pwc-archive/papers-with-abstracts huggingface dataset:
Grid-Aware Provision and Activation of Fast and Slow Flexibilities from Distributed Resources in Low and Medium Voltage Grids
Authors: Ankur Majumdar, Omid Alizadeh-Mousavi
Date: 2021-08-09 00:00:00

As more and more renewable intermittent generations are being connected to the distribution grid, the grid operators require more flexibility to maintain the balance between supply and demand. The intermittencies give rise to situations which require not only slow-ramping flexibility capability but also, fast-ramping flexibility capability from a variety of resources connected at the MV and LV distribution grids. Moreover, the intermittencies may increase the costs of grid reinforcement. Therefore, to defer the reinforcement of the grid assets, the grid needs to be operated optimally. This paper proposes - a) such an optimal operational methodology for the MV and LV grids; and b) an aggregated flexibility estimation methodology estimated separately for fast and slow services at the primary substation (TSO interface). The methodologies based on model-based MV grids and a sensitivity coefficients-based model-less LV grids are suitable for LV grids where an up-to-date and accurate model and topology are not always available. The approaches of the paper use the synchronised and accurate measurements from grid monitoring devices located at the LV distribution grids. It is assumed that the implementation of the methodology is centralised, where a grid monitoring device or a central platform is capable to host grid aware algorithms and to communicate control setpoints to DERs. The approaches have been validated on a real MV and LV networks of a Swiss DSO equipped with grid monitoring devices. The results, in terms of technical losses, grid violation costs and flexibility capability curve, show the efficacy of the optimal operation and flexibility estimation methodologies and therefore, can be easily deployed.
Distribution Grid Robust Operation under Forecast Uncertainties with Flexibility Estimation from Low Voltage Grids using a Monitoring and Control Equipment
Authors: Ankur Majumdar, Omid Alizadeh-Mousavi
Date: 2021-08-09 00:00:00

Due to increased penetration of renewable resources in the distribution grid, the distribution system operator (DSO) faces increased challenges to maintain security and quality of supply. Since, a large proportion of renewables are intermittent generations, maintaining production and consumption balance of the electric system is at stake. The DSO needs to procure flexibilities not only from large resources, but also small-scale resources connected to the LV grid. Therefore, there is a need to estimate the aggregate flexibility at the secondary substation available from the LV grids. The flexibility estimation can only be achieved through monitoring of LV grid and the distributed energy resources (DERs) connected at the LV level. Moreover, the variability of intermittent resources affects the flexibility estimation methodology, and the DSO operation must be robust to the changes in generation or demand outputs. Furthermore, the up-to-date and accurate model of the LV grid is difficult to access. This paper demonstrates a methodology of estimating flexibility by sensitivity coefficients and thus, eliminating the need to have an up-to-date LV grid model. It further presents a robust optimisation based methodology for grid operation to address the impact of forecast uncertainties associated with the variable DER output. The methodologies illustrate the value of grid monitoring with a monitoring equipment. It has been validated on a real network of a Swiss DSO with several grid monitoring devices.
Efficient distribution grid flexibility provision through model-based MV grid and model-less LV grid approach
Authors: Ankur Majumdar, Omid Alizadeh-Mousavi
Date: 2021-08-09 00:00:00
Tasks: model

In order to maintain security and quality of supply while supporting increased intermittent generation and electrification of heating and transport at the LV grid, the provision of flexibility in the framework of distribution grid operation is pivotal. However, the availability of updated and accurate LV grid model is a challenge for the distribution system operator (DSO). This paper demonstrates a methodology of efficient flexibility provision and activation through a sensitivity coefficients-based model-less LV grid and a modelled MV grid approach. The paper further illustrates the value of monitoring and control through a LV DERMS platform for efficient realisation of this flexibility provision and activation. The methodology has been tested on a real MV and LV network of a Swiss DSO. The results show that there is a reduction of cost of operation for a DSO.
Novel convex decomposition of piecewise affine functions
Authors: Nils Schlüter, Moritz Schulze Darup
Date: 2021-08-09 00:00:00

