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- W2893994784 abstract "This paper proposes a method to generate daily wind power time series scenarios based on longitudinal-horizontal clustering strategy. Based on affinity propagation clustering (APC) algorithm, patterns of the daily wind power curves together with their probabilities are obtained by clustering analysis along the longitudinal and the horizontal directions. Representative wind power daily scenarios can be generated according to the obtained discrete stochastic models. The effectiveness tests show that these scenarios can maintain the daily time-sequence features of the historical wind power data. Compared to the conventional probability distribution function model, the scenarios generated by the proposed model show better accuracy in solving the optimal power flow problem, and much less number of scenarios are required to reflect the statistical regularities of wind power." @default.
- W2893994784 created "2018-10-05" @default.
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- W2893994784 date "2018-05-01" @default.
- W2893994784 modified "2023-09-26" @default.
- W2893994784 title "Scenario Generation of Wind Power Based on Longitudinal-Horizontal Clustering Strategy" @default.
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- W2893994784 doi "https://doi.org/10.1109/isgt-asia.2018.8467774" @default.
- W2893994784 hasPublicationYear "2018" @default.
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