Electric load forecasting methods: Tools for decision making

被引:379
作者
Hahn, Heiko [1 ]
Meyer-Nieberg, Silja [1 ]
Pickl, Stefan [1 ]
机构
[1] Univ Bundeswehr, Fak Informat, D-85577 Neubiberg, Germany
关键词
Electric load forecasting; Energy markets; Decision making; Survey; PARTICLE SWARM OPTIMIZATION; RECURRENT NEURAL-NETWORK; GENETIC ALGORITHM; TERM; DEMAND; MODEL; IDENTIFICATION; WEATHER;
D O I
10.1016/j.ejor.2009.01.062
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
For decision makers in the electricity sector, the decision process is complex with several different levels that have to be taken into consideration. These comprise for instance the planning of facilities and an optimal day-to-day operation of the power plant. These decisions address widely different time-horizons and aspects of the system. For accomplishing these tasks load forecasts are very important. Therefore, finding an appropriate approach and model is at core of the decision process. Due to the deregulation of energy markets, load forecasting has gained even more importance. In this article, we give an overview over the various models and methods used to predict future load demands. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:902 / 907
页数:6
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