A Review of Fuzzy Logic and Artificial Neural Network Technologies Used for MPPT

Abstract

Solar electric power generating stations play a major role in meeting the growing demand for electric power. These generating stations make use of solar photovoltaic (PV) panels to perform the conversion of solar energy to electric energy. However, the solar panel output is highly unpredictable because the output is a function of number of factors; some of which are not in the control of humans like the weather conditions, and the output is also a function of the age of PV panel, dust and other debris collected on the panel, direction and angle of elevation and so on. The solar panels exhibit a low efficiency. Currently, a lot of research is going on to overcome these issues. This paper represents a review of two modern techniques used in solar photovoltaic systems which enhance the extraction of maximum output power in an efficient manner. The Artificial Intelligence Based MPPT Techniques for PV Applications, and, a Forecasting System of Solar PV Power Generation using Wavelet Decomposition and Bias- compensated Random Forest are reviewed and compared in this paper.