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    <title>EconStor Collection:</title>
    <link>https://hdl.handle.net/10419/103267</link>
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        <rdf:li rdf:resource="https://hdl.handle.net/10419/315017" />
        <rdf:li rdf:resource="https://hdl.handle.net/10419/324197" />
        <rdf:li rdf:resource="https://hdl.handle.net/10419/324196" />
        <rdf:li rdf:resource="https://hdl.handle.net/10419/302877" />
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    <dc:date>2026-04-29T16:18:50Z</dc:date>
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  <item rdf:about="https://hdl.handle.net/10419/315017">
    <title>The future spatial distribution of onshore wind energy capacity based on a probabilistic investment calculus</title>
    <link>https://hdl.handle.net/10419/315017</link>
    <description>Title: The future spatial distribution of onshore wind energy capacity based on a probabilistic investment calculus
Authors: Pflugfelder, Yannik; Weber, Christoph
Abstract: The spatial distribution of future renewable capacities is a key determinant for developing appropriate grid expansion plans. This is particularly relevant for onshore wind energy. Existing studies mostly extrapolate future installations based on existing capacities and available sites. As wind farm projects are developed mainly by private investors, the economic rationale of investing at specific sites deserves more attention. Therefore, the present contribution develops a model of economic choice for wind investments based on site-specific computations of the achievable net present value, taking into consideration the land availability at the regional level. Therefore, sitespecific investment decisions are modeled as (partly aggregated) discrete choices. The net present value is computed from investment costs and expected yields, which can be estimated based on wind speed time series and power curves. Available land can be identified by excluding settlement, infrastructure, and nature conservation areas with appropriate buffers, as well as sites with topographically unsuitable profiles. The model is formulated as a nested logit model that captures the interdependencies between choices on two levels: the probability of investment in a particular region on the first level and the probability of installing a specific turbine type on the second level. In an application for Germany with the target capacities of the German Renewable Energy Act, the model delivers a spatial distribution of the capacities at the NUTS 3 level. The model also enables the derivation of the necessary compensation level and the most frequently installed turbine types.</description>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://hdl.handle.net/10419/324197">
    <title>A perfect match for district heating networks? An investigation of Power-to-Heat and Combined Heat and Power 2035</title>
    <link>https://hdl.handle.net/10419/324197</link>
    <description>Title: A perfect match for district heating networks? An investigation of Power-to-Heat and Combined Heat and Power 2035
Authors: Furtwängler, Christian
Abstract: The recent energy crisis in Europe has underlined the importance of a fast replacement of fossil fuels like natural gas by green energy carriers. Great hopes for quick decarbonisation mostly rest on two technologies, hypothesized to form a "perfect match": Combined heat and power (CHP) generation units that are in widespread usage across district heating grids today are often planned to be decarbonized by using green fuels, e.g. green hydrogen originating from electrolysis with green electricity. Additionally, the direct usage of electricity for heating purposes (Power-to-Heat, PtH), is seen as a fitting complementing option. This contribution thus aims at investigating the cost structure of the CHP system of the future - and whether this perfect match is a likely outcome in different energy market environments. Three distinct mid-term scenarios for the year 2035 are developed and different heating portfolio setups are tested with regards to the viability of individual heating assets. For this analysis, the stochastic portfolio optimization framework StoOpt is used. The perfect match hypothesis is both theoretically confirmed and practically questioned by the obtained results. At least one of the technologies tends to struggle in different market environments and subsidies might be needed to secure investment in both technologies.</description>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://hdl.handle.net/10419/324196">
    <title>Bidding CHP portfolios consistently into sequential reserve and electricity spot markets</title>
    <link>https://hdl.handle.net/10419/324196</link>
    <description>Title: Bidding CHP portfolios consistently into sequential reserve and electricity spot markets
Authors: Beran, Philip; Furtwängler, Christian; Jahns, Christopher; Vogler, Arne; Weber, Christoph
Abstract: The profitable exploitation of asset portfolios in the European electricity markets has become more challenging in recent years. This is particularly true for combined heat and power (CHP) generation units that are often facing must-run conditions due to heat demands that need to be satisfied. Including the use of flexibility from storage technologies is key to optimize power plant operation margins and therefore it is crucial to adequately account for price uncertainties in the European market design. Stochastic optimization is thus frequently suggested for an optimal bidding and dispatch of said portfolios. In our contribution, we develop a novel chain of one weekly and five daily two-stage stochastic optimizations with recourse to identify the optimal bidding strategies for CHP portfolios to all relevant markets, including the key European electricity market segments, i.e., hourly day-ahead and quarterhourly intraday opening auctions, and control reserve markets, i.e., primary (FCR), secondary (aFRR) and tertiary (mFRR) reserve auctions. We test our model by means of a rolling-horizon approach on historical data and contrast our model's performance with regards to objective function improvement and computation time for various numbers of scenarios. We furthermore benchmark the model against its deterministic representation with and without perfect information. We find that stochastic optimization may substantially increase portfolio returns, without impairing the usability of stochastic optimization frameworks in real-world contexts, a result that is stable with and without the consideration of heat provision and with different market designs regarding FCR provision periods.</description>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://hdl.handle.net/10419/302877">
    <title>Inefficiencies in coupled electricity markets with different time granularity: Exploring the zigzag pattern</title>
    <link>https://hdl.handle.net/10419/302877</link>
    <description>Title: Inefficiencies in coupled electricity markets with different time granularity: Exploring the zigzag pattern
Authors: Jahns, Christopher
Abstract: In European intraday electricity markets, a systematic zigzag pattern can be observed, characterized by alternating maxima and minima at the shift of hourly products. This price formation contradicts the fundamental understanding, that prices to are a monotonously increasing function of residual demand and correspondingly would evolve smoothly across hours. This study investigates the phenomenon of restricted participation as the primary cause of the zigzag pattern. Restricted participation occurs when market participants maintain constant output through subhourly products. A notable instance is the lack of sub-hourly cross-border trading where foreign market participants are restricted from engaging in trading sub-hourly products. This is closely linked to is the differing time granularities observed in electricity trading across European countries. Three research questions guide this investigation: (1) Is restricted participation the main cause of non-smooth intraday prices? (2) How do technical restrictions on cross-border trading contribute? (3) What role do ramping and start-up costs play? Utilizing regression models and openly available data from Germany, the research confirms that restricted participation is the primary cause of the zigzag pattern. Furthermore, an analytical model of restricted participation in cross-border trading is developed, along with empirical parameterization. Based on this model it is estimated that lifting all technical restrictions on trading sub-hourly products would reduce systematic non-smoothness in intraday prices by only about 27%. These findings are unexpected, suggesting that despite economic incentives, a significant number of domestic power plants do not adjust their output based on intraday price signals. Ramping and start-up costs appear to have little influence.</description>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
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