Maximum Power Point Tracking Algorithm Implementation for a Photovoltaic Panel Using Model Predictive Control

Author(s):  
Erik Fernando Mendez Garces ◽  
Gabriela Mafla Medina ◽  
Francisco Javier Reyes Almeida
Author(s):  
A. O. Onol ◽  
U. Sancar ◽  
A. Onat ◽  
S. Yesilyurt

In this paper, a model predictive control (MPC) approach is presented to maximize the energy generated by a small vertical axis wind turbine (VAWT) subject to current and voltage constraints of electrical and power electronic components. Our method manipulates a load coefficient and optimizes the control trajectory over a prediction horizon such that a cost function that measures the deviation from the maximum available energy and the violation of current and voltage constraints is minimized. Simplified models for the VAWT and a permanent magnet generator have been used. A number of simulations have been carried out to demonstrate the performance of the proposed method at step and oscillatory wind conditions. Furthermore, impacts of the constraints on energy generation have been investigated. Moreover, the performance of the MPC has been compared with a typical maximum power point tracking algorithm in order to show that maximizing the instantaneous power does not mean maximizing the energy; and simulation results have shown that the MPC outperforms the maximum power point tracking algorithm in terms of generated energy by allowing deviations from the maximum power instantaneously for future gains in energy generation.


Author(s):  
Gilberto Lopes Filho ◽  
Ricardo Augusto Pereira Franco ◽  
Flávio Henrique Teles Vieira

Abstract In this work, a new maximum power point tracking algorithm (MPPT) for photovoltaic systems is proposed. The considered system is composed of a photovoltaic panel charging a battery using a buck-type DC–DC converter. Computational simulations are carried out to compare the performances of the MPPT algorithms, therein analyzing the output voltage and output power behavior at the photovoltaic panel. Three evaluation scenarios are considered: with constant irradiance and temperature, randomly chosen conditions and using real data. The results of the simulations show that the proposed algorithm applied to the photovoltaic system achieves a better performance than the main MPPT algorithms in the literature.


Author(s):  
I. A. Elzein ◽  
Yu. N. Petrenko

The solar energy is directly converted into electrical energy by solar PV module. Each type of PV module has its own specific characteristic corresponding to the surrounding condition such as irradiation, and temperature and this makes the tracking of maximum power point (MPP) a complicated problem. To overcome this problem, many maximum power point tracking (MPPT) control algorithms have been presented. Fuzzy logic (FL) has been used for tracking the MPP of PV modules because it has the advantages of being robust, relatively simple to design and does not require the knowledge of an exact model where a mathematical model of the PV module, DC-DC converter, are used in the study of FL based MPPT algorithm. It is suggested to present this problem in the form of two-folds; first to identify the deviation of the power to maximum power point, and secondly, to control the voltage of the DC-DC converter corresponding to maximum power. In this paper, the first discussion approach will stress out the integration of model predictive control in maximum power point tracking MPPT and as progressing a second approach is identified as fuzzy logic controller FLC and perturb & Observe P&O algorithms are analyzed. All are interrelated to MPPT model for a photovoltaic module, PVM, to search for and generate the maximum power; in this case what’s called P-max. As per the first technique the focus is on the optimal duty ratio, D, for a series of multi diverse types of converters and load matching. The design of the MPPT for a stand-alone photovoltaic power generation system is applied where the system will consist of a solar array with nonlinear time varying characteristics, and a converter with appropriate filters. The integration of model predictive control will be addressed first in this paper. The second fold will implement an MPPT system that use the FLC and compare it with a classical MPPT P&O algorithm through the utilization of Simulink. The novel design in the FLC will be based on the use of asymmetrical membership functions to compensate for the asymmetrical P-V curve of solar panel.


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