Optimal Control Research Based On Cooling Load Prediction In Ice Storage Air-conditioning System

In order to better balance the electric supply and lighten the tension of urban power grid, ice storage air-conditioning is becoming more popular in our country. There is a key problem for developing ice storage system that how to take optimal advantage of the ice storage system, and make the ice storage system more effective. Throwing these, consumer can achieve the best benefit. During recent years, the optimal control has replaced the chiller priority and ice priority as the most important control method in the ice storage system gradually.Base on the external-melt ice-on-coil thermal storage system in Guangzhou University City, we study of the optimal control of ice storage system and bring up the currently course of optimal control in ice storage system. In this course, we get the way how to predict the thermal load and the math model of load distribution.Firstly, this paper introduce the ice storage air-condoning system in Guangzhou University City, including the district cooling system, main equipment, operating condition and BAS. Author also collected the outdoor temperature and load data in May to July 2007, which provided the sample data for load prediction model.Accurate hourly load prediction is the important precondition for the ice storage system's optimal control. Based on BP theory, author establish temperature predicting ANN model for the next 24 hours. By this method, mean relative error (MRE) is reduced to 0.71% from 5.21%, compared to ASHRAE method. Then day cooling load predicting ANN model for workday and holiday is established respectively, and MRE reaches 4.71% for workday and 8.62% for holiday. According to the temperature predicting model has made, a next-24-hours hourly cooling load prediction ANN model is established, and mean absolute error (MAE) of hourly cooling load prediction is 188Rth. MRE is 5.15% and expected error percentage (EEP) is 2.08%.Finally, a cost-minimum model for ice storage system is established and numerical calculation is carried out. When cooling load is less than ice-melting ability, optimal control strategy is just ice priority, capacity of ice is equivalent to the prediction cooling load multiplied by a certain redundancy coefficient. When cooling load is more than ice-melting ability, according to the remaining ice, optimal control is to keep single chiller load to half of chiller cooling ability (80% normally) and tune ice-melting to meet load, the ice-storage tank is full of ice.Combining BAS, an optimal control blue print of ice storage air-conditioning is given in the final section, which can be used to guide the design of ice storage sysem.