Assessment of small-scale wind turbines to meet high-energy demand in Mexico with Bayesian Decision Networks

Monica Borunda, Raul Garduno, Ann E. Nicholson, Javier de la Cruz

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

Nowadays, an eco-friendly way to satisfy the high-energy demand is by the exploitation of renewable sources. Wind energy is one of the viable sustainable sources. In particular, small-scale wind turbines are an attractive option for meeting the high demand for domestic energy consumption since exclude the installation problems of large-scale wind farms. However, appropriate wind resource, installation costs, and other factors must be taken into consideration as well. Therefore, a feasibility study for the setting up of this technology is required beforehand. This requires a decision-making problem involving complex conditions and a degree of uncertainty. It turns out that Bayesian Decision Networks are a suitable paradigm to deal with this task. In this work, we present the development of a decision-making method, built with Decision Bayesian Networks, to assess the use of small-scale wind turbines to meet the high-energy demand considering the available wind resource, installation costs, reduction in CO2 emissions and the achieved savings.

Original languageEnglish
Title of host publicationAdvances in Soft Computing
Subtitle of host publication18th Mexican International Conference on Artificial Intelligence, MICAI 2019 Xalapa, Mexico, October 27 – November 2, 2019 Proceedings
EditorsLourdes Martínez-Villaseñor, Ildar Batyrshin, Antonio Marín-Hernández
Place of PublicationCham Switzerland
PublisherSpringer
Pages493-506
Number of pages14
ISBN (Electronic)9783030337490
ISBN (Print)9783030337483
DOIs
Publication statusPublished - 2019
EventMexican International Conference on Artificial Intelligence 2019 - Xalapa, Mexico
Duration: 28 Oct 20191 Nov 2019
Conference number: 18th
http://www.micai.org/2019/

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume11835
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceMexican International Conference on Artificial Intelligence 2019
Abbreviated titleMICAI 2019
CountryMexico
CityXalapa
Period28/10/191/11/19
Internet address

Keywords

  • Bayesian Networks
  • Decision-making
  • Energy demand
  • Small-scale wind turbine technology
  • Wind energy

Cite this

Borunda, M., Garduno, R., Nicholson, A. E., & de la Cruz, J. (2019). Assessment of small-scale wind turbines to meet high-energy demand in Mexico with Bayesian Decision Networks. In L. Martínez-Villaseñor, I. Batyrshin, & A. Marín-Hernández (Eds.), Advances in Soft Computing : 18th Mexican International Conference on Artificial Intelligence, MICAI 2019 Xalapa, Mexico, October 27 – November 2, 2019 Proceedings (pp. 493-506). (Lecture Notes in Computer Science; Vol. 11835 ). Cham Switzerland: Springer. https://doi.org/10.1007/978-3-030-33749-0_40