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Relay logic for islanding detection in active distribution systems

Vatani, M ; Sharif University of Technology | 2015

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  1. Type of Document: Article
  2. DOI: 10.1049/iet-gtd.2014.0373
  3. Publisher: Institution of Engineering and Technology , 2015
  4. Abstract:
  5. This study presents a passive model to detect islanding conditions of synchronous distributed generation resources in a distribution network or a microgrid. The proposed approach uses the classification and regression tree algorithm for distinguishing between islanding and non-islanding situations. It utilises the rate of change of frequency (ROCOF) and harmonic content of the equivalent reactance seen at the location of distributed generation as input features for decision tree construction. Indeed the thresholds of the proposed input features are extracted by the decision tree algorithm. The output if-then rules of the decision tree algorithm are then utilised to make a new relay logic for islanding detection. The proposed scheme successfully classifies the input data with approximately zero non-detection zone and prevent false operation of traditional scheme. The performance of the proposed protective algorithm is compared with the traditional ROCOF relay, artificial neural network and support vector machine techniques. The proposed method is implemented in a typical microgrid, which is connected to the transmission network of the dynamic WSCC three-machine, 9bus test system with considering electric faults at upstream transmission and sub-transmission networks
  6. Keywords:
  7. Algorithms ; Decision trees ; Distributed power generation ; Electric power distribution ; Electric relays ; Neural networks ; Trees (mathematics) ; Active distribution systems ; Classification and regression tree ; Decision tree construction ; Decision-tree algorithm ; Distributed generation resources ; Islanding conditions ; Rate of change of frequencies ; Support vector machine techniques ; Data mining
  8. Source: IET Generation, Transmission and Distribution ; Volume 9, Issue 12 , August , 2015 , Pages 1254-1263 ; 17518687 (ISSN)
  9. URL: http://ieeexplore.ieee.org/document/7224097