Autors: Guliashki, V.G., Marinova, G. I., Groumpos, P.P.
Title: Multi-objective optimization approach for energy efficiency in microgrids
Keywords: Bi-criterion optimizations, Construction manager, Decision makers, Energy efficiency optimizations, Environmental pollutions, Investment costs, Multi-objective genetic algorithm, Real problems

Abstract: The aim of this article is to present a methodology and an approach for energy efficiency optimization for buildings, connected in microgrids. The initial investment costs for the building and the energy costs are optimized while the environmental pollution is minimized at the same time. A bi-criterion optimization problem is formulated. It is solved by a multi-objective genetic algorithm in MATLAB. The possibilities of the approach are illustrated by the optimization of the energy efficiency of a group of three-storey houses connected in a microgrid. The obtained results demonstrate that the proposed approach could be implemented for different real problems concerning the buildings energy efficiency and may be helpful for construction managers, architects and decision makers in this area



    IFAC-PapersOnLine Open Access. 19th IFAC Conference on Technology, Culture and International Stability, TECIS 2019; Sozopol; Bulgaria; 26 September 2019 through 28 September 2019, vol. 52, issue 25, pp. 477-482, 2019, Bulgaria, Elsevier B.V., DOI 10.1016/j.ifacol.2019.12.587

    Copyright IF AC (International Federation of Automatic Control) Hosting by Elsevier Ltd.

    Цитирания (Citation/s):
    1. Borissova D., Cvetkova P., Garvanov I., Garvanova M. (2020) A Framework of Business Intelligence System for Decision Making in Efficiency Management. In: Saeed K., Dvorský J. (eds) Computer Information Systems and Industrial Management. CISIM 2020. Lecture Notes in Computer Science, vol 12133. Springer, Cham. - 2020 - в издания, индексирани в Scopus или Web of Science

    Вид: пленарен доклад в международен форум, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus