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- W2905883908 abstract "In recent decades, the demand for electricity continues to rise and the power grid has become increasingly saturated. It is of great significance to analyse and predict the yearly peak load (YPL) in order to maintain the grid stability. In this paper, the generalized extreme value (GEV) theory is employed to analyse the distributions of YPL so as to build a prediction model. By applying the method to YPL data from 1970 to 2014 in the UK, the data is processed for the sake of excluding the impact of grid scale variations. Then, four types of fitting diagnostic graphs are used to check the goodness-of-fit of both the GEV distribution and the Weibull distribution model. Thereafter, an YPL prediction model based on the GEV distribution is proposed. With this forecast model, it is capable to predict the probability as well as the maximum relative future value based on the historic data. Meanwhile, the future YPL value can be easily calculated from the predicted results. Finally, by comparing the predicted YPL to actual data, the feasibility of this GEV-based prediction model of YPL is verified." @default.
- W2905883908 created "2019-01-01" @default.
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- W2905883908 date "2018-10-01" @default.
- W2905883908 modified "2023-09-27" @default.
- W2905883908 title "High Impact Low Frequency Peak Load Analysis using Extreme Value Theory" @default.
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- W2905883908 doi "https://doi.org/10.1109/ei2.2018.8582202" @default.
- W2905883908 hasPublicationYear "2018" @default.
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