Improving Dynamic Performance of Low-Inertia Systems Through Eigensensitivity Optimization

An increasing penetration of renewable generation has led to reduced levels of rotational inertia and damping in the system. The consequences are higher vulnerability to disturbances and deterioration of the dynamic response of the system. To overcome these challenges, novel converter control schemes that provide virtual inertia and damping have been introduced, which raises the question of optimal distribution of such devices throughout the network. This paper presents a framework for performance-based allocation of virtual inertia and damping to the converter-interfaced generators in a low-inertia system. This is achieved through an iterative, eigensensitivity-based optimization algorithm that determines the optimal controller gains. Two conceptually different problem formulations are presented and validated on a 3-area, 12-bus test system.

[1]  Pierluigi Mancarella,et al.  Frequency Response Constrained Economic Dispatch with Consideration of Generation Contingency Size , 2018, 2018 Power Systems Computation Conference (PSCC).

[2]  Goran Andersson,et al.  Impact of Low Rotational Inertia on Power System Stability and Operation , 2013, 1312.6435.

[3]  G. Sybille,et al.  Open data IEEE test systems implemented in SimPowerSystems for education and research in power grid dynamics and control , 2015, 2015 50th International Universities Power Engineering Conference (UPEC).

[4]  David J. Vowles,et al.  SIMPLIFIED 14-GENERATOR MODEL OF THE SE AUSTRALIAN POWER SYSTEM , 2010 .

[5]  Luiz A. C. Lopes,et al.  Virtual synchronous generator control in autonomous wind-diesel power systems , 2009, 2009 IEEE Electrical Power & Energy Conference (EPEC).

[6]  Gabriela Hug,et al.  Understanding Small-Signal Stability of Low-Inertia Systems , 2021, IEEE Transactions on Power Systems.

[7]  Archie C. Chapman,et al.  A Framework for Assessing Renewable Integration Limits With Respect to Frequency Performance , 2018, IEEE Transactions on Power Systems.

[8]  Fernando Paganini,et al.  Global performance metrics for synchronization of heterogeneously rated power systems: The role of machine models and inertia , 2017, Allerton Conference on Communication, Control, and Computing.

[9]  Pedro Rodriguez,et al.  Analysis of derivative control based virtual inertia in multi-area high-voltage direct current interconnected power systems , 2016 .

[10]  Bala Kameshwar Poolla,et al.  Placement and Implementation of Grid-Forming and Grid-Following Virtual Inertia and Fast Frequency Response , 2018, IEEE Transactions on Power Systems.

[11]  Tao Liu,et al.  Effects of rotational Inertia on power system damping and frequency transients , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

[12]  Florian Dörfler,et al.  Increasing the Resilience of Low-inertia Power Systems by Virtual Inertia and Damping , 2017 .

[13]  Sairaj V. Dhople,et al.  Optimizing DER Participation in Inertial and Primary-Frequency Response , 2018, IEEE Transactions on Power Systems.

[14]  Gabriela Hug,et al.  Understanding Stability of Low-Inertia Systems , 2019 .

[15]  Florian Dörfler,et al.  Grid-forming control for power converters based on matching of synchronous machines , 2017, Autom..

[16]  Wanxing Sheng,et al.  Self-Synchronized Synchronverters: Inverters Without a Dedicated Synchronization Unit , 2014, IEEE Transactions on Power Electronics.

[17]  Ulrich Münz,et al.  Comparison of H∞, H2, and pole optimization for power system oscillation damping with remote renewable generation , 2016 .

[18]  Baris Fidan,et al.  H∞ Performance of Mechanical and Power Networks , 2017 .

[19]  Baosen Zhang,et al.  Optimal Design of Virtual Inertia and Damping Coefficients for Virtual Synchronous Machines , 2018, 2018 IEEE Power & Energy Society General Meeting (PESGM).

[20]  Pieter Tielens,et al.  The relevance of inertia in power systems , 2016 .

[21]  Stephen P. Boyd,et al.  A bisection method for computing the H∞ norm of a transfer matrix and related problems , 1989, Math. Control. Signals Syst..

[22]  Pengwei Du,et al.  Wind Integration in ERCOT , 2017 .

[23]  Achim Woyte,et al.  Virtual synchronous generator: An element of future grids , 2010, 2010 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe).

[24]  Christian Rehtanz,et al.  A Virtual Synchronous Generator Control Strategy for VSC-MTDC Systems , 2018, IEEE Transactions on Energy Conversion.

[25]  Gabriela Hug,et al.  Stability Analysis of Converter Control Modes in Low-Inertia Power Systems , 2018, 2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe).

[26]  J. Doyle,et al.  Robust and optimal control , 1995, Proceedings of 35th IEEE Conference on Decision and Control.

[27]  Linyun Xiong,et al.  Stability Enhancement of Power Systems With High DFIG-Wind Turbine Penetration via Virtual Inertia Planning , 2019, IEEE Transactions on Power Systems.

[28]  Florian Dörfler,et al.  Optimal Placement of Virtual Inertia in Power Grids , 2015, IEEE Transactions on Automatic Control.

[29]  Petros Aristidou,et al.  LQR-Based Adaptive Virtual Synchronous Machine for Power Systems With High Inverter Penetration , 2019, IEEE Transactions on Sustainable Energy.

[30]  H.-P. Beck,et al.  Virtual synchronous machine , 2007, 2007 9th International Conference on Electrical Power Quality and Utilisation.

[31]  Mi-Ching Tsai,et al.  Robust and Optimal Control , 2014 .