Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Regression models in wind power forecasting


Affiliations
1 Professor, PES Institute of Technology, 100ft. Road, BSK III Stage, Bangalore - 560 085, India
2 Professor and Dean(Academics), PES Institute of Technology, 100ft. Road, BSK III Stage, Bangalore - 560 085, India
3 Professor,Indian Institute of Science, C V Raman Avenue, Bangalore - 560 012, India
4 Professor and Director (Foreign affairs and Alumni Matters), Jawaharlal Nehru Technological University Anantapur, Saradha Nagar, Ananthapuramu - 515002, India
     

   Subscribe/Renew Journal


Modeling of generation of wind power systems is useful for an effective management and balancing of a power grid, supporting real-time operations. Forecasting the expected wind power production could help to deal with uncertainties. In comparison with the mathematical approach, the data driven approach is useful where both detailed information about the system and real time measurements are unavailable. Winds being a natural phenomenon, statistical methods are more suitable for wind power plants than that of conventional power plants. In this paper, the data on the wind speed and power generated from a location in the state of Karnataka, India, has been analyzed and shown that the probability distribution of wind speed follows Rayleigh or Gaussian/Normal distribution. Short-term wind power forecasting is carried out using Autoregressive models.

Keywords

Wind power forecasting,rayleigh distribution, gaussian distribution, auto - regression.
User
Subscription Login to verify subscription
Notifications
Font Size

Abstract Views: 204

PDF Views: 0




  • Regression models in wind power forecasting

Abstract Views: 204  |  PDF Views: 0

Authors

M. Anuradha
Professor, PES Institute of Technology, 100ft. Road, BSK III Stage, Bangalore - 560 085, India
B. K. Keshavan
Professor and Dean(Academics), PES Institute of Technology, 100ft. Road, BSK III Stage, Bangalore - 560 085, India
T. S. Ramu
Professor,Indian Institute of Science, C V Raman Avenue, Bangalore - 560 012, India
V. Sankar
Professor and Director (Foreign affairs and Alumni Matters), Jawaharlal Nehru Technological University Anantapur, Saradha Nagar, Ananthapuramu - 515002, India

Abstract


Modeling of generation of wind power systems is useful for an effective management and balancing of a power grid, supporting real-time operations. Forecasting the expected wind power production could help to deal with uncertainties. In comparison with the mathematical approach, the data driven approach is useful where both detailed information about the system and real time measurements are unavailable. Winds being a natural phenomenon, statistical methods are more suitable for wind power plants than that of conventional power plants. In this paper, the data on the wind speed and power generated from a location in the state of Karnataka, India, has been analyzed and shown that the probability distribution of wind speed follows Rayleigh or Gaussian/Normal distribution. Short-term wind power forecasting is carried out using Autoregressive models.

Keywords


Wind power forecasting,rayleigh distribution, gaussian distribution, auto - regression.



DOI: https://doi.org/10.33686/prj.v11i3.189413