arXiv subjects

Joachim Peinke

Publications and source records attributed to Joachim Peinke.

At least 37 records · Page 2Linked to original sources

arXiv2021

Taming chaos with active grids -- Reproducibility in turbulent wind tunnel experiments

A wind tunnel experiment is shown to examine the reproducibility of generated wind fields in the laboratory utilizing an active grid. A motion protocol of the grid, designed to mimic a measured atmospheric wind speed time series, is therefore repeated 50 times and the flow is measured by a 2D hotwire (x-wire) system. The acquired wind speed time series are analysed in two different ways to identify the reproducible time scales. A direct comparison using the cross covariance function combined with two filtering methods and a statistic approach using one and two point analysis. Like that the reproducible time and length scales could be linked to the active grid motion and design. The identification of the reproducible time scales of a turbulent signal generated by means of an active grid is suitable to improve the possible wind fields in laboratory experiments.

physics.flu-dyn↗

arXiv2020

Dynamic stall of an airfoil under tailored three-dimensional inflow conditions

Rotor blades of wind turbines in the atmospheric boundary layer regularly experience the aerodynamic phenomenon of dynamic stall consisting of a temporary overshoot of lift and detrimental fatigue loads. Particularly the formation of dynamic stall under three-dimensional inflow conditions raises open questions. Aerodynamic behavior of a DU 91-W2-250 wind profile undergoing light dynamic stall is thus analyzed in a wind tunnel. Effects of a gust with streamwise and spanwise periodic variation are investigated by comparing total and local lift generation with flow formation above the airfoil. The observed stall cycle is divided into five stages of which one reveals lift overshoot of up to $16~\%$. The aerodynamic response of the airfoil shows a delay of about $1/8$ period between evolution of local angle of attack and lift giving a counterclockwise dynamic polar. A proper orthogonal decomposition (POD) analysis of the flow field contributes to understand aerodynamic consequences of the three-dimensional gust. Local inflow, total lift as well as certain lift events are captured by one POD eigenmode, respectively. Obtained results lead to the conclusion that the flow and particularly the stalled wake of an airfoil facing a three-dimensional gust are strongly coupled in the spanwise direction. This yields to flow stabilization, inhibition of stall, and in turn, counterclockwise dynamic polar along with augmented total lift.

physics.flu-dyn↗

arXiv2019

Heterogeneities in electricity grids strongly enhance non-Gaussian features of frequency fluctuations under stochastic power input

Stochastic feed-in of fluctuating renewable energies is steadily increasing in modern electricity grids and this becomes an important risk factor for maintaining power grid stability. Here we study the impact of wind power feed-in on the short-term frequency fluctuations in power grids based on an IEEE test grid structure, the swing equation for the dynamics of voltage phase angles, and a series of measured wind speed data. External control measures are accounted for by adjusting the grid state to the average power feed-in on a time scale of one minute. The wind power is injected at a single node by replacing one of the conventional generator nodes in the test grid by a wind farm. We determine histograms of local frequencies for a large number of one-minute wind speed sequences taken from the measured data and for different injection nodes. These histograms exhibit a common type of shape, which can be described by a Gaussian distribution for small frequencies and a nearly exponentially decaying tail part. Non-Gaussian features become particularly pronounced for wind power injection at locations, which are weakly connected to the main grid structure. This effect is only present when taking into account the heterogeneities in transmission line and node properties of the grid, while it disappears upon homogenizing of these features. The standard deviation of the frequency fluctuations increases linearly with the average injected wind power.

nlin.AO↗

arXiv2019

Propagation of wind-power-induced fluctuations in power grids

Renewable generators perturb the electric power grid with heavily non-Gaussian and time correlated fluctuations. While changes in generated power on timescales of minutes and hours are compensated by frequency control measures, we report subsecond distribution grid frequency measurements with local non-Gaussian fluctuations which depend on the magnitude of wind power generation in the grid. Motivated by such experimental findings, we simulate the sub-second grid frequency dynamics by perturbing the power grid, as modeled by a network of phase coupled nonlinear oscillators, with synthetically generated wind power feed-in time series. We derive a linear response theory and obtain analytical results for the variance of frequency increment distributions. We find that the variance of short-term fluctuations decays, for large inertia, exponentially with distance to the feed-in node, in agreement with numerical results both for a linear chain of nodes and the German transmission grid topology. In sharp contrast, the kurtosis of frequency increments is numerically found to decay only slowly, not exponentially, in both systems, indicating that the non-Gaussian shape of frequency fluctuations persists over long ranges.

physics.soc-ph↗

arXiv2019

Turbulent velocity measurements in high Reynolds cryogenic helium facilities at Service des Basses Temperatures (SBT)

