Adaptive Step Size Incremental Conductance Based Maximum Power Point Tracking (MPPT)

TL;DR

This paper introduces an adaptive step size incremental conductance MPPT algorithm that dynamically adjusts its step size to improve convergence speed and accuracy in photovoltaic systems under changing environmental conditions.

Contribution

The paper presents a novel variable step size incremental conductance algorithm that enhances MPPT efficiency by balancing convergence speed and accuracy adaptively.

Findings

Faster convergence compared to fixed step size methods

Maintains high accuracy in tracking MPP

Effective under varying temperature and irradiance conditions

Abstract

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.