• DocumentCode
    3142937
  • Title

    Green Scheduling for Energy-Efficient Operation of Multiple Chiller Plants

  • Author

    Behl, Madhur ; Nghiem, Truong X. ; Mangharam, Rahul

  • Author_Institution
    Dept. of Electr. & Syst. Eng., Univ. of Pennsylvania, Philadelphia, PA, USA
  • fYear
    2012
  • fDate
    4-7 Dec. 2012
  • Firstpage
    195
  • Lastpage
    204
  • Abstract
    In large building systems, such as a university campus, the air-conditioning systems are commonly served by chiller plants, which contribute a large fraction of the total electricity consumption of the campuses. The power consumption of a chiller is highly affected by its Coefficient of Performance (COP), which is optimal when the chiller is operated at or near full load. For a chiller plant, its overall COP can be optimized by utilizing a Thermal Energy Storage (TES) and switching its operation between COP-optimal charging and discharging modes. However, uncoordinated mode switchings of chiller plants may cause temporally-correlated high electricity demand when multiple plants are charging their TES concurrently. In this paper, a GS approach, proposed in our previous work, is used to schedule the chiller plants to reduce their peak aggregate power demand while ensuring safe operation of the TES. We present a scheduling algorithm based on backward reach set computation of the TES dynamics. The proposed algorithm is demonstrated in a numerical simulation in Mat lab to be effective for reducing the peak power demand and the overall electricity cost.
  • Keywords
    air conditioning; building management systems; energy conservation; numerical analysis; power consumption; thermal energy storage; thermal power stations; COP discharging modes; COP-optimal charging modes; GS approach; Matlab; TES dynamics; backward reach set computation; coefficient of performance; electricity cost; energy-efficient operation; green scheduling; large building systems; multiple chiller plants; numerical simulation; peak aggregate power demand; scheduling algorithm; temporally-correlated high electricity demand; thermal energy storage; total electricity consumption; university campus; Buildings; Cooling; Electricity; Energy storage; Green products; Load modeling; Power demand; Green Scheduling; TES; chiller COP; chiller scheduling; demand charge; peak power reduction; thermal energy storage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Real-Time Systems Symposium (RTSS), 2012 IEEE 33rd
  • Conference_Location
    San Jan
  • ISSN
    1052-8725
  • Print_ISBN
    978-1-4673-3098-5
  • Type

    conf

  • DOI
    10.1109/RTSS.2012.71
  • Filename
    6424803