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.
Highlights
The most recent couple of years have seen enormous development in the utilization of sun powered vitality in the private, business, and modern segments
In this paper the main point of focus are the techniques used for extraction of maximum power from a solar photovoltaic system
The techniques based on fuzzy logic, machine learning, and artificial intelligence seem to be most promising and beneficial in this process since the output of solar photovoltaic is highly dependent on weather conditions which are not predictable over a long period of time[21], [27], [28]
Summary
The most recent couple of years have seen enormous development in the utilization of sun powered vitality in the private, business, and modern segments. Time Series procedures namely AR (Auto-Regressive) and ARX (Auto-Regressive with exogenous information) models are likewise been connected for Solar photovoltaic gauging [8]. Authors form [10], numerous counterfeit neural system (ANN) procedures are assessed for anticipating of sun-powered radiation, for example, multilayer perception (MLP), repetitive neural systems (RNNs) and hereditary calculations, and so forth.
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