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.

Dispatch of distributed Energy Resources to Provide Energy and Reserve in Smart Grids using a Particle Swarm Optimization Approach

The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The optimal schedule minimizes the operation costs and it is obtained using a particle swarm optimization approach, which is compared with a deterministic approach used as reference methodology. The proposed method is applied to a 33-bus distribution network with 32 medium voltage consumers and 66 distributed generation units.

Integration in MASCEM of the Joint Dispatch of Energy and Reserves Provided by Generation and Demand Resources

The provision of reserves in power systems is of great importance in what concerns keeping an adequate and acceptable level of security and reliability. This need for reserves and the way they are defined and dispatched gain increasing importance in the present and future context of smart grids and electricity markets due to their inherent competitive environment. This paper concerns a methodology proposed by the authors, which aims to jointly and optimally dispatch both generation and demand response resources to provide the amounts of reserve required for the system operation. Virtual Power Players are especially important for the aggregation of small size demand response and generation resources. The proposed methodology has been implemented in MASCEM, a multi agent system also developed at the authors’ research center for the simulation of electricity markets.

Demonstration of the Multi-Agent Simulator of Competitive Electricity Markets

Electricity markets are complex environments with very particular characteristics. A critical issue concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, performed so that the competitiveness could be increased, but with exponential implications in the increase of the complexity and unpredictability in those markets’ scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behavior. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This paper presents the Multi-Agent System for Competitive Electricity Markets (MASCEM) – a simulator based on multi-agent technology that provides a realistic platform to simulate electricity markets, the numerous negotiation opportunities and the participating entities.

Real Time Pricing Approaches to Deal With Unexpected Wind Power Variations

The use of renewables have been increased I several countries around the world, namely in Europe. The wind power is generally the larger renewable resource with very specific characteristics in what concerns its variability and the inherent impacts in the power systems and electricity markets operation. This paper focuses on the Portuguese context of renewables use, including wind power. The work here presented includes the use of a real time pricing methodology developed by the authors aiming the reduction of electricity consumption in the moments of unexpected low wind power. A more specific example of application of real time pricing is demonstrated for the minimization of the operation costs in a distribution network. 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.

Load Control Timescales Simulation in a Multi-Agent Smart Grid Platform

Environmental concerns and the shortage in the fossil fuel reserves have been potentiating the growth and globalization of distributed generation. Another resource that has been increasing its importance is the demand response, which is used to change consumers’ consumption profile, helping to reduce peak demand. Aiming to support small players’ participation in demand response events, the Curtailment Service Provider emerged. This player works as an aggregator for demand response events. The control of small and medium players which act in smart grid and micro grid environments is enhanced with a multi-agent system with artificial intelligence techniques – the MASGriP (Multi-Agent Smart Grid Platform). Using strategic behaviours in each player, this system simulates the profile of real players by using software agents. This paper shows the importance of modeling these behaviours for studying this type of scenarios. A case study with three examples shows the differences between each player and the best behaviour in order to achieve the higher profit in each situation.

Multiagent System Architecture for Short-term Operation of Integrated Microgrids

The forthcoming smart grids are comprised of integrated microgrids operating in grid-connected and isolated mode with local generation, storage and demand response (DR) programs. The proposed model is based on three successive complementary steps for power transaction in the market environment. The first step is characterized as a microgrid’s internal market; the second concerns negotiations between distinct interconnected microgrids; and finally, the third refers to the actual electricity market. The proposed approach is modeled and tested using a MAS framework directed to the study of the smart grids environment, including the simulation of electricity markets. This is achieved through the integration of the proposed approach with the MASGriP (Multi-Agent Smart Grid Platform) system.

Study of Load Curves Concerning the Influence of Socioeconomic and Cultural Issues

The increase of electricity demand in Brazil, the lack of the next major hydroelectric reservoirs implementation, and the growth of environmental concerns lead utilities to seek an improved system planning to meet these energy needs. The great diversity of economic, social, climatic, and cultural conditions in the country have been causing a more difficult planning of the power system. The work presented in this paper concerns the development of an algorithm that aims studying the influence of the issues mentioned in load curves. Focus is given to residential consumers. The consumption device with highest influence in the load curve is also identified. The methodology developed gains increasing importance in the system planning and operation, namely in the smart grids context.

Quantum-based Particle Swarm Optimization Application to Studies of Aggregated Consumption Shifting and Generation Scheduling in Smart Grids

Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.

Digital marketing strategies

Internship Report presented to Instituto de Contabilidade e Administração do Porto for the Master’s degree in Marketing Digital under the guidance of Dr. José Magalhães Author Note This internship was carried out under the Erasmus Program for college students and under the agreement between the sending institution, Instituto Superior de Contabilidade e Administração do Porto and the host company, eRise, located in Budapest, Hungary, under the guidance of Vilmos Schwarz.

