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    <id>3920</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>13876</pageFirst>
    <pageLast>13894</pageLast>
    <pageNumber>19</pageNumber>
    <edition/>
    <issue>15</issue>
    <volume>10</volume>
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    <title language="eng">Data Center HVAC Control Harnessing Flexibility Potential via Real-Time Pricing Cost Optimization Using Reinforcement Learning</title>
    <abstract language="eng">With increasing electricity prices, cost savings through load shifting are becoming increasingly important for energy end users. While dynamic pricing encourages customers to shift demand to low price periods, the nonstationary and highly volatile nature of electricity prices poses a significant challenge to energy management systems. In this article, we investigate the flexibility potential of data centers by optimizing heating, ventilation, and air conditioning systems with a general model-free reinforcement learning (RL) approach. Since the soft actor-critic algorithm with feedforward networks did not work satisfactorily in this scenario, we propose instead a parameterization with a recurrent neural network architecture to successfully handle spot-market price data. The past is encoded into a hidden state, which provides a way to learn the temporal dependencies in the observations and highly volatile rewards. The proposed method is then evaluated in experiments on a simulated data center. Considering real temperature and price signals over multiple years, the results show a cost reduction compared to a proportional, integral and derivative controller while maintaining the temperature of the data center within the desired operating ranges. In this context, this work demonstrates an innovative and applicable RL approach that incorporates complex economic objectives into agent decision-making. The proposed control method can be integrated into various Internet of Things-based smart building solutions for energy management.</abstract>
    <parentTitle language="eng">IEEE Internet of Things Journal</parentTitle>
    <identifier type="doi">10.1109/jiot.2023.3263261</identifier>
    <enrichment key="opus.import.data">@articleBiemann.2023, author = Biemann, Marco and Gunkel, Philipp Andreas and Scheller, Fabian and Huang, Lizhen and Liu, Xiufeng, year = 2023, title = Data Center HVAC Control Harnessing Flexibility Potential via Real-Time Pricing Cost Optimization Using Reinforcement Learning, pages = 13876–13894, volume = 10, number = 15, journal = IEEE Internet of Things Journal, doi = 10.1109/jiot.2023.3263261</enrichment>
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    <author>Marco Biemann</author>
    <author>Philipp Andreas Gunkel</author>
    <author>Fabian Scheller</author>
    <author>Lizhen Huang</author>
    <author>Xiufeng Liu</author>
  </doc>
  <doc>
    <id>3936</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>115526</pageFirst>
    <pageLast>115526</pageLast>
    <pageNumber>1</pageNumber>
    <edition/>
    <issue/>
    <volume>277</volume>
    <type>article</type>
    <publisherName/>
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    <title language="eng">From passive to active: Flexibility from electric vehicles in the context of transmission system development</title>
    <abstract language="eng">Electrification of transport in RES-based power system will support the decarbonisation of the transport sector. However, due to the increase in energy demand and the large peak effects of charging, the passive integration of electric cars is likely to undermine sustainability efforts. This study investigates three different charging strategies for electric vehicle in Europe offering various degrees of flexibility: passive charging, smart charging and vehicle-to-grid, and puts this flexibility in perspective with the flexibility offered by interconnections. We use the Balmorel optimization tool to represent the short-term dispatch and long-term investment in the energy system and we contribute to the state-of-the-art in developing new methodologies to represent home charging and battery degradation. Our results show how each step of increased charging flexibility reduces system costs, affects energy mix, impacts spot prices and reduces CO2 emissions until the horizon 2050. We quantify how flexible charging and variable generation mutually support each other (&gt;100 TWh from wind and solar energy in 2050) and restrict the business case for stationary batteries, whereas passive charging results in a substitution of wind by solar energy. The comparison of each charging scheme with and without interconnection expansion highlights the interplay between European countries in terms of electricity prices and CO2 emissions in the context of electrified transport. Although the best outcome is reached under the most flexible scenario at the EU level, the situation of the countries with the cheapest and most decarbonised electricity mix is damaged, which calls for adapted coordination policy at the EU level.</abstract>
    <parentTitle language="eng">Applied Energy</parentTitle>
    <identifier type="issn">1872-9118</identifier>
    <identifier type="doi">10.1016/j.apenergy.2020.115526</identifier>
    <enrichment key="opus.import.data">@articleGunkel.2020, author = Gunkel, Philipp Andreas and Bergaentzlé, Claire and Græsted Jensen, Ida and Scheller, Fabian, year = 2020, title = From passive to active: Flexibility from electric vehicles in the context of transmission system development, pages = 115526, volume = 277, issn = 03062619, journal = Applied Energy, doi = 10.1016/j.apenergy.2020.115526</enrichment>
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    <author>Philipp Andreas Gunkel</author>
    <author>Claire Bergaentzlé</author>
    <author>Ida Græsted Jensen</author>
    <author>Fabian Scheller</author>
  </doc>
  <doc>
    <id>3905</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>103037</pageFirst>
    <pageLast>103037</pageLast>
    <pageNumber>1</pageNumber>
    <edition/>
    <issue/>
    <volume>56</volume>
    <type>article</type>
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    <title language="eng">Future role and economic benefits of hydrogen and synthetic energy carriers in Germany: a review of long-term energy scenarios</title>
    <abstract language="eng">Determining the development of Germany’s energy system is the subject of a series of studies. Since their results play a significant role in the political energy debate for understanding the role of hydrogen and synthetic energy carriers, a better discussion is needed. This article provides an assessment of published transition pathways for Germany to assess the role and advantages of hydrogen-based carriers. Twelve energy studies including 37 scenarios for the years 2030 and 2050 were evaluated. Despite the variations, the carrier will play an important role. While their deployment is expected to have only started by 2030 with a mean demand of 91 TWh/a (4% of the final energy demand) in Germany, they will be an essential part by 2050 with a mean demand of 480 TWh/a (24%). The outcome of the scenarios depends on the chosen methods and assumptions. A moderately positive correlation (0.53) between the decarbonisation targets and the share of hydrogen-based carriers in final energy demand underlines the relevance for reaching the climate targets. Additionally, value creation effects of about 16 billion EUR/a in 2050 can be expected for hydrogen-based carriers. Hydrogen is expected to be produced domestically while synthetic fuels are projected to be mostly imported.</abstract>
    <parentTitle language="eng">Sustainable Energy Technologies and Assessments</parentTitle>
    <identifier type="issn">22131388</identifier>
    <identifier type="doi">10.1016/j.seta.2023.103037</identifier>
    <enrichment key="opus.import.data">@articleScheller.2023, author = Scheller, Fabian and Wald, Stefan and Kondziella, Hendrik and Gunkel, Philipp Andreas and Bruckner, Thomas and Keles, Dogan, year = 2023, title = Future role and economic benefits of hydrogen and synthetic energy carriers in Germany: a review of long-term energy scenarios, pages = 103037, volume = 56, issn = 22131388, journal = Sustainable Energy Technologies and Assessments, doi = 10.1016/j.seta.2023.103037</enrichment>
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    <author>Fabian Scheller</author>
    <author>Stefan Wald</author>
    <author>Hendrik Kondziella</author>
    <author>Philipp Andreas Gunkel</author>
    <author>Thomas Bruckner</author>
    <author>Dogan Keles</author>
    <collection role="institutes" number="fwi">Fakultät Wirtschaftsingenieurwesen</collection>
    <collection role="institutes" number="insys">Institut für Sustainable Energy Systems (INSYS)</collection>
  </doc>
</export-example>
