Direct model predictive control (DMPC) is an attractive control method, in particular, for multilevel converters. However, the computation time for classical DMPC schemes increases exponentially with the number of switching states and, compared to modulation-based controllers, real-time implementation may not be feasible. In this paper, two computationally efficient DMPC schemes with hexagon candidate region (HCR) and triangle candidate region (TCR) for torque and power control of three-level neutral-point clamped back-to-back converters in wind turbine systems with permanent-magnet synchronous generator are proposed. By an appropriate selection of the candidate regions, the number of reasonable switching states is drastically reduced which saves computation time up to 55% for HCR and up to 83% for TCR, respectively. The computational efficiency improvements and the control performances of the proposed DMPC schemes are compared and validated by real-time implementations on an field programmable gate array (FPGA) system and by measurement results at a lab-constructed test bench. The achieved control performance of the proposed methods is comparable with that of the classical DMPC, while the computation times are drastically reduced.

This paper presents a novel finite position set-phase locked loop (FPS-PLL) for sensorless control of surface-mounted permanent-magnet synchronous generators (PMSGs) in variable-speed wind turbines. The proposed FPS-PLL is based on the finite control set-model predictive control concept, where a finite number of rotor positions are used to estimate the back electromotive force of the PMSG. Then, the estimated rotor position, which minimizes a certain cost function, is selected to be the optimal rotor position. This eliminates the need of a fixed-gain proportional-integral controller, which is commonly utilized in the conventional PLL. The performance of the proposed FPS-PLL has been experimentally investigated and compared with that of the conventional one using a 14.5 kW PMSG with a field-oriented control scheme utilized as the generator control strategy. Furthermore, the robustness of the proposed FPS-PLL is investigated against PMSG parameters variations.

The inevitable transition of the power system toward a sustainable and renewable-energy centered power system is accompanied by huge versatility and significant challenges. A corresponding shift in operation strategies, embracing more intelligence and digitization, e.g., a Cyber-Physical System (CPS), is needed to achieve an optimal, reliable and secure operation across all system levels (components, units, plants, grids) and by the use of big data. Digital twins (DTs) are a promising approach to realize CPS. In this paper, their applications in power systems are reviewed comprehensively. The review reveals that there exists a gap between available DT definitions and the requirements for DTs utilized in future power systems. Therefore, by adapting the current definitions to these requirements, a generic definition of a “Digital Twin System (DTS)” is introduced which finally allows proposing a multi-level and arbitrarily extendable “System of Digital Twin Systems (SDTSs)” idea. The SDTSs can be realized with an open-source framework that serves as a central data and communication interface between different DTSs which can interact by “Reporting Modules” and are regulated by “Control Modules” (CMs). Exemplary application scenarios involving multiple system levels are discussed to illustrate the capabilities of the proposed SDTS concept.

This paper proposes modified Second-Order Generalized Integrators (mSOGIs) for a fast estimation of all harmonic components of arbitrarily distorted single-phase signals such as voltages or currents in power systems. The estimation is based on the internal model principle leading to an overall observer consisting of parallelized mSOGIs. The observer is tuned by pole placement. For a constant fundamental frequency, the observer is capable of estimating all harmonic components with prescribed settling time by choosing the observer poles appropriately. For time-varying fundamental frequencies, the harmonic estimation is combined with a modified Frequency Locked Loop (mFLL) with gain normalization, sign-correct anti-windup and rate limitation. The estimation performances of the proposed parallelized mSOGIs with and without mFLL are illustrated and validated by measurement results. The results are compared to standard approaches such as parallelized standard SOGIs (sSOGIs) and adaptive notch filters (ANFs).

Tracking of reference signals $y_{\mathrm{ref}}(\cdot)$ by the output $y(\cdot)$ 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 $e=y-y_{\mathrm{ref}}$ and its derivative $\dot{e}$ within two prespecified performance funnels, respectively. This is achieved by the so-called funnel controller $u(t)=-k_0(t)^2e(t)-k_1(t)\dot{e}(t)$, where the simple proportional error feedback has gain functions $k_0$ and $k_1$ designed in such a way to preclude contact of $e$ and $\dot{e}$ 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.

In this paper, an extended Kalman filter (EKF) is employed to estimate stator currents, rotor speed, rotor position, and mechanical torque of a direct-driven surface-mounted permanent-magnet synchronous generator (PMSG) based variable-speed wind turbine systems controlled by a robust predictive deadbeat (DB) algorithm. Therefore, the flux-oriented control of the PMSG is realized without mechanical sensors (i.e., no position encoders or speed transducers). The estimated stator currents are fed back to the prediction model in order to compensate the one-step delay caused by the digital controller and to reduce the total harmonic distortion of the stator currents. Thus, the torque ripples are also reduced. Furthermore, a simple disturbance observer is presented, which estimates the perturbations caused by parameter variations of the PMSG or by any unmodeled dynamics in order to enhance the robustness of the proposed DB algorithm. The proposed scheme is experimentally validated using a 14.5-kW PMSG and a dSPACE DS1007 real-time platform. Its performance is compared with that of the conventional DB control strategy for all operation conditions and under parameter variations of the PMSG.