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首页> 外文期刊>European Journal of Control >Stochastic model predictive control of photovoltaic battery systems using a probabilistic forecast model
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Stochastic model predictive control of photovoltaic battery systems using a probabilistic forecast model

机译:使用概率预测模型的光伏电池系统的随机模型预测控制

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摘要

Photovoltaic (PV) battery systems allow citizens to take part in a more sustainable energy system. Using the electric energy produced on-site usually entails a financial benefit for the consumer. Furthermore, feed-in peaks during high photovoltaic generation sometimes cause local voltage violations. Therefore, a feed-in limit applies to PV battery systems. In our study, we present a method to generate an optimal control that takes into account the forecast uncertainties. To that end, a stochastic forecast model is developed and used in a dynamic programming framework. We carry out a simulation study assuming the regulatory constraints in Germany. In this setup, our method is shown to mitigate the effects of the forecast uncertainties better than comparable methods. (c) 2020 European Control Association. Published by Elsevier Ltd. All rights reserved.
机译:光伏(PV)电池系统允许公民参加更可持续的能源系统。使用现场生产的电能通常为消费者提供经济利益。此外,高光伏发电期间的进料峰有时会导致局部电压违规。因此,进料限制适用于光伏电池系统。在我们的研究中,我们提出了一种生成最佳控制的方法,考虑到预测不确定性。为此,开发了一个随机预测模型并用于动态编程框架。假设德国的监管限制,我们开展了一项模拟研究。在此设置中,我们的方法被示出了比可比方法更好地减轻预测不确定性的影响。 (c)2020欧洲控制协会。 elsevier有限公司出版。保留所有权利。

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