An innovative mode-based coherency evaluation method for data-driven controlled islanding in power systems
Electric Power Systems Research, ISSN: 0378-7796, Vol: 214, Page: 108808
2023
- 4Citations
- 11Captures
- 1Mentions
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Most Recent News
New Findings from Islamic Azad University Describe Advances in Information Technology (An Innovative Mode-based Coherency Evaluation Method for Data-driven Controlled Islanding In Power Systems)
2023 JUL 11 (NewsRx) -- By a News Reporter-Staff News Editor at Middle East Daily -- A new study on Information Technology is now available.
Article Description
Controlled islanding is considered the last remedial action for preventing power systems from moving toward collapsing. In this respect, power systems should be split into islands, so that each island remains stable from both static and dynamic viewpoints. Therefore, determining the center of each island and its load bus borders is a fundamental task. In this paper, an innovative method is presented to determine the appropriate islanding scheme following the occurrence of a disturbance. This method is based on excited modes and it uses density-based learning approaches to cluster buses of the system in complex planes. The clustering process is performed with respect to each central bus to find candidate area borders. This is crucial, since wide area post disturbance control actions and restoration can be more effective in this way. Additionally, the proposed coherency evaluation method is incorporated into the static load flow analysis to form an optimization problem for determining the borders of each island. Accordingly, both static and dynamic aspects of islands are included in the problem from a control-based viewpoint. The results of applying the proposed approach on test cases demonstrate its effectiveness.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0378779622008628; http://dx.doi.org/10.1016/j.epsr.2022.108808; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85138067054&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0378779622008628; https://dx.doi.org/10.1016/j.epsr.2022.108808
Elsevier BV
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