Open AccessAchieving a minimum power fluctuation rate in wind and photovoltaic output power using discrete Kalman filter based on weighted average approach
Author(s) -
Lamsal Dipesh,
Sreeram Victor,
Mishra Yateendra,
Kumar Deepak
Publication year - 2018
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2017.0346
Subject(s) - control theory (sociology) , photovoltaic system , kalman filter , maximum power point tracking , wind power , smoothing , battery (electricity) , power (physics) , state of charge , mathematics , computer science , engineering , statistics , physics , electrical engineering , control (management) , quantum mechanics , inverter , artificial intelligence
In this study, a discrete Kalman filter‐based approach is presented for minimising the output power fluctuations of wind and photovoltaic systems. The control strategy is based on the change in power fluctuation which is determined by the weighted average of the highest and lowest values of the power fluctuation for each interval of time. A genetic algorithm optimisation approach is utilised to determine the optimal value of weighted average such that the power fluctuation rate is minimum. This study also gives the optimum battery power and its state of charge to achieve smoothing determined by the optimal weighted average. On the basis of this optimum battery power, the specification and configuration of the battery energy storage system are also determined.