Energy Demand Analysis in Smart Grids

被引：0
|
作者：
Schellong, Wolfgang [1 ]
Gerngross, Sarah [1 ]
机构：
[1] Univ Technol Arts & Sci, Cologne, Germany
来源：
2015 INTERNATIONAL ENERGY AND SUSTAINABILITY CONFERENCE (IESC) | 2015年
关键词：
power demand forecast; mathematical modeling; smart grid; regression; neural network;
D O I：
暂无
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
The architecture of the future energy supply can be characterized by a combination of conventional centralized power plants with an increasing number of distributed energy resources, mainly including renewable energy systems. To manage smart grids operations a detailed knowledge of the power demand is necessary. The paper describes the energy data analysis and the basics of the mathematical modeling of the energy demand. A detailed analysis of the structure of load profiles is conducted on the basis of the load data of the power transmission network in Germany. Regression methods and artificial neural networks are used as forecast methods. The paper shows the integration of the forecast tools into energy management systems.
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页数：6
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