A Novel Control Method for Active Power Sharing in Renewable-Energy-Based Micro Distribution Networks

The microgrid is an emerging trend in modern power systems. Microgrids consist of controllable power sources, storage, and loads. An elaborate control infrastructure is established to regulate and synchronize the interaction of these components. The control scheme is divided into a hierarchy of several layers, where each layer is composed of multi-agents performing their dedicated functions and arriving at a consensus of corrective values. Lateral and horizontal interaction of such multi-agents forms a comprehensive hierarchical control structure that regulates the microgrid operation to achieve a compendium of objectives, including power sharing, voltage, and frequency regulation. The success of a multi-agent-based control scheme is dependent on the health of the communication media that is used to relay measurements and control signals. Delays in the transmission of control signals result in an overall deterioration of the control performance and non-convergence. This paper proposes novel multi-agent moving average estimators to mitigate the effect of latent communication links and establishes a hierarchical control scheme incorporating these average estimators to accurately arrive at system values during communication delays. Mathematical models are established for the complete microgrid system to test the stability of the proposed method against conventional consensus-based methods. Case-wise simulation studies and lab-scale experimental verification further establish the efficacy and superiority of the proposed control scheme in comparison with other conventionally used control methods.

Automated summary

The microgrid is a new trend in modern power systems, consisting of controllable power sources, storage, and loads. A hierarchical control scheme composed of multi-agents is established to regulate and synchronize the interaction of these components. Communication delays in transmitting control signals can lead to deteriorated control performance, but this paper proposes novel multi-agent moving average estimators to mitigate the effect of latent communication links and establishes a hierarchical control scheme incorporating these estimators for accurate system values during delays. Mathematical models, simulation studies, and experimental verification demonstrate the efficacy and superiority of the proposed control scheme in comparison with conventional methods.