Abstract
Due to the importance of energy user privacy protection and the development of energy integration technologies, Integrated Demand Response (IDR) of Multi-Energy Systems (MES) should give flexibility to users' energy demand under the premise of privacy protection. In this paper, the coupling model of the MES is designed first. Then, a federated learning(FL) mechanism is designed for local system operators (LSOs), and all LSOs are interconnected with a central parameter server in the MES. In each IDR process, with the multi-energy power balance as the constraint, the FL architecture can calculate the optimal convergence value of the benefits of each LSO under the premise of ensuring customer privacy, and then obtain the optimal value of the benefits of the entire MES. The simulation results of the MES designed at the end of the paper demonstrate the feasibility of this data-driven member interaction model.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
