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Register a new userMaximum power point tracking system design with Buck-Boost converter
تصميم نظام تتبع استطاعة أعظمية مع محول رافع - خافض للجهد
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محول الطاقة DC-DC converter هو أحد أهم العناصر الأساسية المعتمدة من أجل الاستخدام الفعال لمصادر الطاقات المتجددة, الهدف الرئيسي لهذه المقالة هو استخدام نظام لتتبع نقطة الاستطاعة الأعظمية Maximum power point tracking system (MPPT مع محول رافع- خافض للجهد Buck-Boost converter للحصول على أقصى طاقة ممكنة لنظام كهروشمسي photovoltaic (PV) system وفق تغير شروط شدة الإشعاع و درجة الحرارة المحيطة و الحمل.
DC-DC converter is one of the most essential component for efficient utilization in renewable energy sources. The main goal of this paper is to use Maximum power point tracking (MPPT) system and buck-boost DC/DC converter in the photovoltaic (PV) system to maximize the (PV) output power, irrespective of the temperature and irradiation conditions.
References used
MASTERS,G 2014 - Renewable and Efficient Electric Power Systems. A JOHN WILEY & SONS, PUBLICATION, New Jersey, 676 P
TOMABECHI, K , 2010 - Energy Resources in the Future, Energies,Vol.3, pp.686-695
WEISSBACH,R , TORRES,K , 2001- A Non-inverting Buck- Boost Converter with Reduced Components Using a Microcontroller. Proceedings of the Southeast Conference, South Carolina, pp.79-84
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This research deals with improving the efficiency of solar photovoltaic (PV) power
systems using a Maximum Power Point Tracker controller (MPPT controller), based in his
work on the Maximum Power Point Tracking techniques via the direct control met
hod.
Which used to control the duty cycle of DC-DC Voltage Converter, to achieve the
photovoltaic system works at a Maximum Power Point under different atmospheric
changes of the solar insolation and ambient temperature. In this context, our work is
focused on the simulation of the components of the power generating system, such as the
photovoltaic system, DC-DC Boost Converter and a MPPT controller in Matlab/Simulink
environment. The simulating of the MPPT controller was based on several algorithms such
as: Constant Voltage algorithm, Perturb and Observe algorithm and Incremental
Conductance algorithm by using Embedded MATLAB function. The simulation results
showed the effectiveness of the MPPT controller to increase the photovoltaic system power
compared with non-use of a MPPT controller. The results also showed the best
performance of MPPT controller based on Perturb and Observe and Incremental
Conductance algorithm, compared with constant voltage algorithm in tracking the
Maximum Power Point under atmospheric changes.
This paper offer a designed module for buck-boost DC-DC converter, able to solve
unsteady charging voltage problem, due to constant decreasing scale of transformers and
grid or solar panel voltage drop, this module has been designed using fuzzy log
ic in PWM
control and simulated in matlab and all test and its results illustrated the suitable figure.
This research is a study of a new control method of switching non-isolated
dc-dc boost converters used in Photovoltaic systems. This method is called
Sliding Mode Control (SMC), which is considered as an alternative to other
methods, to keep a sta
ble and constant output voltage by changing the input
voltage and load current. The analyzing method of the switching nonisolated
dc-dc boost converters using SMC shows the same complexity of
Clasic circuits, but it gives an increasing potential and a high-dynamic
response to ensure a constant output voltage reaches to 40volt by changing
the input voltage in the range (16-21volt) and the load (8-13Ω). Methods to
measure the accuracy, error, and efficiency of maximum power point
trackers (MPPT) have been identified and presented in a schematic way,
together with definitions of terms and calculations.
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
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.
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