Feasibility study of applicability of recurrence quantification analysis for clustering of power system dynamic responses

A methodology based on Recurrence Quantification Analysis (RQA) for the clustering of generator dynamic behavior is presented. RQA is a nonlinear data analysis method, which is used in this paper to extract features from measured generator rotor angle responses that can be used to cluster generators in groups with similar oscillatory behavior. The possibility of extracting features relevant to damping and frequency of oscillations present in power systems is studied. The k-Means clustering algorithm is further used to cluster the generator responses in groups exhibiting well or poorly damped oscillations, based on the extracted features from RQA. The effectiveness of RQA is investigated using simulated responses from a modified version of the IEEE 68 bus network, including renewable energy resources.

[1]  Zhu Lingzhi,et al.  Power system probabilistic production simulation containing large-scale wind power and photovoltaic power , 2013, 2013 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC).

[2]  Graham Rogers,et al.  Power System Oscillations , 1999 .

[3]  B. Chaudhuri,et al.  Coherency identification in power systems through principal component analysis , 2005, IEEE Transactions on Power Systems.

[4]  Jovica V. Milanovic,et al.  Online Identification of Power System Dynamic Signature Using PMU Measurements and Data Mining , 2016, IEEE Transactions on Power Systems.

[5]  Raja Ayyanar,et al.  Probabilistic Power Flow Analysis With Generation Dispatch Including Photovoltaic Resources , 2013, IEEE Transactions on Power Systems.

[6]  J. V. Milanovic,et al.  Tuning of a Damping Controller for Multiterminal VSC-HVDC Grids Using the Probabilistic Collocation Method , 2014, IEEE Transactions on Power Delivery.

[7]  M. A. M. Ariff,et al.  Coherency identification in interconnected power system - an independent component analysis approach , 2013, 2013 IEEE Power & Energy Society General Meeting.

[8]  Petra Perner,et al.  Data Mining - Concepts and Techniques , 2002, Künstliche Intell..

[9]  Jovica V. Milanovic,et al.  Impact of penetration of non-synchronous generators on power system dynamics , 2015, 2015 IEEE Eindhoven PowerTech.

[10]  D. Ruelle,et al.  Recurrence Plots of Dynamical Systems , 1987 .

[11]  Pratyasa Bhui,et al.  Application of Recurrence Quantification Analysis to Power System Dynamic Studies , 2016, IEEE Transactions on Power Systems.

[12]  Jürgen Kurths,et al.  Recurrence plots for the analysis of complex systems , 2009 .

[13]  D Thukaram,et al.  Identification of coherent synchronous generators in a Multi-Machine Power System using Support Vector Clustering , 2011, 2011 International Conference on Power and Energy Systems.

[14]  I. Kamwa,et al.  Automatic Segmentation of Large Power Systems Into Fuzzy Coherent Areas for Dynamic Vulnerability Assessment , 2007, IEEE Transactions on Power Systems.