Prediction of Distribution Network Line Loss Rate Based on Ensemble Learning
Jian-Yu Ren,
Jian-Wei Zhao,
Nan Pan
et al.
Abstract:The distribution network line loss rate is a crucial factor in improving the economic efficiency of power grids. However, the traditional prediction model has low accuracy. This study proposes a predictive method based on data preprocessing and model integration to improve accuracy. Data preprocessing employs dynamic cleaning technology with machine learning to enhance data quality. Model integration combines long short-term memory (LSTM), linear regression, and extreme gradient boosting (XGBoost) models to ac… Show more
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