Distributed Hybrid Model Predictive Secondary Control of DC Microgrids with Random Communication Disorders

A reliable and robust communication network is essential to exchange information between distributed generators (DGs) and accurately calculate their control actions in microgrids (MGs). However, the integration of the communication network and MGs poses challenges related to the flexibility, availability, and reliability of the system. Furthermore, communication disorders, such as time delays, packet loss, etc., can negatively impact the system's performance. Therefore, the design of a suitable secondary controller (SC) with a fast dynamic response to restore voltage and appropriate power-sharing is essential, while ensuring that the effects of communication disorders are eliminated. In this regard, an optimal distributed secondary controller (DSC) based on the hybrid model predictive control (HMPC) method is presented in this paper. For the purpose of realistic simulation, the simulation results are carried out in a mixed simulation based on Matlab and OMNET++, by considering IEEE 802.11 (WiFi) using the recently developed INET framework. In the implemented application layer, the recoveryUnit is responsible for reducing the impact of random communication delays and packet losses. The effectiveness and performance of the proposed method in comparison with a conventional MPC method are verified by simulation results.