Polyhedral Predictive Regions For Power System Applications

Despite substantial improvement in the development of forecasting approaches, conditional and dynamic uncertainty estimates ought to be accommodated in decision-making in power system operation and market, in order to yield either cost-optimal decisions in expectation, or decision with probabilistic guarantees. The representation of uncertainty serves as an interface between forecasting and decision-making problems, with different approaches handling various objects and their parameterization as input. Following substantial developments based on scenario-based stochastic methods, robust and chance-constrained optimization approaches have gained increasing attention. These often rely on polyhedra as a representation of the convex envelope of uncertainty. In the work, we aim to bridge the gap between the probabilistic forecasting literature and such optimization approaches by generating forecasts in the form of polyhedra with probabilistic guarantees. For that, we see polyhedra as parameterized objects under alternative definitions (under $L_1$ and $L_\infty$ norms), the parameters of which may be modelled and predicted. We additionally discuss assessing the predictive skill of such multivariate probabilistic forecasts. An application and related empirical investigation results allow us to verify probabilistic calibration and predictive skills of our polyhedra.Comment: 8 page

Generation and Evaluation of Space-Time Trajectories of Photovoltaic Power

In the probabilistic energy forecasting literature, emphasis is mainly placed on deriving marginal predictive densities for which each random variable is dealt with individually. Such marginals description is sufficient for power systems related operational problems if and only if optimal decisions are to be made for each lead-time and each location independently of each other. However, many of these operational processes are temporally and spatially coupled, while uncertainty in photovoltaic (PV) generation is strongly dependent in time and in space. This issue is addressed here by analysing and capturing spatio-temporal dependencies in PV generation. Multivariate predictive distributions are modelled and space-time trajectories describing the potential evolution of forecast errors through successive lead-times and locations are generated. Discrimination ability of the relevant scoring rules on performance assessment of space-time trajectories of PV generation is also studied. Finally, the advantage of taking into account space-time correlations over probabilistic and point forecasts is investigated. The empirical investigation is based on the solar PV dataset of the Global Energy Forecasting Competition (GEFCom) 2014.Comment: 33 pages, 11 Figure

Optimizing the Analysis of Electroencephalographic Data by Dynamic Graphs

The brain’s underlying functional connectivity has been recently studied using tools offered by graph theory and network theory. Although the primary research focus in this area has so far been mostly on static graphs, the complex and dynamic nature of the brain’s underlying mechanism has initiated the usage of dynamic graphs, providing groundwork for time sensi- tive and finer investigations. Studying the topological reconfiguration of these dynamic graphs is done by exploiting a pool of graph metrics, which describe the network’s characteristics at different scales. However, considering the vast amount of data generated by neuroimaging tools, heavy computation load and limited amount of time and resources, it is vital to refine this pool of metrics to avoid using non-informative and redundant ones. In this study, we use electroencephalographic (EEG) brain signals, taken from recordings in 5 different experimental conditions, to generate the dynamic graphs by moving a sliding win- dow over the time series. Dynamic graphs are produced under various conditions that are a combination of different window sizes, different numbers of shared time points and various frequency bands. Based on each set of these dynamic graphs, time series of 25 graph metrics, and then their pairwise correlation values are computed. This is done to investigate the metric correlations under various circumstances, and to detect the ones that are always present. We conclude by suggesting a set of uniquely informative and orthogonal metrics that is conve- nient to use for further analysis of brain’s functional connectivit

Simulation of Fatigue Crack Growth in Friction Stir-Welded Joints of 2024-T351 Aluminum Alloy

The present work simulates and predicts the fatigue crack growth in the friction stir welded (FSW) joint of the 2024-T351 Al alloy. The simulation is used to estimate the fatigue life of this welded joint. The study is based on finite element method (FEM) and in the framework of Fracture Analysis Code for two-dimensional (FRANC2D/L), developed by Fracture Group of Cornell University. Fatigue crack behavior through the FSW joint is investigated under Linear Elastic Fracture Mechanics (LEFM) using the Paris’ model. The work concentrated on a stable crack propagation regime, the obtained fatigue life shows good agreement with experimental and analytical results. The present work incorporates a few different types of loading which are 1) the cyclic fatigue loading for the case of R= 0.1, 2) the longitudinal tensile residual stress, 3) the crack closure concept and 4) the residual stress relaxation phenomenon. In the current work the stress intensity factor is calculated by applying displacement correlation technique, which is based on calculating the displacement field around the crack tip. The maximum circumferential tensile stress method was used to predict the fatigue crack direction. In fact FRANC2D/L does not have the capacity to consider different Paris’ constants for FSW zones and it predicts the crack propagation through the welded zones by considering the same values of Paris’ constants. This work presents a strategy to investigate the crack growth based on the corresponding Paris’ constants for each FSW zone. The numerical results are validated with the previous experimental and analytical work, which show a good agreement of 88% and 97%

