Design of Fractional Swarm Intelligent Computing With Entropy Evolution for Optimal Power Flow Problems

Yasir, Muhammad; Khan, R. D.; Raja, Muhammad Asif Zahoor; Ullah, Farman; Chaudhary, Naveed Ishtiaq; He, Yigang

doi:10.1109/access.2020.3002714

Cited by 39 publications

(19 citation statements)

References 76 publications

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“…So MWNN is the best choice to solve such complicated models using the global and local search terminologies GAIPA. In future, MWNN-GAIPA can be implemented to solve the fluid dynamic nonlinear systems, biological nonlinear systems, singular higher order differential systems, fractional processing, direction of arrival estimation, power and eneggy systems [53][54][55][56][57][58][59][60][61][62].…”

Section: Discussionmentioning

confidence: 99%

Design of Morlet Wavelet Neural Network for Solving a Class of Singular Pantograph Nonlinear Differential Models

et al. 2021

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The aim of this study is to design a layer structure of feed-forward artificial neural networks using the Morlet wavelet activation function for solving a class of pantograph differential Lane-Emden models. The Lane-Emden pantograph differential equation is one of the important kind of singular functional differential model. The numerical solutions of the singular pantograph differential model are presented by the approximation capability of the Morlet wavelet neural networks (MWNNs) accomplished with the strength of global and local search terminologies of genetic algorithm (GA) and interior-point algorithm (IPA), i.e., MWNN-GAIPA. Three different problems of the singular pantograph differential models have been numerically solved by using the optimization procedures of MWNN-GAIPA. The correctness of the designed MWNN-GAIPA is observed by comparing the obtained results with the exact solutions. The analysis for 3, 6 and 60 neurons are also presented to check the stability and performance of the designed scheme. Moreover, different statistical analysis using forty number of trials is presented to check the convergence and accuracy of the proposed MWNN-GAIPA scheme.

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Section: Discussionmentioning

confidence: 99%

Design of Morlet Wavelet Neural Network for Solving a Class of Singular Pantograph Nonlinear Differential Models

et al. 2021

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“…Muhammad, et. al [38] proposed Shannon entropy-based diversity in PSO dynamic, i.e., FOPSO-EE to minimize power losses, voltage deviation and overall cost using FACTS devices in IEEE 30-bus system. LAPO is an efficient optimization technique, proposed by Nematollahi et.al.…”

Section: B Literature Reviewmentioning

confidence: 99%

A Novel Modified Lightning Attachment Procedure Optimization Technique for Optimal Allocation of the FACTS Devices in Power Systems

et al. 2021

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The Flexible AC Transmission Systems (FACTS) are the static power electronic devices that are installed and used in AC transmission networks to enhance the capability of transferring the power for providing the controllability and stability. However, the optimization of site and size of these devices is a crucial task due to their high capital cost and practical capabilities. In this paper, the optimal reactive power dispatch (ORPD) embedded with two effective controllers including the Static VAR Compensator (SVC) and Thyristor Control Series Capacitor (TCSC) is solved using a Modified Lightning Attachment Procedure Optimizer (MLAPO). The searching capability of basic LAPO is enhanced and the stagnation of basic LAPO is avoided by application of levy flight distribution and spiral orientation motion. The optimization for these devices is for reducing the power losses, voltage deviations, and the operating cost. MLAPO is examined and tested on modified IEEE30 and IEEE57 bus-standards considering SVC and TCSC. The effectiveness of MLAPO is further analyzed and compared with the outcomes of the well-known optimization techniques namely LAPO, PSO, ALO, EO, MPA, WOA and SCA with and without FACTS devices.

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“…In case of minimizing the power losses for 13 control variables, the by using FPSOGSA is reduced from 5.811 MW (base case) to 4.5308 MW. Judging from Table IX and Table X, the results computed by FPSOGSA are better than MFO [44], C-PSO [37], GWO [40], PSO-CF [23], QOTLBO [41], IGA [43], MICA-IWO [38], PSOGSA [45], FODPSO-EE [50], LAPO [28], ALO [42], MSFS [46], BBO [48] and OGSA [49]. According to Figs.…”

Section: A Orpd Problem Without Rersmentioning

confidence: 99%

Fractional PSOGSA Algorithm Approach to Solve Optimal Reactive Power Dispatch Problems With Uncertainty of Renewable Energy Resources

et al. 2020

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The optimal reactive power dispatch (ORPD) is a major tool, and it plays a vital role for enhancement of the power system performance. ORPD is one multimodal, non-convex, and non-linear problem. Many elegant benefits can be obtained by using the renewable energy resources (RERs), but many technical issues related to the RERs including the stochastic characteristics of these resources due to continuous variations of solar irradiance and the wind speed lead to increasing the uncertainties of system. Thus, solving the ORPD problem with RERs is a crucial task. The contribution of the paper includes application a modified hybrid algorithm for solving the ORPD considering the uncertainties of the RERs and the load demand. The proposed algorithm is based on Fractional Calculus with Particle Swarm Optimization Gravitational Search Algorithm (FPSOGSA) which aims to enhance the searching capabilities of the conventional PSOGSA algorithm and overcome its tendency to stagnation. The proposed algorithm is tested on IEEE 30-bus system for reducing power losses and voltage deviation as well as enhancing voltage stability. The scenario-based method is employed to produce a set of scenarios from the uncertainties of load, wind speed and solar irradiance. The simulation results verify the effectiveness of the proposed algorithm for solving the ORPD problem with and without considering the uncertainties in the system. Furthermore, the proposed algorithm is superior compared with the state-of-the-art techniques in terms of the reduction of power losses and voltage deviations as well as the stability enhancement.

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Design of Fractional Swarm Intelligent Computing With Entropy Evolution for Optimal Power Flow Problems

Cited by 39 publications

References 76 publications

Design of Morlet Wavelet Neural Network for Solving a Class of Singular Pantograph Nonlinear Differential Models

Design of Morlet Wavelet Neural Network for Solving a Class of Singular Pantograph Nonlinear Differential Models

A Novel Modified Lightning Attachment Procedure Optimization Technique for Optimal Allocation of the FACTS Devices in Power Systems

Fractional PSOGSA Algorithm Approach to Solve Optimal Reactive Power Dispatch Problems With Uncertainty of Renewable Energy Resources

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