Mathematical Modeling of Energetic Performance Parameters for Downdraft Gasifiers through Regression Techniques

Authors

  • Eduardo Roberto Gutiérrez-Gualotuña Universidad de las Fuerzas Armadas (ESPE) Author
  • Jorge André Soria-Amancha Universidad de las Fuerzas Armadas (ESPE) Author
  • Paúl Michael Tafur-Escanta Universidad de las Fuerzas Armadas (ESPE) Author
  • Natzarenna Rodríguez-Trujillo Universidad de las Fuerzas Armadas (ESPE) Author
  • Ángelo Homero Villavicencio-Poveda Universidad de las Fuerzas Armadas (ESPE) Author
  • José Arzola-Ruiz Universidad Tecnologica de la Habana "Jose Antonio Echeverria" Author

DOI:

https://doi.org/10.46842/ipn.cien.v23n1a08

Keywords:

operation of energetic installations, renewable energy, downdraft gasification installations, mathematical modeling

Abstract

In the energy facilities, the operation has a considerable influence on efficiency, which is why this research presents results obtained by the authors in the modeling of performance indicators of the operation of biomass gasification facilities with the help of the non-linear regression techniques, from the systemic analysis, its identification and determination of the type of model with the best adjustment of the operation of these facilities. Several bibliographical studies are carried out on previous research, linked to the mathematical modeling of these facilities by the different techniques reflected in the specialized literature. A 3N experimental plan is made with three retorts, from which four non-linear regression models corresponding to respective performance indicators are elaborated using model linearization techniques, with satisfactory results from their evaluation based on the regression coefficients. And standard errors using three types of biomass. The experimental installation and the developed data acquisition system are described below.

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Published

10-09-2024

How to Cite

Mathematical Modeling of Energetic Performance Parameters for Downdraft Gasifiers through Regression Techniques. (2024). Científica, 23(1), 69-81. https://doi.org/10.46842/ipn.cien.v23n1a08