Unified Fast Decoupled Load Flow in a Parallel Distributed Computation Framework
This research proposes a parallel and distributed computation approach for the fast decoupled load flow (FDLF) analysis applicable to both transmission and distribution networks of large electrical power systems. In this approach, the overall repetitive FDLF computations are performed by the respect...
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| Vydáno v: | Electric power components and systems Ročník 48; číslo 1-2; s. 128 - 137 |
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| Hlavní autor: | |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Philadelphia
Taylor & Francis
20.01.2020
Taylor & Francis Ltd |
| Témata: | |
| ISSN: | 1532-5008, 1532-5016 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | This research proposes a parallel and distributed computation approach for the fast decoupled load flow (FDLF) analysis applicable to both transmission and distribution networks of large electrical power systems. In this approach, the overall repetitive FDLF computations are performed by the respective control centers identified for each sub-system, the sub-systems being formed by partitioning the system through a network tearing procedure splitting the identified buses. The data of each subsystem are stored at their own control centers and hence the subsystems are solved using message passing distributed memory architecture. The computations performed by the control centers in various sub-systems are coordinated from a regional control center. The investigations on IEEE 118 bus standard test system indicate that the proposed approach provides faster solution than the conventional approach, without affecting the solution accuracy. The effectiveness of the proposed technique over the conventional approach become more visible when it is applied for the load flow analysis of large scale systems spread over a wide geographical area. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1532-5008 1532-5016 |
| DOI: | 10.1080/15325008.2020.1731875 |