ML Self-Sufficient Sustainable Energy Resiliency Management System: Outage Forecasting, Classification and Restoration with Maintenance Indicators for All Types of Power Outages-Reference-Cited by-同舟云学术

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ML Self-Sufficient Sustainable Energy Resiliency Management System: Outage Forecasting, Classification and Restoration with Maintenance Indicators for All Types of Power Outages

Published:2022-09-01 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Design Methodologies Conference (DMC)
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Author:

Adedokun Susan Oluropo¹,Luo Zhenhua¹,Luk Patrick¹,Balta-Ozkan Nazmiye¹,Khan Mohammad Farhan²,Zhang Xin³

Affiliation:

1. Cranfield University,Bedfordshire,United Kingdom

2. University of Roehampton,London,United Kingdom

3. Brunel University,London,United Kingdom

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9906465/9906466/09906471.pdf?arnumber=9906471

Reference32 articles.

1. A heuristic-based approach for optimizing a small independent solar and wind hybrid power scheme incorporating load forecasting

2. A multi-disaster-scenario distributionally robust planning model for enhancing the resilience of distribution systems

3. An Integrated Transmission Expansion and Sectionalizing-Based Black Start Allocation of BESS Planning Strategy for Enhanced Power Grid Resilience

4. A Review of Machine Learning Applications in Power System Resilience

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine Learning-Based Restoration Forecast with Predictive Power Outage for Diverse Power Outage Scenarios;2023 IEEE International Conference on Energy Technologies for Future Grids (ETFG);2023-12-03

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