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An appraisal of multi objective evolutionary algorithm for possible optimization of renewable energy systems

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F19%3A39915492" target="_blank" >RIV/00216275:25410/19:39915492 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    An appraisal of multi objective evolutionary algorithm for possible optimization of renewable energy systems

  • Original language description

    The development of efficient multi objective evolutionary algorithms (MOEAs) can provide an effective tool for solving the optimization of solely renewable electricity systems. This paper presents an appraisal of multi objective evolutionary algorithms. It covers MOEA framework as a key issue in its design, these are including of MOEA based on decomposition, preference, indicator, hybridization, and co-evolution. Other MOEA frameworks covered in this paper are Target Region-based Multi Objective Evolutionary Algorithm (TMOEA) and Memetic Algorithm (MA) for multi objective evolutionary algorithms. The computational complexity of MOEAs has been presented. Potential direction for future research is in the area of MOEA application in an exclusively renewable energy system, thereby paving the way for the Internet of Renewable Energy (IoRE).

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    50602 - Public administration

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2019

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    2019 IEEE PES/IAS PowerAfrica

  • ISBN

    978-1-72811-011-0

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    370-375

  • Publisher name

    IEEE (Institute of Electrical and Electronics Engineers)

  • Place of publication

    New York

  • Event location

    Abuja

  • Event date

    Aug 20, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article