Optimization of ice-storage air conditioning system With ASAGA

As a distributed energy storage system, ice-storage air conditioning system can not only reduce the cost and improve the efficiency of the existing power system but it can also plays an important role in the demand side management. But how to get the optimal allocation proportion of cooling load between ice storage and chillers still is an unsolved problem. A nonlinear programming is constructed based on the improved model of facilities to achieve the optimization of the ice-storage air conditioning system. Then, an adaptive simulated annealing genetic algorithm (ASAGA) is proposed to solve this nonlinear problem. Finally, the effectiveness of the given facility models and nonlinear program as well as ASAGA are tested by a practical project analysis.