Networked Multi-Agent Distributed Control Framework for Demand Response
Jing Sheng Yu, Meng Yu · 2023
This paper addresses the challenges of massive and dispersed controllable electricity loads and vulnerability to time delay and packet loss for demand response in power systems. To improve the control efficiency of massive and dispersed electricity loads, a novel framework that contains an aggregation layer between the main site and dispersed resources is proposed. This framework enables dispersed electricity loads to follow the global objective in different geographical conditions. However, the increasing number of massive resources can lead to a communication explosion, especially when communication delay and packet loss are considered. To mitigate this issue, a distributed algorithm is introduced to reduce the communication volume, improving the convergence rate. We show that the proposed algorithm achieves consensus. Numerical examples demonstrate the effectiveness of the proposed algorithm on big-scale systems, showing a faster convergence rate than centralized methods.