About | Contact Us | Register | Login
ProceedingsSeriesJournalsSearchEAI
ew 19(23): e1

Research Article

Search and research of energy-efficient configuration of the power supply network

Download1219 downloads
Cite
BibTeX Plain Text
  • @ARTICLE{10.4108/eai.13-7-2018.157032,
        author={V.A. Negadaev},
        title={Search and research of energy-efficient configuration of the power supply network},
        journal={EAI Endorsed Transactions on Energy Web},
        volume={6},
        number={23},
        publisher={EAI},
        journal_a={EW},
        year={2019},
        month={3},
        keywords={genetic algorithm, electric load, electric power distribution, electric power supply network, main structure, model, optimization, energy-efficient configuration},
        doi={10.4108/eai.13-7-2018.157032}
    }
    
  • V.A. Negadaev
    Year: 2019
    Search and research of energy-efficient configuration of the power supply network
    EW
    EAI
    DOI: 10.4108/eai.13-7-2018.157032
V.A. Negadaev1,*
  • 1: T.F. Gorbachev Kuzbass State Technical University, Institute of Power Engineering, Department of electric drive and automation 28, Vesennyaya St., 650000, Kemerovo, the Russian Federation
*Contact email: negadaevva@kuzstu.ru

Abstract

Model of main structure of power-supply is considered for research of states of working collections of induction motors. Model consists of separate electromechanic modules, which can contain different amount of motors. Modules are connected in different points to main cable, laid from transformer before remoted module. On base of this model is developed software program, intended for finding of optimum parameters of structure of network of power-supply with use the genetic algorithm.

Keywords
genetic algorithm, electric load, electric power distribution, electric power supply network, main structure, model, optimization, energy-efficient configuration
Received
2018-06-18
Accepted
2019-01-01
Published
2019-03-21
Publisher
EAI
http://dx.doi.org/10.4108/eai.13-7-2018.157032

Copyright © 2019 V.A. Negadaev et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.

EBSCOProQuestDBLPDOAJPortico
EAI Logo

About EAI

  • Who We Are
  • Leadership
  • Research Areas
  • Partners
  • Media Center

Community

  • Membership
  • Conference
  • Recognition
  • Sponsor Us

Publish with EAI

  • Publishing
  • Journals
  • Proceedings
  • Books
  • EUDL