Title :
Unit commitment and operating reserves with probabilistic wind power forecasts
Author :
Botterud, Audun ; Zhou, Zhengchun ; Wang, Jiacheng ; Valenzuela, Jorge ; Sumaili, Jean ; Bessa, R.J. ; Keko, Hrvoje ; Miranda, V.
Author_Institution :
Decision & Inf. Sci. Div., Argonne Nat. Lab., Argonne, IL, USA
Abstract :
In this paper we discuss how probabilistic wind power forecasts can serve as an important tool to efficiently address wind power uncertainty in power system operations. We compare different probabilistic forecasting and scenario reduction methods, and test the resulting forecasts on a stochastic unit commitment model. The results are compared to deterministic unit commitment, where dynamic operating reserve requirements can also be derived from the probabilistic forecasts. In both cases, the use of probabilistic forecasts contributes to improve the system performance in terms of cost and reliability.
Keywords :
load forecasting; power generation dispatch; power generation reliability; probability; stochastic processes; wind power plants; deterministic unit commitment; dynamic operating reserve requirements; power system operations; probabilistic wind power forecasts; reliability; stochastic unit commitment model; unit commitment; wind power uncertainty; Forecasting; Probabilistic logic; Stochastic processes; Uncertainty; Wind forecasting; Wind power generation; Wind power; dispatch; probabilistic forecasts; scenario reduction; unit commitment;
Conference_Titel :
PowerTech, 2011 IEEE Trondheim
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-8419-5
Electronic_ISBN :
978-1-4244-8417-1
DOI :
10.1109/PTC.2011.6019263