Distributed Consensus-Based Multi-Source Cooperative AGC Method for Microgrids Under Extreme Disasters
Extreme disasters compromise the coordinated frequency regulation of heterogeneous microgrid resources, as centralized automatic generation control (AGC) architectures exhibit single-point vulnerability, high computational burden, and limited scalability. This paper proposes a multi-agent distributed consensus-based cooperative AGC method. A distributed consensus multi-source AGC framework is constructed to enable cooperative secondary frequency regulation. A distributed consensus-based area control error (ACE) discovery algorithm is developed, allowing each regulation unit to communicate only with adjacent units and converge to a global ACE equilibrium. Each unit then participates in frequency regulation through an independently designed PI controller based on its dynamic response characteristics. During the latter half of the regulation period, the output power of slower-response units is adjusted to release the frequency response capability of faster-response units, reserving regulation capacity for subsequent cycles. Simulation models of gas turbines, diesel generators, wind turbines, photovoltaics, and hydrogen fuel cells are established in Matlab/Simulink. Results demonstrate that the proposed AGC method effectively coordinates heterogeneous regulation units, exhibits strong anti-interference capability under extreme disasters, and avoids the need for retraining associated with reinforcement learning approaches. The method offers reduced computational burden, high scalability, and resilience to single-point failures.