A model-based optimization of vapor compression refrigeration system for energy saving

Abstract

In this paper, a model-based global optimization strategy for vapor compression refrigeration system (VCRS) is proposed. The energy models of compressor, evaporator fan and condenser fan are established, and the energy consumption under different working conditions are predicted. To optimize the energy consumption of the entire system under the premise of ensuring indoor cooling demands, heat transfer models of the evaporator and condenser are also established. An objective function and component interaction optimization problem that satisfies indoor cooling capacity constraints are proposed. Six controllable variables related to the performance of the VCRS system are chosen as the control settings. The self-adaptive differential evolution (SADE) algorithm with fast convergence speed is used to solve the optimization problem, and the optimal control settings are obtained. Simulations are carried out and the proposed optimization strategy is compared with the traditional strategy. The results show that the global optimization of the operation strategy can achieve 15.18% energy saving effect on the test day.