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    <title>EconStor Community: Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP)</title>
    <link>https://hdl.handle.net/10419/176725</link>
    <description>Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP)</description>
    <pubDate>Tue, 28 Apr 2026 15:29:42 GMT</pubDate>
    <dc:date>2026-04-28T15:29:42Z</dc:date>
    <item>
      <title>Analyzing the influence of large-scale weather patterns on renewable energy systems: A review</title>
      <link>https://hdl.handle.net/10419/336809</link>
      <description>Title: Analyzing the influence of large-scale weather patterns on renewable energy systems: A review
Authors: Layer, Kira; Gutmayer, Stephanie; Sandmeier, Thorben; Ringger, Jonas; Cermak, Jan; Fichtner, Wolf
Abstract: Electricity generation as well as electricity demand are dependent on the weather and climate, and this dependency is expected to further increase in the future. Challenges in energy systems arising from this dependency can be studied using large-scale weather patterns (WPs). These WPs can help reveal the atmospheric drivers of the challenges, but there exist many different classifications of large-scale WPs. Although WPs are widely used in energy-related studies, to our knowledge, no systematic review has yet evaluated the applicability of weather pattern classifications to analyzing extreme events and variability in energy systems. In this study, we aim to fill this gap by reviewing and combining literature dealing with both WP classifications and weather-induced challenges in energy systems. A total of 69 studies are included, which use different classification methods to study weather-induced challenges on energy systems. Overall, most challenges to the energy system arise during blocking weather patterns. Furthermore, we find that stable large-scale WPs allow for better forecasts of wind power generation if combined with other predictors. This review reveals research gaps underscoring the need to consider the whole energy system, including demand and the electricity grid, not only the generation of wind power and photovoltaics.</description>
      <pubDate>Thu, 01 Jan 2026 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://hdl.handle.net/10419/336809</guid>
      <dc:date>2026-01-01T00:00:00Z</dc:date>
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    <item>
      <title>Design limits and investment risks of mid-term storage under uncertain market conditions</title>
      <link>https://hdl.handle.net/10419/336783</link>
      <description>Title: Design limits and investment risks of mid-term storage under uncertain market conditions
Authors: Stelzer, Jonathan; Esser, Katharina; Weiskopf, Thorsten; Ardone, Armin; Bertsch, Valentin; Fichtner, Wolf
Abstract: The transition to a net-zero energy system requires large-scale integration of variable renewables, increasing demand for flexibility beyond short-term batteries and seasonal hydrogen. Emerging storage technologies feature cost structures that position them between these options, offering discharge durations of several hours to a few days, here referred to as mid-term storage. However, their economic feasibility depends strongly on their techno-economic parameters and evolving market dynamics. Identifying profitable and robust storage configurations under uncertain future market conditions is therefore crucial to bridge the perspectives of technology developers and investors. We employ the agent-based electricity market model PowerACE, which explicitly represents market participants as interacting decision-making agents. Using mean-reverting stochastic representations of fuel prices and renewable generation, we capture the impact of uncertainties on storage profitability from an individual investor's perspective. The analysis determines the maximum capital expenditure that still yields economically viable storage configurations across relevant combinations of techno-economic parameters. The results reveal that profitability is limited under current cost conditions, as the marginal contribution of storage capacity declines sharply with higher storage durations. At the same time, higher round-trip efficiency not only improves returns but also reduces market risk. Balancing efficiency, costs, and duration is essential for mid-term storage competitiveness, while risk-based assessments can guide robust technology and investment decisions.</description>
      <pubDate>Thu, 01 Jan 2026 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://hdl.handle.net/10419/336783</guid>
      <dc:date>2026-01-01T00:00:00Z</dc:date>
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    <item>
      <title>E-Akteur, Akteursbeziehungen in der Kreislaufwirtschaftlichen Wertschöpfung von E-Fahrzeugbatterien: Abschlussbericht</title>
      <link>https://hdl.handle.net/10419/323224</link>
