Optimized Adaptive Overcurrent Protection Using Hybridized Nature-Inspired Algorithm and Clustering in Microgrids

Thiramuni Sisitha Sameera Senarathna and Kullappu Thantrige Manjula Udayanga Hemapala
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Thiramuni Sisitha Sameera Senarathna: Department of Electrical Engineering, University of Moratuwa, Moratuwa 10400, Sri Lanka
Kullappu Thantrige Manjula Udayanga Hemapala: Department of Electrical Engineering, University of Moratuwa, Moratuwa 10400, Sri Lanka

Energies, 2020, vol. 13, issue 13, 1-23

Abstract: Microgrids have been popularized in the past decade because of their ability to add distributed generation into the classic distribution systems. Protection problems are among several other problems that need solutions in order to extract the full capability of these novel networks. This research follows the branches of two major solutions, namely adaptive protection and protection optimization. Adaptive protection implementation with a novel concept of clustering is considered, and protection setting optimization is done using a novel hybrid nature-inspired algorithm. Adaptive protection is utilized to cope with the topology variations, while optimization techniques are used to calculate the protection settings that provide faster fault clearances in coordination with backup protection. A modified IEEE 14 bus system is used as the test system. Validation was done for the fault clearing performance. The selected algorithm was effective than most other algorithms, and the clustering approach for adaptive overcurrent protection was able to reduce the number of relays’ setting groups.

Keywords: adaptive protection; microgrid protection; protection optimization; directional overcurrent protection; nature inspired optimization algorithm; k-means clustering (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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