On the modelling of the energy system of a country for decision making using bayesian artificial intelligence – a case study for Mexico

Monica Borunda, Ann E. Nicholson, Raul Garduno, Hoss Sadafi

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

Abstract

Energy efficiency has attracted the attention of many governments around the world due to the urgent call to reduce investments in energy infrastructure, lower fossil fuel dependency, integrate renewable energies, improve consumer welfare and reduce CO 2 emissions. The conservative and smart use of energy is one of the main approaches to improve energy efficiency. However, the management of energy at the national level is a complex decision making problem involving uncertainty and therefore, Bayesian Networks are suitable paradigm to deal with this task. In this work, we present a progress report on the development of a decision making method, based on Bayesian decision networks, for the efficient use of energy as a function of the cost, efficiency and CO 2 emissions from the source of energy used.

Original languageEnglish
Title of host publicationAdvances in Computational Intelligence
Subtitle of host publication17th Mexican International Conference on Artificial Intelligence, MICAI 2018 Guadalajara, Mexico, October 22–27, 2018 Proceedings, Part II
EditorsIldar Batyrshin, María de Lourdes Martínez-Villaseñor, Hiram Eredín Ponce Espinosa
Place of PublicationCham Switzerland
PublisherSpringer
Pages30-46
Number of pages17
ISBN (Electronic)9783030044978
ISBN (Print)9783030044961
DOIs
Publication statusPublished - 2018
EventMexican International Conference on Artificial Intelligence 2018 - Guadalajara, Mexico
Duration: 22 Oct 201827 Oct 2018
Conference number: 17th
http://www.micai.org/2018/

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume11289
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceMexican International Conference on Artificial Intelligence 2018
Abbreviated titleMICAI 2018
CountryMexico
CityGuadalajara
Period22/10/1827/10/18
Internet address

Keywords

  • Bayesian networks
  • Decision making
  • Energy efficiency
  • Smart energy system

Cite this

Borunda, M., Nicholson, A. E., Garduno, R., & Sadafi, H. (2018). On the modelling of the energy system of a country for decision making using bayesian artificial intelligence – a case study for Mexico. In I. Batyrshin, M. de Lourdes Martínez-Villaseñor, & H. E. Ponce Espinosa (Eds.), Advances in Computational Intelligence: 17th Mexican International Conference on Artificial Intelligence, MICAI 2018 Guadalajara, Mexico, October 22–27, 2018 Proceedings, Part II (pp. 30-46). (Lecture Notes in Computer Science ; Vol. 11289 ). Springer. https://doi.org/10.1007/978-3-030-04497-8_3