Using Probabilistic Forecasts in Stochastic Optimization

被引：3
|
作者：
Gross, Arne [1 ]
Lenders, Antonia [1 ]
Zech, Tobias [1 ]
Wittwer, Christof [1 ]
Dieh, Moritz [2 ]
机构：
[1] Fraunhofer Inst Solar Energy Syst ISE, Freiburg, Germany
[2] Univ Freiburg, IMTEK, Freiburg, Germany
来源：
2020 INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS (PMAPS) | 2020年
关键词：
Stochastic Dynamic Programming; Model Predictive Control; Probabilistic PV Forecasting; Probabilistic Load Forecasting; PV Battery Systems; MODEL-PREDICTIVE CONTROL; ENERGY MANAGEMENT;
D O I：
10.1109/pmaps47429.2020.9183575
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
In the coming years, the energy system will be transformed from central carbon-based power plants to decentralized renewable generation. Due to the dependency of these systems on external influences such as the weather, forecast uncertainties pose a problem. In this paper, we will compare different methods that mitigate the impact of these forecast uncertainties. Our results suggest that estimating these uncertainties and modeling them for optimization can increase the benefit for the individual system.
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收藏
页数：6
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