In this paper, we present a novel approach to decompose a given piecewise affine (PWA) function into two convex PWA functions. Convex decompositions are useful to speed up or distribute evaluations of PWA functions. Different approaches to construct a convex decomposition have already been published. However, either the two resulting convex functions have very high or very different complexities, which is often undesirable, or the decomposition procedure is inapplicable even for simple cases. Our novel methodology significantly reduces these drawbacks in order to extend the applicability of convex decompositions.
Reachability of Dimension-Bounded Linear Systems
Authors: Yiliang Li, Haitao Li, Jun-e Feng, Jinjin Li
Date: 2021-08-09 00:00:00

In this paper, the reachability of dimension-bounded linear systems is investigated.Since state dimensions of dimension-bounded linear systems vary with time, the expression of state dimension at each time is provided.A method for judging the reachability of a given vector space is proposed. In addition, this paper proves that the t-step reachable subset is a linear space, and gives a computing method. The t-step reachability of a given state is verified via a rank condition. Furthermore, annihilator polynomials are discussed and used to illustrate the relationship between the invariant space and the reachable subset after the invariant time point t*. The inclusion relation between reachable subsets at times t*+i and t*+j is shown via an example.
Coordination on Time-Varying Antagonistic Networks
Authors: Wentao Zhang
Date: 2021-08-09 00:00:00

This paper studies coordination problem for time-varying networks suffering from antagonistic information, quantified by scaling parameters. By such a manner, interacting property of the participating individuals and antagonistic information can be quantified in a fully decoupled perspective, thus benefiting from merely directed spanning tree hypothesis is needed, in the sense of usual algebraic graph theory. We start with rigorous argument on the existence of weighted gain, and then derive relation among weighted gain, scaling parameter and Laplacian matrix guaranteeing antagonistic information cannot diverge system state. Based on these arguments, we devise coordination algorithm constrained by topology-dependent average time condition, thus relaxing the examination of directed spanning tree requirement for the union graph that is usually intractable. Moreover, the induced theoretical results are applied to time-varying networks with several mutually uninfluenced agents, in accompanying with some discussions and comparisons with respect to the existing developments.
Dynamic Modelling of Combined Cycle Power Plant for Load Frequency Control With Large Penetration of Renewable Energy
Authors: Songyao Jiang, Takeyoshi Kato
Date: 2021-08-09 00:00:00

As the concern about climate change and energy shortage grow stronger, the incorporation of renewable energy in the power system in the future is foreseeable. In a hybrid power system with a large penetration of PV generation, PV panel is regarded as a negative load in the power system. With the accurate prediction of PV output power, load frequency control could be done by controlling the thermal and hydro power plant in the system. Combined Cycle Power Plant is widely used because of its great advantages of fast response and high efficiency. This article is focusing on the mathematical modelling and analyzing of Combined Cycle Power Plant for the frequency control purpose in a model of hybrid system with large renewable energy generation.
Traffic Assignment Problem for Footpath Networks with Bidirectional Links
Authors: Tanapon Lilasathapornkit, David Rey, Wei Liu, Meead Saberi
Date: 2020-12-06 00:00:00
Tasks: Equilibrium traffic assignment

The estimation of pedestrian traffic in urban areas is often performed with computationally intensive microscopic models that usually suffer from scalability issues in large-scale footpath networks. In this study, we present a new macroscopic user equilibrium traffic assignment problem (UE-pTAP) framework for pedestrian networks while taking into account fundamental microscopic properties such as self-organization in bidirectional streams and stochastic walking travel times. We propose four different types of pedestrian volume-delay functions (pVDFs), calibrate them with empirical data, and discuss their implications on the existence and uniqueness of the traffic assignment solution. We demonstrate the applicability of the developed UE-pTAP framework in a small network as well as a large scale network of Sydney footpaths.
Sampled-Data and Event-triggered Boundary Control of a Class of Reaction-Diffusion PDEs with Collocated Sensing and Actuation
Authors: Bhathiya Rathnayake, Mamadou Diagne, Iasson Karafyllis
Date: 2021-08-07 00:00:00

