%0 Conference Paper %1 lensMeasurementDataBased2022 %A Lens, Hendrik %A Mitrentsis, Georgios %A Abele, Hans %A Lehner, Joachim %A Schoell, Christian %B Power Supply Transformation - Grid Regulation and System Stability; 14. ETG/GMA-Symposium %D 2022 %K from:ftus1 ifk sua %P 76-81 %T Measurement Data Based Identification of the Contribution of Distribution Networks to the Self-Regulating Effect %U https://ieeexplore.ieee.org/abstract/document/10048016 %X The dynamic behaviour of loads plays an important role in the dynamics of the power system in the form of the self-regulating effect. However, the transition to Active Distribution Networks (ADN) due to increased penetration of Distributed Generation (DG) and controllable loads questions the applicability of existing models. To this end, we introduce new models for real ADN using an approach based on measurement data. The acquired frequency responses turn out not to be identifiable from the measurement data under today's conditions, in contrast to the voltage responses, which show clear dependency on DG. Therefore, all measurement data records with similar dynamics are grouped by a clustering method. This allows for the identification of separate load and DG models.

@inproceedings{lensMeasurementDataBased2022, abstract = {The dynamic behaviour of loads plays an important role in the dynamics of the power system in the form of the self-regulating effect. However, the transition to Active Distribution Networks (ADN) due to increased penetration of Distributed Generation (DG) and controllable loads questions the applicability of existing models. To this end, we introduce new models for real ADN using an approach based on measurement data. The acquired frequency responses turn out not to be identifiable from the measurement data under today's conditions, in contrast to the voltage responses, which show clear dependency on DG. Therefore, all measurement data records with similar dynamics are grouped by a clustering method. This allows for the identification of separate load and DG models.}, added-at = {2023-03-08T16:58:49.000+0100}, author = {Lens, Hendrik and Mitrentsis, Georgios and Abele, Hans and Lehner, Joachim and Schoell, Christian}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/26f059ec61e934650a1f33b97e4a63f4a/ifk-admin}, booktitle = {Power {{Supply Transformation}} - {{Grid Regulation}} and {{System Stability}}; 14. {{ETG}}/{{GMA-Symposium}}}, interhash = {a96d048a077a7e20358e6f748eca8544}, intrahash = {6f059ec61e934650a1f33b97e4a63f4a}, keywords = {from:ftus1 ifk sua}, month = sep, pages = {76-81}, timestamp = {2023-04-05T07:11:51.000+0200}, title = {Measurement Data Based Identification of the Contribution of Distribution Networks to the Self-Regulating Effect}, url = {https://ieeexplore.ieee.org/abstract/document/10048016}, year = 2022 }