A metaheuristic algorithm for regulating virtual inertia of a standalone microgrid incorporating electric vehicles

Author:

Mishra Debayani1,Maharana Manoj Kumar2,Kar Manoj Kumar3,Nayak Anurekha4,Islam Md. Minarul5,Ustun Taha Selim6ORCID

Affiliation:

1. Department of Electrical Engineering Ajay Binay Institute of Technology Cuttack Odisha India

2. School of Electrincal Engineering KIIT Deemed to be University Bhubaneswar Odisha India

3. Department of Electrical Engineering Tolani Maritime Institute Talegaon Maharashtra India

4. Department of Electrical Engineering DRIEMS Autonomous Engineering College Cuttack Orissa India

5. Department of Electrical and Electronic Engineering University of Dhaka Dhaka Bangladesh

6. Fukushima Renewable Energy Institute, AIST (FREA) National Institute of Advanced Industrial Science and Technology (AIST), Fukushima Koriyama Japan

Abstract

AbstractModern electrical networks, particularly microgrids, have seen a sharp rise in acquiring non‐conventional sources. The inertia of the microgrid decreases drastically because RESs have been used in place of traditional synchronous generators. The reduced inertia negatively impacts the dynamics and performance of the microgrid with RESs, which decreases the microgrid's stability, especially in operation on an island. The primary purpose of this research study is to enhance the dynamic security of an island microgrid by merging an electric vehicle with a frequency control technique based on virtual inertia control. A Proportional Integral Derivative Filter Constant (PIDFN) controller optimally created using the Modified Differential Evolution (MDE) method served as the foundation for control in the virtual inertia control loop. The effectiveness of the MDE‐based PIDFN controller was examined considering the diverse operational scenarios are compared and contrasted with those of traditional methods Differential Evolution (DE) and Teaching Learning Based Optimization (TLBO)‐based PIDFN controllers. Real‐time wind and solar power statistics and random load fluctuations were incorporated to provide realistic simulation settings. The outcomes demonstrate that the MDE‐based PIDFN controller performs better in reference frequency tracking and reducing frequency disturbances than the other optimization strategies.

Publisher

Institution of Engineering and Technology (IET)

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