  Extracting maximum power available from photovoltaic arrays requires the
system operating at the maximum power point (MPP). Therefore, finding the MPP
is necessary for efficient operation of PV arrays. The MPP changes with
multiple environmental factors, mainly temperature and irradiance.
Traditionally, the incremental conductance technique with fixed step size was
used to find the MPP, which suffers from a trade-off between speed of
convergence and accuracy. In this work, we propose an incremental conductance
maximum power point tracking (MPPT) algorithm with a variable step size, which
adaptively changes the step size after each iteration based on how far away the
current operating point is from a new MPP. This mitigates the aforementioned
trade-off drastically by achieving faster convergence speed without the loss of
accuracy. A series of simulations involving variations in temperature and
irradiance were performed using MATLAB, and the speed of convergence and
accuracy were compared with the traditional IC technique.
