@ARTICLE{Popławski_T._Adaptation_2020,
 author={Popławski, T. and Szeląg, P. and Bartnik, R.},
 volume={68},
 number={No. 6},
 journal={Bulletin of the Polish Academy of Sciences Technical Sciences},
 pages={1491-1501},
 howpublished={online},
 year={2020},
 abstract={The paper proposes an adaptation of mathematical models derived from the theory of deterministic chaos to short-term power forecasts of wind turbines. The operation of wind power plants and the generated power depend mainly on the wind speed at a given location. It is a stochastic process dependent on many factors and very difficult to predict. Classical forecasting models are often unable to find the existing relationships between the factors influencing wind power output. Therefore, we decided to refer to fractal geometry. Two models based on self-similar processes (M-CO) and (M-COP) and the (M-HUR) model were built. The accuracy of these models was compared with other short-term forecasting models. The modified model of power curve adjusted to local conditions (M-PC) and Canonical Distribution of the Vector of Random Variables Model (CDVRM). Examples of applications confirm the valuable properties of the proposed approaches.},
 type={Article},
 title={Adaptation of models from determined chaos theory to short-term power forecasts for wind farms},
 URL={http://www.journals.pan.pl/Content/118378/PDF/24_D1491-1501_01611_Bpast.No.68-6_29.12.20_OK.pdf},
 doi={10.24425/bpasts.2020.135400},
 keywords={chaos theory, fractals, prognostic models, short-term forecasts, time series},
}