ABSTRACT

Maximum Power Point Tracking (MPPT) is the method of operating the photovoltaic system in
a manner that allows the modules to effectively transfer all the power generated from the
panel to the load.Maximum Power Point (MPP) tracking technique based on Balancing Particle
Swarm Optimization (BPSO) were successfully developed in this paper to solve the problem of
premature convergence and also latency in convergence/tracking. The performance of the
developedBPSO was evaluated at solar irradiance of 1000W/m2, 500W/m2 and 600W/m2 at
constant temperatures of 25oC simultaneously. From the BPSO simulation results, it was
observed that, it took the developed model0.23secs to locate the Global maxima (GP) with a
very high-power output. The developed model achieved this by balancing the panel
conductance with the load conductance and also compare the output power with the global
peak power, if the newly output power is greater than the global peak power the MPP tracker
settles at the newly detected output power but if it is less than that it maintains its previous
MPP position.The developed BPSO algorithm settled at GP of 255.063W at 0.2292secs and at
this point, the source impedance balances with that of the load impedance which results to
negligible change in conductance. From the validation result, the convergence time of the
scanningparticle swarm optimization and BPSO technique at MPP was 0.40secs and 0.23secs
which showed that BPSO has42.7%relative improvementin terms of premature convergence
and tracking speed. The simulation was done using 2020B MATLAB SIMULINK.
Keywords:Balancing, Particle, Swarm, Optimization, Photovoltaic, Premature Convergence,
Conductance, Scanning Particle Swarm Optimization,Global optima, maximum power point
tracker