A deep q-networks model for optimising decision-making process in the context of energy transition modelling

A deep q-networks model for optimising decision-making process in the context of energy transition modelling

Ambitious decarbonization mandates and rising volatility in energy markets demand decision-support tools that can learn, adapt, and generalize beyond the static optimization frameworks that dominate contemporary energy transition modelling. Addressing this gap, we articulate and validate a Deep Q-Ne...

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Bibliographic Details
Main Authors: Ana Tănăsescu, Cristian Bucur, Jean Vasile Andrei, Bogdan-George Tudorică, Dorel Mihai Paraschiv, Dorel Dușmănescu
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Environmental Research Communications
Subjects:
energy transition modelling
reinforcement learning
deep q-networks
OpenAI Gym
platform architecture
Online Access:https://doi.org/10.1088/2515-7620/adf530
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https://doi.org/10.1088/2515-7620/adf530

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