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Energies 2015, 8(9), 10504-10521; doi:10.3390/en80910504

Optimal Energy Reduction Schedules for Ice Storage Air-Conditioning Systems

1
Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 80724, Taiwan
2
Department of Electrical Engineering, Cheng-Shiu University, Kaohsiung 83342, Taiwan
3
Department of Engineering and Maintenance, ChangCung Memorial Hospital, Kaohsiung 83341, Taiwan
*
Author to whom correspondence should be addressed.
Academic Editor: Robert Lundmark
Received: 30 July 2015 / Revised: 9 September 2015 / Accepted: 15 September 2015 / Published: 22 September 2015
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Abstract

This paper proposes a hybrid algorithm to solve the optimal energy dispatch of an ice storage air-conditioning system. Based on a real air-conditioning system, the data, including the return temperature of chilled water, the supply temperature of chilled water, the return temperature of ice storage water, and the supply temperature of ice storage water, are measured. The least-squares regression (LSR) is used to obtain the input-output (I/O) curve for the cooling load and power consumption of chillers and ice storage tank. The objective is to minimize overall cost in a daily schedule while satisfying all constraints, including cooling loading under the time-of-use (TOU) rate. Based on the Radial Basis Function Network (RBFN) and Ant Colony Optimization, an Ant-Based Radial Basis Function Network (ARBFN) is constructed in the searching process. Simulation results indicate that reasonable solutions provide a practical and flexible framework allowing the economic dispatch of ice storage air-conditioning systems, and offering greater energy efficiency in dispatching chillers. View Full-Text
Keywords: ice storage air-conditioning system; radial basis function network; ant colony optimization; chiller; economic dispatch ice storage air-conditioning system; radial basis function network; ant colony optimization; chiller; economic dispatch
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Lin, W.-M.; Tu, C.-S.; Tsai, M.-T.; Lo, C.-C. Optimal Energy Reduction Schedules for Ice Storage Air-Conditioning Systems. Energies 2015, 8, 10504-10521.

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