Phasor Measurement Units Optimal Placement and Performance Limits for Fault Localization

Abstract

In this paper, the performance limits of faults localization are investigated using synchrophasor data. The focus is on a non-trivial operating regime where the number of Phasor Measurement Unit (PMU) sensors available is insufficient to have full observability of the grid state. Proposed analysis uses the Kullback Leibler (KL) divergence between different fault location hypotheses, which are associated with the observation model. This analysis shows that the most likely locations are concentrated in clusters of buses more tightly connected to the actual fault site akin to graph communities. Consequently, a PMU placement strategy is derived that achieves a near-optimal resolution for localizing faults for a given number of sensors. The problem is also analyzed from the perspective of sampling a graph signal, and how the placement of the PMUs i.e. the spatial sampling pattern and the topological characteristic of the grid affect the ability to successfully localize faults is studied. To highlight the superior performance of presented fault localization and placement algorithms, the proposed strategy is applied to a modified IEEE 34, IEEE-123 bus test cases and to data from a real distribution grid. Additionally, the detection of cyberphysical attacks is also examined where PMU data and relevant Supervisory Control and Data Acquisition (SCADA) network traffic information are compared to determine if a network breach has affected the integrity of the system information and/or operations [2].

CPS Attacks Mitigation Approaches on Power Electronic Systems With Security Challenges for Smart Grid Applications: A Review

“…Smart grid has synchrophasor-based cyber-security that can provide real-time data to the EMS for controlling and monitoring the physical network [57], [58]. Modern synchrophasor instruments, e.g., digital fault record (DFR), PMU, along with protecting relays with PMU functionality, are vulnerable to various errors [59], [60]. These comprise cyber-attacks, which is considered a challenging issue as the equipment is intertwined with numerous legacy instruments with protection/no protection alongside cyber-attacks [61].…”

Measurement placement in electric power transmission and distribution grids: Review of concepts, methods, and research needs

“…• n c : number of candidate locations for measurement placement; IEEE 13-node 13 [171,186,206] UKGDS #1 16 [181,183] Italy #2 17 [176] Italy #3 25 [199,200] 30-node 30 [162,195] 32-node 32 [185] IEEE 33-node 33 [186,191,194,197] IEEE 34-node 34 [167, 171-174, 201, 204, 205] IEEE 37-node 37 [195] Italy #4 51 [177] 55-node 55 [187] IEEE 69-node 69 [188,190] 70-node 70 [185] UKGDS #2 77 [180,181] Netherlands 77 [184] India #3 85 [188,190] Italy #5 84 [177] Italy #6 95 [182] UKGDS #3 95 [175,178,179,189] 119-node 119 [185,191] IEEE 123-node 123 [171,193,195,205] Brazil #4 134 [203] Brazil #3 136 [192] Brazil #5 141 [202] 183-node 183 [195] Europe #2 906 [195] IEEE 8500-node 8500 [193] • v (k) q : measured voltage phasor on bus q ...…”

Measurement placement in electric power transmission and distribution grids: Review of concepts, methods, and research needs

“…The work in [205] is mostly concerned with the detection of anomalies in distribution grids using micro-PMUs. A comprehensive anomaly detection framework is developed.…”

“…The key idea in [205] is to project (62) onto the subspace spanned by the left singular vector, υ u , corresponding to the smallest singular value of L u . It is expected that this procedure suppresses the effect of quantities associated with buses in which micro-PMUs are not available, thereby making the anomaly detection framework a function of available micro-PMU measurements only.…”