Research On Optimal Control Of Cooling System Energy Saving Of The Air-Condition

With the prevailing use of the Heating, Ventilation and Air-conditioning (HVAC) system, people not only have enjoyed the indoor comfortable environment but also have to face the problem of energy saving. Therefore, people have paid more attention to the issue that how to satisfy the requirements of both comfort and energy saving. Accordingly, the optimal strategy for HVAC control is a good solution for the problems above. Cooling system is the largest energy consumption subsystem in HVAC. From the perspective of system engineering, this article aims at the minimum energy conservation of cooling system, and the optimal control model is proposed and constructed.As for the cooling system of Ground Source Heat Pump, a lot of researches have been done in several aspects such as the cooling system facility model and its’ parameter identification, the cooling load prediction model, the cooling system optimal control model and its solving method. The main researches are as follows:Firstly, based on the analysis of the energy characteristic of facilities in the cooling system, we simplified and improved the facility model built in past few years and presented the mathematical model of energy consumption for the cooling system. With the help of the least square method, we identified the model parameter, which lays a foundation for the optimal control model of cooling system.Secondly, after analyzing influence factors of the cooling load, three kinds of hourly BP neural network models for cooling load prediction were established for Monday, Tuesday to Friday and the weekend. The 2013 year’s data of a Ground Source Heat Pump HVAC from a Jinan company were used to verify and analyze the models. The results basically obey Normal Distribution N(-0.47,5.662) and the possibility of the absolute prediction error which is less than 17 kW·h isn’t less than 99%. The error is within the acceptable range in practice.Thirdly, we analyzed and determined the physical constraints and constraints between equipment of the cooling system. The cooling system optimal control model is confirmed based on the objective function of the minimum energy consumption of cooling system. Considering the time-varying parameters, the parameter adaptive method of cooling system facilities is presented. Besides, the cross entropy optimization algorithm is proposed to solve the cooling system energy saving optimization model. We still used the data form the Jinan company in Jinan for case study, and the results show that the energy saving optimization control model can effectively reduce the energy consumption of HVAC.Finally, the coordination controller of cooling system is designed to monitor the system operation as well as the practical application of optimization control strategies. The work consists of the design of overall system framework, the design of hardware and software and the design of the application of WEB, which lays a solid foundation for transformation from theory to application.