Deep Federated Adaptation: An Adaptative Residential Load Forecasting Approach with Federated Learning

Residential-level short-term load forecasting (STLF) is significant for power system oper-ation. Data-driven forecasting models, especially machine-learning-based models, are sensitive to the amount of data. However, privacy and security concerns raised by supervision departments and users limit the...

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Bibliographic Details
Main Authors:	Shi, Y. (Author), Xu, X. (Author)
Format:	Article
Language:	English
Published:	MDPI 2022
Subjects:	Computation time Data driven Deep learning domain adaptation Domain adaptation electric load forecasting Electric load forecasting Electric power plant loads federated learning Federated learning Forecasting models Global models Houses Power Residential load forecasting Short term load forecasting transfer learning Transfer learning
Online Access:	View Fulltext in Publisher

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View Fulltext in Publisher

Deep Federated Adaptation: An Adaptative Residential Load Forecasting Approach with Federated Learning

Internet

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