Schweitzer Engineering Laboratories, Inc. (SEL) designs, manufactures, and supports products and services ranging from generator and transmission protection to distribution automation and control systems. Founded in 1982 by Edmund O. Schweitzer III, SEL shipped the world's first digital protective relay. Presently, the company designs and manufactures embedded system products for protecting, monitoring, control, and metering of electric power systems.The company serves a variety of industries, including utilities, pulp and paper, transportation, water and wastewater, education, healthcare, government, mission-critical facilities, and oil, gas, and petrochemical operations.SEL is 100 percent employee owned, headquartered in Pullman, Washington, with about 2,300 based there in addition to 2,700 employees in field offices and other manufacturing facilities in about 60 national locations, in addition to another 50 international.
Turn-to-turn short-circuit faults (TSCFs) are among the most common stator faults in induction motor (IM) operating under normal conditions. Although incipient faults typically do not cause noticeable degradation in performance, they can evolve rapidly and lead to more severe failures. In this paper, we analyze the harmonic voltages in a soft-starter fed IM with TSCFs. We propose a method for detecting TSCF during the startup transient based on monitoring the the fifth-order positive-sequence voltage harmonic. An analytical model with a TSCF considering the fifth harmonic in the supply voltage is presented. We then analyze the IM voltages as a result of the operating states of the soft-starter until the bypass contactor closes. In the experimental tests, a three-phase motor with modified windings was used to emulate TSCF by deliberately short-circuiting up to 7% of the stator winding turns. This IM prototype was powered with a soft-starter with programmed voltage ramp times at around 5, 10 and 15 seconds. Based on the measurement voltages at the IM terminals, and considering variations in the supply voltages during the experimental tests, the results show that the positive-sequence magnitude of the fifth harmonic is an effective indicator for detecting faults involving 0.7% of damaged turns during the start-up transient.
Voltage sags (dips) are transient reductions in RMS voltage (10-90% of nominal for 0.5 cycles to 1 minute), represent one of the most critical power quality disturbances affecting industrial operations, causing equipment misoperation and significant economic losses. Accurate classification of voltage sags into the seven IEEE 1159 types (A-G) is essential for precise fault diagnosis, root cause analysis, and targeted mitigation strategies. However, traditional supervised learning approaches for voltage sag classification require extensive labeled datasets, which are expensive and time-consuming to obtain, limiting practical deployment in real world power systems. This paper introduces a semi-supervised learning framework combining FreeMatch with Vision Transformer architecture for label efficient voltage sag classification. By employing adaptive confidence thresholding and self adaptive fairness mechanisms, our approach effectively leverages unlabeled voltage sag waveform data while preventing class imbalance. Using synthetic three phase waveforms following IEEE 1159 and IEEE 1564 specifications, the method achieves competitive 84.14% accuracy with only 15% labeled data, approaching fully supervised performance while dramatically reducing annotation costs by 85%. This represents the first application of FreeMatch to voltage sag classification, specifically, demonstrating that advanced semi-supervised techniques enable practical deployment of fine-grained sag type identification in resource constrained industrial environments where expert labeling of power quality events remains a persistent bottleneck.
Successfully detecting high-impedance faults due to downed or broken power distribution conductors in a timely manner has been a big challenge for decades. When an energized broken conductor makes contact with the ground, it may result in a high-impedance fault that may be a challenge to detect using traditional protection methods. This paper provides a review of the existing solutions to detect downed conductors that have made contact with the ground. It is important to highlight that these solutions detect and isolate the affected circuit section only after the energized conductor has been on the ground for several seconds or minutes. This creates a critical “race-against-time” scenario, posing wildfire risks and public safety hazards. This paper dives deeper into an innovative method that was developed and successfully implemented on 12 kV distribution circuits to detect and isolate broken conductors while they are in the air and before they touch the ground. The IEC 61850 Generic Object-Oriented Substation Event and IEEE Std. C37.118 synchrophasor-based falling conductor protection solution is designed to detect and isolate broken conductors well within 500 ms of the break. This protection-speed solution is applicable to three-phase circuits along with two-phase and single-phase laterals that may be in high fire risk areas. This paper further explores the implementation of the falling conductor protection solution using Ethernet radios, and direct fiber, as well as private long-term evolution communication networks, which form the backbone of the falling conductor protection solution.
