Abstract We present and discuss a new technique based on information theory to detect in advance favorable periods of wind activity (positive ramps) for electricity generation. In addition this technique could also help in the analysis of plant operation and management protocols design. Real data from wind power plants in Germany is used; this information is freely available in the internet with reliable registers every 15 min. A simple protocol to mix such wind energy production with electricity coming from conventional sources is proposed as a way to test the proposed algorithm. The eight-year period 2010–2017 is analyzed looking for different behaviors in wind activity. The first five years (2010–2014) are employed to calibrate the method, while the remaining three years (2015–2017) are used to test previous calibration without any further variation in the tuning possibilities described below. Thus, the proposed protocol is tried on under different seasonal wind conditions. Both the algorithm and the general protocol could be adjusted to optimize performances according to regional conditions. In addition, this algorithm can also be used in retrospective studies to adjust productivity to operational conditions.

中文翻译：

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一种优化风能发电的新方法

摘要 我们提出并讨论了一种基于信息理论的新技术，可以提前检测风力活动的有利时期（正斜坡）以促进发电。此外，该技术还有助于分析工厂运行和管理协议设计。使用来自德国风力发电厂的真实数据；这些信息在互联网上免费提供，每 15 分钟就有一次可靠的登记。提出了一种将这种风能生产与来自传统来源的电力混合的简单协议，作为测试所提出算法的一种方式。分析了 2010 年至 2017 年的八年期间，寻找风活动中的不同行为。前五年（2010-2014）用于校准该方法，而剩下的三年（2015-2017 年）用于测试之前的校准，而不会对下文描述的调谐可能性产生任何进一步变化。因此，建议的协议在不同的季节性风条件下进行试验。算法和通用协议都可以根据区域条件进行调整以优化性能。此外，该算法还可用于回顾性研究，以根据操作条件调整生产率。