This paper provides observer-based sampled-data and event-triggered boundary control strategies for a class of reaction-diffusion PDEs with collocated sensing and Robin actuation. Infinite-dimensional backstepping design is used as the underlying control approach. It is shown that the continuous-time output feedback boundary control applied in a sample-and-hold fashion ensures global closed-loop exponential stability, provided that the sampling period is sufficiently small. Further, robustness to perturbations of the sampling schedule is guaranteed. For the event-triggered implementation of the continuous-time controller, a dynamic triggering condition is utilized. The triggering condition determines the time instants at which the control input needs to be updated. Under the observer-based event-triggered boundary control, it is shown that there is a minimal dwell-time between two triggering instants independent of initial conditions. Further, the global exponential convergence of the closed-loop system to the equilibrium point is established. A simulation example is provided to validate the theoretical results.
Observer-based Event-triggered Boundary Control of a Class of Reaction-Diffusion PDEs
Authors: Bhathiya Rathnayake, Mamadou Diagne, Nicolas Espitia, Iasson Karafyllis
Date: 2020-09-24 00:00:00

This paper presents an observer-based event-triggered boundary control strategy for a class of reaction-diffusion PDEs with Robin actuation. The observer only requires boundary measurements. The control approach consists of a backstepping output feedback boundary controller, derived using estimated states, and a dynamic triggering condition, which determines the time instants at which the control input needs to be updated. It is shown that under the proposed observer-based event-triggered boundary control approach, there is a minimal dwell-time between two triggering instants independent of initial conditions. Furthermore, the well-posedness and the global exponential convergence of the closed-loop system to the equilibrium point are established. A simulation example is provided to validate the theoretical developments.
Probabilistic Reach-Avoid Reachability in Nondeterministic Systems with Time-VaryingTargets and Obstacles
Authors: Wei Liao, Taotao Liang, Xiaohui Wei, Qiaozhi Yin
Date: 2021-08-07 00:00:00

The probabilistic reachability problems of nondeterministic systems are studied. Based on the existing studies, the definition of probabilistic reachable sets is generalized by taking into account time-varying target set and obstacle. A numerical method is proposed to compute probabilistic reachable sets. First, a scalar function in the state space is constructed by backward recursion and grid interpolation, and then the probability reachable set is represented as a nonzero level set of this scalar function. In addition, based on the constructed scalar function, the optimal control policy can be designed. At the end of this paper, some examples are taken to illustrate the validity and accuracy of the proposed method.
Slow expanders invade by forming dented fronts in microbial colonies
Authors: Hyunseok Lee, Jeff Gore, Kirill S. Korolev
Date: 2021-08-09 00:00:00

Most organisms grow in space, whether they are viruses spreading within a host tissue or invasive species colonizing a new continent. Evolution typically selects for higher expansion rates during spatial growth, but it has been suggested that slower expanders can take over under certain conditions. Here, we report an experimental observation of such population dynamics. We demonstrate that the slower mutants win not only when the two types are intermixed at the front but also when they are spatially segregated into sectors. The latter was thought to be impossible because previous studies focused exclusively on the global competitions mediated by expansion velocities but overlooked the local competitions at sector boundaries. We developed a theory of sector geometry that accounts for both local and global competitions and describes all possible sector shapes. In particular, the theory predicted that a slower, but more competitive, mutant forms a dented V-shaped sector as it takes over the expansion front. Such sectors were indeed observed experimentally and their shapes matched up quantitatively with the theory. In simulations, we further explored several mechanism that could provide slow expanders with a local competitive advantage and showed that they are all well-described by our theory. Taken together, our results shed light on previously unexplored outcomes of spatial competition and establish a universal framework to understand evolutionary and ecological dynamics in expanding populations.
Comparison of computing efficiency among FFT, CZT and Zoom FFT in THz-TDS
Authors: Abel Garcia-Devesa, Miguel A Baez-Chorro, Borja Vidal
Date: 2021-08-09 00:00:00

