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@ARTICLE{Tepe:1024779,
      author       = {Tepe, Benedikt and Haberschusz, David and Figgener, Jan and
                      Hesse, Holger and Sauer, Dirk Uwe and Jossen, Andreas},
      title        = {{F}eature-conserving gradual anonymization of load profiles
                      and the impact on battery storage systems},
      journal      = {Applied energy},
      volume       = {343},
      issn         = {0306-2619},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2024-02445},
      pages        = {121191 -},
      year         = {2023},
      note         = {Additional Grants: BMBF within the SimBAS project (Grant
                      No. 03XP0338A)},
      abstract     = {Electric load profiles are highly relevant for battery
                      storage research and industry as they determine system
                      design and operation strategies. However, data obtained from
                      electrical load measurements often cannot be shared or
                      published due to privacy concerns. This paper presents a
                      methodology to gradually anonymize load profiles while
                      conforming to various degrees of anonymity. It segregates
                      the original load profile into base and peak sequences and
                      extracts features from each of the sequences. With the help
                      of the features, a synthetic, anonymized load profile is
                      created. Different levels of anonymization can be selected,
                      which transform the original profile to the desired extent.
                      A random permutation of the peak sequences or base sequences
                      is used to achieve this transformation. Exemplary profiles
                      from a household and an electric vehicle charging station
                      are used to demonstrate the functionality of the
                      anonymization. The indicators of the anonymized load
                      profiles are compared with the original ones in both time
                      and frequency domains, and the effects of load profile
                      anonymization on the operation of battery storage systems in
                      two scenarios are analyzed. While the anonymized load
                      profiles retain the time-invariant indicators from the
                      original profile, the permutation causes a loss of
                      regularity in the load profiles. As a result, relevant
                      indicators of battery storage systems subjected to these
                      anonymized profiles deviate to a greater extent in
                      time-dependent applications such as self-consumption
                      increase. This is reflected in the overestimation of
                      equivalent full cycles by up to $6\%$ and underestimation of
                      self-sufficiency by up to 9 percentage points. In
                      time-independent applications such as peak shaving, however,
                      the indicators can be well reproduced with deviations of up
                      to $3\%$ despite the lost regularity. In order to make the
                      anonymization methodology usable for everyone, we present
                      the open-source tool LoadPAT, in which users can anonymize
                      their load profiles and choose their desired level of
                      anonymization. This work is intended to further encourage
                      the dissemination of open-source data.},
      cin          = {IEK-12 / JARA-ENERGY},
      ddc          = {620},
      cid          = {I:(DE-Juel1)IEK-12-20141217 / $I:(DE-82)080011_20140620$},
      pnm          = {1223 - Batteries in Application (POF4-122) / BMWi-0325666 -
                      Wissenschaftliches Mess- und Evaluierungsprogramm
                      Solarstromspeicher (BMWi-0325666) / BMWi-03ET6117 -
                      Wissenschaftliches Mess- und Evaluierungsprogramm
                      Solarstromspeicher 2.0 (BMWi-03ET6117)},
      pid          = {G:(DE-HGF)POF4-1223 / G:(DE-82)BMWi-0325666 /
                      G:(DE-82)BMWi-03ET6117},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001001351900001},
      doi          = {10.1016/j.apenergy.2023.121191},
      url          = {https://juser.fz-juelich.de/record/1024779},
}