학술논문

An Approach for Rapid Online Robustness Enhancement of Distributed Power Systems using Load Classifier Forecasting
Document Type
Conference
Source
2024 IEEE 21st International Power Electronics and Motion Control Conference (PEMC) Power Electronics and Motion Control Conference (PEMC), 2024 IEEE 21st International. :1-6 Sep, 2024
Subject
Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Damping
Power quality
Signal processing algorithms
Power system stability
Robustness
Generators
Real-time systems
Classification algorithms
Surges
Standards
online robustness control
load classifiers
classifier forecast
Wu’s Elimination Method
distributed power system
BCU method
active damping generator
Language
ISSN
2473-0165
Abstract
In this paper, we propose an online approach to rapidly and efficiently improve the robustness of distributed power systems (DPSs). Based on real-time monitoring of sudden voltage sag the main work includes the following two steps: offline classifier identification and online instantaneous disturbance suppression. In order to accurately forecast load classifiers, we adopt an automatic analytical solution, Wu’s Elimination Method (WEM), to derive the expressions of differential equations that are used to describe the phenomena in DPS. Then the corresponding load classifiers have been obtained by BCU method (Boundary of stability region based Controlling Unstable equilibrium point method). The optimum switching time of the proposed Active Damping Generator can be chosen based on combining the obtained classifiers with digital signal processing. Simulation and experimental results show that through our work the suddenly changed voltage and distorted current of the DPS can be quickly recovered within 15ms which is faster than the standard IEC TS62749-2015.