The Optimal Daily Dispatch of Ice-Storage Air-Conditioning Systems

Abstract

In this paper, the Ant-based Radial Basis Function Network (ARBFN) is proposed to determine the optimal daily dispatch of ice-storage air-conditioning systems. ARBFN is a novel algorithm that is integrated into the Ant Colony Optimization and Radial Basis Function Network. ARBFN is used to construct the function of the cost and operation for each chiller and ice-storage tank and is used to simulate the polynomial function of the cooling load and the cost of power consumption. The best learning rate in the training process is adjusted in ARBFN to improve the accuracy of constructing models for chillers and ice-storage tanks. The electricity savings are thus 4.130% on a summer day and 7.381% on a non-summer day. The results have shown that ARBFN can more accurately calculate the actual power consumption and cooling capability of each chiller and ice-storage tank. Lastly, ACO is used to calculate the daily dispatch of the ice-storage air-conditioning system. The results demonstrated the optimization of energy savings and efficiency for the operation of the ice-storage air-conditioning system.

Automatic Control and System Theory and Advanced Applications—Volume 2

“…In the paper by Tien and Tsai [2], the authors approach the optimization of energy in ice-storage air conditioning systems. The adopted strategy is used to produce ice when air conditioning is not useful and to reuse ice to condition air in the phase when climate conditions require it.…”

“…The basic idea in [2] is recovering energy produced in excess. The very same idea is spreading in many automatic control-related papers.…”