Volume 18, Issue 4 (December 2022)                   IJEEE 2022, 18(4): 163-174 | Back to browse issues page

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Tiwari S P. Fault Detection in Ring Based Smart LVDC Microgrid Using Ensemble of Decision Tree. IJEEE 2022; 18 (4) :163-174
URL: http://ijeee.iust.ac.ir/article-1-2600-en.html
Abstract:   (858 Views)
In modern infrastructure, the demand for DC power-based appliances is rapidly increasing, and this phenomenon has created a positive impact on the acceptance of the DC microgrid. However, due to numerous issues such as the absence of zero crossing, bidirectional behaviour of sources, and different magnitudes of fault current during grid connected and islanded modes of operation, protecting DC microgrid remains a difficult task. Apart from these challenges, intermittent conditions are also a major challenge. Under such type scenarios, shadow conditions in the solar based DERs will reduce the desired output of the solar panels simultaneously in wind based DERs will be affected due to the low pressure of air. In this type of circumstances threshold setting based overcurrent relays may fail to sense the operational dynamics of the system. Therefore, in this manuscript, an ensemble of decision tree-based protection scheme is proposed to provide immunity against the stochastic conditions under the varying natures of the fault resistance. A total of 7150 test cases have been considered for validation of the protection scheme and all modules have been tested.
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  1.  Modeling of the wind intermittency to observe the behavior the intermittency through Weibull function.
  2. Development of the ensemble of protection schemes to identify the mode of operation, fault detection/classification with faulty section identification.
  3. Validation of the proposed scheme through the test cases under diverse conditions.
  4. Simulation of the DC microgrid model to simulate the fault scenarios.
  5. Analysis of the protection scheme with other techniques.

Type of Study: Closed - Microgrid Special Issue 2022 | Subject: Artificial Intelligence Techniques
Received: 2022/07/26 | Revised: 2024/05/13 | Accepted: 2022/12/10

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Creative Commons License
© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.