Paramo, G.; Bretas, A. Proactive Frequency Stability Scheme: A Distributed Framework Based on Particle Filters and Synchrophasors. Energies2023, 16, 4530.
Paramo, G.; Bretas, A. Proactive Frequency Stability Scheme: A Distributed Framework Based on Particle Filters and Synchrophasors. Energies 2023, 16, 4530.
Paramo, G.; Bretas, A. Proactive Frequency Stability Scheme: A Distributed Framework Based on Particle Filters and Synchrophasors. Energies2023, 16, 4530.
Paramo, G.; Bretas, A. Proactive Frequency Stability Scheme: A Distributed Framework Based on Particle Filters and Synchrophasors. Energies 2023, 16, 4530.
Abstract
The reactive nature of traditional frequency stability methods can lead to delayed corrective actions and unnecessary loss-of-load. This work presents a distributed model predictive control method for proactive power system frequency stability. Dynamic state estimation model is derived through a particle filter. By being able to estimate the future state of frequency, corrective actions can be taken before the system reaches a critical condition. Proactive approach makes it possible to optimize the response to a disturbance, which results in a decrease of the amount of compensation utilized.
The method is tested via Matlab simulations based on Kundur's Two-Area System, and the IEEE 14-Bus system. Performance metrics are provided and evaluated against other contemporary solutions found in literature. Easy-to-derive model, without hard-to-design parameters, indicate potential towards real-life applications.
Keywords
Frequency Control; Model Predictive Control; Particle Filter; Phasor Measurement Units; Power Systems
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
