Multi-kalman filter to wind power forecasting

Wind power forecasting methods are important for the safety of wind renewable energy utilization. However, because wind power is weather dependent and, thus, can be variable and intermittent over different time-scales, it’s difficult to build accurate and robust predictive models. In this context, an accurate model is a relevant contribution for a reliable large-scale wind power integration. This paper explores a new approach using a multi-model Kalman filter to provide an estimate of the average hourly wind speed, in a 24 hours horizon. The K-means algorithm is used to obtain the characteristics curves of wind speed each time the sub-model is used for forecasting. The accuracy of the proposed forecasting model is compared with other statistical methods, namely some that are usually considered suitable, robust and accurate.info:eu-repo/semantics/publishedVersio

Hybrid PSO-cubic spline for autonomous robots optimal trajectory planning

This paper presents a new version of the Particle Swarm Optimization algorithm where the particles are replaced by spline functions. The developed algorithm generates smooth motion trajectories with two times continuously differentiable curvature avoiding obstacles placed in the workspace. It can be used for autonomous robot path planning or transport problems. The spline based trajectory generation gives us continuous, smooth and optimized path trajectories. Simulation and experimental results demonstrate the effectiveness of the proposed method.info:eu-repo/semantics/publishedVersio

The soft power of China and the European Union in the context of the belt and road initiative and global strategy

Soft power has emerged as a topic of growing interest in Chinese foreign policy and its expression gained new salience when it was anchored within the framework of the Belt and Road Initiative (BRI). This article proposes a comparative analysis of the soft power of China and the European Union (EU) in the context of the BRI and Global Strategy of June 2016. Drawing on the role theory, this study seeks to fill a gap in previous scholarly works, focusing on the soft power dynamics underlying the China–EU relationship, which do not incorporate the BRI as an increasingly influential soft power tool in Chinese foreign policy. It concludes that the BRI and Global Strategy have infused China’s and EU’s soft power, respectively, with innovating aspects; and despite the emergence of some common ground as a result of that, differences between the two actors regarding role conception, role expectation and role performance remain noticeable.The authors acknowledges that this study was conducted at the Research Center in Political Science (UIDB/CPO/00758/2020), University of Minho/University of Evora, and was supported by the Portuguese Foundation for Science and Technology and the Portuguese Ministry of Education and Science through national funds

Economic and risk factors of a transhipment system using electric cargo bikes for urban courier services

The distribution of goods in urban areas is a major challenge for managers in the public and private sectors, due to population growth, high density in large urban centers and, in many cases, lack of planning in urban cargo transport systems. In this context, the objective of this paper is to propose a novel collaborative urban cargo distribution system for logistics service providers, based on a transshipment terminal and usage of electric cargo bikes, highlighting the main aspects to consider on estimating its beneficial economic and environmental impacts in terms of emissions and the risk factors of the investment. The evaluation of this solution may be based on applying simple vehicle routing heuristics for assessing the distance travelled, costs and emissions. Also, a more sophisticated cost model is proposed to estimate the economic viability and risks associated to the use of electric cargo bikes. Finally, risk aspects can be evaluated through a structured methodology including both qualitative and quantitative approaches.This work has been supported by FCT -Fundacao para a Ciencia e Tecnologia (Portugal) within the Project Scope: UID/CEC/00319/2019

Sistema de sensorização móvel e controlo baseado em ZigBee para bicicletas elétricas

Este artigo apresenta um sistema de monitorização e controlo centrado em dispositivos móveis concebido para aplicação em cenários que permitem tirar partido de uma bicicleta eléctrica. A bicicleta, para além de um meio de transporte, é uma excelente ferramenta para a promoção do exercício físico, podendo contribuir para melhorar a aptidão física de utilizadores de diversas faixas etárias. O sistema proposto, baseado numa rede ZigBee, permite recolher sinais fisiológicos dos utilizadores e controlar o motor elétrico da bicicleta de modo a possibilitar a implementação de diversos modos de utilização. Este trabalho descreve a solução utilizada para implementar a comunicação sem fios entre os sensores ZigBee e um smartphone Android, bem como os sensores para monitorização de sinais fisiológicos que foram desenvolvidos. De modo a ajudar a perceber onde este trabalho pode ser aplicado, são explicados alguns modos de utilização baseados no controlo do esforço físico, bem como as vantagens do sistema em relação às bicicletas convencionais e bicicletas estáticas.Fundação para a Ciência e a Tecnologia (FCT

