Intelligent Energy Demand Forecasting

✍ Scribed by Wei-Chiang Hong (auth.)

Publisher: Springer-Verlag London
Year: 2013
Tongue: English
Leaves: 202
Series: Lecture Notes in Energy 10
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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 methods to calculate optimal electric energy allocation to reach equilibrium of the supply and demand.

Evolutionary algorithms and intelligent analytical tools to improve energy demand forecasting accuracy are explored and explained in relation to existing methods. To provide clearer picture of how these hybridized evolutionary algorithms and intelligent analytical tools are processed, Intelligent Energy Demand Forecasting emphasizes on improving the drawbacks of existing algorithms.

Written for researchers, postgraduates, and lecturers, Intelligent Energy Demand Forecasting helps to develop the skills and methods to provide more accurate energy demand forecasting by employing novel hybridized evolutionary algorithms and intelligent analytical tools.

✦ Table of Contents

Front Matter....Pages i-xiii
Introduction....Pages 1-20
Modeling for Energy Demand Forecasting....Pages 21-40
Evolutionary Algorithms in SVR’s Parameter Determination....Pages 41-92
Chaos/Cloud Theories to Avoid Trapping into Local Optimum....Pages 93-155
Recurrent/Seasonal Mechanism to Improve the Accurate Level of Forecasting....Pages 157-189

✦ Subjects

Energy Policy, Economics and Management; Energy Technology; Simulation and Modeling; Energy Economics

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