Publication

Full Discrete Modeling, Controller Design, and Sensitivity Analysis for High-Performance Grid-Forming Converters in Islanded Microgrids

Abstract

Recent works have shown that the state-feedback decoupling of capacitor voltage allows for drastic bandwidth enlarging of current controllers for grid-forming converters in islanded microgrids. Furthermore, Smith predictor and lead compensation have been also proved as very effective implementations for compensating the controller delays. These features are key to fulfill demanding requirements in terms of voltage regulation in islanded applications. This work deepens in the discrete-time domain modeling and implementation issues of the above-mentioned techniques. A full discrete-time and sensitivity analyses reveal phenomena not properlymodeled in previousworks, which limits the performance: the presence of high-frequency oscillations due to discrete poles with negative real part. Subsequently, proper design countermeasures (i.e., limit bandwidth) are proposed. Discrete implementation of the voltage controller is also addressed, and design guidelines are provided. Experimental tests in accordance with the high demanding standards for uninterruptible power supply systems verify the theoretical analysis.

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Related concepts (33)
Discrete-time Fourier transform
In mathematics, the discrete-time Fourier transform (DTFT), also called the finite Fourier transform, is a form of Fourier analysis that is applicable to a sequence of values. The DTFT is often used to analyze samples of a continuous function. The term discrete-time refers to the fact that the transform operates on discrete data, often samples whose interval has units of time. From uniformly spaced samples it produces a function of frequency that is a periodic summation of the continuous Fourier transform of the original continuous function.
Discrete wavelet transform
In numerical analysis and functional analysis, a discrete wavelet transform (DWT) is any wavelet transform for which the wavelets are discretely sampled. As with other wavelet transforms, a key advantage it has over Fourier transforms is temporal resolution: it captures both frequency and location information (location in time). Haar wavelet The first DWT was invented by Hungarian mathematician Alfréd Haar. For an input represented by a list of numbers, the Haar wavelet transform may be considered to pair up input values, storing the difference and passing the sum.
Discrete Fourier transform
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