Ramli, Suzana Pil and Pashaei, Meysam and Karimi, Mazaher and Kauhaniemi, Kimmo and Pourdaryaei, Alireza and Daryaei, Mehdi and Zarei, Masoud (2022) The Recent Development of Optimal DOCR Protection Strategies for Sustainable Power Systems via Computational Intelligence Techniques. IEEE Access, 10. pp. 134277-134291. ISSN 2169-3536, DOI https://doi.org/10.1109/ACCESS.2022.3231603.
Full text not available from this repository.Abstract
In the past decade, there has been unprecedented growth in distributed generation (DG) to cater to more load demand in the power grid. However, as the volume of these resources in the distribution network (DN) continues to increase, new challenges in voltage regulation, system stability, and protection coordination have emerged. The system is substantially changed when multiple types of DGs are incorporated into DN. These include new fault condition sources, different fault stages, a blinding influence on the protection scheme, a decrease in the relays' range, and a decline in the ability of existent relays to detect low-level fault currents. Due to the bidirectional current flow, this raises the fault current and, if improperly coordinated, causes the relays to trip unintentionally. Since fault current can flow in either direction (i.e., upstream or downstream), it is crucial that grid-mounted relays can detect it. This goal can be reached by including an optimal directional overcurrent relay (DOCR) coordination scheme in the system. In fact, DOCRs in interconnected power grids need to be coordinated effectively. This paper gives a comprehensive overview of the uses of various optimization strategies. The evaluation examines the benefits and drawbacks of the strategies used to address DOCR coordination problems. Additionally, this paper discusses future lines of inquiry for optimum DOCR coordination.
| Item Type: | Article |
|---|---|
| Funders: | University of Vaasa, Business Finland (6937/31/2021) |
| Uncontrolled Keywords: | Computational intelligence; directional overcurrent relay; distributed generation; distribution network; renewable energy resources |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering > Department of Electrical Engineering |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 17 Jan 2025 02:03 |
| Last Modified: | 17 Jan 2025 02:03 |
| URI: | http://eprints.um.edu.my/id/eprint/40485 |
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