germany

Abstract: The stochastic nature of wind alters the unit commitment and dispatch problem. By accounting for this uncertainty when scheduling the system, more robust schedules are produced, which should, on average, reduce expected costs. In this paper, the effects of stochastic wind and load on the unit commitment and dispatch of power systems with high levels of wind power are examined. By comparing the costs, planned operation and performance of the schedules produced, it is shown that stochastic optimization results in less costly, of the order of 0.25%, and better performing schedules than deterministic optimization. The impact of planning the system more frequently to account for updated wind and load forecasts is then examined. More frequent planning means more up to date forecasts are used, which reduces the need for reserve and increases performance of the schedules. It is shown that mid merit and peaking units and the interconnection are the most affected parts of the system where uncertainty of wind is concerned

Keywords: power generation dispatch; power system economics; stochastic systems; wind power generation (search for similar items in EconPapers)
JEL-codes: Q4 Q42 Q47 (search for similar items in EconPapers)
Date: 2009-05-01
References: View complete reference list from CitEc
Citations: View citations in EconPapers (121)

Published in IEEE Transactions on Power Systems 2.24(2009): pp. 885-895

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/34849/1/MPRA_paper_34849.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:34849

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().