Photovoltaic systems (PVs)offer an environmentally friendlysource of electricity;
however, up till now its price is still relatively high.Achieving the maximum power of
these systemsand maintaining it with lowest price in real applications is highl
y associated
with Maximum Power Point Tracking (MPPT) under different operation conditions.
This paper proposes the use of Genetic Algorithm (GA) for tracking maximum
power point depending on the solar cell model. GA gives, directly and precisely, the
optimal operating voltage (VOP) of the cell where the DC/DC converter will be adjusted
according to it based on the previous knowledge of the open circuit voltage (VOC) and
short circuit current (ISC) of the cell.
To validate the correctness and effectiveness of the proposed algorithm, MATLAB
R2010a programs for GA and PV system are written and incorporated together where the
series resistant of the cell is considered while the shunt resistant is neglected.
Simulation results of applying GA on different types of solar panels showedthe
possibilityof the accurateadjusting of the voltagetothe optimum valueand thusoperating the
systemat maximum power point.
This paper shows how to design and implement control circuit in the movement of
pv board to reach to maximal possible output, by designing a system to integrate several
methods of of control with each other. During this work, we will design through
formation
a unified system combine control by light sensors, and control via data base on the other
hand. In addition to compare pv angle in both ways. The proposed circuit designed,
conduct a simulation, and implementation a miniature model simulates reality, and
discussed the result to to conflict the advantage and the goal of using the proposed system.
All that by using micro controller (PIC).
Search is based on the first stage DC/DC in the solar photovoltaic system, where it
was appropriate to use Ripple Correlation Control method for tracking the maximum
power point of photovoltaic arrays. The technique takes advantage of the signal ri
pple,
which is automatically present in power converters, where the ripple is interpreted as a
perturbation from which a gradient ascent optimization can be realized. The Basic feature
of Ripple Correlation Control technique converges asymptotically at maximum speed to
the maximum power point, and has simple circuit implementations. And will validate the
results in practice.
