Abstract
Faster detection of faults, can lead to better and
more efficient control of power system against cascading failures
triggered by the faults. This article presents a novel detection
algorithm using statistical methods for the detection of events
that lead to FIDVR. Furthermore we show that the algorithm is
computationally efficient and quick enough to provide the control
inputs to an UVLS scheme using in-feed PMU data. Thus, it is
ensured that the minimal level of load to be shed is determined
on-the-fly as the event develops.
more efficient control of power system against cascading failures
triggered by the faults. This article presents a novel detection
algorithm using statistical methods for the detection of events
that lead to FIDVR. Furthermore we show that the algorithm is
computationally efficient and quick enough to provide the control
inputs to an UVLS scheme using in-feed PMU data. Thus, it is
ensured that the minimal level of load to be shed is determined
on-the-fly as the event develops.
| Original language | English |
|---|---|
| Title of host publication | IET Conference Publications |
| Publisher | IEEE |
| Number of pages | 6 |
| Edition | CP759 |
| ISBN (Print) | 9781785617911, 9781839531330 |
| DOIs | |
| Publication status | Published - 2019 |
| Event | 11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion - Dubrovnik, Croatia Duration: 12 Nov 2018 → 15 Nov 2018 http://medpower2018.com/ |
Publication series
| Name | IET Conference Publications |
|---|---|
| Number | CP759 |
| Volume | 2018 |
Conference
| Conference | 11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion |
|---|---|
| Abbreviated title | MEDPOWER 2018 |
| Country | Croatia |
| City | Dubrovnik |
| Period | 12/11/18 → 15/11/18 |
| Internet address |