In order to solve the problems of low equipment running hours and low energy saving rate caused by the mismatch between the configuration capacity of the distributed energy system and the actual load

a capacity optimization model considering variable electric refrigeration rate is proposed

in which the particle swarm optimization(PSO) algorithm with the compression factor and traversal method is used

and the maximum primary energy saving rate and annual total cost saving rate is taken as the target. Moreover

this model is applied to the capacity optimization of distributed energy system in a dormitory building in Beijing

and the result is compared with that by the method considering fixed electric refrigeration rate

and the annual operation of the heat storage system under two different optimization methods is analyzed. The final result shows that

the capacity optimization method considering variable electric refrigeration rate could effectively improve the economy and comprehensive performance of the system. The hourly optimized electric refrigeration rate can reduce both the residual heat of the system and the capacity of the heat storage system. In addition

the influences of capacity change of key equipment on system performance are analyzed.