<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>16371</id>
    <completedYear/>
    <publishedYear>2015</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>5</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace>Piscataway, NJ</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2016-05-30</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">The Effect of Variable Renewable Energy Sources on the Volatility of Wholesale Electricity Prices - A Stylized Full Cost Approach</title>
    <parentTitle language="eng">Proceedings, 12th International Conference on the European Energy Market (EEM), Lisbon, 19-22 May 2015</parentTitle>
    <identifier type="doi">10.1109/EEM.2015.7216772</identifier>
    <identifier type="isbn">978-1-4673-6692-2</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <author>
      <firstName>Thomas</firstName>
      <lastName>Möbius</lastName>
    </author>
    <submitter>
      <firstName>Juliane</firstName>
      <lastName>Wolf</lastName>
    </submitter>
    <author>
      <firstName>Felix</firstName>
      <lastName>Müsgens</lastName>
    </author>
    <collection role="institutes" number="3203">FG Energiewirtschaft</collection>
  </doc>
  <doc>
    <id>20911</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>5</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace>Piscataway, NJ</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2018-01-10</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Electricity Market Equilibria and Intermittent Renewables – A Stochastic Approach</title>
    <parentTitle language="eng">14th International Conference on the European Energy Market (EEM), Dresden Germany, 6-9 June 2017</parentTitle>
    <identifier type="doi">10.1109/EEM.2017.7981988</identifier>
    <identifier type="isbn">978-1-5090-5499-2</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <author>
      <firstName>Thomas</firstName>
      <lastName>Möbius</lastName>
    </author>
    <submitter>
      <firstName>Thomas</firstName>
      <lastName>Möbius</lastName>
    </submitter>
    <author>
      <firstName>Felix</firstName>
      <lastName>Müsgens</lastName>
    </author>
    <collection role="institutes" number="3203">FG Energiewirtschaft</collection>
  </doc>
  <doc>
    <id>22787</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>5</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace>Piscataway, NJ</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2018-11-29</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Integrated Electricity and Gas Market Modeling – Effects of Gas Demand Uncertainty</title>
    <abstract language="eng">This paper develops an integrated fundamental investment model which considers both the gas and electricity sector. Furthermore, we adopt the theory of stochastic programming with recourse in the combined model to account for uncertainty in the gas market. This approach enables us to analyze how uncertain gas demand in other sectors affects decisions to invest in electricity generation capacities. We find an overall decrease and a reallocation of investments in gas-fired power plants. We also quantify the expected costs of ignoring uncertainty.</abstract>
    <parentTitle language="eng">15th International Conference on the European Energy Market (EEM), 27-29 June 2018,  Lodz, Poland</parentTitle>
    <identifier type="isbn">978-1-5386-1488-4</identifier>
    <identifier type="url">https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&amp;arnumber=8469790</identifier>
    <identifier type="doi">10.1109/EEM.2018.8469790</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <author>
      <firstName>Iegor</firstName>
      <lastName>Riepin</lastName>
    </author>
    <submitter>
      <firstName>Iegor</firstName>
      <lastName>Riepin</lastName>
    </submitter>
    <author>
      <firstName>Thomas</firstName>
      <lastName>Möbius</lastName>
    </author>
    <author>
      <firstName>Felix</firstName>
      <lastName>Müsgens</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>electricity market</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>integrated energy system modeling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>natural gas market</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>stochastic modeling</value>
    </subject>
    <collection role="institutes" number="3203">FG Energiewirtschaft</collection>
  </doc>
  <doc>
    <id>28687</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>14</pageNumber>
    <edition/>
    <issue/>
    <volume>285</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2022-03-16</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Modelling uncertainty in coupled electricity and gas systems - is it worth the effort?</title>
    <abstract language="eng">The interdependence of electricity and natural gas markets is becoming a major topic in energy research. Integrated energy models are used to assist decision-making for businesses and policymakers addressing challenges of energy transition and climate change. The analysis of complex energy systems requires large-scale models, which are based on extensive databases, intertemporal dynamics and a multitude of decision variables. Integrating such energy system models results in increased system complexity. This complexity poses a challenge for energy modellers to address multiple uncertainties that affect both markets. Stochastic optimisation approaches enable an adequate consideration of uncertainties in investment and operation planning; however, stochastic modelling of integrated large-scale energy systems further scales the level of complexity. In this paper, we combine integrated and stochastic optimisation problems and parametrise our model for European electricity and gas markets. We analyse and compare the impact of uncertain input parameters, such as gas and electricity demand, renewable energy capacities and fuel and CO2 prices, on the quality of the solution obtained in the integrated optimisation problem. Our results quantify the value of encoding uncertainty as a part of a model. While the methodological contribution should be of interest for energy modellers, our findings are relevant for industry experts and stakeholders with an empirical interest in the European energy system.</abstract>
