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Maximum power point tracking and parameter estimation for multiple-photovoltaic arrays based on enhanced pigeon-inspired optimization with Taguchi method

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F22%3A10251952" target="_blank" >RIV/61989100:27240/22:10251952 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S0360544222007666?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0360544222007666?via%3Dihub</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.energy.2022.123863" target="_blank" >10.1016/j.energy.2022.123863</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Maximum power point tracking and parameter estimation for multiple-photovoltaic arrays based on enhanced pigeon-inspired optimization with Taguchi method

  • Original language description

    The simulation, control and optimization of photovoltaic (PV) modules require the extraction of parameters from actual data and the construction of highly accurate PV cells. Multiple PV modules supplying power to a common load is the most common form of power distribution in PV systems. In these PV systems, providing separate maximum power point tracking (MPPT) technology for each PV module would increase the cost of the entire system. Determining how to accurately identify the internal parameter information of the PV modules and control the MPPT technology is the problem solved in this paper. we proposes an improved pigeon-inspired optimization (PIO) algorithm based on Taguchi method to solve the above problems. In this paper, we use the CEC2014 test library for testing and cross-sectional comparison. Experimental results show that the PIO algorithm based on Taguchi method is more competitive than other algorithms. The proposed algorithm uses measurement data to extract the unknown parameter in the PV modules and then uses this information to optimize the MPPT of all PV systems under partially shaded conditions (PSCs). Simulation results demonstrate the fitness value of the unknown parameters extracted by TPIO is 9.7525 x 10(-4), which is better than the compared algorithms.(c) 2022 Elsevier Ltd. All rights reserved.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2022

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Energy

  • ISSN

    0360-5442

  • e-ISSN

    1873-6785

  • Volume of the periodical

    251

  • Issue of the periodical within the volume

    červenec 2022

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    16

  • Pages from-to

    nestrankovano

  • UT code for WoS article

    000798564200008

  • EID of the result in the Scopus database