This paper introduces a hybrid-methodology for online identification and clustering of generator oscillatory behavior, based on measured responses. The dominant modes in generator measured responses are initially identified using a mode identification technique and then introduced, in the next step, as input into a clustering algorithm. Critical groups of generators that exhibit poorly or negatively damped oscillations are identified, in order to enable corrective control actions and stabilize the system. The uncertainties associated with operation of modern power systems, including Renewable Energy Sources (RES) are investigated, with emphasis on the impact of the dynamic behavior of power electronic interfaced RES.
- online dynamic security assessment
- renewable generation
- unsupervised maching learning
Papadopoulos, P. N., Papadopoulos, T. A., Chrysochos, A. I., & Milanović, J. V. (2018). Measurement based method for online characterization of generator dynamic behaviour in systems with renewable generation. IEEE Transactions on Power Systems. https://doi.org/10.1109/TPWRS.2018.2830817