Driver Training Based Optimized Fractional Order PI-PDF Controller for Frequency Stabilization of Diverse Hybrid Power System

Author:

Zhang Guoqiang1,Daraz Amil12ORCID,Khan Irfan Ahmed3ORCID,Basit Abdul12,Khan Muhammad Irshad4ORCID,Ullah Mirzat5ORCID

Affiliation:

1. School of Information Science and Engineering, NingboTech University, Ningbo 315100, China

2. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China

3. Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya, Federal Territory of Kuala Lumpur 50603, Malaysia

4. College of Electronics and Information Engineering, Nanjing University of Aeronautics and Astronautics (NUAA), Nanjing 210000, China

5. Graduate School of Economics and Management, Ural Federal University, Yekaterinburg 620002, Russia

Abstract

This work provides an enhanced novel cascaded controller-based frequency stabilization of a two-region interconnected power system incorporating electric vehicles. The proposed controller combines a cascade structure comprising a fractional-order proportional integrator and a proportional derivative with a filter term to handle the frequency regulation challenges of a hybrid power system integrated with renewable energy sources. Driver training-based optimization, an advanced stochastic meta-heuristic method based on human learning, is employed to optimize the gains of the proposed cascaded controller. The performance of the proposed novel controller was compared to that of other control methods. In addition, the results of driver training-based optimization are compared to those of other recent meta-heuristic algorithms, such as the imperialist competitive algorithm and jellyfish swarm optimization. The suggested controller and design technique have been evaluated and validated under a variety of loading circumstances and scenarios, as well as their resistance to power system parameter uncertainties. The results indicate the new controller’s steady operation and frequency regulation capability with an optimal controller coefficient and without the prerequisite for a complex layout procedure.

Funder

Young Talent Sub-project of Ningbo Yongjiang Talent Introduction Programme

Publisher

MDPI AG

Subject

Statistics and Probability,Statistical and Nonlinear Physics,Analysis

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