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Control of Low Inertia Power Grids: A model reduction approach


S. Curi

Master Thesis, FS16

The penetration of renewable energy sources on the power grid pose problems on its stability, operation and control. Besides its stochastic nature, renewable sources are interfaced with the grid through inverters which provide almost no energy storage capacity, no physical synchronization mechanism, and lack a robust voltage controller. Traditional power sources are interfaced to the grid with a synchronous generator. Synchronous generators have robust voltage controllers, their frequencies are synchronized through the grid physics, and they store kinetic energy in their rotating masses. This stored energy compensates active power imbalances in the network with small frequency changes. Inverters, on the other hand, do not have a significant energy storage element. Under the same active power imbalance, frequency oscillations are much higher and this can lead to faults or even blackouts. In this work the theoretical foundations of the power system are revisited. A comprehensive model of the power system components is developed based on first-principles physical modeling and their interconnection. These components are synchronous generators, inverters, loads, voltage buses, and transmission lines. The resulting model is a high-order non-linear system which is intractable for control purposes. The contributions of this work are: (1) reduce the model into a lower-order model through a singular perturbation analysis, (2) derive a synchronization mechanism for inverters that is based on model matching with generators, (3) provide decentralized realizable control laws that make the system passive with respect to a Hamiltonian shifted around the desired operating point, (4) derive linear controllers that outperform current controllers around the operating point, and (5) develop a detailed simulator code that is modular and can deal with the non-linear dynamics of the power grid.

Supervisors: Dominic Gross, Florian Dörfler


Type of Publication:

(12)Diploma/Master Thesis

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2017:IFA_5621
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