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  <title>EconStor Collection:</title>
  <link rel="alternate" href="https://hdl.handle.net/10419/107939" />
  <subtitle />
  <id>https://hdl.handle.net/10419/107939</id>
  <updated>2026-04-28T16:54:17Z</updated>
  <dc:date>2026-04-28T16:54:17Z</dc:date>
  <entry>
    <title>Market based decarbonization and the interaction with reliability policies</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/285121" />
    <author>
      <name>Thomaßen, Georg</name>
    </author>
    <author>
      <name>Bruckner, Thomas</name>
    </author>
    <id>https://hdl.handle.net/10419/285121</id>
    <updated>2024-03-14T15:13:32Z</updated>
    <published>2024-01-01T00:00:00Z</published>
    <summary type="text">Title: Market based decarbonization and the interaction with reliability policies
Authors: Thomaßen, Georg; Bruckner, Thomas
Abstract: This paper investigates market-based decarbonization, driven by carbon pricing, and under different regulatory settings. These consist of a conventional energy-only market (EOM), an EOM with operating reserve demand curve (ORDC) and a capacity market (CM). We find that contrary to previous research findings, all markets produce conclusive market outcomes in all stages of decarbonization, as flexible technologies create market signals that ensure the economic viability of renewables. This is relevant for systems that rely on carbon pricing, but also for those relying on out-of-the-market measures to deploy renewables, as it implies that markets can be deregulated again later if carbon prices are sufficiently high. All three regulatory scenarios further achieve close-to-optimal market outcomes, if they are calibrated well. The outcome in CMs, however, is especially prone to suboptimal configurations, relying on several design parameters, which are commonly deducted from weather data and system projections. Varying only one of these parameters induced large changes in the observed generation mix. ORDCs provided more stable results, even if the input parameters differed strongly from optimal values. We therefore recommend to rely on ORDCs to maintain resource adequacy, as they appear to produce lower costs and interfere less with the general market dynamics than CMs.</summary>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Spatial characteristics to explain residential photovoltaic adoption intentions: An exploratory analysis</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/278114" />
    <author>
      <name>Schulte, Emily</name>
    </author>
    <author>
      <name>Bruckner, Thomas</name>
    </author>
    <author>
      <name>Scheller, Fabian</name>
    </author>
    <id>https://hdl.handle.net/10419/278114</id>
    <updated>2024-03-12T15:05:20Z</updated>
    <published>2023-01-01T00:00:00Z</published>
    <summary type="text">Title: Spatial characteristics to explain residential photovoltaic adoption intentions: An exploratory analysis
Authors: Schulte, Emily; Bruckner, Thomas; Scheller, Fabian
Abstract: Despite their relevance for adoption levels in spatial analyses, previous studies on adoption intention excluded measures characterizing the living environment of participants such as population density and previous photovoltaic (PV) installations so far. To fill this gap, this study was designed to investigate relations between residential PV adoption intention and characteristics of the living environment of respondents. A quantitative survey was performed on a representative sample of 1,800 homeowners in Germany and matched with registered spatial characteristics on the zip-code level. The Mann-Whitney U test was used to compare the adoption intention between groups with low and high expressions of the independent variables with the total sample, and with consumer segments using the Sinus-Milieu model. The results for the total sample demonstrated that actual PV diffusion, population density, city-type and share of (semi-) detached houses are not significantly related to the individual adoption intention, whereas perceived diffusion is. Two milieu groups showed higher intentions with lower actual PV diffusion in their spatial environment, and two groups revealed higher intentions along with relatively higher incomes. Perceived diffusion is only weakly related to actual diffusion levels, implying a gap between reality and perceptions. Overall, the results imply that spatial characteristics on the zip-code level are not related to individual adoption intention, whereas the perceived presence of PV systems in the social and spatial environment positively influences adoption intention.</summary>
    <dc:date>2023-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>A review of designing empirically grounded agent-based models of innovation diffusion: Development process, conceptual foundation and research agenda</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/191981" />
    <author>
      <name>Scheller, Fabian</name>
    </author>
    <author>
      <name>Johanning, Simon</name>
    </author>
    <author>
      <name>Bruckner, Thomas</name>
    </author>
    <id>https://hdl.handle.net/10419/191981</id>
    <updated>2023-12-26T03:00:38Z</updated>
    <published>2019-01-01T00:00:00Z</published>
    <summary type="text">Title: A review of designing empirically grounded agent-based models of innovation diffusion: Development process, conceptual foundation and research agenda
Authors: Scheller, Fabian; Johanning, Simon; Bruckner, Thomas
Abstract: Modeling the diffusion of innovations is a very challenging task, as there are various influencing factors to consider. At the same time, insights into the diffusion process can help decision makers to detect weak points of potential business models. In the literature, various models and methodologies that might tackle this problem are presented. Between these, empirically grounded agent-based modeling turned out to be one of the most promising approaches. However, the current culture is dominated by papers that fail to document critical methodological details. Thus, existing agent-based models for real-world analysis differ extensively in their design and grounding and therefore also in their predictions and conclusions. Additionally, the selection of modeling aspects seems too often be ad hoc without any defendable rationale. Concerning this matter, to draw on experiences could guide the researcher. This research paper seeks to synthesize relevant publications at the interface of empirical grounding, agent-based modeling and innovation diffusion to provide an overview of the existing body of knowledge. The major aim is to assess existing approaches regarding development procedure, entity and dynamics consideration and theoretical grounding to suggest a future research agenda. This might lead to the development of more robust models. According to the findings of this review, future work needs to focus on generic design, model coupling, research consistency, modular testing, actor involvement, behavior modeling, network foundation, and data transparency. In a subsequent step and based on the findings, a novel model approach needs to be designed and implemented.</summary>
    <dc:date>2019-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Causes and effects of historical transmission grid collapses and implications for the German power system</title>
    <link rel="alternate" href="https://hdl.handle.net/10419/190501" />
    <author>
      <name>Behnert, Marika</name>
    </author>
    <author>
      <name>Bruckner, Thomas</name>
    </author>
    <id>https://hdl.handle.net/10419/190501</id>
    <updated>2023-11-12T02:28:00Z</updated>
    <published>2018-01-01T00:00:00Z</published>
    <summary type="text">Title: Causes and effects of historical transmission grid collapses and implications for the German power system
Authors: Behnert, Marika; Bruckner, Thomas
Abstract: Against the background of the energy transition accompanied by a rising penetration of renewable energy (REN) sources and a stepwise phase out of conventional power plants in order to fulfill climate protection targets, the requirements for a reliable transmission grid infrastructure increased in the last years. High coordination and communication efforts among market and system operators as well as weather extremes that occur more frequently enhance the probability of critical network states. In this paper, causes and impacts of 250 prominent transmission grid collapses in the period from 1965 to 2012 were analyzed. Based on historical events, blackout data sets were clustered inter alia by their date, affected continent as well as the duration of interrupted supply, respectively. We find an ascending number of outages along with a longer averaged duration over time. It is studied how different categories of causes evoking large-scale power blackouts are distributed regionally and temporally. Furthermore, challenges to prevent grid malfunctions, both from a technical and societal perspective, are elaborated focusing on the German power system.</summary>
    <dc:date>2018-01-01T00:00:00Z</dc:date>
  </entry>
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