    <parentTitle language="eng">Applied Energy</parentTitle>
    <identifier type="url">https://www.sciencedirect.com/science/article/abs/pii/S0306261920317426?via%3Dihub</identifier>
    <identifier type="doi">10.1016/j.apenergy.2020.116363</identifier>
    <identifier type="issn">1872-9118</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="Artikelnummer">116363</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <author>
      <firstName>Iegor</firstName>
      <lastName>Riepin</lastName>
    </author>
    <submitter>
      <firstName>Taimyra</firstName>
      <lastName>Batz Liñeiro</lastName>
    </submitter>
    <author>
      <firstName>Thomas</firstName>
      <lastName>Möbius</lastName>
    </author>
    <author>
      <firstName>Felix</firstName>
      <lastName>Müsgens</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Energy markets and pricing</value>
    </subject>
    <collection role="institutes" number="3203">FG Energiewirtschaft</collection>
  </doc>
  <doc>
    <id>32533</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>38</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>articlenr</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-18</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A hybrid model for day-ahead electricity price forecasting: Combining fundamental and stochastic modelling</title>
    <abstract language="eng">The accurate prediction of short-term electricity prices is vital for effective trading strategies, power plant scheduling, profit maximisation and efficient system operation. However, uncertainties in supply and demand make such predictions challenging. We propose a hybrid model that combines a techno-economic energy system model with stochastic models to address this challenge. The techno-economic model in our hybrid approach provides a deep understanding of the market. It captures the underlying factors and their impacts on electricity prices, which is impossible with statistical models alone. The statistical models incorporate non-techno-economic aspects, such as the expectations and speculative behaviour of market participants, through the interpretation of prices. The hybrid model generates both conventional point predictions and probabilistic forecasts, providing a comprehensive understanding of the market landscape. Probabilistic forecasts are particularly valuable because they account for market uncertainty, facilitating informed decision-making and risk management. Our model delivers state-of-the-art results, helping market participants to make informed decisions and operate their systems more efficiently.</abstract>
    <parentTitle language="eng">arXiv</parentTitle>
    <identifier type="doi">10.48550/arXiv.2304.09336</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <author>
      <firstName>Mira</firstName>
      <lastName>Watermeyer</lastName>
    </author>
    <submitter>
      <firstName>Maria</firstName>
      <lastName>Stojan</lastName>
    </submitter>
    <author>
      <firstName>Thomas</firstName>
      <lastName>Möbius</lastName>
    </author>
    <author>
      <firstName>Oliver</firstName>
      <lastName>Grothe</lastName>
    </author>
    <author>
      <firstName>Felix</firstName>
      <lastName>Müsgens</lastName>
    </author>
    <collection role="institutes" number="3203">FG Energiewirtschaft</collection>
    <collection role="institutes" number="7003">Energie-Innovationszentrum / Energy Economics Lab</collection>
  </doc>
  <doc>
    <id>32532</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>30</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-18</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Enhancing energy system models using better load forecasts</title>
    <abstract language="eng">Since energy system models require a large amount of technical and economic data, their quality significantly affects the reliability of the results. However, some publicly available data sets, such as the transmission system operators’ day-ahead load forecasts, are known to be biased and inaccurate, leading to lower energy system model performance. We propose a time series model that enhances the accuracy of transmission system operators’ load forecast data in real-time, using only the load forecast error’s history as input. We further present an energy system model developed specifically for price forecasts of the short-term day-ahead market. We demonstrate the effectiveness of the improved load data as input by applying it to this model, which shows a strong reduction in pricing errors, particularly during periods of high prices and tight markets. Our results highlight the potential of our method the enhance the accuracy of energy system models using improved input data.</abstract>
    <parentTitle language="eng">Energy Systems</parentTitle>
    <identifier type="doi">10.1007/s12667-023-00590-3</identifier>
