| bibtype |
J -
Journal Article
|
| ARLID |
0600099 |
| utime |
20241101081030.9 |
| mtime |
20241101235959.9 |
| SCOPUS |
85153256678 |
| WOS |
000973226900001 |
| DOI |
10.1007/s11081-023-09801-3 |
| title
(primary) (eng) |
A SDP relaxation of an optimal power flow problem for distribution networks |
| specification |
| page_count |
30 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0297191 |
| ISSN |
1389-4420 |
| title
|
Optimization and Engineering |
| volume_id |
24 |
| volume |
4 (2024) |
| page_num |
2973-3002 |
| publisher |
|
|
| keyword |
Electric power distribution network |
| keyword |
Optimal power flow |
| keyword |
Convex relaxation |
| keyword |
Pareto-front |
| author
(primary) |
| ARLID |
cav_un_auth*0475404 |
| name1 |
Desveaux |
| name2 |
V. |
| country |
FR |
| garant |
K |
|
| author
|
| ARLID |
cav_un_auth*0475405 |
| name1 |
Handa |
| name2 |
Marouan |
| institution |
UTIA-B |
| full_dept (cz) |
Matematická teorie rozhodování |
| full_dept |
Department of Decision Making Theory |
| department (cz) |
MTR |
| department |
MTR |
| country |
JP |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
GA22-15524S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0447354 |
|
| abstract
(eng) |
In this work, we are interested in an optimal power flow problem with fixed voltage magnitudes in distribution networks. This optimization problem is known to be non-convex and thus difficult to solve. A well-known solution methodology consists in reformulating the objective function and the constraints of the original problem in terms of positive semi-definite matrix traces, to which we add a rank constraint. To convexify the problem, we remove this rank constraint. Our main focus is to provide a strong mathematical proof of the exactness of this convex relaxation technique. To this end, we explore the geometry of the feasible set of the problem via its Pareto-front. We prove that the feasible set of the original problem and the feasible set of its convexification share the same Pareto-front. From a numerical point of view, this exactness result allows to reduce the initial problem to a semi-definite program, which can be solved by more efficient algorithms. |
| result_subspec |
WOS |
| RIV |
BB |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10102 |
| reportyear |
2025 |
| inst_support |
RVO:67985556 |
| permalink |
https://hdl.handle.net/11104/0357459 |
| confidential |
S |
| mrcbC91 |
C |
| mrcbT16-e |
ENGINEERINGMULTIDISCIPLINARY|MATHEMATICSINTERDISCIPLINARYAPPLICATIONS|OPERATIONSRESEARCHMANAGEMENTSCIENCE |
| mrcbT16-j |
0.638 |
| mrcbT16-D |
Q3 |
| arlyear |
2024 |
| mrcbU14 |
85153256678 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000973226900001 WOS |
| mrcbU63 |
cav_un_epca*0297191 Optimization and Engineering Roč. 24 č. 4 2024 2973 3002 1389-4420 1573-2924 Springer |
|