Why is China going polar? Understanding engagement and implications for the Arctic and Antarctica

In a context of globalization of world economy, environmental change and progressive blurring of traditional borders, the Arctic and Antarctica have witnessed growing geopolitical competition. While in recent years, developments in the Arctic regarding geopolitics and governance-related issues, and energy resources management have been subject to academic enquiry, the same cannot be said regarding Antarctica. This chapter attempts to fill this gap by providing a comparative study focusing on China’s engagement of in the North and South Poles and its implications. It argues that China’s stance in the Arctic has been largely conditioned by the regional governance dynamics structured around the Arctic Council, whilst in Antarctica this country has attempted to explore the absence of both coastal states and more regulated interstate relations to carve for itself an advantageous position with the post-2048 South Pole governance perspectives in view.The authors acknowledge that this study was conducted at the Research Center in Political Science (UIDB/CPO/00758/ 2020), University of Minho/University of Évora, and that it was supported by the Portuguese Foundation for Science and Technology and the Portuguese Ministry of Education and Science, through national fund

Interfaces for renewable energy sources with electric power systems

This paper presents technological solutions that intend to contribute both for the efficient production of electric energy from renewable non-pollutant sources (namely Wind and Sun) and to the improvement of power quality in the electrical systems. It proposes the development of low-cost and high-efficiency power controllers that optimize energy extraction from hybrid systems, constituted by photovoltaic solar panels and wind power turbines, in small renewable energy power plants. Main innovations are the use of a single microcontroller for both sources’ power control and the development of an interface between the DC link and the AC electrical system. This interface uses a control system based in the p-q theory that takes into account power quality issues. The paper also presents a cost study regarding products for renewable systems available in the market.Fundação para a Ciência e a Tecnologia (FCT) - POCTI/ESE/41170/2001

A tool for obtaining information on DTN traces

International audienceThe applications for dynamic networks are growing every day, and thus, so is the number of studies on them. An important part of such studies is the generation of results through simulation and comparison with other works. We implemented a tool to generate information on a given network trace, obtained by building its corresponding evolving graph. This information is useful to help researchers choose the most suitable trace for their work, to interpret the results correctly and to compare data from their work to the optimal results in the network. In this work, we present the implementation of the DTNTES tool which provides the aforementioned services and use the system to evaluate the DieselNet trace

Production time prediction for contract manufacturing industries using automated machine learning

The estimation of production time is an essential part of the manufacturing domain, allowing companies to optimize their production plan and meet the dates required by the customers. In the last years, there have been several approaches that use Machine Learning (ML) to predict the time needed to finish production orders. In this paper, we use the CRISP-DM methodology and Automated Machine Learning (AutoML) to address production time prediction for a Portuguese contract manufacturing company that produces metal containers. We performed three CRISP-DM iterations using real data provided by the company related to production orders and production operations. We compared four open-source modern AutoML technologies to predict production time across the three iterations: AutoGluon, H2O AutoML, rminer, and TPOT. Overall, the best results were achieved in the third CRISP-DM iteration by the H2O AutoML tool, which obtained an average error of 3.03 days. The obtained results suggest that the inclusion of data about individual manufacturing operations is useful for improving production time for the entire production order.This work has been supported by the European Regional Development Fund (FEDER) through a grant of the Operational Programme for Competitivity and Internationalization of Portugal 2020 Partnership Agreement (POCI-01-0247-FEDER-046102, PRODUTECH4S&C)