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@PHDTHESIS{Kotzur:858675,
      author       = {Kotzur, Leander},
      title        = {{F}uture {G}rid {L}oad of the {R}esidential {B}uilding
                      {S}ector},
      volume       = {442},
      school       = {RWTH Aachen},
      type         = {Dr.},
      address      = {Jülich},
      publisher    = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
      reportid     = {FZJ-2018-07520},
      isbn         = {978-3-95806-370-9},
      series       = {Schriften des Forschungszentrums Jülich Reihe Energie $\&$
                      Umwelt / Energy $\&$ Environment},
      pages        = {xxi, 213 S.},
      year         = {2018},
      note         = {RWTH Aachen, Diss., 2018},
      abstract     = {The installation and operation of distributed energy
                      resources in the form of photovoltaics, co-generation units,
                      or batteries, and the electrification of the heat supply are
                      seen as promising options to reduce greenhouse gas emissions
                      of residential buildings. Nevertheless, their uptake
                      significantly changes the interaction of the residential
                      building stock with the electricity grid and the centralized
                      supply infrastructure and questions their current design.
                      Therefore, the objective of this work is to derive the
                      future residential electricity grid load spatially and
                      temporally resolved to define a decision basis for future
                      grid and market designs. In order to generally predict the
                      future structure, design and operation of residential supply
                      systems and efficiency measures, a Mixed-Integer Linear
                      Program is introduced that minimizes the total annual energy
                      supply cost of a single buildings since the technology
                      adoption is mainly economically driven. The minimization of
                      the greenhouse gas footprint can be added as second
                      objective. The optimization model accounts for the temporal
                      occupant activities, their related device usage, tolerated
                      room temperature levels, limited roof capacities, or
                      different levels of additional insulation. Since the variety
                      of investment and operation options make the model
                      computationally challenging, clustering based times series
                      aggregation techniques are developed and introduced to
                      reduce the complexity of the model. A novel aggregation
                      algorithm based on Mixed-Integer Quadratic Programs is
                      introduced to scale the technology adoption and operation
                      from the single building perspective to a nationwide scope
                      by creating a spatially resolved archetype building stock
                      from Census data and building databases. 200 archetype
                      buildings are concluded to sufficiently represent the
                      diversity of building types in the different municipalities
                      in Germany. These archetype buildings are optimized for the
                      weather years 2010 until 2015 and the results are validated
                      to residential energy consumption value from public
                      statistics, whereby the regional demand impact of different
                      weather years is illustrated. Afterwards, a scenario frame
                      for 2050 is defined and the buildings are optimized to reach
                      a carbon neutral building stock with minimal cost. As
                      result, at least 130 GWof photovoltaic are deployed and
                      above 90 TWh/a of the generated electricity are used for
                      self-consumption in the residential buildings. Nevertheless,
                      the total demand for electricity significantly increases
                      since 17 to 26 GWel of heat pumps are installed to replace
                      combustion boilers, while only 30 $\%$ of space heat are
                      saved by refurbishment measures. The spatially resolved
                      archetype building stock allows new insights: The urban
                      areas can compensate the increasing electricity demand by
                      efficient co-generation units, e.g. in form of fuel cells.
                      Nevertheless, those are not cost efficient in the rural
                      areas where the photovoltaic generation and the heatpump
                      demand temporally disjoin, resulting in a doubling of the
                      peak electricity loadin the winter hours.},
      cin          = {IEK-3},
      cid          = {I:(DE-Juel1)IEK-3-20101013},
      pnm          = {134 - Electrolysis and Hydrogen (POF3-134)},
      pid          = {G:(DE-HGF)POF3-134},
      typ          = {PUB:(DE-HGF)3 / PUB:(DE-HGF)11},
      urn          = {urn:nbn:de:0001-2019020614},
      url          = {https://juser.fz-juelich.de/record/858675},
}