Multi-population evolutionary computing based multi-agent smart distribution system service restoration
Author:
Funder
ministry of science and technology, taiwan
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Electrical and Electronic Engineering
Link
https://link.springer.com/content/pdf/10.1007/s00202-022-01547-y.pdf
Reference35 articles.
1. Chidanandappa R, Ananthapadmanabha T, Ranjith HC (2016) Genetic algorithm based service restoration in distribution systems with multiple DGs for time varying loads. In: Proceedings of 2016 biennial international conference on power and energy systems: towards sustainable energy (PESTSE), Bengaluru, India, 21–23 January 2016, pp 1–7
2. Chidanandappa R, Ananthapadmanabha T, Ranjith HC (2015) Genetic algorithm based network reconfiguration in distribution systems with multiple DGs for time varying loads. Procedia Technol 21:460–467. https://doi.org/10.1016/j.protcy.2015.10.023
3. Huang Y-C, Chang W-C, Hsu H, Kuo C-C (2021) Planning and research of distribution feeder automation with decentralized power supply. Electronics 10:362. https://doi.org/10.3390/electronics10030362
4. Zidan A, Khairalla M, Abdrabou AM, Khalifa T, Shaban K, Abdrabou A, El Shatshat R, Gaouda AM (2017) Fault detection, isolation, and service restoration in distribution systems: state-of-the-art and future trends. IEEE Trans Smart Grid 8:2170–2185
5. Nasir MNM, Shahrin NM, Bohari ZH, Sulaima MF, Hassan MY (2014) A distribution network reconfiguration based on PSO: considering DGs sizing and allocation evaluation for voltage profile improvement. In: Proceedings of the 2014 IEEE student conference on research and development (SCOReD 2014), Penang, Malaysia, 16–17 December 2014, pp 1–6
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