Distributed dual gradient tracking for economic dispatch in power systems with noisy information

Distributed algorithms can be efficiently used for solving economic dispatch problem (EDP) in power systems. To implement a distributed algorithm, communication network is required, making the algorithm vulnerable to noise which may cause detrimental decisions or even instability. In this paper, we propose an agent-based method enables fully solution of EDP systems with noisy information exchange. Through novel design gradient tracking update and introducing suppression parameters, proposed effectively alleviate impact it shown more robust than existing algorithms. The convergence also established under standard assumptions. Moreover, strategy are presented accelerate our algorithm. Finally, tested on several IEEE bus demonstrate its effectiveness scalability.