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Abstract

The static synchronous compensator (STATCOM) is the multipurpose FACTS device with the multiple input and multiple output system for the enhancement of its dynamic performance in power system. Based on artificial intelligence (AI) optimization technique, a novel controller is proposed for CSC based STATCOM. In this paper, the CSC based STATCOM is controlled by the LQR. But the best constant values for LQR controller's parameters are obtained laboriously through trial and error method, although time consuming. So the goal of this paper is to investigate the ability of AI techniques such as genetic algorithm (GA) and particle swarm optimization (PSO) methods to search the best values of LQR controller's parameters in a very short time with the desired criterion for the test system. Performances of the GA, PSO & ABC based LQR controllers are also compared. Applicability of the proposed scheme is demonstrated through simulation in MATLAB and the simulation results are shown an improvement in the input-output response of CSC-STATCOM.
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Authors and Affiliations

Sandeep Gupta
Vipin Kumar Tripathi
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Abstract

The hybridization of a recently suggested Harris hawk’s optimizer (HHO) with the traditional particle swarm optimization (PSO) has been proposed in this paper. The velocity function update in each iteration of the PSO technique has been adopted to avoid being trapped into local search space with HHO. The performance of the proposed Integrated HHO-PSO (IHHOPSO) is evaluated using 23 benchmark functions and compared with the novel algorithms and hybrid versions of the neighbouring standard algorithms. Statistical analysis with the proposed algorithm is presented, and the effectiveness is shown in the comparison of grey wolf optimization (GWO), Harris hawks optimizer (HHO), barnacles matting optimization (BMO) and hybrid GWO-PSO algorithms. The comparison in convergence characters with the considered set of optimization methods also presented along with the boxplot. The proposed algorithm is further validated via an emerging engineering case study of controller parameter tuning of power system stability enhancement problem. The considered case study tunes the parameters of STATCOM and power system stabilizers (PSS) connected in a sample power network with the proposed IHHOPSO algorithm. A multi-objective function has been considered and different operating conditions has been investigated in this papers which recommends proposed algorithm in an effective damping of power network oscillations.
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Authors and Affiliations

Ramesh Devarapalli
1
ORCID: ORCID
Vikash Kumar
1

  1. Department of Electrical Engineering, B.I.T. Sindri, Dhanbad, Jharkhand, India

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