Automated Network Topology Extraction Based on Graph Theory for Distributed Microgrid Protection in Dynamic Power Systems

Abstract

Unlike conventional grids, microgrids may utilize different connections and the overall topology can be variable. Considering this, it is required to develop a new protection concept/scheme for safe operation. Maintaining proper selective operation of the relays in these dynamic microgrid structures is a challenge itself. This requires monitoring the connections and updating time delays of the relays which will ensure the desired hierarchy in the system. In this paper, a novel approach has been taken where electrical networks are modeled according to graph theory. Smart algorithms, such as network graph discovery, local manager selection, and protection coordination strategy, are run to automatically detect topology changes and ensure proper protection operation. Furthermore, distributed nature of this method mitigates the risks associated with central controller-based schemes. The developed method is applicable to all power system operations, and it poses a unique implementation in postdisaster recovery. After a disaster or terror attack, this self-diagnosis, self-healing system can identify healthy sections and run them as a standalone system until the relief arrives. The ability of the protection system to be run as a distributed control makes sure that any healthy part of the system can be restructured and utilized, without the dependency, on any central controller or connection.

Efficient unmanned aerial vehicle paths design for post‐disaster damage assessment of overhead transmission lines

“…The computational complexity increases linearithmically with the number of clusters and power grid size. However, due to their inherent nature, power grids graphs are sparse [67], that is, the total number of edges is much less than the square of the number of nodes ( Γ ≪ N 2 ). This means that when obtaining the shortest path, some of the adjacent nodes might be revisited.…”

Figures of Graph Partitioning by Counting, Sequence and Layer Matrices

“…The classifiers discussed above seem perfectly fit for this task (like Table 10 contains a summary for Figure 1 as the exemplified case). 4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27, 28} U2, D2: {1, 2, 3,4,6,7,9,10,11,12,13,14,15,16,18,19,20,21,22,24,25,26,27 Regarding the pairing (U2, D2) appearing for C 28 − T d (Figure 27), this pairing does not appear for C 28 − D 2 (Figure 25 vs. Figure 26) suggesting that its ...…”

“…Graph theory is at the foundations of the Internet [1]; parallel [2] and distributed [3] computing; molecular topology [4] and dynamics [5]; and energy [6], electric [7] and electronic [8] circuit design.…”

Distributed System Vulnerability Model Based on Reliability Theory

“…When the property is false, there is a safe state that can be reached from the initial state, the exact definition of safe depends on the specific application. The state diagram is shown in Figure 1 [15][16].…”