Ice-storage air-conditioning system, while known for its advantage of shifting power consumption at peak hours during the day to the nighttime, can increase both energy consumption and CO(2) emission. The study adopts particle swarm algorithm to facilitate optimization of ice-storage air-conditioning systems and to develop optimal operating strategies, using minimal life cycle cost as the objective function. Increase in power consumption and CO(2) emission triggered by the use of ice-storage air-conditioning system is also examined and analyzed. Case study is based on a typical air-conditioning system in an office building. Results indicate that, with proper parameters, particle swarm algorithm can be effectively applied to the optimization of ice-storage air-conditioning system. in addition, optimal capacity of the ice-storage tank can be obtained. However, the volume of power consumption and CO(2) emission rises with the increase in ice-storage tank capacity. Consideration of additional costs of power consumption like carbon tax can therefore lead to changes in the optimal system configuration. (C) 2009 Elsevier Ltd. All rights reserved.