Due to its very low viscosity, cryogenic helium has been used for years to generate high Reynolds turbulent flows. The measurement of velocity fluctuations in such high Reynolds flows is however a challenging issue, as it is necessary to develop small size (typically micron-length), robust sensors, to measure the whole spectrum of fluctuations of the velocity, which may extend to hundreds of kHz and possibly higher. SBT has developed for years different facilities, in particular taking benefit of the refrigeration capacities available at CEA Grenoble. In this article we present the current status of developments of hot wire sensors at CEA. Different characterizations of Wollaston hot wires are shown, and measurements of velocity fluctuations in different conditions, in normal helium as well as in superfluid helium are shown.

physics.flu-dyn↗

arXiv2018

Bridging between Load-Flow and Kuramoto-like Power Grid Models: A Flexible Approach to Integrating Electrical Storage Units

In future power systems, electrical storage will be the key technology for balancing feed-in fluctuations. With increasing share of renewables and reduction of system inertia, the focus of research expands towards short-term grid dynamics and collective phenomena. Against this backdrop, Kuramoto-like power grids have been established as a sound mathematical modeling framework bridging between the simplified models from nonlinear dynamics and the more detailed models used in electrical engineering. However, they have a blind spot concerning grid components, which cannot be modeled by oscillator equations, and hence do not allow to investigate storage-related issues from scratch. We remove this shortcoming by bringing together Kuramoto-like and algebraic load-flow equations. This is a substantial extension of the current Kuramoto framework with arbitrary grid components. Based on this concept, we provide a solid starting point for the integration of flexible storage units enabling to address current problems like smart storage control, optimal siting and rough cost estimations. For demonstration purpose, we here consider a wind power application with realistic feed-in conditions. We show how to implement basic control strategies from electrical engineering, give insights into their potential with respect to frequency quality improvement and point out their limitations by maximum capacity and finite-time response.

nlin.AO↗

arXiv2018

Insights into the Periodic Gust Response of Airfoils

The unsteady lift response of an airfoil in a sinusoidal gust can be modeled by two transfer functions: the first-order Sears function and the second-order Atassi function, albeit leading to different results under certain conditions. Previous studies have shown that the Sears function holds in experiments, but recently Cordes et al. (2017) reported experimental data that corresponded to the Atassi function rather than the Sears function. In order to clarify the observed discrepancy, the specific differences between these models are isolated analytically in this study and are related to physical gust parameters. Gusts with these parameters are then produced in wind-tunnel experiments using an active-grid gust generator. Measurements of the unsteady gust loads on an airfoil in the wind tunnel at Reynolds numbers ($Re_c$) of $2.0\times 10^5$ and $2.6\times 10^5$ and reduced frequencies between 0.09 and 0.42 confirm that the decisive difference between the Sears and Atassi functions lies in the character of the gust and not in the characteristics of the airfoil. The differences in the gust-response data between Sears and Atassi gust conditions are shown to be significant only at low reduced frequencies. These findings are supported by numerical simulations of the experimental setup. Finally, the influence of boundary-layer turbulence on experimental convergence with model predictions is investigated. These results serve to clarify the conditions under which the Sears and Atassi functions can be applied, and they establish the validity of both in an experimental context.

physics.flu-dyn↗

arXiv2018

The Fokker-Planck Approach to Complex Spatio-Temporal Disordered Systems

When the complete understanding of a complex system is not available, as, e.g., for systems considered in the real-world, we need a top-down approach to complexity. In this approach one may start with the desire to understand general multi-point statistics. Here such a general approach is presented and discussed based on examples from turbulence and sea waves. Our main idea is based on the cascade picture of turbulence, entangling fluctuations from large to small scales. Inspired by this cascade picture, we express the general multi-point statistics by the statistics of scale-dependent fluctuations of variables and relate it to a scale-dependent process, which finally is a stochastic cascade process. We show how to extract from empirical data a Fokker-Planck equation for this cascade process, which allows to generate surrogate data to forecast extreme events as well as to develop a non-equilibrium thermodynamics for the complex systems. For each cascade events an entropy production can be determined. These entropies fulfil accurately a rigorous law, namely the integral fluctuations theorem.

cond-mat.stat-mech↗

arXiv2018

On universal features of the turbulent cascade in terms of non-equilibrium thermodynamics

