Electricity Load Combination Prediction Based on Fuzzy Clustering

This paper proposes a power load combination forecasting method combining the fuzzy clustering analysis algorithm. Based on the analysis of historical load data, the method selects historical data similar to the predicted data, and establishes a similar day matching model based on fuzzy clustering....

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Bibliographic Details
Published in2023 6th International Conference on Energy, Electrical and Power Engineering (CEEPE) pp. 944 - 949
Main Authors Huang, Xianan, Jiang, Wenjin, Yang, Xiaodong, Hu, Zhenda, Liu, Lin, Tu, Xiazhe, Guo, Chuangxin
Format Conference Proceeding
LanguageEnglish
Published IEEE 12.05.2023
Subjects
Clustering algorithms
combination prediction
Data models
fuzzy clustering
Load forecasting
Power engineering
Power grids
Prediction algorithms
Predictive models
similar day
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Summary:This paper proposes a power load combination forecasting method combining the fuzzy clustering analysis algorithm. Based on the analysis of historical load data, the method selects historical data similar to the predicted data, and establishes a similar day matching model based on fuzzy clustering. According to the similar historical data, the combination prediction model is trained. Then the well-trained model is used to obtain the predicted value. Finally, the data of a power grid from April 2019 to June 2020 is used as historical data, and the data in July 2020 is used as test data to prove the effectiveness of the model.
DOI:10.1109/CEEPE58418.2023.10165887