• DocumentCode
    631036
  • Title

    Demand response for chemical manufacturing using Economic MPC

  • Author

    Mendoza-Serrano, David I. ; Chmielewski, Daniel J.

  • Author_Institution
    Dept. of Chem. & Biol. Eng., Illinois Inst. of Technol., Chicago, IL, USA
  • fYear
    2013
  • fDate
    17-19 June 2013
  • Firstpage
    6655
  • Lastpage
    6660
  • Abstract
    The notion of demand response in electric power systems is to use time varying electricity price structures to encourage consumers to track generation availability. Specifically, when available generation is low, either due to high demand or a lack of renewable sources, an increase in electricity rates is intended to encourage smart grid participants to reduce consumption. Similarly, when on-line generation is higher than demand, smart grid participants may benefit from low electricity rates. While many think of smart grid participants as residential consumers, the commercial building and industrial sectors will likely result in a higher grid impact to implementation cost ratio. In this work we investigate potential demand response mechanisms from the chemical manufacturing industry. It will be shown that depending on the type of upgrade hardware selected the smart grid operating policy will either be an application of Real-Time Optimization (RTO) or Economic Model Predictive Control (EMPC). In the case of EMPC the impact of prediction horizon size will be highlighted.
  • Keywords
    chemical industry; demand side management; industrial economics; power consumption; power generation economics; power grids; EMPC; RTO; chemical manufacturing industry; consumption reduction; demand response; economic MPC; economic model predictive control; electric power systems; electricity rates; real time optimization; residential consumer; smart grid; Electricity; Fuels; Load management; Materials; Smart grids; Throughput; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2013
  • Conference_Location
    Washington, DC
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-0177-7
  • Type

    conf

  • DOI
    10.1109/ACC.2013.6580884
  • Filename
    6580884