Long-term memory in financial prices: evidence from the Dutch stock market returns

Prepared for presentation at the Portuguese Finance Network International Conference 2014, Vilamoura, Portugal, June 18-20

Innovative manufacturing process for hybrid pultruded products based on cork and polymeric pre-shapes

Pultruded products are being targeted by a growing demand due to its excellent mechanical properties and low chemical reactivity, ensuring a low level of maintenance operations and allowing an easier assembly operation process than equivalent steel bars. In order to improve the mechanical drawing process and solve some acoustic and thermal insulation problems, pultruded pipes of glass fibre reinforced plastics (GFRF) can be filled with special products that increase their performance regarding the issues previously referred. The great challenge of this work was drawing a new equipment able to produce pultruded pipes filled with cork or polymeric pre-shaped bars as a continuous process. The project was carried out successfully and the new equipment was built and integrated in the pultrusion equipment already existing, allowing to obtain news products with higher added-value in the market, covering some needs previously identified in the field of civil construction.

Controlo de um sistema domótico KNX

Esta dissertação descreve o estudo, concepção e desenvolvimento de uma aplicação baseada no sistema operativo Windows 8 que interage com um sistema domótico KNX, permitindo ao utilizador controlar a sua instalação domótica. Esta proposta, que combina a área de integração/instalação de sistemas domóticos e a de desenvolvimento de aplicações para Windows 8 e Windows 8 Phone, constitui um desafio particularmente interessante para quem tem experiência profissional nas duas áreas. A domótica surgiu na década de 70 como uma aplicação da eletrónica e das tecnologias da informação às instalações residenciais, comerciais e industriais. Esta nova área desencadeou uma revolução, não só, ao nível da produção e comercialização, mas, também, do ponto de vista do utilizador, ao promover a comodidade, segurança, personalização e o controlo de pessoas e bens. Os smartphones e tablets vieram permitir que o desenvolvimento de aplicações móveis de interacção com os sistemas domóticos. Ao longo desta dissertação são descritas e analisadas as múltiplas áreas de intervenção da domótica assim como as diferentes tecnologias de aplicação e mercados. Também são analisados os sistemas operativos que existentes, as respetivas cotas de mercado e os tipos de dispositivos disponíveis. Por último, a aplicação foi concebida, implementada e testada para verificar a correcta interacção com o sistema domótico KNX e as funcionalidades de controlo da instalação domótica.

A política agrícola comum (PAC) e o comércio internacional - estudo econométrico do efeito da PAC sobre as exportações agrícolas portuguesas para a União Europeia (1975-2012)

Dissertação apresentada ao Instituto Superior de Contabilidade e Administração do Porto para obtenção do Grau de Mestre em Empreendedorismo e Internacionalização Orientadora: Professora Doutora Maria Clara Ribeiro Coorientadora: Mestre Maria Luísa Verdelho Alves

Day-ahead Resource Scheduling Including Demand Response for Electric Vehicles

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.

Modified Particle Swarm Optimization Applied to Integrated Demand Response and DG Resources Scheduling

The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the operation costs of a virtual power player that manages the resources in a distribution network and the network itself. Resources include the DER available in the considered time period and the energy that can be bought from external energy suppliers. Network constraints are considered. The proposed approach uses Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310 consumers and 548 distributed generators. The obtained solutions are compared with a deterministic approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.

Distributed, Agent-Based Intelligent System for Demand Response Program Simulation in Smart Grids

A distributed, agent-based intelligent system models and simulates a smart grid using physical players and computationally simulated agents. The proposed system can assess the impact of demand response programs.

Decision Support Concerning Demand Response Programs Design and Use – A Conceptual Framework and Simulation Tool

Demand response can play a very relevant role in the context of power systems with an intensive use of distributed energy resources, from which renewable intermittent sources are a significant part. More active consumers participation can help improving the system reliability and decrease or defer the required investments. Demand response adequate use and management is even more important in competitive electricity markets. However, experience shows difficulties to make demand response be adequately used in this context, showing the need of research work in this area. The most important difficulties seem to be caused by inadequate business models and by inadequate demand response programs management. This paper contributes to developing methodologies and a computational infrastructure able to provide the involved players with adequate decision support on demand response programs and contracts design and use. The presented work uses DemSi, a demand response simulator that has been developed by the authors to simulate demand response actions and programs, which includes realistic power system simulation. It includes an optimization module for the application of demand response programs and contracts using deterministic and metaheuristic approaches. The proposed methodology is an important improvement in the simulator while providing adequate tools for demand response programs adoption by the involved players. A machine learning method based on clustering and classification techniques, resulting in a rule base concerning DR programs and contracts use, is also used. A case study concerning the use of demand response in an incident situation is presented.

Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.

Dynamic load management in a smart home to participate in demand response events

In future power systems, in the smart grid and microgrids operation paradigms, consumers can be seen as an energy resource with decentralized and autonomous decisions in the energy management. It is expected that each consumer will manage not only the loads, but also small generation units, heating systems, storage systems, and electric vehicles. Each consumer can participate in different demand response events promoted by system operators or aggregation entities. This paper proposes an innovative method to manage the appliances on a house during a demand response event. The main contribution of this work is to include time constraints in resources management, and the context evaluation in order to ensure the required comfort levels. The dynamic resources management methodology allows a better resources’ management in a demand response event, mainly the ones of long duration, by changing the priorities of loads during the event. A case study with two scenarios is presented considering a demand response with 30 min duration, and another with 240 min (4 h). In both simulations, the demand response event proposes the power consumption reduction during the event. A total of 18 loads are used, including real and virtual ones, controlled by the presented house management system.

