A Partition Optimization Control Strategy For River Water Source Heat Pump System

Development of renewable energy and improve energy efficiency is an important measure to adjust energy structure, to ease the energy supply pressure. As a renewable energy technology, river water source heat pump system is famous for its energy saving features. In this paper, the river water source heat pump system was studied. Based on the analysis of river water temperature and the building load characteristics, the partition optimal control strategy was proposed to further enhance the energy-saving potential of the system.Whether a river water source heat pump system can achieve the desired energy savings or not depends largely on the temperature characteristics of the river. In order to grasp the variation of temperature of the river, river water temperature data was analysed. A river water temperature model was established using mutual information method. NSC(Nash efficiency coefficient), RMSE(root mean square error), MAE(the maximum absolute error) as criteria were used to verify the accuracy of temperature model established, the results show that the temperature model capable of expressing the relationship between the average daily temperature and daily mean water temperature, the temperature model can provide temperature data for the design and regulation of water source heat pump system. Another important factor affecting the river water source heat pump system is the load characteristics of the building. Using DeST software, load models of hotels, shopping malls, office buildings were established, and load characteristics together with river temperature distribution characteristics were analysed.With river water source heat pump system energy consumption model, a sensitivity analysis was performed to determine the key factors affecting the system energy consumption. Based on the above analysis, the air mass flow mair, chilling water flow mIWP, the set chilled water outlet temperature Tset, intake water flow mEWP was regulated to adapting its produced thermal energy to the actual thermal demand.Finally, a case study was presented using TRNSYS simulation platform, energy consumption of the reference control strategy(traditiongal on/off), variable frequency optimization control strategy(no partitions) and partition optimal control strategy were analyzed. The simulation results show that in whole cooling season, variable frequency optimization control strategy can achieve an energy saving rate of 7.11% compared with the reference control strategy, partition optimal control strategy can achieve an energy saving rate of 19.93% compared with the partition optimal control strategy.