Islanding Detection in Grid-Connected Urban Community Multi-Microgrid Clusters Using Decision-Tree-Based Fuzzy Logic Controller for Improved Transient Response

• Main Authors: Venkata Pavan Kumar, Y., Naga Venkata Bramareswara Rao, S., Kannan, R.
• Format: Article
• Published: Multidisciplinary Digital Publishing Institute (MDPI) 2023
• Online Access: http://scholars.utp.edu.my/id/eprint/37357/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172098880&doi=10.3390%2furbansci7030072&partnerID=40&md5=fb89f306bf9d6487c8e795be64d8cf00

The development of renewable-energy-based microgrids is being considered as a potential solution to lessen the unrelenting burden on the centralized utility grid. Furthermore, recent studies reveal that integrated multi-microgrid cluster systems developed in urban communities maximize the effectiveness of microgrids and greatly decrease the utility grid dependence. However, due to the uncertain nature of renewable energy sources and frequent load variations, these systems face issues with unintentional islanding operations. This can create severe damage to the microgrid�s performance in its stable operating condition and lead to undesired transient responses. Hence, islanding must be identified rapidly to take preventive measures to address the issue. This requires the development of a suitable anti-islanding technique that is faster in terms of accuracy and timely detection. With this intention, this paper proposes a decision-tree-based fuzzy logic (DT-FL) controller for the rapid identification of islands in an urban community multi-microgrid cluster. The DT-FL controller�s operation includes two steps. First, the decision tree extracts the electrical parameters at the point of common coupling of the multi-microgrid system. Second, these extracted parameters are utilized for the online tuning of the fuzzy logic controller, for the fast detection of islanding. The multi-microgrid cluster under study, along with the proposed islanding technique, is implemented in the MATLAB-2021a software. The efficacy of the proposed DT-FL controller is validated by comparing its performance with that of the conventional fuzzy logic controller under different test scenarios. From the results, it is observed that the proposed DT-FL controller shows superior performance in terms of the islanding detection time as well as the transient response of the system when compared with the conventional controller. © 2023 by the authors.