Fresh-cut aromatic herbs: Nutritional quality stability during shelf-life

Fresh-cut vegetables are a successful convenient healthy food. Nowadays, the presence of new varieties of minimally processed vegetables in the market is common in response to the consumers demand for new flavours and high quality products. Within the most recent fresh-cut products are the aromatic herbs. In this work, the objective was to evaluate the nutritional quality and stability of four fresh-cut aromatic herbs. Several physicochemical quality characteristics (colour, pH, total soluble solids, and total titratable acidity) were monitored in fresh-cut chives, coriander, spearmint and parsley leaves, stored under refrigeration (3 ± 1 ºC) during 10 days. Their nutritional composition was determined, including mineral composition (phosphorous, potassium, sodium, calcium, magnesium, iron, zinc, manganese and copper) and fat- and water-soluble vitamin contents. Total soluble phenolics, flavonoids and the antioxidant capacity were determined by spectrophotometric methods. The aromatic herbs kept their fresh appearance during the storage, maintaining their colour throughout shelf-life. Their macronutrient composition and mineral content were stable during storage. Coriander had the highest mineral and fatsoluble vitamin content, while spearmint showed the best scores in the phenolic, flavonoid and antioxidant capacity assays. Vitamins and antioxidant capacity showed some variation during storage, with a differential behaviour of each compound according to the sample.

TV Recommendation and Personalization Systems: Integrating Broadcast and Video On-demand Services

he expansion of Digital Television and the convergence between conventional broadcasting and television over IP contributed to the gradual increase of the number of available channels and on demand video content. Moreover, the dissemination of the use of mobile devices like laptops, smartphones and tablets on everyday activities resulted in a shift of the traditional television viewing paradigm from the couch to everywhere, anytime from any device. Although this new scenario enables a great improvement in viewing experiences, it also brings new challenges given the overload of information that the viewer faces. Recommendation systems stand out as a possible solution to help a watcher on the selection of the content that best fits his/her preferences. This paper describes a web based system that helps the user navigating on broadcasted and online television content by implementing recommendations based on collaborative and content based filtering. The algorithms developed estimate the similarity between items and users and predict the rating that a user would assign to a particular item (television program, movie, etc.). To enable interoperability between different systems, programs characteristics (title, genre, actors, etc.) are stored according to the TV-Anytime standard. The set of recommendations produced are presented through a Web Application that allows the user to interact with the system based on the obtained recommendations.

Estudo e Implementação de Ferramentas Lean

Neste documento, apresenta-se o reflexo sobre o trabalho de estágio desenvolvido entre 17 de Fevereiro e 31 de Julho de 2014, nas instalações da Fábrica das Estruturas Metálicas da Faurecia, em São João da Madeira, num Projecto Final no âmbito de Implementação de Ferramentas Lean. O objetivo proposto foi a participação na procura e implementação de soluções, com vista à melhoria contínua do sistema de produção. Foi utilizado, para esse efeito, um vasto conjunto de ferramentas entre as quais os 5S, QRCI, Standardized Work, entre outras e amplamente empregues na indústria automóvel (e nesta empresa em particular), através do Sistema de Excelência Faurecia (FES), aplicado ao ramo de negócio onde está solidamente implantada esta multinacional de origem francesa. O período de tempo em que decorreu o estágio constituiu uma oportunidade única para o estagiário contactar com os problemas existentes no departamento de produção, num mercado tão concorrencial e competitivo como é o da indústria de componentes para automóveis. O presente trabalho de estágio apresenta duas vertentes distintas: uma de caráter interno à empresa e outra relativa aos fornecedores e clientes. Em termos internos, foi visível a batalha pela diminuição das variabilidades que surgem no plano da produção ao absorver grande parte do esforço dos agentes que trabalham na otimização dos processos. Externamente, observou-se a dificuldade em encontrar fornecedores adequados a satisfazer os aprovisionamentos da Faurecia, em quantidade e qualidade, e um elevado grau de exigência imposto por parte dos vários clientes. Por fim, este Projeto possibilitou a aplicação de conhecimentos adquiridos não só ao longo do curso como também durante a realização do estágio, o conhecimento da realidade industrial e o enriquecimento técnico e pessoal.

Virtual Power Player Using Demand Response to Deal with Unexpected Low Wind Power Generation

Demand response is assumed as an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets and of the increasing use of renewable-based energy sources. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed in this paper aims the minimization of the operation costs in a distribution network operated by a virtual power player that manages the available energy resources focusing on hour ahead re-scheduling. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs. Real time pricing is also applied. The proposed model is especially useful when actual and day ahead wind forecast differ significantly. Its application is illustrated in this paper implementing the characteristics of a real resources conditions scenario in a 33 bus distribution network with 32 consumers and 66 distributed generators.

Maximizing the Social Welfare of Virtual Power Players Operation in Case of Excessive Wind Power

The integration of growing amounts of distributed generation in power systems, namely at distribution networks level, has been fostered by energy policies in several countries around the world, including in Europe. This intensive integration of distributed, non-dispatchable, and natural sources based generation (including wind power) has caused several changes in the operation and planning of power systems and of electricity markets. Sometimes the available non-dispatchable generation is higher than the demand. This generation must be used; otherwise it is wasted if not stored or used to supply additional demand. New policies and market rules, as well as new players, are needed in order to competitively integrate all the resources. The methodology proposed in this paper aims at the maximization of the social welfare in a distribution network operated by a virtual power player that aggregates and manages the available energy resources. When facing a situation of excessive non-dispatchable generation, including wind power, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. This method is especially useful when actual and day-ahead resources forecast differ significantly. The distribution network characteristics and concerns are addressed by including the network constraints in the optimization model. The proposed methodology has been implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20.310 consumers and 548 distributed generators, some of them non-dispatchable and with must take contracts. The implemented scenario corresponds to a real day in Portuguese power system.