Intelligent Energy Demand Forecasting

Description

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.

Subjects

Series Statement

• Lecture Notes in Energy -- 10

Links

• http://dx.doi.org/10.1007/978-1-4471-4968-2

Other Editions

• Intelligent Energy Demand ForecastingElectronic resourceImprint: Springer2013-01-01
• Intelligent Energy Demand ForecastingHardcoverBrand: Springer2013-03-07
• Intelligent Energy Demand ForecastingPaperbackSpringer2013-03-27
• Intelligent Energy Demand ForecastingSpringer2015-01-01