TY - GEN
T1 - AC Transmission System Expansion Planning using a Q-learning Algorithm
AU - Llivisaca, Mateo D.
AU - Torres Contreras, Santiago Patricio
AU - Astudillo Salinas, Darwin Fabian
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025/10/6
Y1 - 2025/10/6
N2 - The Transmission Network Expansion Planning (TNEP) is a complex optimization problem. Metaheuristic techniques and mathematical methods are currently used to obtain reliable results for linearized or simplified TNEP formulations. However, solving the TNEP problem using the full AC equations remains an issue. The use of machine learning in the context of power systems optimization has increased in recent years. Therefore, this research explores the application of reinforcement learning to solve the AC TNEP problem, framing it as an episodic decision-making process where each episode represents a distinct planning scenario. The results obtained for the Garver 6-bus system show that it is a viable method.
AB - The Transmission Network Expansion Planning (TNEP) is a complex optimization problem. Metaheuristic techniques and mathematical methods are currently used to obtain reliable results for linearized or simplified TNEP formulations. However, solving the TNEP problem using the full AC equations remains an issue. The use of machine learning in the context of power systems optimization has increased in recent years. Therefore, this research explores the application of reinforcement learning to solve the AC TNEP problem, framing it as an episodic decision-making process where each episode represents a distinct planning scenario. The results obtained for the Garver 6-bus system show that it is a viable method.
KW - Episodic problem
KW - Q-Learning
KW - Reinforcement Learning
KW - Transmission Expansion Planning
UR - https://ieeexplore.ieee.org/abstract/document/11180229
UR - https://www.scopus.com/pages/publications/105019303118
UR - https://www.mendeley.com/catalogue/0b64c0fb-ccc3-3e6b-979b-d9d55cdbea8f/
U2 - 10.1109/PowerTech59965.2025.11180229
DO - 10.1109/PowerTech59965.2025.11180229
M3 - Contribución a la conferencia
SN - 9798331543976
T3 - 2025 IEEE Kiel PowerTech, PowerTech 2025
BT - 2025 IEEE Kiel PowerTech, PowerTech 2025
PB - Institute of Electrical and Electronics Engineers Inc.
ER -