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- W4386711580 abstract "Abstract As electricity market reforms continue and households consume more electricity, Household Electricity Response (HER) becomes an essential part of Demand Response (DR). The ability of households to adjust their electricity demand is a critical factor in evaluating the demand-side response capacity of the power systems. Therefore, a prediction method of household adjustable electricity (HAE) based on cross-domain generalization is proposed to solve the problem. In our method, the convolutional neural networks (CNNs) model with Maximum Mean Discrepancy (MMD) loss term is constructed to realize the goal, which improves the accuracy and generalization of HAE prediction in different regions and provides technical support for DR." @default.
- W4386711580 created "2023-09-14" @default.
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- W4386711580 date "2023-09-01" @default.
- W4386711580 modified "2023-10-18" @default.
- W4386711580 title "The Method of Household Adjustable Electricity Prediction Based on Maximum Mean Discrepancy" @default.
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- W4386711580 doi "https://doi.org/10.1088/1742-6596/2588/1/012021" @default.
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