Line Outage Identification Algorithm Based On Phasor Measurement Unit In Smart Grid

In recent years, power systems all over the world have experienced several large-scale blackouts caused by cascading failure. These cascading failures, induced by tiny perturbations in the electric power system, can cause large area collapse with disastrous consequences. Research on the cascading failure ensued from frequent occurrence of such accidents. One key to preventing such accidents is to locate the initial failure quickly and accurately, including both single and multi-transmission line outages. Thus, it is highly important to identify the transmission line outages as fast and accurately as possible in large-scale smart grid. With widespread deployment of the Phasor Measurement Unit (PMU), solving the transmission line outage identification problem using PMU becomes possible. Direct use of PMU for the transmission line outage detection is becoming a new research direction.In this paper, the problem is solved by mapping the circuit diagram to a graph and finding a particular edge, with measurements of real-time voltage phase angle information both before and after the line outage by PMU, trying to locate line outage in the grid through an optimization model.Starting with the principle of the DC power flow calculation, after which the graph theory is introduced, with the grid equivalent to a graph model. By modeling through the simplified DC power flow equation and incorporating the Laplace matrix of network topology, a system model is established to identify line outage. Based on the inherent sparse nature of the problem, an algorithm using global phase angle information from PMU is proposed to identify line outages.Limited by cost considerations, currently PMUs are only equipped to the local hub nodes and key transmission sections in the grid. This paper proposes an algorithm to locate line outages using only internal observation of PMU data, namely dividing the system into two parts:the internal system in which nodes can be measured by PMUs and external system in which nodes are immeasurable by PMUs. Only through PMU voltage phase angle measurements of the internal nodes to estimate line outages in the whole network. By blocking the weighted Laplacian matrix, an equation using only the partial observation is deduced. Identification of the external line outages is solved by combining with compressed sensing techniques such as orthogonal matching pursuit algorithm, which can achieve real-time identification. Simulation results on the IEEE 118 bus system show the algorithm reaches satisfactory accuracy of estimation without introducing additional computational complexity.In the case of multiple line outages, direct identification could be more time-consuming with worse accuracy. We introduce a random sampling perspective to this problem of line outage identification. It avoids the accumulated error caused by directly solving the problem in a greedy fashion. From the perspective of maximizing the likelihood probability, probabilistic model is introduced. Assuming that each transmission line outage is subject to a Bernoulli distribution, iterations are performed with respect to this probability using random samples. Simulation results on IEEE 118 bus system show that the proposed method has better accuracy without few iterations for multiple line outages situation.