Cucker-Smale Model Based Consensus Algorithm for Enhanced Convergence in Communication Network of Distributed Energy Systems

Consensus problems and algorithms are being increasingly applied in problems associated with the management of renewable energy integration in power systems. The concept of numerous microgrid integration needs appropriate coordination and communication, and optimization infrastructure that can be achieved with the multi-agent system formation solved with consensus algorithms. The primary objective of a consensus algorithm is to facilitate the process by which a group of distributed agents may come to a consensus over a quantity of interest by sharing information with one another through a communication network. In this respect, faster convergence quantifies the efficiency of the consensus algorithm. In this paper, Cucker-Smale flocking model is developed for the consensus algorithm. By using this model, consensus can be achieved by randomly choosing the initial positions and velocities of the birds with a minimum number of iterations. The proposed methodology is tested and validated on a ring and mesh communication network topologies with 3 and 12 nodes. The results obtained validate the efficiency of fast convergence of information sharing among the nodes.