Coherent groups identification under high penetration of non-synchronous generation

The current power systems are facing an important transition due to the integration of non-synchronous generation through back-to-back Full Rated Converters' (FRC). Coherency behaviour under the presence of large inclusion of renewables requires special attention in order to understand the swing oscillations when the inertia is decreasing due to the decoupling. This paper presents the application of the so-called Koopman operator for the identification of coherent groups in power systems with the influence of non-synchronous generation. The method provides a clustering observation tool based on measurement signals allowing to identify the dynamic changes effected through the derived spectral analysis of the Koopman modes. The applied method of coherency identification is evaluated in the Nordic test system through gradually increasing integration and different fault locations.

[1]  Clarence W. Rowley,et al.  Koopman spectral analysis of separated flow over a finite-thickness flat plate with elliptical leading edge , 2011 .

[2]  I. Mezic,et al.  Nonlinear Koopman Modes and Coherency Identification of Coupled Swing Dynamics , 2011, IEEE Transactions on Power Systems.

[3]  D. N. Kosterev,et al.  Planning efforts to evaluate dynamic response of increased penetration of variable generation within the Western Interconnection , 2012, 2012 IEEE Power and Energy Society General Meeting.

[4]  Robert Eriksson,et al.  Suitable placements of multiple FACTS devices to improve the transient stability using trajectory sensitivity analysis , 2013, 2013 North American Power Symposium (NAPS).

[5]  Vijay Vittal,et al.  Impact of increased penetration of DFIG based wind turbine generators on transient and small signal stability of power systems , 2009, IEEE PES General Meeting.

[6]  B. Bowler,et al.  An Analysis of Interarea Dynamics of Multi-Machine Systems , 1981, IEEE Transactions on Power Apparatus and Systems.

[7]  Joe H. Chow,et al.  Inertial and slow coherency aggregation algorithms for power system dynamic model reduction , 1995 .

[8]  Robin Podmore,et al.  Identification of Coherent Generators for Dynamic Equivalents , 1978, IEEE Transactions on Power Apparatus and Systems.

[9]  I. Mezić,et al.  Spectral analysis of nonlinear flows , 2009, Journal of Fluid Mechanics.

[10]  Johan Björnstedt.  Integration of Non-synchronous Generation - Frequency Dynamics , 2012 .

[11]  P. K. Jain,et al.  Power management and control of a wind energy conversion system (WECS) with a fuzzy logic based maximum power point tracking (MPPT) , 2012, IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society.

[12]  Takashi Hikihara,et al.  Partitioning power grids via nonlinear Koopman Mode Analysis , 2014, ISGT 2014.

[13]  Robert J. Thomas,et al.  Coherency identification for large electric power systems , 1982 .

[14]  A. Mullane,et al.  Frequency control and wind turbine technologies , 2005, IEEE Transactions on Power Systems.

[15]  I. Mezić.  Spectral Properties of Dynamical Systems, Model Reduction and Decompositions , 2005 .

[16]  Prem K Naik,et al.  Identification of coherent generator groups in power system networks with windfarms , 2011, AUPEC 2011.

[17]  I. Mezić,et al.  Applied Koopmanism. , 2012, Chaos.

[18]  Andrew J. Roscoe,et al.  Inertia Emulation Control Strategy for VSC-HVDC Transmission Systems , 2013, IEEE Transactions on Power Systems.

[19]  M. Jonsson,et al.  A new method suitable for real-time generator coherency determination , 2004, IEEE Transactions on Power Systems.

[20]  Xavier Guillaud,et al.  High Wind Power Penetration in Isolated Power Systems—Assessment of Wind Inertial and Primary Frequency Responses , 2013, IEEE Transactions on Power Systems.

[21]  Hector Chavez,et al.  Regulation Adequacy Analysis Under High Wind Penetration Scenarios in ERCOT Nodal , 2012, IEEE Transactions on Sustainable Energy.