Research Article
Research on Short-Term Load Forecasting Based on PCA-GM
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@INPROCEEDINGS{10.1007/978-3-030-51103-6_15, author={Hai-Hong Bian and Qian Wang and Linlin Tian}, title={Research on Short-Term Load Forecasting Based on PCA-GM}, proceedings={Multimedia Technology and Enhanced Learning. Second EAI International Conference, ICMTEL 2020, Leicester, UK, April 10-11, 2020, Proceedings, Part II}, proceedings_a={ICMTEL PART 2}, year={2020}, month={7}, keywords={Short-term Load forecasting PCA-GM}, doi={10.1007/978-3-030-51103-6_15} }- Hai-Hong Bian
Qian Wang
Linlin Tian
Year: 2020
Research on Short-Term Load Forecasting Based on PCA-GM
ICMTEL PART 2
Springer
DOI: 10.1007/978-3-030-51103-6_15
Abstract
In this paper, a short-term load forecasting model based on PCA dimensionality reduction technology and grey theory is proposed. After the correlation analysis between meteorological factors and load indicators, the data is carried out by combining PCA dimensionality reduction technology and grey theoretical load forecasting model. In this paper, the validity of the load data verification model in a western region is selected. The analysis of the example shows that compared with the general gray prediction model GM (1, 1), the accuracy of the model prediction result is much higher, which proves the model. Effectiveness and practicality.
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