78831

Автор(ы): 

Автор(ов): 

6

Параметры публикации

Тип публикации: 

Доклад

Название: 

An Approach for Rapid Online Robustness Enhancement of Distributed Power Systems using Load Classifier Forecasting

DOI: 

10.1109/PEMC61721.2024.10726396

Наименование конференции: 

  • 2024 IEEE 21st International Power Electronics and Motion Control Conference (PEMC)

Наименование источника: 

  • IEEE Xplore Digital Library

Обозначение и номер тома: 

10726396

Город: 

  • Pilsen, Czech Republic

Издательство: 

  • IEEE

Год издания: 

2024

Страницы: 

https://ieeexplore.ieee.org/document/10726396
Аннотация
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.

Библиографическая ссылка: 

Wei X., Сидоров Д.Н., Дрегля А.И., Искаков А.Б., Wang Z., Wang L. An Approach for Rapid Online Robustness Enhancement of Distributed Power Systems using Load Classifier Forecasting / IEEE Xplore Digital Library. Pilsen, Czech Republic: IEEE, 2024. 10726396. С. https://ieeexplore.ieee.org/document/10726396.