ABSTRACT Hydropower is essential for global electricity production, but it consumes water by evaporation from the reservoir surface. Here, a new approach is introduced in relation to modelling the water footprint of electricity (WFe) from hydropower. Two of the most important variables in calculating the WFe are volume of evaporation (EV) and electricity production (EP). In this study, the random forest (RF) model was used to predict both EV and EP. For analysing hybrid models, wavelet transform was used and wavelet RF (WRF) models were developed. After decomposing the input variables by wavelet transform, the relief algorithm (RA) was used to recognize important components and inserted into the RF model. The proposed approach was applied at Mahabad Hydropower in Iran. The results suggest that applying the wavelet transform on input data and using algorithms such as RA can be regarded as a good approach for modelling of EV and EP.

中文翻译：

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开发一种使用小波变换结合随机森林模型模拟电力水足迹的间接方法

摘要 水电对全球电力生产至关重要，但它通过从水库表面蒸发消耗水。在这里，介绍了一种与水力发电 (WFe) 的水足迹建模相关的新方法。计算 WFe 时最重要的两个变量是蒸发量 (EV) 和发电量 (EP)。在本研究中，随机森林 (RF) 模型用于预测 EV 和 EP。为了分析混合模型，使用了小波变换并开发了小波 RF (WRF) 模型。通过小波变换对输入变量进行分解后，采用浮雕算法（RA）识别重要成分并插入到射频模型中。提议的方法已应用于伊朗的马哈巴德水电。