Title :
A Versatile Probability Distribution Model for Wind Power Forecast Errors and Its Application in Economic Dispatch
Author :
Zhao-Sui Zhang ; Yuan-Zhang Sun ; Gao, David Wenzhong ; Jin Lin ; Lin Cheng
Author_Institution :
Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
Abstract :
The existence of wind power forecast errors is one of the most challenging issues for wind power system operation. It is difficult to find a reasonable method for the representation of forecast errors and apply it in scheduling. In this paper, a probability distribution model named “versatile distribution” is formulated and developed along with its properties and applications. The model can well represent forecast errors for all forecast timescales and magnitudes. The incorporation of the model in economic dispatch (ED) problems can simplify the wind-induced uncertainties via a few analytical terms in the problem formulation. The ED problem with wind power could hence be solved by the classical optimization methods, such as sequential linear programming which has been widely accepted by industry for solving ED problems. Discussions are also extended on the incorporation of the proposed versatile distribution into unit commitment problems. The results show that the new distribution is more effective than other commonly used distributions (i.e., Gaussian and Beta) with more accurate representation of forecast errors and better formulation and solution of ED problems.
Keywords :
linear programming; power generation dispatch; wind power plants; ED problem; economic dispatch; sequential linear programming; versatile probability distribution model; wind power forecast error; wind power system operation; Linear programming; Mathematical model; Predictive models; Probability density function; Shape; Wind forecasting; Wind power generation; Cumulative distribution function (CDF); economic dispatch (ED); forecast; forecast span (FS); probability density function (PDF); sequential linear programming (SLP); versatile distribution; wind power;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2013.2249596