This letter proposes a data-driven inertia estimator for inverter-based resources (IBRs) with grid-forming control. It is able to track both constant and time-varying inertia. By utilizing the Thevenin equivalent, the virtual frequency inside IBRs is first estimated with only its terminal voltage and current phasor measurements. The virtual frequency and the measurements are then used together to derive the state-space swing equation model. Then, an enhanced adaptive Unscented Kalman filter (EAUKF) is developed to estimate IBR inertia. Numerical results on the modified IEEE 39-bus power system demonstrate that the proposed inertia estimator remarkably outperforms the existing state-of-art methods both in tracking speed and accuracy.
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Frequency Response Improvement of PMSG Wind Turbines Using a Washout Filter
High integration of renewable energy resources, such as wind turbines, to the power grid decreases the power system inertia. To improve the frequency response of a low-inertia system, virtual inertia approach can be used. This letter proposes a control method to decrease the frequency transients and restore frequency to its nominal value. A wind turbine usually works based on maximum power point tracking (MPPT) curves to achieve the maximum power. In this letter, the proposed controller uses a non-MPPT method to leave power for frequency regulation during transients. Moreover, it uses a washout filter-based method to remove the steady-state error in the frequency. Simulation results in the PSCAD environment validate the improved performance of the proposed method during load changes by comparing it with the MPPT and non-MPPT methods.
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- NSF-PAR ID:
- 10282666
- Date Published:
- Journal Name:
- Energies
- Volume:
- 13
- Issue:
- 18
- ISSN:
- 1996-1073
- Page Range / eLocation ID:
- 4797
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Inertia from rotating masses of generators in power systems influence the instantaneous frequency change when an imbalance between electrical and mechanical power occurs. Renewable energy sources (RES), such as solar and wind power, are connected to the grid via electronic converters. RES connected through converters affect the system's inertia by decreasing it and making it time-varying. This new setting challenges the ability of current control schemes to maintain frequency stability. Proposing adequate controllers for this new paradigm is key for the performance and stability of future power grids. The contribution of this paper is a framework to learn sparse time-invariant frequency controllers in a power system network with a time-varying evolution of rotational inertia. We model power dynamics using a Switched-Affine hybrid system to consider different modes corresponding to different inertia coefficients. We design a controller that uses as features, i.e. input, the systems states. In other words, we design a control proportional to the angles and frequencies. We include virtual inertia in the controllers to ensure stability. One of our findings is that it is possible to restrict communication between the nodes by reducing the number of features in the controller (from 22 to 10 in our case study) without disrupting performance and stability. Furthermore, once communication between nodes has reached a threshold, increasing it beyond this threshold does not improve performance or stability. We find a correlation between optimal feature selection in sparse controllers and the topology of the network.more » « less
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/en13184797