A study of alternative transforms to FFT in order to compare their potential to enhance resolution and computation time in the framework of THz time domain spectroscopy (THz-TDS) instruments is carried out. Both from simulated and experimental data it is shown that, as expected, resolution cannot be enhanced using CZT or Zoom FFT and, in terms of computing efficiency, FFT is in practical cases, the most efficient one.
Effectiveness of regional diffusion MRI measures in distinguishing multiple sclerosis abnormalities within the cervical spinal cord
Authors: Haykel Snoussi, Julien Cohen-Adad, Benoit Combes, Elise Bannier, Slimane Tounekti, Anne Kerbrat, Christian Barillot, Emmanuel Caruyer
Date: 2021-08-09 00:00:00
Tasks: Diffusion  MRI, Prognosis, Quantitative MRI

Multiple sclerosis is an inflammatory disorder of the central nervous system. Quantitative MRI has huge potential to provide intrinsic and normative values of tissue properties useful for diagnosis, prognosis and ultimately clinical follow-up of this disease. However, there is a large discrepancy between the clinical observations and how the pathology is exhibited in MRI brain scans. Complementary to brain imaging, the study of multiple sclerosis lesions in the spinal cord has recently gained interest as a potential marker for early physical impairment. Therefore, investigating how the spinal cord is damaged using quantitative imaging, in particular, diffusion MRI, becomes an acute challenge. In this work, we extract average diffusion MRI metrics per vertebral level from spinal cord data acquired from multiple clinical sites. The diffusion-based metrics involved are extracted from the diffusion tensor imaging and Ball-and-Stick models and quantified for every cervical vertebral level using a collection of image processing methods and an atlas-based approach. Then, we perform a statistical analysis study to characterize the feasibility of these metrics to detect lesions. Specifically, we study the usefulness of combining different metrics to improve the accuracy prediction score associated with the presence of multiple sclerosis lesions. We demonstrate the grade of sensitivity to underlying microstructure changes in MS patients of each metric. Ball-and-Stick provides novel information about the MS damage to tissue microstructure. In addition, we show that choosing a subset of metrics: [FA, RD, MD] and [FWW, MD, Stick-AD, RD], which bring complementary information, has significantly increased the prediction score of the presence of the MS lesion in the cervical spinal cord.
Evaluation of distortion correction methods in diffusion MRI of the spinal cord
Authors: Haykel Snoussi, Julien Cohen-Adad, Olivier Commowick, Benoit Combes, Elise Bannier, Soizic Leguy, Anne Kerbrat, Christian Barillot, Emmanuel Caruyer
Date: 2021-08-09 00:00:00
Tasks: Diffusion  MRI, distortion correction

Background: Magnetic field inhomogeneities generate important geometric distortions in reconstructed echo-planar images. Various procedures were proposed for correcting these distortions on brain images; yet, few neuroimaging studies tailored and incorporated the use of these techniques in spinal cord diffusion MRI. Purpose: We present a comparative evaluation of distortion correction methods that use the reversed gradient polarity technique on spinal cord. We propose novel geometric metrics to measure the alignment of the reconstructed diffusion model with the apparent centerline of the spinal cord. Subjects: 95 subjects, among which 29 healthy controls and 66 multiple sclerosis patients. Assessment: Geometric distortions were corrected using 4 state-of-the-art methods. We measured the alignment of the principal direction of diffusion with the apparent centerline of the spine after correction and the correlation with the reference anatomical image. Results are computed per vertebral level, to evaluate the impact on different portions of the spine. Besides, subjective evaluation of the quality of the correction of healthy subjects images was performed by three expert raters. Results: As a result of distortion correction, the diffusion directions are better aligned locally with the centerline, in particular at both ends of the acquisition window. The cross-correlation with anatomical image is also improved by Hyperelastic Susceptibility Artefact Correction (HySCO) and block-matching. The subjective evaluation for HySCO is significantly better (p < 0.05) than for Block-Matching; TOPUP performs significantly worse than the three other methods. Conclusion: Correction based on HySCO provide best results among the selected methods.
A Theoretical Analysis of Logistic Regression and Bayesian Classifiers
Authors: Roman V. Kirin
Date: 2021-08-08 00:00:00
Tasks: regression

