Before revision:  While during the cooperation of local data owners, data exchange and centralized data storage may increase the risk of power consumer privacy breaches . To eliminate the potential risks, a novel NILM method named Fed-NILM ap-plying Federated Learning (FL) is proposed in this paper.
After revision:  While during the cooperation of local data owners, data exchange and centralized data storage may increase the risk of power consumer privacy breaches may be encountered by local data owners during the NILM model training. To prevent such potential risks, a novel NILM method named Fed-NILM ap-plying Federated Learning (FL) is proposed in this paper.