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Transformer Less Grid Integrated Single Phase PV Inverter Using Prognosticative Control

Chandla Ellis1,*, C. Chellamuthu1, J. Jayaseelan2

1 Department of Electrical and Electronics Engineering, R.M.K Engineering College, Chennai, 601206, Tamil Nadu, India
2 Department of Mechanical Engineering, Dr. M G R Educational and Research Institute, Chennai, 601206, Tamil Nadu, India

* Corresponding Author: Chandla Ellis. Email:

Intelligent Automation & Soft Computing 2022, 33(2), 1121-1138.


Nature's remarkable and merciful gift to the planet Earth is sunlight which may be highly lucrative if harvested and harnessed properly. Photovoltaic (PV) panels are used to convert the solar energy to electrical energy which are currently used to feed AC loads/grid. In this paper, modelling, performance and power flow studies of grid connected single phase inverter fed from PV array under steady state as well as transient conditions are considered. This paper focuses on the study and development of analytical model of micro-grid integrated single phase five level cascaded H-bridge inverter (MGISPFLCHBPVI) powered by a PV panel. A simple power control strategy for MGISPFLCHBPVI is also considered. The simulations are completely carried out using MATLAB software for power-flow studies. The performance characteristics of the inverter are studied from the analytical model developed. The validation of the analytical model is carried out by comparing the results of simulation in Simulink/Matlab. In order to reduce the time to reach steady state taken by the system, a simple PQ control strategy for insolation is introduced in this paper. The proposed method is evaluated based on performance parameters such as settling time and rising time of the system compared with the results available in the literature.


Cite This Article

C. Ellis, C. Chellamuthu and J. Jayaseelan, "Transformer less grid integrated single phase pv inverter using prognosticative control," Intelligent Automation & Soft Computing, vol. 33, no.2, pp. 1121–1138, 2022.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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