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PIC16LF877A-I/ML 其他数据使用手册 - Microchip（微芯）
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PIC16 系列 368 B RAM 14 kB 闪存 8 位 增强型 微控制器 - QFN-44
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International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 13 (2017) pp. 3622-3630
© Research India Publications. http://www.ripublication.com
3622
Low-Cost Implementation of P&O MPPT based on Microntroller
PIC16F877A
Mhamed Rebhi*, Ali Benatiallah** and Mebrouk Sellam***
*Laboratory of SmartGrids & Renewable Energies, Bechar university, Algeria.
**Laboratory of Energies , Information’s System , Adrar University, Algeria.
***Laboratory of ENERGARID, Bechar University, Algeria.
*Corresponding author
*ORCID: 0000-0003-4652-9498
Abstract
The photovoltaic module has a nonlinear current-voltage
characteristic curve presenting an operating point called a
maximum power point (MPP) depending on the variation of
weather conditions. Boost converter with MPPT controller
based on Perturbation & Observation algorithm is proposed.
This work studies an experimental prototype and its
performances on decreasing the oscillation around the MPP
and a low-cost implementation based on the microcontroller
PIC16F877A.
Keywords: Photovoltaic, MPPT, Boost, Observation &
Perturbation.
INTRODUCTION
Since the world economic crisis in seventies of the 20
th
century, the renewable energies have been taking an important
situation in scientific research to substitute the fossil energy.
Photovoltaic energy is one of these alternative sources, that
has gained a lot of attention in recent years because it is
environmentally friendly and sustainable compared to
traditional energy sources. Good examples include large-scale
grid-connected wind turbines, solar water heating, and off-
grid stand-alone PV systems [1].The photovoltaic panels may
seem like a good source of electricity that converting the
sunlight via a number of solar cells connected in series and
parallels to obtain the desired current and voltage levels,
however their efficiency is still low (12 -40%) and their
current-voltage curve characteristic is nonlinear presenting an
operating point called maximum power point (MPP)
depending on the variation of weather conditions such as
irradiation and temperature [2]. To make PV panel providing
a maximum power to load profile at all times, a power
electronic DC-DC converter has to be located between them
switched periodically with a maximum power point tracking
(MPPT) controller.
Many different techniques or algorithms implemented in
MPPT controller to maximize PV power to various loads have
been developed [3] the Perturb & observe algorithm is widely
used because of its simple structure and ease of
implementation, nevertheless it provides some drawbacks
such as oscillation around MPP, slow response speed and
even tracking wrong direction under rapidly atmospheric
conditions [ 4 ]
The incremental conductance MPPT is another approach to
overcome the previous shortcomings whereas it is more
complex in implementation than the P&O MPPT and it
requires a fast computation for the incremental conductance
dI/dV, if the speed of computation is slow under the rapidly
changing weather condition the approximation of dI/dV is not
valid [5]
The fuzzy logic MPPT is an intelligent method robust and
simple widely used in literature, this technique does not
require the knowledge of the exact model of system, on the
other hand, the designer needs complete knowledge of the PV
system operation .It based on the error (dP/dV ) and the
change in error (∆( dP/dV))at sampled times k [6]
Recently, the Artificial Neural Network (ANN) has attracted
widespread interest in tracking of the MPP, it is a good
solution giving the best efficiency and response time in steady
state, and under irradiation variations [ 7]
Other approaches are less effectiveness for tracking the
maximum power point such as constant controlled voltage,
short-current method, open voltage technique, temperature
method [8].
This paper aims at investigating and analyzing experimentally
the performances such as to decrease the oscillation around
the MPP and a low-cost implementation based on the
microcontroller PIC16F877A under the climate conditions in
the south- west of Algeria.
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