Title :
Application of Gray Forecasting Model Optimized by Genetic Algorithm in Electricity Demand Forecasting
Author :
Xie, Yan ; Li, Mu
Author_Institution :
Dept. of Electr. & Inf. Eng., Wuhan Polytech. Univ., Wuhan, China
Abstract :
The traditional gray forecasting model is widely used in various fields, but it has some limitations. In this paper, a method based on genetic algorithm optimizing gray modeling process is introduced, and the flow chart of modeling is given. This method makes full use of the advantages of the gray forecasting model and characteristics of genetic algorithm to find global optimization. So the forecasting model is more accurate. The result shows that the model can be used as electricity demand an effective tool for forecasting.
Keywords :
genetic algorithms; grey systems; load forecasting; electricity demand forecasting; genetic algorithm; global optimization; gray forecasting model; Biological cells; Demand forecasting; Differential equations; Genetic algorithms; Grid computing; Iterative algorithms; Load forecasting; Optimization methods; Power engineering computing; Predictive models; electricity demand forecasting; genetic algorithm; gray modeling; optimization;
Conference_Titel :
Computer Modeling and Simulation, 2010. ICCMS '10. Second International Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-1-4244-5642-0
Electronic_ISBN :
978-1-4244-5643-7
DOI :
10.1109/ICCMS.2010.156