Features of the turbulent cascade are investigated for various datasets from three different turbulent flows. The analysis is focused on the question as to whether developed turbulent flows show universal small scale features. To answer this question, 2-point statistics and joint multi-scale statistics of longitudinal velocity increments are analysed. Evidence of the Markov property for the turbulent cascade is shown, which corresponds to a 3-point closure that reduces the joint multi-scale statistics to simple conditional probability density functions (cPDF). The cPDF are described by the Fokker-Planck equation in scale and its Kramers-Moyal coefficients (KMCs). KMCs are obtained by a self-consistent optimisation procedure from the measured data and result in a Fokker-Planck equation for each dataset. The knowledge of these stochastic cascade equations enables to make use of the concepts of non-equilibrium thermodynamics and thus to determine the entropy production along individual cascade trajectories. In addition to this new concept, it is shown that the local entropy production is nearly perfectly balanced for all datasets by the integral fluctuation theorem (IFT). Thus the validity of the IFT can be taken as a new law of the turbulent cascade and at the same time independently confirms that the physics of the turbulent cascade is a memoryless Markov process in scale. IFT is taken as a new tool to prove the optimal functional form of the Fokker-Planck equations and subsequently to investigate the question of universality of small scale turbulence. The results of our analysis show that the turbulent cascade contains universal and non-universal features. We identify small scale intermittency as a universality breaking feature. We conclude that specific turbulent flows have their own particular multi-scale cascade, with other words their own stochastic fingerprint.

physics.flu-dyn↗

arXiv2018

The footprint of atmospheric turbulence in power grid frequency measurements

Fluctuating wind energy makes a stable grid operation challenging. Due to the direct contact with atmospheric turbulence, intermittent short-term variations in the wind speed are converted to power fluctuations that cause transient imbalances in the grid. We investigate the impact of wind energy feed-in on short-term fluctuations in the frequency of the public power grid, which we have measured in our local distribution grid. By conditioning on wind power production data, provided by the ENTSO-E transparency platform, we demonstrate that wind energy feed-in has a measurable effect on frequency increment statistics for short time scales (< 1 sec) that are below the activation time of frequency control. Our results are in accordance with previous numerical studies of self-organized synchronization in power grids under intermittent perturbation and rise new challenges for a stable operation of future power grids fed by a high share of renewable generation.

physics.data-an↗

arXiv2017

Normal behaviour models for wind turbine vibrations: An alternative approach

The identification of abnormal behaviour in mechanical systems is key to anticipate and avoid their potential failure. Thus wind turbine health is commonly assessed monitoring series of $10$-minute SCADA and high frequency data from sensors. To monitor wind turbine vibrations, normal behaviour models are built to predict tower top accelerations and drive-train vibrations. Signal deviations from model prediction are labelled as anomalies and are further investigated. More efficient models are expected to help enhancing the identification of abnormal behaviour. In this paper we assess a stochastic approach to reconstruct the $1$ Hz tower top acceleration signal, which was measured in a wind turbine located at the wind farm Alpha Ventus in the German North Sea. We compare the resulting data reconstruction with that of a model based on a neural network, which has been previously reported as a data-mining algorithm suitable for reconstructing this signal. In order to focus the discussion on the similarities and differences of both approaches, we limit our evaluation to a single input-output system; in doing so, we avoid other differences, i.e. loading type, pre-processing or model complexity. Our results present evidence that the stochastic approach outperforms the neural network in the high frequency domain ($1$ Hz). Although neural network retrieve accurate step-forward predictions, with low mean square errors, the stochastic approach predictions better preserve the statistics and the frequency components of the original signal, remaining high accuracy levels. The implementation of our stochastic approach is available as open source code and can easily be adapted for other situations involving stochastic data reconstruction. Based on our findings we argue that such an approach could be implemented in signal reconstruction for monitoring purposes or for abnormal behaviour detection.

physics.data-an↗

arXiv2017

Rogue waves and entropy consumption

Based on data from the Japan Sea and the North Sea the occurrence of rogue waves is analyzed by a scale dependent stochastic approach, which interlinks fluctuations of waves for different spacings. With this approach we are able to determine a stochastic cascade process, which provides information of the general multipoint statistics. Furthermore the evolution of single trajectories in scale, which characterize wave height fluctuations in the surroundings of a chosen location, can be determined. The explicit knowledge of the stochastic process enables to assign entropy values to all wave events. We show that for these entropies the integral fluctuation theorem, a basic law of non-equilibrium thermodynamics, is valid. This implies that positive and negative entropy events must occur. Extreme events like rogue waves are characterized as negative entropy events. The statistics of these entropy fluctuations changes with the wave state, thus for the Japan Sea the statistics of the entropies has a more pronounced tail for negative entropy values, indicating a higher probability of rogue waves.

physics.ao-ph↗

arXiv2017

Directed percolation in aerodynamics: resolving laminar separation bubble on airfoils

