Privacy-preserving Energy Scheduling for Smart Grid with Renewables
We consider joint demand response and power procurement to optimize the average social welfare of a smart power grid system with renewable sources. The renewable sources such as wind and solar energy are intermittent and fluctuate rapidly. As a consequence, the demand response algorithm needs to be executed in real time to ensure the stability of a smart grid system with renewable sources. We develop a demand response algorithm that converges to the optimal solution with superlinear rates of convergence. In the simulation studies, the proposed algorithm converges roughly thirty time faster than the traditional subgradient algorithm. In addition, it is fully distributed and can be realized either synchronously or in asynchronous manner, which eases practical deployment.
© 2020 IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. Received February 13, 2020, accepted March 12, 2020, date of publication March 24, 2020, date of current version July 29, 2020. The associate editor coordinating the review of this manuscript and approving it for publication was Ning Kang.
Published - 09046244.pdf