Distributed Control Algorithms for Microgrids Under Wireless Communication Scenarios With Stochastic and Asymmetric Natures

Lei Huang, Wei Sun, Qian Zhang, Qiyue Li, Weitao Li

Abstract: The stochastic and asymmetric characteristics of wireless communication can degrade the accuracy of average voltage observation and the optimal dispatch of active power in microgrids, resulting in reduced power quality and higher operational costs. To mitigate these issues, this paper investigates the limitations of conventional distributed average consensus and resource allocation algorithms under asymmetric communication and identifies the factors impeding their convergence. Building on this analysis, improved distributed average consensus and resource allocation algorithms are proposed, incorporating the designed deviation recording and transmission mechanism to counteract communication asymmetry. Leveraging these improved algorithms, a distributed secondary control strategy for microgrids is proposed, ensuring robustness against stochastic asymmetric communication. Subsequently, convergence criteria of distributed control tailored to stochastic asymmetric communication scenarios are then derived, providing a foundation for the design of control parameters. Finally, hardware-in-the-loop (HIL) experiments validate the proposed strategy’s ability to achieve precise average voltage regulation and economically optimal active power dispatch, outperforming existing approaches in stochastic asymmetric communication environments. Note to Practitioners—This paper was motivated by the challenge of maintaining reliable voltage regulation and cost-effective power dispatch in microgrids that rely on wireless communication. In practice, wireless links such as Wi-Fi or Zigbee are subject to random interference and asymmetric message exchange, meaning that one device may frequently receive information without being able to send it back with equal reliability. Conventional distributed control algorithms cannot fully cope with these conditions, leading to voltage fluctuations and inefficient operation. This paper proposes enhanced distributed algorithms that record and compensate for deviations caused by irregular communication. With these improvements, generators can still achieve accurate voltage regulation and optimal power sharing even under stochastic and asymmetric conditions. Hardware-in-the-loop experiments confirm the feasibility and show clear performance improvements over existing methods. The current limitation is that the strategy has not yet been deployed in real microgrid systems. Future work will focus on field implementation and scaling. The approach may also benefit other distributed automation systems operating over unreliable wireless networks.

External IDs:dblp:journals/tase/HuangSZLL26