Open AccessKalman filter approach for dispatching and attenuating the power fluctuation of wind and photovoltaic power generating systems
Author(s) -
Lamsal Dipesh,
Sreeram Victor,
Mishra Yateendra,
Kumar Deepak
Publication year - 2018
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2017.0663
Subject(s) - photovoltaic system , wind power , kalman filter , maximum power point tracking , wind speed , electric power system , solar irradiance , irradiance , power (physics) , computer science , control theory (sociology) , power optimizer , engineering , meteorology , electrical engineering , physics , control (management) , quantum mechanics , inverter , artificial intelligence
The battery energy storage system (BESS) is a popularly used source to smooth the power fluctuation caused by variation of wind speed and solar irradiance. The forecasted data of wind and solar irradiance may contain bias error and does not provide the true power available from wind and photovoltaic generating systems. This study proposes a method based on discrete Kalman filter (DKF) to eliminate the bias error present in the forecasted data so that true power of wind and photovoltaic systems could be predicted. A DKF‐based state‐space approach is utilised to predict the true power obtained through wind and photovoltaic generating systems. The proposed approach also attenuates the power fluctuation of wind and PVGSs considering the desired power dispatched to the load as well as evaluates the BESS power needed for this purpose.