Privacy-aware optimal load scheduling for energy management system of smart home

The wide deployment of smart meters has brought the significant challenge to privacy protection of residential users. However, the existing rechargeable battery schemes cannot protect the privacy when the consumer power usage is either high or low for a long period. A new energy management scheme for smart home is proposed to enhance the privacy protection ability while ensuring the electricity cost and comfort in the article. This article enhances privacy while addressing the joint optimization problem for smart home. Firstly, an energy management architecture incorporated the rechargeable batteries and renewable resources is constructed for enhancing privacy, where the user's privacy is enhanced by utilizing the rechargeable batteries as well as the home appliance shifting. Secondly, the incentive probability is defined according to user satisfaction and the participation degree of demand response, and a probabilistic incentive mechanism is introduced to encourage more users to participate in household load schedule. Finally, the power cost, privacy as well as user satisfaction are systematically characterized in the objective function of the load scheduling, which is further decomposed by load classification. Then a hierarchical optimization method is leveraged to solve the optimal problem, maximizing the utilization of both residential users and power provider. The simulation results based on Pecan Street dataset validate the performance of the proposed strategy, and compared with the rechargeable battery schemes, the proposed scheme can save 19.72% of the electricity cost while ensuring privacy. & COPY; 2023 Elsevier Ltd. All rights reserved.