An Effective Hybridized GWO-BSA for Resolving Optimal Power Flow Problem with the Inclusion of Unified Power Flow Controller

Priya, J. Lakshmi; Christa, S.T. Jaya

doi:10.1080/03772063.2021.1942245

Cited by 14 publications

(7 citation statements)

References 41 publications

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“…In this section, the proposed ImBSA is compared with some recently proposed variants of BSA, namely GWO-BSA [ 45 ], e-SOSBSA [ 46 ], BS-DE [ 47 ], LFBSA [ 11 ], IBS [ 10 ], and hDEBSA [ 48 ]. For this comparison, the CEC 2017 test functions with ten dimensions have been considered.…”

Section: Performance Results Analysis Of Cec 2014 and Cec 2017 Test Functionsmentioning

confidence: 99%

A Bio-Inspired Multi-Population-Based Adaptive Backtracking Search Algorithm

Nama

Saha

2022

Cogn Comput

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Backtracking search algorithm (BSA) is a nature-based optimization technique extensively used to solve various real-world global optimization problems for the past few years. The present work aims to introduce an improved BSA (ImBSA) based on a multi-population approach and modified control parameter settings to apprehend an ensemble of various mutation strategies. In the proposed ImBSA, a new mutation strategy is suggested to enhance the algorithm’s performance. Also, for all mutation strategies, the control parameters are updated adaptively during the algorithm’s execution. Extensive experiments have been performed on CEC2014 and CEC2017 single-objective benchmark functions, and the results are compared with several state-of-the-art algorithms, improved BSA variants, efficient differential evolution (DE) variants, particle swarm optimization (PSO) variants, and some other hybrid variants. The nonparametric Friedman rank test has been conducted to examine the efficiency of the proposed algorithm statistically. Moreover, six real-world engineering design problems have been solved to examine the problem-solving ability of ImBSA. The experimental results, statistical analysis, convergence graphs, complexity analysis, and the results of real-world applications confirm the superior performance of the suggested ImBSA.

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Section: Performance Results Analysis Of Cec 2014 and Cec 2017 Test Functionsmentioning

confidence: 99%

A Bio-Inspired Multi-Population-Based Adaptive Backtracking Search Algorithm

Nama

Saha

2022

Cogn Comput

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“…Hybrid GWO-BSA algorithm is applied in [37]. In the proposed MOOPF problem, the pareto dominance notion has been employed to find out the non-dominated solutions.…”

Section: Mogwo-bsamentioning

confidence: 99%

Application of Hybrid GWO-BSA Technique for Resolving Multi-Objective Optimal Power Flow Problem by Incorporating Unified Power Flow Controller

S.T

2024

Preprint

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The optimal power flow (OPF) is an illustrious and a substantial approach for the reliable and cost-effective working of a power system. It is a multifaceted nonlinear problem that evaluates the ideal settings of generator capacity, bus voltage, and transformer tap setting. In this study, the objectives such as minimization of fuel cost, minimization of power losses, reduction of voltage variation and augmentation of voltage stability have been solved by considering six double objective scenarios and four triple objective scenarios. The above mentioned objectives have been solved by using hybridized Grey Wolf Optimization and Backtracking Search optimization Algorithm (GWO-BSA) and by incorporating Unified Power Flow Controller (UPFC). In the multi-objective OPF problem, the Optimum Compromise Solution (OCS) is estimated by means of fuzzy set theory. For demonstrating the enactment of the hybrid GWO-BSA, simulations are performed using MATLAB on standard IEEE 30-bus and 57-bus test systems. Moreover, the comparisons have been made between the hybrid GWO-BSA and other recognized algorithms for showing the greater efficacy and robustness of the GWO-BSA against others. The comparisons divulge that the GWO-BSA offers optimal, viable, global outcomes to the OPF problems with good convergence rate.

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“…An increase in the impedance of a circuit produces a higher voltage drop between its ends and higher losses, so Kirchoff's voltage law for entangled networks in OPF must be modified by (23) and (24).…”

Section: 2 Opf With Tcscmentioning

confidence: 99%

“…There are multiple research articles [22][23][24][25] that implement FACTS controllers as part of the NR load flow algorithm; however, this implementation increases the complexity of the programming code due to some reasons that we can mention [6,15]. As a first reason, the incorporation of the FACTS controller requires the definition of new transmission lines and/or reference buses.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of FACTS Contributions Using Branch Flow Model and Newton–Raphson Algorithm

Corpus,

Leite

2024

Energies

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Flexible alternating current transmission systems (FACTSs) have been widely incorporated in electric power systems in order to control system parameters. This paper proposes the modeling of four FACTS devices, using the Branch Flow Model (BF) as an optimization problem to reduce the complexity of the Newton–Raphson (NR) load flow code with FACTS devices. The devices are represented as variable impedances, as a function of a firing angle, and as voltage source converters (VSCs) located on the buses and transmission lines. This proposed model solves the problem associated with the selection of appropriate initial conditions of the parameters of each device that guarantee convergence. The model is validated by evaluating its percentage deviation with respect to the NR method, using the standard test systems, IEEE 5-bus, IEEE 14-bus, IEEE 30-bus, and IEEE 57-bus systems.

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An Effective Hybridized GWO-BSA for Resolving Optimal Power Flow Problem with the Inclusion of Unified Power Flow Controller

Cited by 14 publications

References 41 publications

A Bio-Inspired Multi-Population-Based Adaptive Backtracking Search Algorithm

A Bio-Inspired Multi-Population-Based Adaptive Backtracking Search Algorithm

Application of Hybrid GWO-BSA Technique for Resolving Multi-Objective Optimal Power Flow Problem by Incorporating Unified Power Flow Controller

Evaluation of FACTS Contributions Using Branch Flow Model and Newton–Raphson Algorithm

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