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  4. AI agents assessing flexibility: the value of demand side management in times of high energy prices
 
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2022
Conference Paper
Title

AI agents assessing flexibility: the value of demand side management in times of high energy prices

Abstract
High energy and electricity prices, coupled with high price volatility, increase the value of demand response and demand side management. Energy management systems that are predictive and exchange-price oriented can help to leverage flexibility while lowering energy costs. In this paper, the value of flexibility is assessed in two scenarios of low and high energy prices. To that end, a self-learning home energy management system is introduced that takes into account the new volatility of high stock market electricity prices. The proposed approach is compared to a baseline system, which is a typical household self-consumption optimization. The findings indicate a significant economic potential of an exchange-price oriented usage of residential flexibility options in contrast to self-consumption optimization. Furthermore, the value of flexibility for the exemplary residential system increased more than fivefold between 2021 and 2022, while prices increased about fourfold.
Author(s)
Dreher, Marian Alexander  orcid-logo
Fraunhofer-Institut für Energiewirtschaft und Energiesystemtechnik IEE  
Martmann, Lisa Marie
Fraunhofer-Institut für Energiewirtschaft und Energiesystemtechnik IEE  
Lehna, Malte
Fraunhofer-Institut für Energiewirtschaft und Energiesystemtechnik IEE  
Roelofs, Cyriana Maria Antonia
Fraunhofer-Institut für Energiewirtschaft und Energiesystemtechnik IEE  
Bergsträßer, Jonathan  orcid-logo
Fraunhofer-Institut für Energiewirtschaft und Energiesystemtechnik IEE  
Scholz, Christoph
Fraunhofer-Institut für Energiewirtschaft und Energiesystemtechnik IEE  
Slaby, Wolfgang  
Fraunhofer-Institut für Energiewirtschaft und Energiesystemtechnik IEE  
Wetzel, Heike
Mainwork
EEM 2022, 18th International Conference on the European Energy Market  
Conference
International Conference on the European Energy Market 2022  
DOI
10.1109/EEM54602.2022.9920982
Language
English
Fraunhofer-Institut für Energiewirtschaft und Energiesystemtechnik IEE  
Keyword(s)
  • Demand Side Management

  • Energy Management

  • Power System Economics

  • Reinforcement Learning

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