Resilient Control Strategy and Analysis for Power Systems using (n, k)-Star Topology

Abstract

This research focuses on developing novel approaches in load balancing and restoration problems in electrical power distribution systems. The first approach introduces an inter-connected network topology, referred to as (n, k)-star topology. While power distribution systems can be constructed in different communication network topologies, the performance and fault assessment of the networked systems can be challenging to analyze. The (n, k)-star topologies have well defined performance and stability analysis metrics. Typically, these metrics are defined based on: i) degree, ii) diameter, and iii) conditional diagnosability of a faulty node. These parameters could be evaluated and assessed before a physical (n, k)-star topology power distribution system is constructed. Moreover, in the second approach, we evaluate load balancing problems by using a decentralized algorithm, i.e., the Multi-Agent System (MAS) based consensus algorithm on an (n, k)-star power topology. With aforementioned research approaches, an (n, k)-star power distribution system can be assessed with proposed metrics and assessed with encouraging results compared to other topology networked systems. Other encouraging results are found in efficiency and performance enhancement during information exchange using the decentralized algorithm. It has been proven that a load balance solution is convergent and asymptotically stable with a simple gain controller. The analysis can be achieved without constructing a physical network to help evaluate the design. Using the (n, k)-star topology and MAS, the load balancing/restoration problems can be solved much more quickly and accurately compared to other approaches shown in the literature.