This research deals with the modeling of a Multi-Layers Feed Forward Artificial Neural
Networks (MLFFNN), trained using Gradient Descent algorithm with Momentum factor &
adaptive learning rate, to estimate the output of the neural network correspon
ding to the
optimal Duty Cycle of DC-DC Boost Converter to track the Maximum Power Point of
Photovoltaic Energy Systems. Thus, the DMPPT-ANN “Developed MPPT-ANN”
controller proposed in this research, independent in his work on the use of electrical
measurements output of PV system to determine the duty cycle, and without the need to
use a Proportional-Integrative Controller to control the cycle of the work of the of DC-DC
Boost Converter, and this improves the dynamic performance of the proposed controller to
determine the optimal Duty Cycle accurately and quickly. In this context, this research
discusses the optimal selection of the proposed MLFFNN structure in the research in terms
of determining the optimum number of hidden layers and the optimal number of neurons in
them, evaluating the values of the Mean square error and the resulting Correlation
Coefficient after each training of the neural network. The final network model with the
optimal structure is then adopted to form the DMPPT-ANN Controller to track the MPP
point of the PV system. The simulation results performed in the Matlab / Simulink
environment demonstrated the best performance of the proposed DMPPT-ANN controller
based on the MLFFNN neural network model, by accurately estimating the Duty Cycle and
improving the response speed of the PV system output to MPP access, , as well as finally
eliminating the resulting oscillations in the steady state of the Power response curve of PV
system compared with the use of a number of reference controls: an advanced tracking
controller MPPT-ANN-PI based on ANN network to estimate MPP point voltage with
conventional PI controller, a MPPT-FLC and a conventional MPPT-INC uses the
Incremental Conductance technique INC
In the following study we make a simulation of an independent
photovoltaic system connected to an (ohm
- unit of electrical resistance) load which consists of the following
parts:
(Photovoltaic Module - Converter dc- dc - Control system to
track
ing the maximum power point via MATLAB & Simulink
program)
Taking advantage of equations of Photovoltaic Module we chart
the graph and simulate curves of the Module.
We also simulate the converter –type Cuk- which gives higher or
lower voltage than input voltage but with reversed polarity.
We also make a comparison between the two systems tracking:
the first tracker is a traditional one and the second one is a system
in which it uses a fuzzy logic tracker.
The results of the comparison shows different capacities taking into
consideration the varieties of weather conditions of regular solar
radiation as well as the partial shadow.
Such results showed that fuzzy logic has got more capability to
harmonize with all conditions especially in cases of low solar
radiation and partial shadow.
The limitations of global resources of fossil and nuclear fuel, has necessitated
an urgent search for alternative sources of energy. Therefore, a new way has to be
found to balance the supply and demand without resorting to coal and gas fuelled
ge
nerators.Environment safety has become very important for any energy system,
Increasing demand of conventional sources has further increases the need and
optimizes cost of non-conventional energy sources.
This paper has analyzed the development of a method for the mathematical
modeling of PV System.behavior of the PV Array with series resistance model are
studied in this paper. Included effects are: temperature dependence, solar radiation
change, diode ideality factor and series resistance influence,and shows the
mathematical modeling of stand-alone PV system and then compare withAnalysis
of Perturb and Observe MPPT and without MPPT simulation of photovoltaic
modules with Matlab/Simulink, And Calculate the increase in efficiency resulting
from the use of technology MPPT.
This paper deals with the analysis and study of performance of solar panels, so we
choose working on the solar panel (module) MSX-50, in addition to improve his power by
tracking the maximum power point, this is done by using boost (step up) choppe
r to obtain
the largest possible capacity of solar panel.
We will determine a mathematical model equivalent to the real solar panel (not ideal)
through studying photovoltaic cells, where we will use the iterative method in addition to
the Newton-Raphson algorithm in order to determine the value serial resistance of module
Rs parallel resistance of module Rp.
As has been the implementation of perturbation and observation p&o algorithm in
addition studying and designing the circuit of step up (boost) chopper, and selection the
components (coil L, capacitor C), based on both the operation frequency f, ripple factor of
output voltage and output current .
Based on the our study, we have performed a modeling process of the solar module
MSX-50 using MATLAB/SIMULINK program, where we designed a graphical user
interface GUI to display the module characteristics and calculate resistance Rp and Rs, in
addition to build an algorithm p&o and design circuit of boost (step up) chopper.
The proposed model has been applied to the ohmic load according to the principle of
the maximum power point tracking MPPT, and discuss the results of two cases wich are
the following the solar module is connected directly to load, connected through chopper
driven by p&o algorithm.
With the increase in reliance on solar energy to produce electricity, so many maximum power point
tracking techniques for photovoltaic panels were developed to maximize the produced energy and a lot of
these are well established in the literature.
These techniques vary in many aspects such as: simplicity,
convergence speed, digital or analogical implementation, required sensors, cost, range of effectiveness, as
well as in other aspects.
This paper presents a comparative study of ten widely-adopted mppt algorithms; their performance is
evaluated from energy point of view using the simulation tool (Matlab), considering different solar
irradiance variations. Also, an economic evaluation has been made to make a comparison according to
performance and cost, to determine the optimal choice.
Fuzzy logic control is used to connect a photovoltaic system to the electrical grid by using three phase fully
controlled converter (inverter), This controller is going to track the maximum power point and inject the
maximum available power from th
e PV system to the grid by determining the trigger angle that must be
applied on the switches: Linguistic variables are going to be chosen to determine the amount of change in
the trigger angle of the inverter to track the maximum power.
