The role of cooperative information spreading paradigms for Smart Grid monitoring

The large-scale deployment of the Smart Grid paradigm will support the evolution of conventional electrical power systems toward active, flexible and self-healing web energy networks composed of distributed and cooperative energy resources. In this field, the application of traditional hierarchical monitoring paradigms has some disadvantages that could hinder their application in Smart Grids where the constant growth of grid complexity and the need for massive pervasion of Distribution Generation Systems (DGS) require more scalable, more flexible control and regulation paradigms. To overcome these challenges, this paper proposes the concept of a decentralized non-hierarchical monitoring architecture based on intelligent and cooperative smart entities. These devices employ traditional sensors to acquire local bus variables and run information spreading algorithms in order to assess the main variables describing the global grid state. Two average consensus algorithms are compared : Kuramoto and Gossiping respectively and important remarks are underlined.