원문정보
초록
영어
Predicting the load in a building is essential for the optimal control of heating, ventilating and air-conditioning (HVAC) systems that use Ice Thermal Energy Storage (ITES) technology and also for cost and energy reduction of the non-storage systems. To solve the problems of the low accuracy of prediction by a single method, and most load predictions focusing on short-time prediction that cause reducing the practical significance, the application of the combined prediction method of time series and neural networks is presented in this paper. A case study shows that high accuracy is achieved by using the combined prediction model based on these two methods compared with the time series method in predicting the building load for longer time.
목차
1. Introduction
2. Time Series Model
3. Artificial Neural Networks (Ann) Model
4. The Combined Model
5. The Load Prediction by Using the Combined Model
5.1. Removing Periodicity of Load
5.2. Model Identification by Using Time Series Method
5.3. TES Load Prediction Based On the Combined Model
6. Conclusion
References