Title :
Maximum Power Point Tracking using Model Predictive Control of a flyback converter for photovoltaic applications
Author :
Shadmand, Mohammad B. ; Balog, Robert S. ; Abu Rub, Haitham
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX, USA
fDate :
Feb. 28 2014-March 1 2014
Abstract :
Due to the variable, stochastic behavior of the solar energy resource, Maximum Power Point Tracking (MPPT) of photovoltaic (PV) is required to ensure continuous operation at the maximum power point to generate the most electrical energy. This paper presents a Model Predictive Control (MPC) MPPT technique. Extracting the maximum power from PV systems has been widely investigated within the literature; the main contribution of this paper is improvement of the Perturb and Observe (P&O) method through a fixed step predictive control under measured fast solar radiation variation. The proposed predictive control to achieve Maximum Power Point (MPP) speeds up the control loop since it predicts error before the switching signal is applied to the flyback DC/DC converter. Comparing the developed technique to the conventional P&O method indicates significant improvement in PV system performance. The proposed MPC-MPPT technique for a flyback converter is implemented using the dSpace CP 1103.
Keywords :
maximum power point trackers; perturbation techniques; photovoltaic power systems; power generation control; predictive control; solar radiation; MPC-MPPT technique; P&O method; PV systems; dSpace CP 1103; electrical energy; fast solar radiation variation; fixed step predictive control; flyback dc-dc converter; maximum power point tracking; model predictive control; perturb and observe method; photovoltaic applications; switching signal; Maximum power point trackers; Photovoltaic systems; Power electronics; Predictive control; Switches; Voltage control;
Conference_Titel :
Power and Energy Conference at Illinois (PECI), 2014
Conference_Location :
Champaign, IL
DOI :
10.1109/PECI.2014.6804540