The identification of fault types and their locations is crucial for power system protection/operation when a fault occurs in the lines. In general, this involves a human-in-the-loop analysis to capture the transient voltage and current signals using a common format for transient data exchange for power systems (COMTRADE) file. Then, protection engineers can identify the fault types and the line locations after the incident. This paper proposes intelligent and novel methods of faulty line and location detection based on convolutional neural networks in the power system. The three-phase fault information contained in the COMTRADE file is converted to an image file and extracted adaptively by the proposed CNN, which is trained by a large number of images under various kinds of fault conditions and factors. A 500 kV power system is simulated to generate different types of electromagnetic fault transients. The test results show that the proposed CNN-based analyzer can classify the fault types and locations under various conditions and reduce the fault analysis efforts.

Power substations are the crucial nodes of an interconnected grid, serving as the points where power is transferred from the transmission/distribution grids to the loads. However, interconnected cyberphysical systems and communication-based operations at substations lead to many cybersecurity vulnerabilities. Therefore, more sophisticated cybersecurity vulnerability analyses and threat modeling are required during productization phases, and system hardening is mandatory for the commercialization of products. This paper shows the design and methods to test the cybersecurity of multicast messages for digital substations. The proposed vulnerability assessment methods are based on the semantics of IEC61850 Generic Object Oriented Substation Event (GOOSE) and Sampled Value (SV), and cybersecurity features from IEC62351-6. Different case scenarios for cyberattacks are considered to check the vulnerabilities of the device under test (DUT) based on the IEC62351-6 standard. In order to discover security vulnerabilities in a digital substation, the proposed cybersecurity tester will generate malicious packets that compromise the regular functionality. The results show that the proposed cybersecurity testing module is able to detect potential vulnerabilities in multicast messages and the authentication methods (e.g., message authentication code) of multicast communications. Both commercial and simulated devices are used for the case studies.

Phasor measurement units (PMUs) have been widely deployed for power grid monitoring, supporting system analytics, protection, automation, and control. However, with the continuous infiltration of inverter resources, the smart grid introduces more inherent uncertainties, leading to system state transformation. The most common method used by PMUs to estimate phasors is discrete Fourier transform (DFT) for 50 Hz and 60 Hz fundamental frequency, which is not applicable to capture dynamic disturbances under non-nominal frequency conditions. Unlikely, the modern grid operates more dynamically than the traditional power grid. The attenuated phasors can be produced if the grids operate at undesired frequencies during oscillation or dynamic events. The mono-phasor estimation algorithm may not fit all grid possible operating conditions. This paper proposes the wavelet transform (WT) based phasor estimation algorithm for both PMU classes. The phasor estimation algorithm is dynamically switched among the best options using energy theory for higher performance of the PMU-based applications. The proposed phasor estimation architecture simulation results indicate superior measurement accuracy performance.

The computing infrastructure to support the power grid monitoring and control evolves with the increasing system complexity and integration of distributed energy resources (DERs). The integration of DERs requires a stability assessment application to monitor and control at a faster rate compared to the legacy system. Distributed computing architecture provides opportunities for managing these key changes by introducing solutions within substation computers and digital devices such as phasor measurement unit. The proposed decentralized voltage stability using a distributed coordination platform is a secondary emergency control mechanism utilizing large amounts of data in real-time for faster monitoring and control with the legacy system. The developed algorithms have been validated using the IEEE 30, 57, 118, and 300 bus systems using offline and real-time hardware-in-the-loop testbed modeling and simulation. To demonstrate the flexibility of the distributed coordination blocks, multiple case studies and implementation are presented. With control decisions required under changing operating conditions, the IEEE 30 bus system is simulated in real-time using a digital simulator and a network simulator (NS-3). The impact of the SYN flood cyberattack and tolerance of the computing infrastructure to resulting missing data have also been illustrated.