Optimized small-scaled hybrid energy management of a smart house based on genetic algorithm

Viktor Ten, Zhandos Yessenbayev, Akmaral Shamshimova, Albina Khakimova

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

2 Citations (Scopus)

Abstract

Renewable energy sources provide both electricity and heating for experimental smart house located at renewable energy test site at Nazarbayev University. Smart house's electric and heating subsystems are supplied by PV cells and solar thermal heater respectively. Partially the system consumes the electricity from utility grid. The dynamics of the system consists of electrical and thermal parts based on the state of charge of accumulator battery stack and temperatures of the heating system and smart house itself. The goal of designed control is to maintain the states of the system inside of required ranges and simultaneously to minimize the expenses for power consumption from utility grid. The task of minimization is solved using genetic algorithm. The simulation results are obtained in MATLAB and confirm the efficiency of designed control.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1153-1158
Number of pages6
ISBN (Electronic)9781509002870
DOIs
Publication statusPublished - Mar 2 2016
EventIEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015 - Miami, United States
Duration: Dec 9 2015Dec 11 2015

Other

OtherIEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015
CountryUnited States
CityMiami
Period12/9/1512/11/15

Keywords

  • Energy management
  • Genetic algorithm
  • Renewable energy

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications

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  • Cite this

    Ten, V., Yessenbayev, Z., Shamshimova, A., & Khakimova, A. (2016). Optimized small-scaled hybrid energy management of a smart house based on genetic algorithm. In Proceedings - 2015 IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015 (pp. 1153-1158). [7424475] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMLA.2015.64