- By:
- Gui, Yonghao ; Wang, Hong ; Xue, Yaosuo
- Page Number:
- 1-6
- Book Title:
- 2025 57th North American Power Symposium (NAPS)
- Publication Date:
- March 12, 2026
- Publisher Location:
- IEEE, New Jersey, United States of America
- Conference Name:
- The 57th North American Power Symposium (NAPS)
- Conference Location:
- Hartford, Connecticut, United States of America
- Conference Sponsor:
- IEEE
- View DOI Listing:
- https://doi.org/10.1109/NAPS66256.2025.11272292
Abstract
It is well-known that power systems operation always affected by various uncertainties which make the bus voltage a random process that can be characterized by its probability density function (PDF) at any time instant. In this context, this paper presents a novel PDF-based voltage control framework for power systems. By modeling voltage as a stochastic process, we formulate a stochastic differential equationthat captures grid uncertainties. The associated Fokker-Planck-Kolmogorov equation is derived to describe the evolution of the voltage PDF, which enables the formulation of a PDF-shaping control strategy. To simplify the PDF control formulation, a B-spline neural network is introduced for real-time estimation and regulation of the voltage distribution. The proposed PDF control law updates voltage references for energy storage systems and synchronous generators using real-time PDF measurements and feedback signals. The proposed method is validated on a modified Kundur’s two-area system. Simulation results demonstrate that the controller can significantly improve the voltage stability under stochastic conditions, highlighting its effectiveness in modern inverter-rich grids.
