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• W3096353266 abstract "Electricity load forecasting plays an important role in planning and a vital role in the operational management of an electric power system based on smart grids. In this work, several data-driven approaches are used to forecast the individual electricity demand for the subsequent hour of three Italian households in a nanogrid context. For each user, the tested prediction models exploit only the historic series of total electricity consumption. The results show similar performances in all models implemented. Despite a widespread delay, the predictions follow the measurement trend well, while also highlighting the particular difficulty of predicting peak values." @default.
• W3096353266 created "2020-11-09" @default.
• W3096353266 creator A5026870973 @default.
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• W3096353266 date "2020-09-23" @default.
• W3096353266 modified "2023-10-01" @default.
• W3096353266 title "Consumption based-only load forecasting for individual households in nanogrids: a case study" @default.
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• W3096353266 doi "https://doi.org/10.23919/aeit50178.2020.9241127" @default.
• W3096353266 hasPublicationYear "2020" @default.
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