Partial Information Perturbation-Based Specified Time Consensus With Asynchronous Switching: A Distributed Energy Dispatching Strategy

With the widespread integration of distributed renewable energy, traditional centralized dispatching architectures face challenges in robustness and flexibility. It is essential to develop distributed energy optimization strategies to enhance the efficient utilization of renewable energy. Nevertheless, the exchange of information in distributed dispatching task execution entails potential risks of sensitive data exposure. This paper aims to investigate an improved privacy masking-based distributed privacy-preserving specified-time consensus algorithm for the economic dispatch problem (EDP) in energy systems (ESs). Therein, a privacy protection mechanism suitable for directed graphs is proposed by integrating state decomposition mechanisms and privacy masking techniques, ensuring both the accuracy of optimal solutions for EDP and the generality of communication topologies. Under this mechanism, a consensus algorithm with specified time performance is introduced, eliminating complex parameter constraints associated with predefined time bounds in distributed tasks. Additionally, an asynchronous switching law is incorporated into the privacy-preserving consensus protocol, allowing the algorithm to better adapt to environmental changes and dynamic parameter adjustments. Finally, the proposed method is applied to solve EDP in combined heat and power (CHP)-based ESs, demonstrating its excellent convergence and privacy performance.