Three-level neutral-point-clamped (NPC) inverters need to ensure the balance of the neutral-point (NP) potential during operation. The zero-sequence voltage injection balance algorithms based on the carrier-based puls...
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Three-level neutral-point-clamped (NPC) inverters need to ensure the balance of the neutral-point (NP) potential during operation. The zero-sequence voltage injection balance algorithms based on the carrier-based pulse width modulation (CBPWM) have been proposed in many papers and proved to be effective in controlling the NP potential. In industrial applications, the algorithms are mostly implemented by digital controllers, which have inherent computation digital delay. However, there is little attention to how the digital delay influences the balance algorithms. In this paper, the influence of the digital delay on the zero-sequence voltage injection balance algorithm has been studied in detail. It is found that the digital delay causes a fluctuation of the NP potential. The frequency of the fluctuation is 1/6 control frequency, and the amplitude of the fluctuation is related to the control frequency, the modulation index, the output current, and the dc-side capacitance. Furthermore, in order to eliminate the NP potential fluctuation caused by the digital delay, a digital delay compensation method is proposed in this paper. The correctness of the theoretical analysis and the effectiveness of the compensation method have been verified by the simulation and experiment results.
In the realm of modern wind turbine engineering, where precision is paramount for stability, control, and observability, this article introduces a groundbreaking method leveraging time-weighted Gramians. The focal poi...
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In the realm of modern wind turbine engineering, where precision is paramount for stability, control, and observability, this article introduces a groundbreaking method leveraging time-weighted Gramians. The focal point of this work is the reduction of model order in wind turbines featuring a double-fed induction generator with time-varying rotational speeds. Employing sophisticated state-space representations, we establish a comprehensive and systematic framework for analyzing wind turbine performance, ensuring adherence to stringent grid standards. A distinctive aspect of our proposed approach lies in the utilization of time-weighted Gramians and an innovative balanced realization technique to reduce the dimensionality of large state-space models effectively. Stability and reduced approximation errors are guaranteed by creating a lower-order system. A significant improvement is the availability of an a priori formula for error-bound, which allows for more efficient and faster computations. The use of time-weighted Gramians allowed for the application of this groundbreaking technique to time-sensitive systems in the real world, such as wind turbines. The optimization of models utilizing vast simulation data is what makes our methodology better than current methods. Wind turbines that allow for real-time adjustment of rotating speeds are part of this dataset. A lot of consideration is given to stability and error calculation in this study, which makes it innovative. The use of time-weighted Gramians in practical, real-time systems has greatly improved the accuracy and efficiency of modeling approaches.
In wind turbine engineering, stability and control rely on precision. A new approach for discrete-time systems is presented in this study, which makes use of constrained Gramians and frequency weights. Wind turbines w...
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In wind turbine engineering, stability and control rely on precision. A new approach for discrete-time systems is presented in this study, which makes use of constrained Gramians and frequency weights. Wind turbines with a double-fed induction generator and dynamic rotational speeds can have their model order reduced using the suggested method, which makes use of sophisticated state-space representations. A novel balanced realization method, along with frequency-weighted and limited Gramians, successfully lowers the dimensionality of large state models. Minimizing approximation errors and ensuring stability are both achieved by the resulting lower-order system. This paper makes a significant contribution by offering an a priori formula for error boundaries, which allows for more efficient and faster computations. A paradigm shift in improving the accuracy of modeling techniques is marked by this groundbreaking method, which applies frequency-weighted and limited Gramians to real-time systems like wind turbines.
Modern wind turbines are steady, controlled, and observable because of the analytical and modeling precision used in their design. In the context of a varying speed-based wind turbine powered by a double-feeded induct...
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ISBN:
(纸本)9798350308266;9798350308259
Modern wind turbines are steady, controlled, and observable because of the analytical and modeling precision used in their design. In the context of a varying speed-based wind turbine powered by a double-feeded induction generator, this article offers a state-of-the-art technique for reducing model order. The proposed method leverages state-space representations to establish a comprehensive and systematic framework to analyze wind turbine performance and ensure conformity to grid requirements. Dimension reduction in the large state-space model is accomplished using time-constrained Gramians and a unique, balanced realization procedure. The reduced-order system is stable and offers less approximation error. As an additional perk, the proposed method gives researchers an a priori formula for the error-bound, which is easier to compute. Using extensive simulation data, we prove that our approach best optimizes models incorporating wind turbines with varying rotational speeds in the context of stability and error calculation compared to other approaches. To improve the efficacy and accuracy of their modeling procedures, wind turbine analysis academics and researchers should consider this new methodology seriously.
The problem of joint eigenvalue estimation for the non-defective commuting set of matrices A is addressed. A procedure revealing the joint eigenstructure by simultaneous diagonalization of. A with simultaneous Schur d...
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The problem of joint eigenvalue estimation for the non-defective commuting set of matrices A is addressed. A procedure revealing the joint eigenstructure by simultaneous diagonalization of. A with simultaneous Schur decomposition （SSD） and balance procedure alternately is proposed for performance considerations and also for overcoming the convergence difficulties of previous methods based only on simultaneous Schur form and unitary transformations, it is shown that the SSD procedure can be well incorporated with the balancing algorithm in a pingpong manner, i. e., each optimizes a cost function and at the same time serves as an acceleration procedure for the other. Under mild assumptions, the convergence of the two cost functions alternately optimized, i. e., the norm of A and the norm of the left-lower part of A is proved. Numerical experiments are conducted in a multi-dimensional harmonic retrieval application and suggest that the presented method converges considerably faster than the methods based on only unitary transformation for matrices which are not near to normality.
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