Abstract:
The availability of solar energy varies widely
with ambient temperature, different atmospheric and
partially shaded conditions. The generated photovoltaic
(PV) voltage of each module becomes unequal. Under
partially shaded conditions, when the PV module
characteristics get more complex with multiple peaks of
output power, in such systems, analyzing the performance of
maximum power points tracking (MPPT) schemes for
independent control of each of the PV modules becomes
essential. In this system, the experimental implementation
and the MATLAB / SIMULINK based simulations are
compared with fuzzy logic control (FLC) and adaptive neurofuzzy
inference system (ANFIS) MPPT algorithms in terms of
parameters like global peak, tracking speed, power
extraction, and harmonic analysis under various partial
shading conditions. In this topology, each cascaded Hbridge
inverter (CHBMLI) unit is connected to an individual
PV module through an interleaved soft switching boost
inverter (ISSBC). This topology permits independent control
of each PV module to operate at the maximum power point. It
also offers another advantage such as lower ripple current
and switching loss compared to the conventional boost
inverter. The performance of the selective harmonic
elimination (SHE) PWM, with a trained ANN sub system for
a single phase CHBMLI to generate balanced output voltage
even under partially shadowed condition of PV modules is
analyzed. The results are evaluated by simulation and
experimental implemented on a 300W PV panel prototype
with the microcontroller platform. The simulation and
hardware results show that ANFIS algorithm is more
efficient than the FLC algorithm.
