Random Matrix Generators for Optimizing a Fuzzy Biofuel Supply Chain System

Ganesan, Timothy; Vasant, Pandian; Sanghvi, Pratik; Thomas, Jim; Litvinchev, Igor

doi:10.25073/jaec.202041.268

Cited by 25 publications

(9 citation statements)

References 40 publications

(45 reference statements)

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“…( 2009)).Theauthorsin(Mahapatra&Jha,2016)haveapplied ahybridalgorithmforattainingoptimalpowerflowwithvoltagestability.Varioussoftcomputing techniques have been implemented to generate improved RPP solution with different constraints byauthorsin(Bhattacharyya&Raj(2017);Bhattacharyya&Karmakar(2020); Mahapatra,Raj& Krishna(2020); Mahapatra,Badi&Raj(2019);Bhattacharyya&Karmakar(2019)).Forsolving multi-objectiveproblems,metaheuristicalgorithmswhichareeitherevolutionarybasedorswarm intelligence type are being applied frequently in various areas of research (Geleta & Manshahia (2020); Manshahia(2018); Manshahia(2019);Geleta&Manshahia(2020);Somanietal. (2019); Kajela&Manshahia(2017); Vasant,Zelinka&Weber(2019); Vasant,Zelinka&Weber(2020); Ganesan et al (2020); Vasant, Kose & Watada (2017)). Operating strategy in distribution system for configuration management using harmony search algorithm has been discussedin (Kumar&Ali,2020).Energymanagement,micro-gridanddistributiongenerationhas beenstudiedin (Kumar&Singh,2018).Voltagedependentloadshavebeenmodelledintheform ofloadcombinationstorepresenttherealworldloadsforcalculationofenergyefficiencyin (Ali& Thomas,2015).HybridPSOtechniquehasbeenstudiedin(Subbaraj&Rajnarayanan,2010)forthe solutionofreactivepowerdispatch.…”

Section: Literature Reviewmentioning

confidence: 99%

Implementation and Optimal Sizing of TCSC for the Solution of Reactive Power Planning Problem Using Quasi-Oppositional Salp Swarm Algorithm

Raj

Mahapatra

Shiva

et al. 2021

International Journal of Energy Optimization and Engineering

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In this article, innovative algorithms named as salp swarm algorithm (SSA) and hybrid quasi-oppositional SSA (QOSSA) techniques have been proposed for finding the optimal coordination for the solution of reactive power planning (RPP). Quasi-oppositional based learning is a promising technique for improving convergence and is implemented with SSA as a new hybrid method for RPP. The proposed techniques are successfully implemented on standard test systems for deprecation of real power losses and overall cost of operation along with retention of bus voltages under acceptable limits. Optimal planning has been achieved by minimizing reactive power generation and transformer tap settings with optimal placement and sizing of TCSC. Identification of weakest branch in the power network is done for optimal TCSC placement and is tendered through line stability index method. Optimal TCSC placement renders a reduction in transmission loss by 8.56% using SSA and 8.82% by QOSSA in IEEE 14 bus system and 7.57% using SSA and 9.64% by QOSSA in IEEE 57 bus system with respect to base condition.

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Section: Literature Reviewmentioning

confidence: 99%

Implementation and Optimal Sizing of TCSC for the Solution of Reactive Power Planning Problem Using Quasi-Oppositional Salp Swarm Algorithm

Raj

Mahapatra

Shiva

et al. 2021

International Journal of Energy Optimization and Engineering

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“…Research has been conducted on the initialization methods of swarm intelligence optimization algorithms in Refs. 11 – 13 , optimizing the optimization effectiveness and convergence of the algorithms. In practical engineering applications, Ref.…”

Section: Introductionmentioning

confidence: 99%

A novel lifting point location optimization method of transmission line tower based on improved grey wolf optimizer

Wang,

Ding,

Huang

et al. 2023

Sci Rep

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In the erection process of transmission line tower, the appropriate lifting point position is an important factor in ensuring the stability and balance of the lifting process and preventing deformation and damage to the towers. In this paper, a improved grey wolf optimization algorithm is proposed to solve the issues of low optimization efficiency and easily getting trapped in local minima when optimizing the lifting point position of transmission line towers. The improved algorithm includes the use of a good point-set strategy to enhance the initialization method of grey wolf individuals, ensuring a more uniform distribution of the population and reducing ineffective searches in the early stages of optimization. Furthermore, two random operators are utilized to combine and mutate the optimal grey wolf position, thereby enhancing the algorithm's ability to escape local optima. Finally, the trend information of the optimization process is considered, and the median value of the population is used to improve the stability of the optimization algorithm. Experimental results demonstrate that the proposed algorithm has better optimization performance and faster convergence speed compared to genetic algorithm, particle swarm optimization algorithm, and artificial fish swarm algorithm. It effectively addresses the optimization problem of lifting point position for transmission line towers.

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“…e frequent occurrence of contradictions in the water supply industry also means that the water supply industry must make revolutionary innovations in the management style [2]. However, although the number of urban residents has been increasing in recent years and the city has been expanding to meet the development needs, the pipeline network infrastructure has also been growing, resulting in an urban water supply pipeline network with multiple water sources, multiple water plants, multiple transmission and distribution ring networks, and frequent uncertainty accidents, but the way urban infrastructure is managed has not changed much [3].…”

Section: Introductionmentioning

confidence: 99%

A Multivariate Statistical Model of Water Leakage in Urban Water Supply Networks Based on Random Matrix Theory

Chen¹,

Yang

2022

Mathematical Problems in Engineering

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In this paper, model construction of random matrix theory is carried out to analyze water leakage of urban water supply pipeline network, and a multivariate statistical model of water leakage of urban water supply pipeline network based on random matrix theory is proposed. This paper presents a three-level DMA, short-term water demand prediction method based on water use patterns, aiming to solve the problem of inaccurate water demand prediction caused by climate and social factors. Correlation analysis and factor analysis analyze the main factors affecting daily water demand changes. The extracted information of the main influencing factors and historical monitoring data are used to establish the Elman water demand prediction model. At the same time, the daily water consumption pattern was extracted by correlation analysis, matched with the water consumption pattern of the predicted day, and combined with the expected value of water demand for momentary water demand allocation, which improved the prediction accuracy of short-term water demand. This paper is based on the precise leakage location based on the real-time hydraulic model. The real-time hydraulic model under leakage conditions is established, GA and NSGA2 are designed, and the nondominated ranking algorithm with elite strategy is used to achieve accurate leakage location using hydraulic model calibration search. This paper uses a random matrix algorithm to establish the leakage estimation model. A laboratory case pipe network is built to simulate the water supply conditions in residential areas, and the operating data of the laboratory case pipe network are used to confirm that the random matrix leakage estimation model can estimate the leakage. The applicability of the random matrix leakage estimation model and the wavelet transform algorithm for leakage calculation are compared in an engineering example. The example confirms that the leakage amount calculated by the random matrix model has a less relative error and more similar trend than the wavelet transform algorithm.

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Random Matrix Generators for Optimizing a Fuzzy Biofuel Supply Chain System

Cited by 25 publications

References 40 publications

Implementation and Optimal Sizing of TCSC for the Solution of Reactive Power Planning Problem Using Quasi-Oppositional Salp Swarm Algorithm

Implementation and Optimal Sizing of TCSC for the Solution of Reactive Power Planning Problem Using Quasi-Oppositional Salp Swarm Algorithm

A novel lifting point location optimization method of transmission line tower based on improved grey wolf optimizer

A Multivariate Statistical Model of Water Leakage in Urban Water Supply Networks Based on Random Matrix Theory

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