Intelligent Energy Demand Forecasting

• Main Author: Hong, Wei-Chiang (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: London : Springer London : Imprint: Springer, 2013.
• Series: Lecture Notes in Energy, 10
• Subjects: Energy.; Energy policy.; Energy and state.; Computer simulation.; Electric power production.; Energy industries.; Energy Policy, Economics and Management.; Energy Technology.; Simulation and Modeling.; Energy Economics.

As industrial, commercial, and residential demands increase and with the rise of privatization and deregulation of the electric energy industry around the world, it is necessary to improve the performance of electric operational management. Intelligent Energy Demand Forecasting offers approaches and...

Table of Contents:

• 1.Introduction
• 2.Modeling for Energy Demand Forecasting
• 3.Evolutionary Algorithms in SVR’s Parameters Determination
• 4.Chaos/Cloud Theories to Avoid Trapping into Local Optimum
• 5.Recurrent/Seasonal Mechanism to Improve the Accurate Level of Forecasting.