This study aims to show the fundamental difference between logistic regression and Bayesian classifiers in the case of exponential and unexponential families of distributions, yielding the following findings. First, the logistic regression is a less general representation of a Bayesian classifier. Second, one should suppose distributions of classes for the correct specification of logistic regression equations. Third, in specific cases, there is no difference between predicted probabilities from correctly specified generative Bayesian classifier and discriminative logistic regression.
Including the asymmetry of the Lorenz curve into measures of economic inequality
Authors: Mario Schlemmer
Date: 2021-08-08 00:00:00

The Gini index signals only the dispersion of the distribution and is not very sensitive to income differences at the tails of the distribution. The widely used index of inequality can be adjusted to also measure distributional asymmetry by attaching weights to the distances between the Lorenz curve and the 45-degree line. The measure is equivalent to the Gini if the distribution is symmetric. The alternative measure of inequality inherits good properties from the Gini but is more sensitive to changes in the extremes of the income distribution.
Fully Modified Least Squares Cointegrating Parameter Estimation in Multicointegrated Systems
Authors: Igor L. Kheifets, Peter C. B. Phillips
Date: 2021-08-07 00:00:00
Tasks: parameter estimation

Multicointegration is traditionally defined as a particular long run relationship among variables in a parametric vector autoregressive model that introduces additional cointegrating links between these variables and partial sums of the equilibrium errors. This paper departs from the parametric model, using a semiparametric formulation that reveals the explicit role that singularity of the long run conditional covariance matrix plays in determining multicointegration. The semiparametric framework has the advantage that short run dynamics do not need to be modeled and estimation by standard techniques such as fully modified least squares (FM-OLS) on the original I(1) system is straightforward. The paper derives FM-OLS limit theory in the multicointegrated setting, showing how faster rates of convergence are achieved in the direction of singularity and that the limit distribution depends on the distribution of the conditional one-sided long run covariance estimator used in FM-OLS estimation. Wald tests of restrictions on the regression coefficients have nonstandard limit theory which depends on nuisance parameters in general. The usual tests are shown to be conservative when the restrictions are isolated to the directions of singularity and, under certain conditions, are invariant to singularity otherwise. Simulations show that approximations derived in the paper work well in finite samples. The findings are illustrated empirically in an analysis of fiscal sustainability of the US government over the post-war period.
Culling the herd of moments with penalized empirical likelihood
Authors: Jinyuan Chang, Zhentao Shi, Jia Zhang
Date: 2021-08-07 00:00:00
Tasks: valid

Models defined by moment conditions are at the center of structural econometric estimation, but economic theory is mostly agnostic about moment selection. While a large pool of valid moments can potentially improve estimation efficiency, in the meantime a few invalid ones may undermine consistency. This paper investigates the empirical likelihood estimation of these moment-defined models in high-dimensional settings. We propose a penalized empirical likelihood (PEL) estimation and establish its oracle property with consistent detection of invalid moments. The PEL estimator is asymptotically normally distributed, and a projected PEL procedure further eliminates its asymptotic bias and provides more accurate normal approximation to the finite sample behavior. Simulation exercises demonstrate excellent numerical performance of these methods in estimation and inference.