Ice Storage Air-Conditioning System Simulation with Dynamic Electricity Pricing: A Demand Response Study

Chi-Chun Lo, Shang-Ho Tsai and Bor-Shyh Lin
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Chi-Chun Lo: Institute of Electrical and Control Engineering, National Chiao Tung University, Hsinchu 30010, Taiwan
Shang-Ho Tsai: Institute of Electrical and Control Engineering, National Chiao Tung University, Hsinchu 30010, Taiwan
Bor-Shyh Lin: Institute of Imaging and Biomedical Photonics, National Chiao Tung University, Tainan 71150, Taiwan

Energies, 2016, vol. 9, issue 2, 1-16

Abstract: This paper presents an optimal dispatch model of an ice storage air-conditioning system for participants to quickly and accurately perform energy saving and demand response, and to avoid the over contact with electricity price peak. The schedule planning for an ice storage air-conditioning system of demand response is mainly to transfer energy consumption from the peak load to the partial-peak or off-peak load. Least Squares Regression (LSR) is used to obtain the polynomial function for the cooling capacity and the cost of power consumption with a real ice storage air-conditioning system. Based on the dynamic electricity pricing, the requirements of cooling loads, and all technical constraints, the dispatch model of the ice-storage air-conditioning system is formulated to minimize the operation cost. The Improved Ripple Bee Swarm Optimization (IRBSO) algorithm is proposed to solve the dispatch model of the ice storage air-conditioning system in a daily schedule on summer. Simulation results indicate that reasonable solutions provide a practical and flexible framework allowing the demand response of ice storage air-conditioning systems to demonstrate the optimization of its energy savings and operational efficiency and offering greater energy efficiency.

Keywords: ice storage system; air-conditioning system; dynamic electricity price; demand response; bee swarm optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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