A Federated Learning Algorithm That Combines DCScaffold and Differential Privacy for Load Prediction

A Federated Learning Algorithm That Combines DCScaffold and Differential Privacy for Load Prediction

Accurate residential load forecasting plays a crucial role in optimizing demand-side resource integration and fulfilling the needs of demand-side response initiatives. To tackle challenges, such as data heterogeneity, constrained communication resources, and data security in smart grid load predicti...

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Bibliographic Details
Main Authors:	Yong Xiao, Xin Jin, Tingzhe Pan, Zhenwei Yu, Li Ding
Format:	Article
Language:	English
Published:	MDPI AG 2025-03-01
Series:	Energies
Subjects:	federated learning load forecasting differential privacy data heterogeneity communication costs
Online Access:	https://www.mdpi.com/1996-1073/18/6/1482
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