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A Soft Curtailment of Wide-Area Central Air Conditioning Load

Author

Listed:
  • Leehter Yao

    (Department of Electrical Engineering, National Taipei University of Technology, Taipei 10608, Taiwan)

  • Lei Yao

    (Department of Electrical Engineering, National Taipei University of Technology, Taipei 10608, Taiwan)

  • Wei Hong Lim

    (Faculty of Engineering, Technology and Built Environment, UCSI University, Kuala Lumpur 56000, Malaysia)

Abstract

An innovative solution to provide a demand response for power system is proposed in this paper by considering the feasibility of two-way direct load control (TWDLC) of central air conditioning chiller system for wide-area in real-time manner. Particularly, the proposed TWDLC scheme is designed to tackle the load shedding ratio optimization problem for all under-controlled customers, aiming to satisfy the target load curtailment defined in each scheduling step. Another notable contribution of this work is the utilization of constraint loosening concept on actual load, curtailed to overcome the uncertainties of load reduction during TWDLC. Given the presence of fuzzy constraints, the proposed load shedding ratio optimization problem can be tackled using fuzzy linear programming. A delicate strategy is then formulated to transform the proposed fuzzy linear programming problem into a regular linear programming problem. A selection scheme used to obtain the feasible candidates set for load shedding at every sampling interval of TWDLC is also designed along with the fuzzy linear programming.

Suggested Citation

  • Leehter Yao & Lei Yao & Wei Hong Lim, 2018. "A Soft Curtailment of Wide-Area Central Air Conditioning Load," Energies, MDPI, vol. 11(3), pages 1-15, February.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:3:p:492-:d:133458
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    Cited by:

    1. Leehter Yao & Wei Hong Lim & Sew Sun Tiang & Teng Hwang Tan & Chin Hong Wong & Jia Yew Pang, 2018. "Demand Bidding Optimization for an Aggregator with a Genetic Algorithm," Energies, MDPI, vol. 11(10), pages 1-22, September.

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