Title :
Demand Dispatch and Probabilistic Wind Power Forecasting in Unit Commitment and Economic Dispatch: A Case Study of Illinois
Author :
Botterud, Audun ; Zhou, Zhi ; Wang, Jianhui ; Sumaili, Jean ; Keko, Hrvoje ; Mendes, Joana ; Bessa, Ricardo J. ; Miranda, Vladimiro
Author_Institution :
Decision & Inf. Sci. Div., Argonne Nat. Lab., Argonne, IL, USA
Abstract :
In this paper, we analyze how demand dispatch combined with the use of probabilistic wind power forecasting can help accommodate large shares of wind power in electricity market operations. We model the operation of day-ahead and real-time electricity markets, which the system operator clears by centralized unit commitment and economic dispatch. We use probabilistic wind power forecasting to estimate dynamic operating reserve requirements, based on the level of uncertainty in the forecast. At the same time, we represent price responsive demand as a dispatchable resource, which adds flexibility in the system operation. In a case study of the power system in Illinois, we find that both demand dispatch and probabilistic wind power forecasting can contribute to efficient operation of electricity markets with large shares of wind power.
Keywords :
load forecasting; power generation dispatch; power generation economics; power generation scheduling; power markets; wind power plants; Illinois; centralized unit commitment; demand dispatch; dispatchable resource; dynamic operating reserve requirements estimation; economic dispatch; price responsive demand; probabilistic wind power forecasting; real-time electricity markets; Electricity supply industry; Forecasting; Load management; Probabilistic logic; Uncertainty; Wind forecasting; Wind power generation; Demand dispatch; dynamic operating reserves; economic dispatch; electricity markets; probabilistic forecasts; unit commitment; wind power;
Journal_Title :
Sustainable Energy, IEEE Transactions on
DOI :
10.1109/TSTE.2012.2215631