Some advanced parametric methods for assessing waveform distortion in a smart grid with renewable generation

Alfieri, L.

doi:10.1186/s13634-015-0195-0

Cited by 6 publications

(8 citation statements)

References 39 publications

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“…Hence, for such types of WTS, because of the double feeding, the high-frequency spectral components both of the rotor and stator side are injected at the PCC. Additionally, for WTSs, the high-frequency secondary emissions are due to background voltage distortions and PLC [23].…”

Section: High-frequency Distortions In Power Systemsmentioning

confidence: 99%

New Power Quality Indices for the Assessment of Waveform Distortions from 0 to 150 kHz in Power Systems with Renewable Generation and Modern Non-Linear Loads

2017

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Abstract:The widespread use of power electronics converters, e.g., to interface renewable generation systems with the grid or to supply some high-efficiency loads, has caused increased levels of waveform distortions in the modern distribution system. Voltage and current waveforms include spectral components from 0 kHz to 150 kHz, characterized by a non-uniform time-frequency behavior. This wide interval of frequencies is currently divided into "low-frequency" (from 0 kHz to 2 kHz) and "high-frequency" (from 2 kHz to 150 kHz). While the low-frequencies have been exhaustively investigated in the relevant literature and are covered by adequate standardization, studies for the high-frequencies have been addressed only in the last decade to fill current regulatory gaps. In this paper, new power quality (PQ) indices for the assessment of waveform distortions from 0 kHz to 150 kHz are proposed. Specifically, some currently available indices have been properly modified in order to extend their application also to wide-spectrum waveforms. In the particular case of waveform distortions due to renewable generation, numerical applications prove that the proposed indices are useful tools for the characterization of problems (e.g., overheating, equipment malfunctioning, losses due to skin effects, hysteresis losses or eddy current losses) in cases of both low-frequency and high-frequency distortions.

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Section: High-frequency Distortions In Power Systemsmentioning

confidence: 99%

New Power Quality Indices for the Assessment of Waveform Distortions from 0 to 150 kHz in Power Systems with Renewable Generation and Modern Non-Linear Loads

2017

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“…Figure 6b shows a focus on the graphical comparison among the actual modulated frequency, the STFTM, SWEM and SWWMEM estimations. Note that, since in this case the actual value of the spectral component was known "a priori", for STFTM it is assumed that a single component is around 17,598 Hz and the other components are spectral leakage. So the modulated component in Figure 5 is that with the maximum amplitude value in a range of 20 Hz around the actual mean value .…”

Section: Case Studymentioning

confidence: 99%

A Wavelet-Modified ESPRIT Hybrid Method for Assessment of Spectral Components from 0 to 150 kHz

et al. 2017

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Abstract:Waveform distortions are an important issue in distribution systems. In particular, the assessment of very wide spectra, that include also components in the 2-150 kHz range, has recently become an issue of great interest. This is due to the increasing presence of high-spectral emission devices like end-user devices and distributed generation systems. This study proposed a new sliding-window wavelet-modified estimation of signal parameters by rotational invariance technique (ESPRIT) method, particularly suitable for the spectral analysis of waveforms that have very wide spectra. The method is very accurate and requires reduced computational effort. It can be applied successfully to detect spectral components in the range of 0-150 kHz introduced both by distributed power plants, such as wind and photovoltaic generation systems, and by end-user equipment connected to grids through static converters, such as fluorescent lamps.

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“…In [5], a data processing network for an in-house low-voltage smart grid is considered. The aim of the paper is the proposal of a high-rate measurement architecture for data processing, monitoring, and management in a smart grid characterized by real-time measurements and sophisticated control integrating fluctuating renewable power sources and/or prosumers (such as electrical vehicles and storage systems).Papers [6][7][8] are focused on different aspects of power quality in smart grids. In particular, the problem of new hardware with adequate computational capability and time intensive, cost-ineffective manual implementations in advanced power quality metering algorithms is studied in [6].…”

mentioning

confidence: 99%

“…The proposed estimator is applied to numerous numerical case studies showing higher accuracy than the classical IEC flickermeter and can be included in signal processing tools for interharmonic penetration studies due to renewable energy sources in future smart grids. In [8], power quality level reduction caused by dispersed renewable generation connected to the grid through static converters is considered. In particular, advanced parametric methods for assessing waveform distortions (such as Prony and ESPRIT, and some hybrid methods) are critically compared on the basis of their accuracy and the computational effort required.…”

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Guest editorial introduction to the special issue on “advanced signal processing techniques and telecommunications network infrastructures for smart grid analysis, monitoring, and management”

Bracale

Barros

Cacciapuoti

et al. 2015

EURASIP J. Adv. Signal Process.

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Electrical power systems are undergoing a radical change in structure, components, and operational paradigms, and are progressively approaching the new concept of smart grids (SGs). Future power distribution systems will be characterized by the simultaneous presence of various distributed resources, such as renewable energy systems (i.e., photovoltaic power plant and wind farms), storage systems, and controllable/non-controllable loads. Control and optimization architectures will enable network-wide coordination of these grid components in order to improve system efficiency and reliability and to limit greenhouse gas emissions. In this context, the energy flows will be bidirectional from large power plants to end users and vice versa; producers and consumers will continuously interact at different voltage levels to determine in advance the requests of loads and to adapt the production and demand for electricity flexibly and efficiently also taking into account the presence of storage systems. This evolution of power distribution networks involves also an increasingly complex and performing Information and Communication Technology (ICT) infrastructure. An increasing and continuous flow of information will be exchanged among the various levels of such systems in order to ensure an optimized operation of the network and an efficient management of distributed resources. Then, SGs operate with two-way flows of both electricity and information. The necessary communication resources heavily depend on the choices related to the required signal processing for analysis, monitoring, and management of the network.Many research contributions have been published recently in the relevant literature, covering the innovative topics associated with this new concept of functional power systems. However, few papers have addressed the problems inherent to the study of the advanced signal processing techniques and telecommunications network infrastructures which are needed for the modern SGs. This is the reason for this special issue.There are many aspects where signal processing plays a crucial role for planning and operation of SGs. This special issue focuses on some of them, addressing in particular the development of new, advanced, signal processing methods for studying the characteristics of highly non-stationary waveforms involved in the analysis, monitoring and management of the electrical quantities at nodes/branches of the smart grids.Our call for papers attracted numerous submissions worldwide. In response to the call for papers for this special issue, after the review process, 12 were accepted for publication, with co-authors from Asia, Europe, South America, and the USA These papers are briefly described in the following.In [1], the authors use higher-order statistics-based feature extraction and regression algorithms implemented in artificial neural networks (ANNs) to classify power quality disturbances. The novel aspect of the method proposed is the use of a feature vector based on the combination of time and frequency d...

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Some advanced parametric methods for assessing waveform distortion in a smart grid with renewable generation

Cited by 6 publications

References 39 publications

New Power Quality Indices for the Assessment of Waveform Distortions from 0 to 150 kHz in Power Systems with Renewable Generation and Modern Non-Linear Loads

New Power Quality Indices for the Assessment of Waveform Distortions from 0 to 150 kHz in Power Systems with Renewable Generation and Modern Non-Linear Loads

A Wavelet-Modified ESPRIT Hybrid Method for Assessment of Spectral Components from 0 to 150 kHz

Guest editorial introduction to the special issue on “advanced signal processing techniques and telecommunications network infrastructures for smart grid analysis, monitoring, and management”

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