Chance-Constrained Optimization of Storage and PFC Capacity for Railway Electrical Smart Grids Considering Uncertain Traction Load
Author:
Affiliation:
1. School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China
2. Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, U.K.
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Computer Science
Link
http://xplorestaging.ieee.org/ielx7/5165411/10372481/10124245.pdf?arnumber=10124245
Reference34 articles.
1. Power Quality Issues in Railway Electrification: A Comprehensive Perspective
2. An Energy Storage System for Recycling Regenerative Braking Energy in High-Speed Railway
3. Railway Electrical Smart Grids: An introduction to next-generation railway power systems and their operation.
4. Smart Electrical Infrastructure for AC-Fed Railways With Neutral Zones
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1. A Real-Time Energy Management Strategy of Flexible Smart Traction Power Supply System Based on Deep Q-Learning;IEEE Transactions on Intelligent Transportation Systems;2024-08
2. Multi-agent deep reinforcement learning-based multi-time scale energy management of urban rail traction networks with distributed photovoltaic–regenerative braking hybrid energy storage systems;Journal of Cleaner Production;2024-08
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