    <identifier type="issn">1868-3975</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <author>
      <firstName>Thomas</firstName>
      <lastName>Möbius</lastName>
    </author>
    <submitter>
      <firstName>Maria</firstName>
      <lastName>Stojan</lastName>
    </submitter>
    <author>
      <firstName>Mira</firstName>
      <lastName>Watermeyer</lastName>
    </author>
    <author>
      <firstName>Oliver</firstName>
      <lastName>Grothe</lastName>
    </author>
    <author>
      <firstName>Felix</firstName>
      <lastName>Müsgens</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Data pre-processing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Day-ahead electricity prices</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Energy system modelling</value>
    </subject>
    <collection role="institutes" number="3203">FG Energiewirtschaft</collection>
    <collection role="institutes" number="7003">Energie-Innovationszentrum / Energy Economics Lab</collection>
  </doc>
  <doc>
    <id>32535</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>126</volume>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-18</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Risk aversion and flexibility options in electricity markets</title>
    <abstract language="eng">Investments in electricity transmission and generation capacity must be made despite significant uncertainty about the future developments. The sources of this uncertainty include, among others, the future levels and spatiotemporal distribution of electricity demand, fuel costs and future energy policy. In recent years, these uncertainties have increased due to the ongoing evolution of supply- and demand-side technologies and rapid policy changes designed to encourage a transition to low-carbon energy systems. Because transmission and generation investments have long lead times and are difficult to reverse, they are subject to a considerable – and arguably growing – amount of risk.</abstract>
    <parentTitle language="eng">Energy Economics</parentTitle>
    <identifier type="issn">0140-9883</identifier>
    <identifier type="issn">1873-6181</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Artikelnummer">106767</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <author>
      <firstName>Thomas</firstName>
      <lastName>Möbius</lastName>
    </author>
    <submitter>
      <firstName>Maria</firstName>
      <lastName>Stojan</lastName>
    </submitter>
    <author>
      <firstName>Iegor</firstName>
      <lastName>Riepin</lastName>
    </author>
    <author>
      <firstName>Felix</firstName>
      <lastName>Müsgens</lastName>
    </author>
    <author>
      <firstName>Adriaan H.</firstName>
      <lastName>van der Weijde</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Flexibility</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Storage</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Demand response</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Generation and transmission</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>expansion</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Investment</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Risk aversion</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Stochastic programming</value>
    </subject>
    <collection role="institutes" number="3203">FG Energiewirtschaft</collection>
    <collection role="institutes" number="7003">Energie-Innovationszentrum / Energy Economics Lab</collection>
  </doc>
  <doc>
    <id>32531</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>articlenr</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-18</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Grok It and Use It: Teaching Energy Systems Modeling</title>
    <abstract language="eng">This article details our experience developing and teaching an “Energy Systems Modeling” course, which sought to introduce graduate-level students to operations research, energy economics, and system modeling using the General Algebraic Modeling System (GAMS). In this paper, we focus on (i) the mathematical problems discussed in the course, (ii) the energy-related empirical interpretations of these mathematical problems, and (iii) the best teaching practices (i.e., our experiences regarding how to make the content interesting and accessible for students).</abstract>
    <parentTitle language="eng">SSRN eLibrary</parentTitle>
    <identifier type="doi">10.2139/ssrn.4320978</identifier>
    <identifier type="issn">1556-5068</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <author>
      <firstName>Iegor</firstName>
      <lastName>Riepin</lastName>
    </author>
    <submitter>
      <firstName>Maria</firstName>
      <lastName>Stojan</lastName>
    </submitter>
    <author>
      <firstName>Smaranda</firstName>
      <lastName>Sgarciu</lastName>
    </author>
    <author>
      <firstName>Maximilian</firstName>
      <lastName>Bernecker</lastName>
    </author>
    <author>
      <firstName>Thomas</firstName>
      <lastName>Möbius</lastName>
    </author>
    <author>
      <firstName>Felix</firstName>
      <lastName>Müsgens</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Energy Systems</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Mathematical Programming</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Teaching</value>
    </subject>
    <collection role="institutes" number="3203">FG Energiewirtschaft</collection>
    <collection role="institutes" number="7003">Energie-Innovationszentrum / Energy Economics Lab</collection>
  </doc>
</export-example>
