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Neural Processing Letters

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05-04-2022

A Novel Quasi-oppositional Chaotic Harris Hawk’s Optimization Algorithm for Optimal Siting and Sizing of Distributed Generation in Radial Distribution System

Authors: Korra Balu, V. Mukherjee

Published in: Neural Processing Letters | Issue 5/2022

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Abstract

This article proffers a novel quasi-oppositional chaotic Harris hawk’s optimization (HHO) (QOCHHO) algorithm for interpreting global optimization problems. In the proposed QOCHHO algorithm, quasi-opposition based learning (QOBL) and chaotic local search (CLS) approaches are integrated with the basic HHO for better quality of solution and faster convergence. The idea of QOBL assists to explore new regions of the search space and offers superior exploration. Again, CLS guides the search process nearby the most favorable regions of the search space yielding superior exploitation. Thus, a superior balance between the exploration and the exploitation holds in the case of QOCHHO making this newly projected algorithm more robust as correlated to the HHO algorithm. To demonstrate and validate effectiveness of the suggested QOCHHO algorithm, twenty-nine benchmark test functions of various categories, varied complexities (i.e., unimodal, multimodal, fixed dimension and composite functions) and different dimensions (i.e., 30 and 100) are used for simulation experiments. The simulation results attained by the projected QOCHHO algorithm are compared with the results obtained by recently surfaced HHO and other state-of-the-art algorithms (i.e., particle swarm optimization, moth-flame optimization algorithm, grey wolf optimizer, sine cosine algorithm, salp swarm algorithm, whale optimization algorithm and multi verse optimization algorithm). The outcomes of the benchmark test functions evidence that the anticipated QOCHHO algorithm is able to offers better outcomes in terms of improved exploration, local optima circumvention and faster convergence characteristics. The proposed QOCHHO algorithm is further employed to decipher real world engineering optimization problem (i.e., optimal siting and sizing of distributed generation (DG) in IEEE 33-bus and practical Brazil 136-bus radial distribution system (RDS) considering different types of load models at three load levels) and proffers a real application of the suggested algorithm in the field of electrical engineering. The simulation outcomes evidence that the obtained location and size of DGs in the RDS may be feasible one and the suggested QOCHHO algorithm may be a promising optimization algorithm for the chosen engineering optimization application.

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Title: A Novel Quasi-oppositional Chaotic Harris Hawk’s Optimization Algorithm for Optimal Siting and Sizing of Distributed Generation in Radial Distribution System
Authors: Korra Balu
V. Mukherjee
Publication date: 05-04-2022
Publisher: Springer US
Published in: Neural Processing Letters / Issue 5/2022
Print ISSN: 1370-4621
Electronic ISSN: 1573-773X
DOI: https://doi.org/10.1007/s11063-022-10800-1

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