在随机优化中的概率预测

2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) Pub Date : 2020-08-01 DOI:10.1109/PMAPS47429.2020.9183575

Arne Groß, Antonia Lenders, T. Zech, C. Wittwer, M. Diehl

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引用次数: 4

摘要

在未来几年，能源系统将从中央碳基发电厂转变为分散的可再生能源发电。由于这些系统依赖于天气等外部影响，因此预报的不确定性构成了一个问题。在本文中，我们将比较减轻这些预测不确定性影响的不同方法。我们的研究结果表明，估计这些不确定性并对其进行建模以进行优化可以增加单个系统的效益。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Using Probabilistic Forecasts in Stochastic Optimization

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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来源期刊

2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)

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