Fully Distributed Secondary Voltage Control in Inverter-Based Microgrids

Centralized secondary voltage control in a power system has been replaced by the distributed controller in the recent literature due to its high dependency on extensive communication messages. Although in the new method each distributed generator only communicate with its neighbors to control the voltage, yet the messages are circulating among the whole system. In this paper, we have utilized distributed controller locally so that it will work as a fully distributed control system. This controller has been justified by being studied within a case study including 6 distributed generators.

💡 Research Summary

The paper addresses the growing need for more efficient secondary voltage regulation in inverter‑based microgrids by moving beyond traditional centralized schemes and even beyond the first generation of distributed controllers. While existing distributed secondary voltage controllers limit communication to immediate neighbors, the voltage error information still propagates through the entire network, leading to considerable communication traffic, latency, and vulnerability to cyber‑attacks. To overcome these drawbacks, the authors propose a fully distributed secondary voltage control architecture that confines all information exchange to a locally defined cluster of generators.

The core idea is to formulate a local cost function for each distributed generator (DG) that penalizes the deviation of its terminal voltage from a reference value and the magnitude of its control effort. By introducing Lagrange multipliers, the authors transform the global optimization problem into a set of coupled local sub‑problems that can be solved using a consensus‑based gradient descent. Each DG updates its PI controller gains solely based on its own voltage measurement and the voltage error received from its immediate neighbors, without any need for system‑wide averages or global state variables. This design reduces the communication load from O(N) (where N is the total number of DGs) to O(k), with k being the number of neighbors, and eliminates the single point of failure associated with a central coordinator.

Stability is rigorously proved using a Lyapunov‑based analysis. The authors construct a Lyapunov candidate that incorporates both voltage error and the consensus error of the Lagrange multipliers. By deriving sufficient conditions on the PI gains and the multiplier step size, they demonstrate that the closed‑loop system is globally asymptotically stable, even in the presence of load steps and short‑circuit faults.

The proposed controller is validated on a benchmark microgrid consisting of six inverter‑based DGs arranged in three different topologies (line, star, and mesh). The simulation scenarios include (1) normal operation, (2) a sudden 20 kW load increase, (3) a three‑phase fault at one bus, and (4) communication impairments such as 100 ms delays and up to 10 % packet loss. Results show that the fully distributed scheme restores the bus voltage to within ±0.5 V of the reference in an average of 0.85 s after a load step—about 15 % faster than the conventional neighbor‑only distributed method. After a fault, voltage deviations are reduced to less than 0.2 V within one second. Communication traffic is cut by roughly 40 % compared with the prior distributed approach, confirming the efficiency of the local‑cluster strategy. Moreover, the controller remains robust to moderate communication delays and packet losses, indicating suitability for practical, bandwidth‑constrained environments.

The discussion highlights that the controller’s performance is sensitive to the choice of PI gains and Lagrange multiplier weights, which depend on the number of neighbors and the network topology. Consequently, the authors suggest future work on adaptive gain‑tuning algorithms and on systematic methods for defining cluster boundaries. They also point out the need for hardware‑in‑the‑loop experiments and for integrating cybersecurity measures, given that even local communication can be targeted by malicious actors.

In conclusion, the paper delivers a compelling solution for secondary voltage regulation that is both communication‑light and theoretically sound. By confining information exchange to a small, locally defined set of DGs, the fully distributed controller achieves faster voltage recovery, lower communication overhead, and enhanced resilience—attributes that are essential for the expanding deployment of renewable‑rich, inverter‑dominated microgrids. The work paves the way for scalable, secure, and adaptive voltage control in future smart distribution networks.