Browsing by Author "Delport, Jacques"
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- Critical Substation Risk Assessment and MitigationDelport, Jacques (Virginia Tech, 2018-06-01)Substations are joints in the power system that represent nodes that are vital to stable and reliable operation of the power system. They contrast the rest of the power system in that they are a dense combination of critical components causing all of them to be simultaneously vulnerable to one isolated incident: weather, attack, or other common failure modes. Undoubtedly, the loss of these vital links will have a severe impact to the to the power grid to varying degrees. This work creates a cascading model based on protection system misoperations to estimate system risk from loss-of-substation events in order to assess each substation's criticality. A continuation power flow method is utilized for estimating voltage collapse during cascades. Transient stability is included through the use of a supervised machine learning algorithm called random forests. These forests allow for fast, robust and accurate prediction of transient stability during loss-of-substation initiated cascades. Substation risk indices are incorporated into a preventative optimal power flow (OPF) to reduce the risk of critical substations. This risk-based dispatch represents an easily scalable, robust algorithm for reducing risk associated with substation losses. This new dispatch allows operators to operate at a higher cost operating point for short periods in which substations may likely be lost, such as large weather events, likely attacks, etc. and significantly reduce system risk associated with those losses. System risk is then studied considering the interaction of a power grid utility trying to protect their critical substations under a constrained budget and a potential attacker with insider information on critical substations. This is studied under a zero-sum game theoretic framework in which the utility is trying to confuse the attacker. A model is then developed to analyze how a utility may create a robust strategy of protection that cannot be heavily exploited while taking advantage of any mistakes potential attackers may make.
- Lateral Motion Prediction of On-Road Preceding Vehicles: A Data-Driven ApproachWang, Chen; Delport, Jacques; Wang, Yan (MDPI, 2019-05-07)Drivers’ behaviors and decision making on the road directly affect the safety of themselves, other drivers, and pedestrians. However, as distinct entities, people cannot predict the motions of surrounding vehicles and they have difficulty in performing safe reactionary driving maneuvers in a short time period. To overcome the limitations of making an immediate prediction, in this work, we propose a two-stage data-driven approach: classifying driving patterns of on-road surrounding vehicles using the Gaussian mixture models (GMM); and predicting vehicles’ short-term lateral motions (i.e., left/right turn and left/right lane change) based on real-world vehicle mobility data, provided by the U.S. Department of Transportation, with different ensemble decision trees. We considered several important kinetic features and higher order kinematic variables. The research results of our proposed approach demonstrate the effectiveness of pattern classification and on-road lateral motion prediction. This methodology framework has the potential to be incorporated into current data-driven collision warning systems, to enable more practical on-road preprocessing in intelligent vehicles, and to be applied in autopilot-driving scenarios.
- Synchronized Measurement of Machine Rotor Angle and Its ApplicationDelport, Jacques (Virginia Tech, 2015-01-31)The internal voltage angle of a generator is an important parameter that indicates the stability, both transient and steady-state, of the generator. This paper proposes a method of measuring and synchronizing the internal angle using a microprocessor and an optical encoder installed on the shaft of a generator. With a synchronized angle measurement, accurate stability studies and wide-area controls can be implemented. The experimental setup for measuring the rotor angle of a generator is explained in this work. A wide-area power system stabilizer implementing the synchronized angle measurement is then investigated using a four machine, two-area system. A synchronized remote feedback rotor angle signal is included in a traditional stabilizer design. It is shown that this remote signal helps increase the stability of the system while also having the benefit of being able to be predicted accurately. This capability makes bad data detection and communication delay compensation possible.