Maximum Power Point Tracking of a Photovoltaic System Using Modified Incremental Algorithm and Model Predictive Control
Author(s) -
Ahmad Dehghanzadeh,
Gholamreza Farahani,
Mohsen Maboodi
Publication year - 2018
Publication title -
journal of control
Language(s) - English
Resource type - Journals
eISSN - 2538-3752
pISSN - 2008-8345
DOI - 10.29252/joc.12.2.67
Subject(s) - photovoltaic system , maximum power point tracking , model predictive control , tracking (education) , control theory (sociology) , maximum power principle , power (physics) , predictive power , computer science , point (geometry) , algorithm , mathematics , control (management) , engineering , artificial intelligence , physics , psychology , pedagogy , geometry , quantum mechanics , inverter , electrical engineering
In this paper a systematic methodology to design a modified incremental conductance and a model predictive control (MPC) for maximum power point tracking of a photovoltaic system is presented. The PV system includes a PV module that supplies a DC link and also an energy storage system using a buck DC-DC converter. The incremental conductance (INC) method with two modifications is employed for maximum power point tracking (MPPT) within P-V characteristic curve according to changes in weather condition. To avoid a finite set control signal, the average model of the PV system is analytically calculated and subsequently the model is linearized around MPP. Designing an MPC with continuous control set, its performance respect to finite control set MPC is compared. The simulations demonstrate that the proposed controller with augmented integrator could track the MPP faster and with less steady state error.
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