山东电力技术2024，Vol.51Issue(7)：19-26,60,9.DOI:10.20097/j.cnki.issn1007-9904.2024.07.003
基于EMD-DBO-BiLSTM的风电外送线路载流量预测方法
Wind Power Transmission Line Ampacity Prediction Method Based on EMD-DBO-BiLSTM
刘明林1
作者信息
- 1. 国网山东省电力公司,山东 济南 250001
- 折叠
摘要
Abstract
The ampacity of overhead transmission lines for wind power delivery is intricately linked with surrounding meteorological factors.Precisely forecasting this ampacity holds paramount significance in augmenting the transmission capability of wind farms.However,there are two major problems with existing load capacity prediction methods:insufficient extraction of data features of meteorological elements on transmission lines,and poor robustness of a single prediction model.In response,the empirical mode decomposition(EMD)algorithm is introduced to dissect the time series of meteorological elements into various components with differing frequencies,thereby uncovering latent correlation patterns within the data.Following this,the bidirectional long short-term memory(BiLSTM)neural network is deployed to individually predict each component,supplemented by the dung beetle optimizer(DBO)algorithm for fine-tuning BiLSTM hyperparameters,thus enhancing the stability of line carrying capacity predictions.Based on the above research,a wind power transmission line carrying capacity prediction method based on EMD-DBO-BiLSTM is proposed.Case analysis shows that compared to the four traditional methods,the average absolute error of the proposed method has decreased by 22.74%,9.30%,7.08%and 7.76%respectively.The analysis results verify the effectiveness of the method.关键词
架空线路/蜣螂优化/双向长短期记忆网络/经验模态分解/动态增容Key words
overhead transmission line/dung beetle optimizer/bidirectional long short-term memory network/empirical mode decomposition/dynamic rating increase分类
动力与电气工程引用本文复制引用
刘明林..基于EMD-DBO-BiLSTM的风电外送线路载流量预测方法[J].山东电力技术,2024,51(7):19-26,60,9.
