Multi-objective Optimization for the Management of the Response to the Electrical Demand in Commercial Users

Edwin M. Garcia, Idi Amin Isaac Millan

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

    6 Scopus citations

    Abstract

    This document mentions alternatives so that the commercial user can have an energetic saving inside their facilities and minimizes the electrical consumption in a determined time, the answer to the electrical demand allows the user to make decisions of the consumption in the schedules of greater demand that are considered peak hours, aiming to carry out a direct control of their loads in these schedules that allow them to have economic and ecological benefits by reducing the use of obsolete equipment within their facilities and in addition to reducing the emission of CO2 to the environment that is Gives at the time of the start of the thermal power plants that are central of backup in the schedules of maximum electrical consumption at national level.

    Original languageEnglish
    Title of host publicationProceedings - 2017 International Conference on Information Systems and Computer Science, INCISCOS 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages14-20
    Number of pages7
    ISBN (Electronic)9781538626443
    DOIs
    StatePublished - 2 Jul 2017
    Event2nd International Conference on Information Systems and Computer Science, INCISCOS 2017 - Quito, Ecuador
    Duration: 23 Nov 201725 Nov 2017

    Publication series

    NameProceedings - 2017 International Conference on Information Systems and Computer Science, INCISCOS 2017
    Volume2017-November

    Conference

    Conference2nd International Conference on Information Systems and Computer Science, INCISCOS 2017
    Country/TerritoryEcuador
    CityQuito
    Period23/11/1725/11/17

    Bibliographical note

    Publisher Copyright:
    © 2017 IEEE.

    Keywords

    • AMI
    • BMS
    • Demand Response
    • Electric Generation
    • Minimization
    • Renewable Energy
    • Smart Grid

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