计及相似日的VMD-FE-LSTM光伏出力组合预测模型研究

王涛; 李薇; 许野; 王旭; 王鑫鹏

doi:10.19912/j.0254-0096.tynxb.2023-0093

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太阳能学报 ›› 2024, Vol. 45 ›› Issue (5) : 490-499. DOI: 10.19912/j.0254-0096.tynxb.2023-0093

计及相似日的VMD-FE-LSTM光伏出力组合预测模型研究

王涛, 李薇, 许野, 王旭, 王鑫鹏

作者信息 +

STUDY ON PHOTOVOLTAIC POWER PREDICTION OF VMD-FE-LSTM CONSIDERING SIMILAR DAYS

Wang Tao, Li Wei, Xu Ye, Wang Xu, Wang Xinpeng

Author information +

文章历史 +

摘要

针对光伏出力的随机性和波动性导致预测精度偏低的问题,构建一套融合相似日理论、变分模态分解法、模糊熵计算方法和深度学习算法的光伏出力组合预测模型。在运用灰色关联分析法确定影响光伏出力的关键气象因素和使用综合相似距离法选定待预测日的历史相似日的基础上,利用模糊熵对变分模态分解的光伏出力分量进行重组,得到若干规律性较强的新序列;然后,分别构建各重组序列的长短期记忆神经网络预测模型;最终,对重组序列的预测值进行求和得到预测结果。该组合模型在云南某光伏电站的应用结果表明,对比其他模型,所提出的组合预测模型精度更高,具有很好的应用前景。

Abstract

In order to solve the low prediction-accuracy issue caused by strong randomness and volatility of photovoltaic output, in this study, a combined photovoltaic electricity prediction model composed of similar day theory, variational mode decomposition （VMD） method, fuzzy entropy （FE） and deep learning algorithm was established innovatively. The grey relation analysis （GRA） method was firstly used to identify the critical meteorological factors affecting photovoltaic output; Secondly, the historical similar day of predictive day was selected by aid of the comprehensive similar distance method; Then, the photovoltaic output sequence decomposed by VMD method was reorganized based on FE calculation result, leading to several new sequences with strong regularity. Next, the long-short term memory （LSTM） neural network prediction model was formulated for each sequence; Finally, the predicted result was obtained through summing up the predicted value of each sub-sequence. The applied results of this combined model in the photovoltaic plant of Yunnan province demonstrated that, compared with other models, the proposed model had the high prediction accuracy and good prospect.

导出引用

王涛, 李薇, 许野, 王旭, 王鑫鹏. 计及相似日的VMD-FE-LSTM光伏出力组合预测模型研究[J]. 太阳能学报. 2024, 45(5): 490-499 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0093

Wang Tao, Li Wei, Xu Ye, Wang Xu, Wang Xinpeng. STUDY ON PHOTOVOLTAIC POWER PREDICTION OF VMD-FE-LSTM CONSIDERING SIMILAR DAYS[J]. Acta Energiae Solaris Sinica. 2024, 45(5): 490-499 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0093

中图分类号： TM615

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