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Grid-friendly Matching Control of Synchronous Machines by DC/AC Converters in Bulk Power Networks


T. Jouini

Master Thesis, HS15 (10480)

An islanded inverter-based microgrid is a collection of heterogeneous DC energy resources, e.g., photovoltaic arrays, fuel cells, and energy-storage devices, interfaced to an AC distribution network and operated independently from the bulk power system. Energy conversion is typically managed by power-electronics in voltage source inverters. Drawing from the control of synchronous machines in bulk power systems, different control schemes have be recently adopted in order to achieve a stable network operation. The vast majority of academic and industrial efforts opt for these strategies during real-time control of inverters. Starting with a dynamical averaged DC/AC converter model, we review different controllers by presenting its main scope analytically and through simulations. Next, we explore a new alternative of controlling DC/AC converters in bulk power systems by matching traditional synchronous machines with emphasis on the role that DC-circuit can play in control architecture, usually neglected in conventional strategies. Compared to standard emulation methods, our controller relies solely on readily available DC-side measurements and takes into account the natural DC and AC storage elements. As a result, our controller is generally faster and less vulnerable to delays and measurement inaccuracies. We additionally provide insightful interpretations of the suggested control, various plug-and-play properties of the closed loop, such as steady-state power flow analysis, passivity with respect to the DC and AC ports, stability proof as well as high-level control architectures contributing to enhancing the controller performance and attaining further control goals, which we illustrate in both analysis and simulation.

Supervisors: Frank Allgöwer (Universität Stuttgart), Catalin Arghir, Florian Dörfler


Type of Publication:

(12)Diploma/Master Thesis

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2016:IFA_5441
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