P. Teimourzadeh Baboli, D. Ruwan Kumara Bowatte, and Davood Babazadeh
10th Smart Grid Conference (SGC2020)
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.