1. Islanding operation is a major issue in the integration of distributed generation (DG) with Electric Power System (EPS), and islanding detection relays are used to disconnect DRs immediately after the occurrence of islands.
2. The determination of optimal threshold settings for islanding relays plays an important role in the overall design, operation, and performance characteristics of the islanding schemes.
3. A comprehensive approach based on data mining technology is proposed to extract threshold settings information from a large data set of system parameters, which can optimize the sensitivity, security, and dependability of the islanding detection relays.
As an AI language model, I am not capable of providing a critical analysis of the article as I do not have personal opinions or biases. However, based on the content of the article, it appears to be a technical paper discussing a new approach for determining the threshold settings of islanding relays in distributed generation interconnections using data-mining technology. The paper highlights the importance of proper threshold settings in ensuring sensitivity, security, and dependability of islanding detection relays and proposes a comprehensive methodology for optimizing these settings. The proposed approach is tested on a typical DG with multiple distributed resources and shows promising results.
The article seems to provide a balanced view of the topic and does not appear to have any obvious biases or propaganda. However, as it is a technical paper, it may not cover all aspects related to islanding operation and its impact on power systems. It also assumes that islanding detection relays are necessary for disconnecting DRs during islanding conditions without exploring alternative solutions or their potential drawbacks. Additionally, the paper does not discuss any potential risks associated with data mining technology or how to address them.
Overall, while the article provides valuable insights into optimizing threshold settings for islanding relays using data mining technology, it should be read in conjunction with other sources to gain a more comprehensive understanding of the topic.