Vol.33, No.1, 2022, pp.651-667, doi:10.32604/iasc.2022.023890
Integrated Renewable Smart Grid System Using Fuzzy Based Intelligent Controller
  • V. Vijayal1,*, K. Krishnamoorthi2
1 Department of EEE, RMK College of Engineering and Technology, Chennai, 601206, India
2 Department of EEE, Sona College of Technology, Salem, 636302, India
* Corresponding Author: V. Vijayal. Email:
Received 25 August 2021; Accepted 02 November 2021; Issue published 05 January 2022
In high power medium voltage applications, the utilization of 5-H Bridge Multi-Level Inverter (MLI) has grown vastly in recent years. The 5-H Bridge MLI can effectively control link voltage as well as power factor. However, the inverter imparts harmonics owing to the high switching frequency. Hence Inductance Capacitance Inductance (LCL) filter is implemented at its output to mitigate harmonics in presence of non-linear load. It’s of highly important to choose LCL parameters wisely in order to attain good filtering effect. This work investigates the application of 5-H Bridge MLI with LCL filter at the output for efficient integration of renewable energy sources on to the grid. A modified fuzzy heuristic approach is used to solve LCL power filter optimization problem at output of 5-H Bridge Multi-Level Inverter. Subject to the constraint’s harmonic distortion and losses of the inverter, multi objective optimization problem is solved to obtain LCL filter optimal values. The optimized LCL filter design was applied to a grid connected cascaded H-bridge MLI of rating 4.5 MW, 11 kV. MATLAB-Simulink is utilized for modelling and simulating the system. The results showed that the system is more efficient and generic. dSPACE Hardware in Loop (HIL) test system was used to verify the efficacy of the prototype system.
5-H bridge MLI; LCL filter; renewable energy; power quality; fuzzy heuristic algorithm; genetic algorithm
Cite This Article
V. Vijayal and K. Krishnamoorthi, "Integrated renewable smart grid system using fuzzy based intelligent controller," Intelligent Automation & Soft Computing, vol. 33, no.1, pp. 651–667, 2022.
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