Improvement of EMC in MPPT Control of Photovoltaic System Using Auto-Tuning Adaptive Velocity Estimator
Author(s) -
Tsuyoshi Ohba,
Risa Matsuda,
Haruo Suemitsu,
Takami Matsuo
Publication year - 2015
Publication title -
journal of robotics and mechatronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.257
H-Index - 19
eISSN - 1883-8049
pISSN - 0915-3942
DOI - 10.20965/jrm.2015.p0489
Subject(s) - maximum power point tracking , control theory (sociology) , estimator , photovoltaic system , maximum power principle , observer (physics) , noise (video) , computer science , mathematics , voltage , engineering , electrical engineering , physics , artificial intelligence , statistics , image (mathematics) , control (management) , quantum mechanics , inverter
Proposed modified-IC method Output by a photovoltaic array is nonlinear and changes with solar irradiation and cell temperature. Maximum Power Point Tracking (MPPT) is needed to maximize the energy produced. Most MPPT techniques include the time derivative of current and voltage. These electrical signals are disturbed by high-frequency noise such as from the power device switching. Lowpass filters are used to reduce circuit noise, but estimation error occurs when the maximum power point is calculated. We therefore apply an adaptive observer to estimate the time derivative of noisy signals. Specifically, we propose an auto-tuning velocity estimator with a forgetting factor based on the adaptive observer. We also improve the incremental conductance method by using an auto-tuning velocity estimator.
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