Background
Trajectory sensitivity (TS) is a powerful approach to aid in dynamic security assessment (DSA). However, its practical usage has been limited so far due to concerns associated with its scalability. With a focus on increasing penetration of inverter-based resources and a long queue of pending generation interconnection requests, large-scale and clock time-friendly power system planning studies are crucial. One component of these studies requires performing time domain simulations for different system settings. This can be a repetitive, time-consuming and computationally intensive process to implement.
Invention Description
Researchers at Arizona State have developed a low-ranking compression of trajectory sensitivities for dynamic security assessments. This invention provides a systematic methodology to store and perform calculations using the trajectory sensitivity (TS) data to estimate post fault trajectories using singular value decomposition (SVD). This technology has the potential to make TS analysis more widespread for operation and planning of large-scale systems.
Potential Applications:
- Optimization and Algorithm Development
- Power Systems Engineering and Analysis
- Data Science and Machine Learning
Benefits and Advantages:
- Quicker computational time – 10 times faster estimated trajectory results
- Versatile – wide variety of monitoring variables and system perturbations
- Efficient – practical and scalable approach in dynamic security assessment (DSA)