Mitigating the Risk of Voltage Collapse Using Statistical Measures From PMU Data
| Autor: | Samuel Chevalier, Paul Hines |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
Data stream mining 020209 energy Phasor Energy Engineering and Power Technology 02 engineering and technology AC power Electric power system Test case Control theory 0202 electrical engineering electronic engineering information engineering Time domain Observability Electrical and Electronic Engineering |
| Zdroj: | IEEE Transactions on Power Systems. 34:120-128 |
| ISSN: | 1558-0679 0885-8950 |
| Popis: | With the continued deployment of synchronized phasor measurement units (PMUs), high sample rate data are rapidly increasing the real time observability of power systems. Prior research has shown that the statistics of these data can provide useful information regarding network stability, but it is not yet known how this statistical information can be actionably used to improve power system stability. To address this issue, this paper presents a method that gauges and improves the voltage stability of a system using the statistics present in PMU data streams. Leveraging an analytical solver to determine a range of “critical” bus voltage variances, the presented methods monitor raw statistical data in an observable load pocket to determine when control actions are needed to mitigate the risk of voltage collapse. A simple reactive power controller is then implemented, which acts dynamically to maintain an acceptable voltage stability margin within the system. Time domain simulations on 3-bus and 39-bus test cases demonstrate that the resulting statistical controller can outperform more conventional feedback control systems by maintaining voltage stability margins while loads simultaneously increase and fluctuate. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|