Abstract
In order to improve the power grid load detection ability, an optimal method of load signal control of power based on state difference clustering is proposed, and the big data statistical analysis model of the power grid load is constructed. The clustering analysis and state mining of grid load are carried out by using the distributed detection method of association features, and the regression analysis model of grid load state difference is constructed to realize the state differential clustering of power grid load signal in high-dimensional phase space. Based on the classification and fusion of the extracted characteristic sets of grid load, big data analysis method is used to optimize the intelligent control of power grid load signal. The simulation results show that the proposed method has better accurate classification performance and lower misdivision rate, which improves the output stability of power grid load.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Zhao, Y., Lang, P. (2019). Optimal Method of Load Signal Control of Power Based on State Difference Clustering. 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 302. Springer, Cham. https://doi.org/10.1007/978-3-030-36405-2_7
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DOI: https://doi.org/10.1007/978-3-030-36405-2_7
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