@inproceedings{P. 2020,Author = {P. Teimourzadeh Baboli, Davood Babazadeh, and D. Ruwan Kumara Bowatte},Title = {Measurement-based Modeling of Distribution Grid Dynamics: A Digital Twin Approach},Year = {2020},Booktitle = {10th Smart Grid Conference (SGC2020)},Doi = {10.1109/SGC52076.2020.9335750},Url = {https://ieeexplore.ieee.org/abstract/document/9335750},type = {inproceedings},Abstract = {The renewable energy resources have paved the way for distributed energy resources (DERs) integration in to the distribution grid. As a result, the load composition and their dynamics have become complex. The weather phenomena and new emerging consumer load patters like electric vehicle contribute to time varying dynamics of these loads. In order to optimize the utilization of transmission assets and flexibility of DERs, the identification of time varying load dynamics is necessary. In this paper, time varying load dynamics identification by combining system identification methods and nonlinear numerical optimization is explored. The identified model parameters are then related to measurement data by means of artificial neural networks, which enable identification of similar dynamics without opting to numerical optimization methods.}}@COMMENT{Bibtex file generated on }