In nature, phase transitions prevail amongst inherently different systems, while frequently showing a universal behavior at their critical point. As a fundamental phenomenon of fluid mechanics, recent studies suggested laminar-turbulent transition belonging to the universality class of directed percolation. Beyond, no indication was yet found that directed percolation is encountered in technical relevant fluid mechanics. Here, we present first evidence that the onset of a laminar separation bubble on an airfoil can be well characterized employing the directed percolation model on high fidelity particle image velocimetry data. In an extensive analysis, we show that the obtained critical exponents are robust against parameter fluctuations, namely threshold of turbulence intensity that distinguishes between ambient flow and laminar separation bubble. Our findings indicate a comprehensive significance of percolation models in fluid mechanics beyond fundamental flow phenomena, in particular, it enables the precise determination of the transition point of the laminar separation bubble. This opens a broad variety of new fields of application, ranging from experimental airfoil aerodynamics to computational fluid dynamics.

physics.flu-dyn↗

arXiv2017

Flow Modulation by an Active Grid

A new approach is shown, which estimates active grid wake features and enables to generate specific dynamically changing flow fields in a wind tunnel by means of an active grid. For example, measurements from free field can be reproduced in a wind tunnel. Here, the approach is explained and applied. Moreover, the approach is validated with wind tunnel measurements, in terms of time series and stochastic features. Thus, possibilities and limitations become obvious. We conclude that this new active grid wake estimating approach deepens the knowledge about specific flow modulations and shows new working ranges of active grids.

physics.flu-dyn↗

arXiv2016

On the stability and quality of power grids subjected to intermittent feed-in

Feed-in fluctuations induced by renewables are one of the key challenges to the stability and quality of electrical power grids. In particular short-term fluctuations disturb the system on a time scale, on which load balancing does not operate yet and the system is intrinsically governed by self-organized synchronization. Wind and solar power are known to be strongly non-Gaussian with intermittent increment statistics in these time scales. We investigate the impact of short-term wind fluctuations on the basis of a Kuramoto-like power grid model considering stability in terms of desynchronization and frequency and voltage quality aspects. We compare intermittent feed-in with a realistic power spectrum, correlated Gaussian noise of the same spectrum, and Gaussian white noise. We found out that the likelihood of severe outages is mainly determined by the temporal correlation of the feed-in. The intermittent nature of wind power is transferred into frequency and voltage fluctuations. This establishes a novel type of fluctuations with severe consequences on frequency and voltage quality, which are beyond engineering status of knowledge.

nlin.AO↗

arXiv2016

Suppressing the non-Gaussian statistics of Renewable Power from Wind and Solar

The power from wind and solar exhibits a nonlinear flickering variability, which typically occurs at time scales of a few seconds. We show that high-frequency monitoring of such renewable powers enables us to detect a transition, controlled by the field size, where the output power qualitatively changes its behaviour from a flickering type to a diffusive stochastic behaviour. We find that the intermittency and strong non-Gaussian behavior in cumulative power of the total field, even for a country-wide installation still survives for both renewable sources. To overcome the short time intermittency, we introduce a time-delayed feedback method for power output of wind farm and solar field that can change further the underlying stochastic process and suppress their strong non- gaussian fluctuations.

physics.soc-ph↗

arXiv2016

Short term fluctuations of wind and solar power systems

Wind and solar power are known to be highly influenced by weather events and may ramp up or down abruptly. Such events in the power production influence not only the availability of energy, but also the stability of the entire power grid. By analysing significant amounts of data from several regions around the world with resolutions of seconds to minutes, we provide strong evidence that renewable wind and solar sources exhibit multiple types of variability and nonlinearity in the time scale of {\it seconds} and characterise their stochastic properties. In contrast to previous findings, we show that only the jumpy characteristic of renewable sources decreases when increasing the spatial size over which the renewable energies are harvested. Otherwise, the strong non-Gaussian, intermittent behaviour in the cumulative power of the total field survives even for a country-wide distribution of the systems. The strong fluctuating behaviour of renewable wind and solar sources can be well characterised by Kolmogorov-like power spectra and $q-$exponential probability density functions. Using the estimated potential shape of power time series, we quantify the jumpy or diffusive dynamic of the power. Finally we propose a time delayed feedback technique as a control algorithm to suppress the observed short term non-Gaussian statistics in spatially strong correlated and intermittent renewable sources.

physics.data-an↗

arXiv2016

The Langevin Approach: An R Package for Modeling Markov Processes

We describe an R package developed by the research group Turbulence, Wind energy and Stochastics (TWiSt) at the Carl von Ossietzky University of Oldenburg, which extracts the (stochastic) evolution equation underlying a set of data or measurements. The method can be directly applied to data sets with one or two stochastic variables. Examples for the one-dimensional and two-dimensional cases are provided. This framework is valid under a small set of conditions which are explicitly presented and which imply simple preliminary test procedures to the data. For Markovian processes involving Gaussian white noise, a stochastic differential equation is derived straightforwardly from the time series and captures the full dynamical properties of the underlying process. Still, even in the case such conditions are not fulfilled, there are alternative versions of this method which we discuss briefly and provide the user with the necessary bibliography.

physics.data-an↗