• DocumentCode
    183974
  • Title

    Model predictive control approach to online computation of demand-side flexibility of commercial buildings HVAC systems for Supply Following

  • Author

    Maasoumy, Mehdi ; Rosenberg, Catherine ; Sangiovanni-Vincentelli, A. ; Callaway, Duncan S.

  • Author_Institution
    Dept. of Mech. Eng., Univ. of California, Berkeley, Berkeley, CA, USA
  • fYear
    2014
  • fDate
    4-6 June 2014
  • Firstpage
    1082
  • Lastpage
    1089
  • Abstract
    Commercial buildings have inherent flexibility in how their HVAC systems consume electricity. We investigate how to take advantage of this flexibility. We first propose a means to define and quantify the flexibility of a commercial building. We then propose a contractual framework that could be used by the building operator and the utility to declare flexibility on the one side and reward structure on the other side. We then design a control mechanism for the building to decide its flexibility for the next contractual period to maximize the reward, given the contractual framework. Finally, we perform at-scale experiments to demonstrate the feasibility of the proposed algorithm.
  • Keywords
    HVAC; buildings (structures); control system synthesis; power consumption; predictive control; HVAC systems; commercial buildings; contractual framework; control mechanism design; demand-side flexibility; electricity consumption; model predictive control approach; online computation; reward structure; supply following; Buildings; Contracts; Cooling; Electricity; Heating; Optimal control; Power demand; Building and facility automation; Power systems; Predictive control for nonlinear systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2014
  • Conference_Location
    Portland, OR
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-3272-6
  • Type

    conf

  • DOI
    10.1109/ACC.2014.6858874
  • Filename
    6858874