An Intelligent Based DC Series Electric Springs in DC Micro Grids

Authors

  • P. Naga Lakshmi Research Scholar, Department of Electrical Engineering, Annamalai University, Tamil Nadu, India
  • R. Ashok Kumar Professor, Department of Electrical Engineering, Annamalai University, Tamil Nadu, India
  • K. Hari Krishna Professor, Department of Electrical & Electronics Engineering, Kallam Haranadahreddy Institute of Technology, Guntur, Andhra Pradesh, India

Keywords:

Artificial Neural Network (ANN), DCSES, PI control, DC Micro grid, LMBP

Abstract

The integration of intermittent energy sources into DC grids gains far-flung interest among researchers. However, it introduces issues with power quality like voltage stability and ripples in large power systems using intermittent renewable energy resources (IRES). The research analysis aims to utilise the concept of DC series electric springs (DCSES) to minimise the power delivered by the main grid during a generation shortage of IRES. This investigation briefs the emerging DC-DC converter-based DCSES technology with an artificial neural network (ANN)-based intelligent controller for mitigating issues of voltage regulation, harmonic reduction, and improving the battery's lifetime by reducing the storage capacity. ANN generates pulses for the DC-DC converter using the Levenberg-Marquardt-based back propagation algorithm (LMBP) for network training. The simulation is carried out in Mat lab/Simulink. Performance parameters like voltage regulation, DC harmonics, and voltage ripple are analysed and compared with conventional PI controllers. The results prove that the LMBP-based intelligent controller for DCSES, with its fast and accurate convergence speed, yields better performance compared with conventional PI controllers.

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Published

07.02.2024

How to Cite

Lakshmi, P. N. ., Kumar, R. A. ., & Krishna, K. H. . (2024). An Intelligent Based DC Series Electric Springs in DC Micro Grids. International Journal of Intelligent Systems and Applications in Engineering, 12(15s), 333 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4757

Issue

Vol. 12 No. 15s (2024)

Section

Research Article

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