Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2014 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) |
| Seiten | 1-6 |
| Seitenumfang | 6 |
| Auflage | March |
| Publikationsstatus | Veröffentlicht - 23 März 2014 |
Publikationsreihe
| Name | Asia-Pacific Power and Energy Engineering Conference, APPEEC |
|---|---|
| ISSN (Print) | 2157-4839 |
Abstract
The precise prediction of changes in load flows, currents and voltage magnitudes due to changes in power is important for forecasting and managing grid congestions, voltage deviations and minimizing grid losses for example. This paper describes three different methods and further variants of those for state prediction and compares their approximations, neglects and quality of prediction. Since PTDFs and PFD modify the characteristics of the non-linear load flow equations by approximations and neglects, their qualities of prediction are less than those of the AC-PTDFs. To consider the way changings in grid losses are counteracted by the grid a new variant to consider secondary control reserve in the prediction is established. The AC-PTDFs deliver the highest quality of current and loss prediction, the most comprehensive mathematical approximation of the non-linear load flow equations, and the most potential for further development like optimized management of multiple congestions and Optimal Power Flow.
ASJC Scopus Sachgebiete
- Energie (insg.)
- Energieanlagenbau und Kraftwerkstechnik
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2014 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC). March. Aufl. 2014. S. 1-6 (Asia-Pacific Power and Energy Engineering Conference, APPEEC).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Comparison of methods for state prediction: Power Flow Decomposition (PFD), AC Power Transfer Distribution factors (AC-PTDFs), and Power Transfer Distribution factors (PTDFs)
AU - Leveringhaus, T.
AU - Hofmann, L.
N1 - Publisher Copyright: © 2014 IEEE. Copyright: Copyright 2016 Elsevier B.V., All rights reserved.
PY - 2014/3/23
Y1 - 2014/3/23
N2 - The precise prediction of changes in load flows, currents and voltage magnitudes due to changes in power is important for forecasting and managing grid congestions, voltage deviations and minimizing grid losses for example. This paper describes three different methods and further variants of those for state prediction and compares their approximations, neglects and quality of prediction. Since PTDFs and PFD modify the characteristics of the non-linear load flow equations by approximations and neglects, their qualities of prediction are less than those of the AC-PTDFs. To consider the way changings in grid losses are counteracted by the grid a new variant to consider secondary control reserve in the prediction is established. The AC-PTDFs deliver the highest quality of current and loss prediction, the most comprehensive mathematical approximation of the non-linear load flow equations, and the most potential for further development like optimized management of multiple congestions and Optimal Power Flow.
AB - The precise prediction of changes in load flows, currents and voltage magnitudes due to changes in power is important for forecasting and managing grid congestions, voltage deviations and minimizing grid losses for example. This paper describes three different methods and further variants of those for state prediction and compares their approximations, neglects and quality of prediction. Since PTDFs and PFD modify the characteristics of the non-linear load flow equations by approximations and neglects, their qualities of prediction are less than those of the AC-PTDFs. To consider the way changings in grid losses are counteracted by the grid a new variant to consider secondary control reserve in the prediction is established. The AC-PTDFs deliver the highest quality of current and loss prediction, the most comprehensive mathematical approximation of the non-linear load flow equations, and the most potential for further development like optimized management of multiple congestions and Optimal Power Flow.
KW - AC Power Transfer Distribution factors (AC-PTDFs)
KW - Power Flow Decomposition (PFD)
KW - Power Transfer Distribution factors (PTDF)
KW - congestion management
KW - distributed slack
KW - optimal power flow
UR - http://www.scopus.com/inward/record.url?scp=84983122482&partnerID=8YFLogxK
U2 - 10.1109/appeec.2014.7066183
DO - 10.1109/appeec.2014.7066183
M3 - Conference contribution
T3 - Asia-Pacific Power and Energy Engineering Conference, APPEEC
SP - 1
EP - 6
BT - 2014 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)
ER -