Optimization for ice-storage air-conditioning system using particle swarm algorithm

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.