Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2016 IEEE International Conference on Power System Technology, POWERCON 2016 |
| Seiten | 1-6 |
| Seitenumfang | 6 |
| ISBN (elektronisch) | 9781467388481 |
| Publikationsstatus | Veröffentlicht - 22 Nov. 2016 |
Abstract
By changing active and reactive power to counteract the increasing number of multiple congestions and multiple inadmissible voltage deviations in the grid of ENTSO-E, grid losses are influenced significantly as well. Thus, different available measures against the aforementioned off-limit conditions can differ not only in their efficiency due to off-limit conditions but also in regard to grid losses. Furthermore, measures for power flow optimization can cause or worsen off-limit conditions. Since grid losses cannot be optimized with linear approaches a quadratic approach is needed for the objective function. Its derivation considering a distributed slack according to control reserve and its application is shown in this paper. The linear constraints of the optimization (e.g.Thermal current limits and voltage bandwidth) are derived as well. The novel approach by combining optimal power flow and optimized congestion management delivers a global optimum even with nonconvex functions, fast and reproducible results and a proper prediction.
ASJC Scopus Sachgebiete
- Energie (insg.)
- Erneuerbare Energien, Nachhaltigkeit und Umwelt
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
- Energie (insg.)
- Energieanlagenbau und Kraftwerkstechnik
Ziele für nachhaltige Entwicklung
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2016 IEEE International Conference on Power System Technology, POWERCON 2016. 2016. S. 1-6 7753927.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Optimal power flow comprising congestions and voltage management by global quadratic optimization of active and reactive power
AU - Leveringhaus, T.
AU - Hofmann, L.
N1 - Publisher Copyright: © 2016 IEEE. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2016/11/22
Y1 - 2016/11/22
N2 - By changing active and reactive power to counteract the increasing number of multiple congestions and multiple inadmissible voltage deviations in the grid of ENTSO-E, grid losses are influenced significantly as well. Thus, different available measures against the aforementioned off-limit conditions can differ not only in their efficiency due to off-limit conditions but also in regard to grid losses. Furthermore, measures for power flow optimization can cause or worsen off-limit conditions. Since grid losses cannot be optimized with linear approaches a quadratic approach is needed for the objective function. Its derivation considering a distributed slack according to control reserve and its application is shown in this paper. The linear constraints of the optimization (e.g.Thermal current limits and voltage bandwidth) are derived as well. The novel approach by combining optimal power flow and optimized congestion management delivers a global optimum even with nonconvex functions, fast and reproducible results and a proper prediction.
AB - By changing active and reactive power to counteract the increasing number of multiple congestions and multiple inadmissible voltage deviations in the grid of ENTSO-E, grid losses are influenced significantly as well. Thus, different available measures against the aforementioned off-limit conditions can differ not only in their efficiency due to off-limit conditions but also in regard to grid losses. Furthermore, measures for power flow optimization can cause or worsen off-limit conditions. Since grid losses cannot be optimized with linear approaches a quadratic approach is needed for the objective function. Its derivation considering a distributed slack according to control reserve and its application is shown in this paper. The linear constraints of the optimization (e.g.Thermal current limits and voltage bandwidth) are derived as well. The novel approach by combining optimal power flow and optimized congestion management delivers a global optimum even with nonconvex functions, fast and reproducible results and a proper prediction.
KW - AC optimal power flow
KW - distributed slack
KW - management of multiple congestions
KW - optimization
KW - redispatch
UR - http://www.scopus.com/inward/record.url?scp=85006717156&partnerID=8YFLogxK
U2 - 10.1109/powercon.2016.7753927
DO - 10.1109/powercon.2016.7753927
M3 - Conference contribution
SP - 1
EP - 6
BT - 2016 IEEE International Conference on Power System Technology, POWERCON 2016
ER -