Ali Moradi Amani

Finding the Most Influential Nodes in Pinning Controllability of Complex Networks

Identifying the best drivers (i.e., the nodes to apply the control signals in a large complex network), which gives the fastest synchronization to the reference state, is a challenge in pinning control of a network. There is not yet a method that exactly predicts a set of best drivers. In this brief, we introduce a novel method that gives first-order approximation for the importance of nodes in pinning control. A spectral measure (the largest eigenvalue of the augmented Laplacian matrix divided by the smallest eigenvalue) is considered as a pinning controllability metric. We develop this method based on the sensitivity analysis of the Laplacian eigenratio, resulting in the scoring of nodes based on their importance in pinning control. The method is rather simple to compute and needs a single eigendecomposition of the Laplacian matrix of the connection graph. Applying this technique on a number of model networks reveals its effectiveness over heuristic approaches.

Roles of node dynamics and data network structure on cooperative secondary control of distributed power grids

In this paper we study stability of a power system consisting distributed generation units. A complete model for the power grid including dynamics of loads as well as interchange of power is taken into account. A cooperative secondary control scheme takes into account internal dynamic of each node and is implemented to improve the stability of the system. In this paper, a condition for the stability of power grid in the presence of communication network is achieved. We support the results by numerical simulations on various connection topologies including scale-free and random structures. We find that increasing the number of communication links does not generally improve the stability of the whole power network.