This paper outlines an approach to perform small-signal stability analysis of a power network with conventional synchronous generators and a wind farm composed of Type-3 wind turbines as the number of turbines in the farm is varied. An enabling ingredient to perform this analysis is a dynamic reduced-order aggregate model for a wind farm that preserves the model order and structure of individual wind turbines. This facilitates stability analysis since the number of wind turbines can be varied with ease and small-signal stability of the mixed machine and inverter-interfaced turbines can be examined systematically. Although there is a vast body of literature on small-signal stability of wind farms, penetration level of wind farms is significantly less studied in this context; this paper introduces a systematic approach for such an analysis. Case studies for a modified Kundur two-area system with an integrated wind farm indicate that as the number of wind turbines is increased to a point that the penetration level is approximately 25%, there is a loss of small-signal stability. We validate this with time-domain simulations for the nonlinear system dynamics and also propose a redesign strategy grounded in a system-theoretic analysis of the dynamical models.
|Original language||English (US)|
|Title of host publication||2019 IEEE Power and Energy Society General Meeting, PESGM 2019|
|Publisher||IEEE Computer Society|
|State||Published - Aug 2019|
|Event||2019 IEEE Power and Energy Society General Meeting, PESGM 2019 - Atlanta, United States|
Duration: Aug 4 2019 → Aug 8 2019
|Name||IEEE Power and Energy Society General Meeting|
|Conference||2019 IEEE Power and Energy Society General Meeting, PESGM 2019|
|Period||8/4/19 → 8/8/19|
Bibliographical noteFunding Information:
Funding support from the the U.S. Department of Energy under Contract No. DE-EE0000-1583 and the National Science Foundation under grants 1453921, 1254129 is gratefully acknowledged.
© 2019 IEEE.
- Modal analysis
- Nonlinear systems
- Numerical simulation
- Power system stability
- Wind energy