• DocumentCode
    32885
  • Title

    Managing Industrial Energy Intelligently: Demand Response Scheme

  • Author

    Mohagheghi, Salman ; Raji, Neda

  • Author_Institution
    Electr. Eng. & Comput. Sci. Dept., Colorado Sch. of Mines, Golden, CO, USA
  • Volume
    20
  • Issue
    2
  • fYear
    2014
  • fDate
    March-April 2014
  • Firstpage
    53
  • Lastpage
    62
  • Abstract
    Electric demand-side management (DSM) focuses on changing the electricity consumption patterns of end-use customers through improving energy efficiency and optimizing the allocation of power. Demand response (DR ) is a DSM solution that targets residential, commercial, and industrial customers and is developed for demand reduction or demand shifting at a specific time for a specific duration. In the absence of on-site generation or the possibility of demand shifting, the consumption level needs to be lowered. While the noncriticality of loads at the residential and commercial levels allows for demand reduction with relative ease, demand reduction of industrial processes requires a more sophisticated solution. Production constraints, inventory constraints, maintenance schedules, and crew management are some of the many factors that have to be considered before one or more processes can be temporarily shut down. An intelligent system is designed in this article for implementation of DR at an industrial site. Based on the various operational constraints of the industrial process, it determines the loads that could be potentially curtailed. Fuzzy/expert systems are used to derive a priority factor for different candidate loads. This information can then be used by the plant operator/DR client to make a comply/opt out decision during a utility-initiated DR event.
  • Keywords
    demand side management; energy conservation; expert systems; fuzzy systems; maintenance engineering; DSM; crew management; demand reduction; demand response scheme; demand shifting; electric demand side management; electricity consumption patterns; energy efficiency; fuzzy-expert systems; intelligent system; inventory constraints; maintenance schedules; operational constraints; power allocation; production constraints; Energy consumption; Energy efficiency; Energy management; Industrial plants; Maintenance engineering; Optimized production technology; Workstations;
  • fLanguage
    English
  • Journal_Title
    Industry Applications Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1077-2618
  • Type

    jour

  • DOI
    10.1109/MIAS.2013.2288387
  • Filename
    6689333