Table of contents
About this book
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.
- DOI https://doi.org/10.1007/978-1-4471-4968-2
- Copyright Information Springer-Verlag London 2013
- Publisher Name Springer, London
- eBook Packages Energy
- Print ISBN 978-1-4471-4967-5
- Online ISBN 978-1-4471-4968-2
- Series Print ISSN 2195-1284
- Series Online ISSN 2195-1292
- About this book