Proceedings of the International Conference on Intelligent Systems for a Sustainable Future (ISSF 2026)

Performance Improvement of Transformer less Grid- Connected PV Inverters Using ANN-Assisted Control

Authors
K. Praveena1, *, B. Shravani1, J. Pavithra1, K. Bala Krishna1, S. Afreen1, N. Dinesh Kumar1
1Department of Electrical and Electronics Engineering, Srinivasa Ramanujan Institute of Technology, Anantapur, India
*Corresponding author. Email: 224g1a0268@srit.ac.in
Corresponding Author
K. Praveena
Available Online 16 June 2026.
DOI
10.2991/978-94-6239-693-7_69How to use a DOI?
Abstract

Transformer less grid-connected photovoltaic (PV) inverters are gaining in usage due to their vast efficiency and small size. But, because of variations in common-mode voltage, the absence of galvanic isolation might result in leakage currents, which usually reduce power quality. The conventional proportional-integral (PI) control technique works poorly for nonlinear and time-varying system operation, increasing total harmonic distortion (THD) and decreasing mitigation capabilities. A control technique assisted by artificial neural networks (ANNs) is proposed in this research to address this issue. The conventional inverter control approach is assisted by the ANN, an adaptive auxiliary component, which cannot be replaced but,helps in reduction of THD. An adaptive assist component in transformer less photovoltaic systems, the ANN minimizes THD in the grid current, hence reducing common-mode voltage swings that cause leakage current. To illustrate the suggested method, MATLAB/Simulink is used to simulate a number of system operating circumstances, including start-up, load imbalance, variations in solar radiation, and grid disruptions. In comparison to the conventional PI controller, the simulation results demonstrate that the ANN-assisted controller significantly reduces the grid current’s THD while still meeting IEEE 519 and IEC 61727 requirements. Power quality and system performance are increased in the results, which confirm that the primary method for reducing leakage current is ANN-assisted THD mitigation.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Intelligent Systems for a Sustainable Future (ISSF 2026)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
16 June 2026
ISBN
978-94-6239-693-7
ISSN
2589-4919
DOI
10.2991/978-94-6239-693-7_69How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - K. Praveena
AU  - B. Shravani
AU  - J. Pavithra
AU  - K. Bala Krishna
AU  - S. Afreen
AU  - N. Dinesh Kumar
PY  - 2026
DA  - 2026/06/16
TI  - Performance Improvement of Transformer less Grid- Connected PV Inverters Using ANN-Assisted Control
BT  - Proceedings of the International Conference on Intelligent Systems for a Sustainable Future (ISSF 2026)
PB  - Atlantis Press
SP  - 699
EP  - 708
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6239-693-7_69
DO  - 10.2991/978-94-6239-693-7_69
ID  - Praveena2026
ER  -