Study On Energy Consumption Analysis And Energy Saving Operation Method Of Ground Source Heat Pump Air Conditioner

Energy consumption analysis of ground source heat pump air conditioning is an important approach to control energy cost,reduce the impact of energy consumption on the environment and improve the value of building equipment.Efficient energy consumption analysis and energy-saving strategy can reduce the operating cost of air conditioning system.Data analysis plays an important role in continuously monitoring and managing the energy consumption of the existing GSHP central air-conditioning system.Accurate prediction analysis and energy saving optimization can provide guidance for building equipment owners to improve the energy efficiency of central air-conditioning system.However,the energy consumption of central air conditioning system is often affected by many factors,such as the interaction of weather condition,schedule,equipment performance,etc.Moreover,real-time energy consumption has non-linear and non-stationary characteristics,and its energy consumption analysis and energy-saving operation are complex and challenging.The main research contents of this paper include:(1)Parameter optimization method,particle swarm algorithm,genetic algorithm and mind evolution algorithm were used to optimize BP neural network when predicting central air conditioning energy consumption.The accuracy and calculation time of various methods were compared,and an improved particle swarm algorithm optimizing BP neural network was proposed to change the inertia factor adaptively,thus improving the prediction accuracy.(2)The parallel pump system is modeled and optimized by genetic algorithm to improve accuracy and speed,which is consistent with the results of enumeration method.The three-dimensional diagram is used to observe the relationship between the variables.(3)Modeling and regression analysis of the main equipment of water-cooled central air conditioning were carried out to find the relationship between the total energy consumption of the air conditioning and the pump speed and the number of units in operation.The three-dimensional diagram is used to observe the relationship between energy consumption and flow.The genetic algorithm and simulated annealing algorithm were used to establish a new energy consumption optimization model to optimize the energy consumption per minute per day and reduce the energy consumption.(4)TRNSYS-based central air conditioning control system of ground source heat pump is designed according to the control mode of the air conditioning system in the actual project.The performance of buried pipe heat exchanger was analyzed and verified by simulation.The relation between unit efficiency and temperature flow is analyzed.In summer,water cooling unit and heat pump unit are added for refrigeration and cooling tower is used for cooling.According to the load,the pump operating frequency is changed to achieve energy conservation.(5)The load distribution of the ground source heat pump system makes it basically equal to the heat exchange amount of soil in winter and summer.The genetic algorithm,simulated annealing algorithm and improved immune genetic algorithm are used to optimize the energy saving of heat pump units and water cooling units respectively,and the results of the three methods were compared.Compared with genetic algorithm,the improved immune genetic algorithm has faster calculation speed and better optimization effect.To sum up,this paper analyzes the energy consumption data of ground source heat pump air conditioning and proposes a new energy saving optimization method for air conditioning.