Full- & Reduced-Order State-Space Modeling of Wind Turbine Systems with Permanent-Magnet Synchronous Generator

Wind energy is an integral part of nowadays energy supply and one of the fastest growing sources of electricity in the world today. Accurate models for wind energy conversion systems (WECSs) are of key interest for the analysis and control design of present and future energy systems. Existing control-oriented WECSs models are subject to unstructured simplifications, which have not been discussed in literature so far. Thus, this technical note presents are thorough derivation of a physical state-space model for permanent magnet synchronous generator WECSs. The physical model considers all dynamic effects that significantly influence the system's power output, including the switching of the power electronics. Alternatively, the model is formulated in the $(a,b,c)$- and $(d,q)$-reference frame. Secondly, a complete control and operation management system for the wind regimes II and III and the transition between the regimes is presented. The control takes practical effects such as input saturation and integral windup into account. Thirdly, by a structured model reduction procedure, two state-space models of WECS with reduced complexity are derived: a non-switching model and a non-switching reduced-order model. The validity of the models is illustrated and compared through a numerical simulation study.Comment: 23 pages, 11 figure

Instantaneous conduction and switching losses in two-level voltage source inverters

A mathematical model is derived which allows to compute instantaneously the conduction and switching losses in two-level voltage source inverters (2L-VSIs) regardless of the employed modulation scheme. The model is based on the use of switching vectors applied to the considered VSI, taking into account the instantaneous conduction and switching losses of the semiconductor devices. The advantages of this method are, (i) it can be extended to any type of VSI and any modulation scheme, (ii) it can be applied to analyze the power losses of VSIs during any desired period, and (iii) it can be easily implemented in any kind of the simulation software (e.g. Matlab/Simulink)

Asymptotic tracking by funnel control with internal models

Funnel control achieves output tracking with guaranteed tracking performance for unknown systems and arbitrary reference signals. In particular, the tracking error is guaranteed to satisfy time-varying error bounds for all times (it evolves in the funnel). However, convergence to zero cannot be guaranteed, but the error often stays close to the funnel boundary, inducing a comparatively large feedback gain. This has several disadvantages (e.g. poor tracking performance and sensitivity to noise due to the underlying high-gain feedback principle). In this paper, therefore, the usually known reference signal is taken into account during funnel controller design, i.e. we propose to combine the well-known internal model principle with funnel control. We focus on linear systems with linear reference internal models and show that under mild adjustments of funnel control, we can achieve asymptotic tracking for a whole class of linear systems (i.e. without relying on the knowledge of system parameters)

Rethinking Hybrid Teaching: The Hybrid Rhombus Model as an Approach to Understanding Hybrid Settings

[EN] After extended periods of remote-only teaching at university, lecturers tried to come back to lecture halls. Due to restrictions not all students could participate on-site. Therefore, hybrid teaching models proliferated. To reflect the transformative effects on teaching practice, we conducted focus groups with lecturers and found that didactic models aimed at capturing dynamics of the in-situ learning experience do not provide sufficient understanding of the bifurcated nature of hybrid teaching. The hybrid rhombus model is an approach to conceptual understanding of the newly developed situation of teaching in a hybrid way. This paper gives a brief description of the model description and the empirical background, to contribute to the debate of hybrid teaching in relation to digital or on-site teaching.Handle-Pfeiffer, D.; Winter, C.; Löw, C.; Hackl, C. (2022). Rethinking Hybrid Teaching: The Hybrid Rhombus Model as an Approach to Understanding Hybrid Settings. En 8th International Conference on Higher Education Advances (HEAd'22). Editorial Universitat Politècnica de València. 1367-1375. https://doi.org/10.4995/HEAd22.2022.146021367137

Funnel control for systems with relative degree two

PublishedJournal ArticleTracking of reference signals yref (·) by the output y(·) of linear (as well as a considerably large class of nonlinear) single-input, single-output systems is considered. The system is assumed to have strict relative degree two with (weakly) stable zero dynamics. The control objective is tracking of the error e = y - yref and its derivative e within two prespecified performance funnels, respectively. This is achieved by the so-called funnel controller u(t) = -k0(t)2e(t)-k 1(t)e(t), where the simple proportional error feedback has gain functions k0 and k1 designed in such a way to preclude contact of e and e with the funnel boundaries, respectively. The funnel controller also ensures boundedness of all signals. We also show that the same funnel controller (i) is applicable to relative degree one systems, (ii) allows for input constraints provided a feasibility condition (formulated in terms of the system data, the saturation bounds, the funnel data, bounds on the reference signal, and the initial state) holds, (iii) is robust in terms of the gap metric: if a system is sufficiently close to a system with relative degree two, stable zero dynamics, and positive high-frequency gain, but does not necessarily have these properties, then for small initial values the funnel controller also achieves the control objective. Finally, we illustrate the theoretical results by experimental results: the funnel controller is applied to a rotatory mechanical system for position control. © 2013 Society for Industrial and Applied Mathematics