基于LSTM-Transformer的分布式光伏违规扩容识别方法

魏梅芳, 李雄, 周文晴, 李彬, 苏盛

太阳能学报 ›› 2025, Vol. 46 ›› Issue (12) : 324-332.

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太阳能学报 ›› 2025, Vol. 46 ›› Issue (12) : 324-332. DOI: 10.19912/j.0254-0096.tynxb.2024-1146

基于LSTM-Transformer的分布式光伏违规扩容识别方法

  • 魏梅芳1, 李雄2, 周文晴2, 李彬2, 苏盛2
作者信息 +

ILLEGAL EXPANDING CAPACITY IDENTIFICATION METHOD FOR DISTRIBUTED PHOTOVOLTAIC BASED ON LSTM-Transformer

  • Wei Meifang1, Li Xiong2, Zhou Wenqing2, Li Bin2, Su Sheng2
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文章历史 +

摘要

针对用户分布式光伏违规扩容威胁配电系统安全可靠运行的问题,提出一种基于长短期记忆网络(LSTM)-Transformer的分布式光伏违规扩容识别方法,首先进行时间序列数值和形态相似性预处理,筛选出与标杆电站气象情况一致的光伏电站;然后构建LSTM-Transformer模型,利用预处理后的数据进行训练和参数优化,预测光伏电站的理论出力;进而采用高斯核函数,基于实际发电功率与模型预测输出偏差计算违规扩容指数(IEI),基于IEI的数值和突变时间检测光伏用户违规扩容严重程度和扩容时间。通过实际光伏用户数据验证了所提方法的有效性。

Abstract

With the wide application of distributed PV systems, the problem of users' illegal capacity expansion is gradually highlighted, which poses a threat to the stable operation of the power grid. In order to effectively identify the expansion behavior of distributed PV users, a distributed PV violation expansion identification method based on LSTM-Transformer is proposed. The method firstly screens out the PV power plants that are consistent with the meteorological conditions of the benchmark power plants through time series numerical and morphological similarity preprocessing, then constructs the LSTM-Transformer model, and uses the preprocessed data for training and parameter optimization to predict the theoretical output power of PV power plants. By comparing the actual power generation with the predicted output of the model, Gaussian kernel function is used to calculate the illegal expansion index (EVI), detecting the severity of illegal expansion of PV users through the size of EVI, and determining the time of illegal expansion of users through the time of EVI mutation. The effectiveness of the proposed method was verified based on the actual data of photovoltaic users.

关键词

分布式光伏 / 长短期记忆网络 / Transformer模型 / 发电预测 / 高斯核函数 / 异常检测

Key words

distributed photovoltaic / long short-term memory network / Transformer model / generated power forecasting / Gaussian kernel function / anomaly detection

引用本文

导出引用
魏梅芳, 李雄, 周文晴, 李彬, 苏盛. 基于LSTM-Transformer的分布式光伏违规扩容识别方法[J]. 太阳能学报. 2025, 46(12): 324-332 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1146
Wei Meifang, Li Xiong, Zhou Wenqing, Li Bin, Su Sheng. ILLEGAL EXPANDING CAPACITY IDENTIFICATION METHOD FOR DISTRIBUTED PHOTOVOLTAIC BASED ON LSTM-Transformer[J]. Acta Energiae Solaris Sinica. 2025, 46(12): 324-332 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1146
中图分类号: TM615   

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基金

国网湖南省电力公司科技项目(5216AP220001)

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