This data is for deep reinforcement leaming in real-time security constrained ecomomic dispatch on IEEE 118-bus system. The data includes system topology, wind generation and power demand for 1000 days with 5 min temporal resolution.

Dataset Files

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[1] Yujian Ye, Jianxiong Hu, "dataset for “Towards Risk-Aware Real-Time Security Constrained Economic Dispatch: A Tailored Deep Reinforcement Learning Approach“", IEEE Dataport, 2023. [Online]. Available: http://dx.doi.org/10.21227/vqn4-d248. Accessed: Apr. 22, 2024.
@data{vqn4-d248-23,
doi = {10.21227/vqn4-d248},
url = {http://dx.doi.org/10.21227/vqn4-d248},
author = {Yujian Ye; Jianxiong Hu },
publisher = {IEEE Dataport},
title = {dataset for “Towards Risk-Aware Real-Time Security Constrained Economic Dispatch: A Tailored Deep Reinforcement Learning Approach“},
year = {2023} }
TY - DATA
T1 - dataset for “Towards Risk-Aware Real-Time Security Constrained Economic Dispatch: A Tailored Deep Reinforcement Learning Approach“
AU - Yujian Ye; Jianxiong Hu
PY - 2023
PB - IEEE Dataport
UR - 10.21227/vqn4-d248
ER -
Yujian Ye, Jianxiong Hu. (2023). dataset for “Towards Risk-Aware Real-Time Security Constrained Economic Dispatch: A Tailored Deep Reinforcement Learning Approach“. IEEE Dataport. http://dx.doi.org/10.21227/vqn4-d248
Yujian Ye, Jianxiong Hu, 2023. dataset for “Towards Risk-Aware Real-Time Security Constrained Economic Dispatch: A Tailored Deep Reinforcement Learning Approach“. Available at: http://dx.doi.org/10.21227/vqn4-d248.
Yujian Ye, Jianxiong Hu. (2023). "dataset for “Towards Risk-Aware Real-Time Security Constrained Economic Dispatch: A Tailored Deep Reinforcement Learning Approach“." Web.
1. Yujian Ye, Jianxiong Hu. dataset for “Towards Risk-Aware Real-Time Security Constrained Economic Dispatch: A Tailored Deep Reinforcement Learning Approach“ [Internet]. IEEE Dataport; 2023. Available from : http://dx.doi.org/10.21227/vqn4-d248
Yujian Ye, Jianxiong Hu. "dataset for “Towards Risk-Aware Real-Time Security Constrained Economic Dispatch: A Tailored Deep Reinforcement Learning Approach“." doi: 10.21227/vqn4-d248