Abstract
Traditional data mining algorithms have problems such as poor applicability, high false positive rate or high false positive rate, resulting in low security and stability of the power system. For this reason, the regional photovoltaic power generation data mining algorithm is studied. Classification of data sources facilitates correlation calculations, and matrix relationships are used to calculate data associations. Combined with the data relevance, the association rules are output, and the output results inherit the clustering processing and time series distribution of the implicit data, thereby realizing the extraction of hidden data and completing the regional photovoltaic power generation data mining. The experimental results show that the regional PV power generation data mining algorithm has high stability and can effectively solve the system security problem.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Lei, Z., Yang, Yb. (2019). Research on Data Mining Algorithm for Regional Photovoltaic Generation. In: Gui, G., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 301. Springer, Cham. https://doi.org/10.1007/978-3-030-36402-1_46
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DOI: https://doi.org/10.1007/978-3-030-36402-1_46
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