Human-centered place branding: an integrated approach to place branding

Recently, several scholars have called for rethinking the concept of place branding (PB), articulating fundamental questions in favour of furthering its theory and practice. They have suggested the re-assessment of the applications, constructs, measures, and strategies of PB which necessitate the cross-disciplinary elaborations towards the development of the field. Place branding is, however, considered a complex social practice due to the multiplicity of stakeholders, diversity of components and approaches involved in the process, as well as the complexity of the places where the process takes place. Hence, an alternative integrated perspective is required that extends conventional approaches and frameworks beyond mere economic interests and fixed market-driven solutions. The purpose of this thesis is to conceptualise an integrated place branding (IPB) framework, to determine and demonstrate how such a framework can be developed, and to reflect upon what an integrated approach implies for the development of PB theory and practice. The research indicates that the development of such a process requires long-term negotiation and participation of internal stakeholders, an all-inclusive human-centred approach, and the application of social innovation (SI) strategies. The proposed framework is then examined through a survey of residents of six different cities in Canada, Iran, and Portugal. Partial Least Squares Structural Equation Modeling (PLSSEM) is used to empirically evaluate the proposed framework. This thesis provides several theoretical and practical contributions to the field. While developing an IPB framework based on SI strategies, this study represents a practical tool for policymakers and brand managers to foster, facilitate and enhance the processes of PB, development, and transformation in an integrated way. This thesis’ findings highlight the impact of IPB on several aspects of improvements in the place including sociocultural, institutional, and territorial developments. The results indicate such a framework can bring about changes in community values, beliefs, and norms, socio-political relations, and overall image of the place supporting the development of innovative practices and multi-purpose activities and fostering a creative atmosphere and competencies in the place that might improve the local economy. The findings also show the opportunities for the development of a multilevel governance system that involves disadvantaged groups in decisions, and new multiscalar social organisations that support social inclusion and community empowerment.Recentemente, diversos estudiosos têm defendido a necessidade de repensar o conceito de place branding (PB), em prol do seu aprofundamento teórico e prático. Neste contexto, e com base em abordagens interdisciplinares, é oportuna a reavaliação de constructos, métodos de mensuração, estratégias e ações, o que poderá contribuir para o desenvolvimento desta área de investigação. Place branding é, pois, considerada uma prática social complexa devido à multiplicidade de stakeholders, componentes e abordagens envolvidas no processo de criação da marca dos lugares. O lugar é, devido à sua natureza compósita, uma entidade complexa. Consequentemente, a adoção de uma perspetiva integrada de PB, que estenda as abordagens e estruturas convencionais além de meros interesses económicos e soluções fixas voltadas para o mercado, é um fator crítico de sucesso na gestão dos lugares. O objetivo desta investigação é concetualizar um modelo integrado de place branding (IPB) e contribuir para a operacionalização do constructo. A pesquisa indica que o desenvolvimento deste processo requer negociação e participação de longo prazo entre as partes interessadas, tendo como base uma abordagem inclusiva e centrada no ser humano, através da aplicação de estratégias de inovação social (IS). O modelo integrado de place branding proposto é testado em seis cidades no Canadá, Irão e Portugal. Este estudo fornece contributos teóricos e empíricos. Os resultados apresentam-se com utilidade prática para gestores públicos, políticos e profissionais responsáveis pela criação e gestão de marcas de lugares. Além disso, destacam o impacto da abordagem integrada de gestão da marca dos lugares, sobretudo ao nível sociocultural, institucional e territorial, com impactos nos valores partilhados pela comunidade, crenças e normas, relações sociopolíticas e imagem geral do local. Pode, ainda, contribuir para o desenvolvimento de práticas inovadoras e atividades polivalentes, promovendo uma atmosfera criativa e estimulando competências no lugar com reflexos na economia local. Além disso, contribui para criar condições à implementação de um sistema de governança multinível no qual estão envolvidos grupos desfavorecidos e novas organizações sociais, uma evolução do sentido da inclusão social e do empoderamento da comunidade.This research was supported by the FCT – Portuguese Foundation for Science and Technology under the project UIDB/ 04020/2020

Ellipsoidal Prediction Regions for Multivariate Uncertainty Characterization

While substantial advances are observed in probabilistic forecasting for power system operation and electricity market applications, most approaches are still developed in a univariate framework. This prevents from informing about the interdependence structure among locations, lead times and variables of interest. Such dependencies are key in a large share of operational problems involving renewable power generation, load and electricity prices for instance. The few methods that account for dependencies translate to sampling scenarios based on given marginals and dependence structures. However, for classes of decision-making problems based on robust, interval chance-constrained optimization, necessary inputs take the form of polyhedra or ellipsoids. Consequently, we propose a systematic framework to readily generate and evaluate ellipsoidal prediction regions, with predefined probability and minimum volume. A skill score is proposed for quantitative assessment of the quality of prediction ellipsoids. A set of experiments is used to illustrate the discrimination ability of the proposed scoring rule for misspecification of ellipsoidal prediction regions. Application results based on three datasets with wind, PV power and electricity prices, allow us to assess the skill of the resulting ellipsoidal prediction regions, in terms of calibration, sharpness and overall skill.Comment: 8 pages, 7 Figures, Submitted to IEEE Transactions on Power System

Application of numerical method to investigation of fatigue crack behavior through the friction stir welding

Fatigue crack propagation through a friction stir welded (FSW) joint of 2024-T351 Al alloy is investigated numerically. The governing relationships for predicting the crack behavior including incremental crack length, crack growth rate, and crack growth direction are presented. Stress intensity is calculated based on displacement correlation technique, and fatigue crack growth through the FSW joint is investigated under linear elastic fracture mechanics (LEFM) using the Paris model. The concepts of crack closure, residual stress, and stress relaxation are incorporated into the Paris model to support the final results. Maximum circumferential tensile stress method is applied to predict the crack growth direction. Finally, the numerical approaches are employed to the high number of elements in the framework of Fracture Analysis Code (FRANC2D/L) to simulate the fatigue crack propagation through the FSW joint including various zones with different material properties. Fatigue lifetime of the welded joint is predicted by implementing the same procedure for various loading values. The obtained numerical results are validated with the experimental work (Ali et al., Int J Fatigue 30:2030–2043, 2008)