الفهرس 
Maximum power point tracking techniquesOnly 14 pages are availabe for public view
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Abstract
This thesis presents a dynamic model for a standalone PV system. The proposed model of
the PV system is a fractional-order model. The system identification technique is applied to
develop the model. Experimentally, real data is gathered, and the real data is provided for
system identification in MATLAB software. The least squares technique is used in the
identification process to minimize the error between the model output and the real data. The
model parameters are identified depending on the Levenberg–Marquardt algorithm. The
quality of the driven model is estimated based on the Euclidean norm of the model output error.
Matignon’s stability theorem is applied to check the stability of the driven model. The time and
frequency responses of the model transfer function are investigated. The driven fractional order
model is compared with an integer order model that is driven in MATLAB with the same
measured data. The validation of the driven fractional order model is checked by using a data
set that has not been used before.
A fractional order PID controller (FOPID) is set up to track the maximum power from the
PV system. The parameters of the FOPID controller are optimized by the equilibrium optimizer
algorithm in MATLAB software. In the simulation environment, The FOPID controller is
compared with classical algorithms, such as the perturb and observe (P&O) algorithm and the
incremental conductance algorithms. MATLAB support package for Arduino hardware is used
for making connections between the Arduino Mega 2560 microcontroller and
MATLAB/Simulink. Experimentally, the FOPID controller for tracking the maximum power
is implemented on Arduino Mega 2560 microcontroller. A comparison between the FOPID
controller and the P&O algorithm has been carried out by Arduino Mega 2560.