      <description>Title: E-Akteur, Akteursbeziehungen in der Kreislaufwirtschaftlichen Wertschöpfung von E-Fahrzeugbatterien: Abschlussbericht
Authors: Huster, Sandra; Rudi, Andreas; Schultmann, Frank; Schneider, Ralph; Schmidt, Charlotte; Honold, Valentin
Abstract: Das Projekt "E-Akteur" untersuchte zentrale rechtliche, ökonomische und soziale Aspekte des End-of-Life-Managements von Elektrofahrzeugbatterien im Kontext einer zirkulären Wertschöpfung. Analysiert wurden Akteursrollen entlang der Batterie-Wertschöpfungskette, insbesondere bislang wenig beachtete Akteure wie Endkunden und Werkstätten. Im rechtlichen Teil wurden die EU-Batterieverordnung sowie weitere relevante Regelungen hinsichtlich Anforderungen an die Wiederverwendung und Umwidmung von Batterien ausgewertet. Es wird deutlich, dass klare Zuständigkeiten und rechtliche Verbindlichkeit benötigt werden. Empirische Erhebungen zeigen eine differenzierte Akzeptanz der Wiederverwendung von Batterien: Während Verbraucher vor allem niedrigere Preise im Vergleich zu Neubatterien und eine lange zweite Nutzungsdauer erwarten, bestehen bei Werkstätten Bedenken bezüglich Haftung und Rentabilität. Andere wirtschaftliche Akteure bewerten die Profitabilität ebenfalls als zentrales Entscheidungskriterium. Ein entwickeltes Simulationsmodell prognostiziert zukünftige Batteriemengenströme für das Recycling, die Umnutzung und die Wiederverwendung in Fahrzeugen bis 2050 unter verschiedenen Annahmen hinsichtlich technischer Entwicklungen und Akteursentscheidungen. Durch Variation der Annahmen werden verschiedene Szenarien betrachtet. Auf Basis der Akteursbefragungen, der Auswertung des Rechtsrahmens und der Simulationsergebnisse wird empfohlen, Verbraucheraufklärung zu betreiben, wirtschaftliche Anreize gezielt gemäß des gewünschten Batterieverwertungswegs zu setzen, und die regulatorischen Rahmenbedingungen zu harmonisieren. Eine zukunftsfähige Kreislaufwirtschaft für Traktionsbatterien erfordert das koordinierte Zusammenspiel aller relevanten Akteure.</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://hdl.handle.net/10419/323224</guid>
      <dc:date>2025-01-01T00:00:00Z</dc:date>
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    <item>
      <title>A review of challenges and opportunities in occupant modeling for future residential energy demand</title>
      <link>https://hdl.handle.net/10419/328261</link>
      <description>Title: A review of challenges and opportunities in occupant modeling for future residential energy demand
Authors: Vogl, Jonathan; Kleinebrahm, Max; Raab, Moritz; McKenna, Russell; Fichtner, Wolf
Abstract: Electrified heating and mobility, the uptake of air conditioning and distributed energy resources are reshaping residential electricity demand and will require substantial investment. Yet the dependencies that drive present and future residential demand across sociodemographic characteristics, occupant activities, energy service demands, local technologies, and interactions with the overarching energy system remain poorly understood. Activity-based, bottom-up models make these dependencies explicit, better informing flexible operation and investment in low-carbon technologies. We review 45 activity-based residential models and assess coverage of appliances, domestic hot water, space heating and cooling, and mobility (electric vehicle charging), which are rarely considered jointly in one integrated model. We identify methodological gaps for consistently modeling behavior: To our knowledge, this is the first review to include activity-based mobility modeling, thereby identifying methodological gaps in consistent behavior modeling across residential energy services: First, most studies simulate single occupants in isolation rather than entire households, thereby overlooking interdependencies among occupants. Second, predominant use of Markov models or independent univariate sampling limits temporal consistency. Based on these findings, future studies should combine complementary behavioral datasets with sophisticated models (e.g., deep neural networks) capable of capturing complex dependencies to generate high-quality synthetic behavioral data as a basis for future bottom-up residential energy demand modeling. Further progress requires open datasets and reproducible validation frameworks to benchmark and compare activity-based models and to ensure consistent progress in the field. Currently, there is no model available in the literature that derives energy demand for thermal comfort, hot water, mobility, and other services consistently from one fundamental representation of household behavior.</description>
      <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://hdl.handle.net/10419/328261</guid>
      <dc:date>2025-01-01T00:00:00Z</dc:date>
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