A review of application of artificial intelligence for space vector pulse width modulated inverter-based grid interfaced photovoltaic system

Naseem Jaidi, Gitanjali Mehta


Artificial intelligence (AI) is being proposed for a range of subfields that deal with photovoltaic (PV) systems as a result of improvements in computer power, tool accessibility, and data generation. The methods employed at present in the PV industry for a variety of tasks, including the outcomes of design, forecasting, control, and maintenance, have been found to be relatively inaccurate. Additionally, the use of AI to carry out these tasks has improved in terms of accuracy and precision, which has made the topic itself highly interesting. In light of this, the goal of this article is to examine the effect AI approaches have on the solar value chain. The article involves creating a map of all currently accessible AI technologies, identifying potential future uses for AI, and weighing the advantages and disadvantages of these technologies’ relative to more conventional approaches. This article lays special emphasis on discussing AI techniques for improving the power quality in grid systems involving space vector pulse width modulated inverters interfacing the photovoltaic to the grid along with power converter defect monitoring, filter flaw detection, and battery monitoring.


artificial intelligence; battery monitoring; photovoltaic system; power quality; space vector pulse width; modulation

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DOI: http://doi.org/10.11591/ijape.v12.i2.pp218-228


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International Journal of Applied Power Engineering (IJAPE)
p-ISSN 2252-8792, e-ISSN 2722-2624

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