A Reinforcement Learning approach for the continuous electricity market of Germany: Trading from the perspective of a wind park operator

A Reinforcement Learning approach for the continuous electricity market of Germany: Trading from the perspective of a wind park operator

With the rising extension of renewable energies, the intraday electricity markets have recorded a growing popularity amongst traders as well as electric utilities to cope with the induced volatility of the energy supply. Through their short trading horizon and continuous nature, the intraday markets...

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Bibliographic Details
Main Authors: Malte Lehna, Björn Hoppmann, Christoph Scholz, René Heinrich
Format: Article
Language:English
Published: Elsevier 2022-05-01
Series:Energy and AI
Subjects:
Deep Reinforcement Learning
German intraday electricity trading
Deep neural networks
Markov Decision Process
Proximal Policy Optimization
Electricity price forecast
Online Access:http://www.sciencedirect.com/science/article/pii/S2666546822000039

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http://www.sciencedirect.com/science/article/pii/S2666546822000039

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