A reconstrução tomográfica em SPECT com utilização dos novos métodos iterativos “WBR”: comparação com métodos analíticos

Os métodos utilizados pela Medicina moderna no âmbito da Imagem Molecular e na sua capacidade de diagnosticar a partir da “Função do Orgão” em vez da “Morfologia do Orgão”, vieram trazer á componente fundamental desta modalidade da Imagiologia Médica – A Medicina Nuclear – uma importância acrescida, que se tem traduzido num aumento significativo no recurso á sua utilização nas diferentes formas das suas aplicações clínicas. Para além dos aspectos meramente clínicos, que só por si seriam suficientes para ocupar várias dissertações como a presente; a própria natureza desta técnica de imagem, com a sua inerente baixa resolução e tempos longos de aquisição, vieram trazer preocupações acrescidas quanto ás questões relacionadas com a produtividade (nº de estudos a realizar por unidade de tempo); com a qualidade (aumento da resolução da imagem obtida) e, com os níveis de actividade radioactiva injectada nos pacientes (dose de radiação efectiva sobre as populações). Conhecidas que são então as limitações tecnológicas associadas ao desenho dos equipamentos destinados á aquisição de dados em Medicina Nuclear, que apesar dos avanços introduzidos, mantêm mais ou menos inalteráveis os conceitos base de funcionamento de uma Câmara Gama, imaginou-se a alteração significativa dos parâmetros de aquisição (tempo, resolução, actividade), actuando não ao nível das condições técnico-mecânicas dessa aquisição, mas essencialmente ao nível do pós-processamento dos dados adquiridos segundo os métodos tradicionais e que ainda constituem o estado da arte desta modalidade. Este trabalho tem então como objectivo explicar por um lado, com algum pormenor, as bases tecnológicas que desde sempre têm suportado o funcionamento dos sistemas destinados á realização de exames de Medicina Nuclear, mas sobretudo, apresentar as diferenças com os inovadores métodos, que aplicando essencialmente conhecimento (software), permitiram responder ás questões acima levantadas.

Desenvolvimento de Anticorpos Plásticos para um Biomarcador do Cancro

O trabalho descrito compreende o desenvolvimento de um anticorpo plástico (MIP, do inglês Molecularly Imprinted Polymer) para o antigénio carcinoembrionário (CEA, do inglês Carcinoembriogenic Antigen) e a sua aplicação na construção de dispositivos portáteis, de tamanho reduzido e de baixo custo, tendo em vista a monitorização deste biomarcador do cancro do colo-retal em contexto Point-of-Care (POC). O anticorpo plástico foi obtido por tecnologia de impressão molecular orientada, baseada em eletropolimerização sobre uma superfície condutora de vidro recoberto por FTO. De uma forma geral, o processo foi iniciado pela electropolimerização de anilina sobre o vidro, seguindo-se a ligação por adsorção do biomarcador (CEA) ao filme de polianilina, com ou sem monómeros carregados positivamente (Cloreto de vinilbenziltrimetilamónio, VB). A última fase consistiu na electropolimerização de o-fenilenodiamina (oPD) sobre a superfície, seguindo-se a remoção da proteína por clivagem de ligações peptídicas, com o auxílio de tripsina. A eficiência da impressão do biomarcador CEA no material polimérico foi controlada pela preparação de um material análogo, NIP (do inglês, Non-Imprinted Polymer), no qual nem a proteína nem o monómero VB estavam presentes. Os materiais obtidos foram caracterizados quimicamente por técnicas de Infravermelho com Transformada de Fourier (FTIR, do inglês, Fourier Transform Infrared Spectroscopy) e microscopia confocal de Raman. Os materiais sensores preparados foram entretanto incluídos em membranas poliméricas de Poli(cloreto de vinilo) (PVC) plastificado, para construção de sensores (biomiméticos) seletivos a CEA, tendo-se avaliado a resposta analítica em diferentes meios. Obteve-se uma boa resposta potenciométrica em solução tampão de Ácido 4-(2-hidroxietil)piperazina-1-etanosulfónico (HEPES), a pH 4,4, com uma membrana seletiva baseada em MIP preparada com o monómero carregado VB. O limite de deteção foi menor do que 42 pg/mL, observando-se um comportamento linear (versus o logaritmo da concentração) até 625 pg/mL, com um declive aniónico igual a -61,9 mV/década e r2>0,9974. O comportamento analítico dos sensores biomiméticos foi ainda avaliado em urina, tendo em vista a sua aplicação na análise de CEA em urina. Neste caso, o limite de deteção foi menor do que 38 pg/mL, para uma resposta linear até 625 pg/mL, com um declive de -38,4 mV/década e r2> 0,991. De uma forma geral, a aplicação experimental dos sensores biomiméticos evidenciou respostas exatas, sugerindo que os biossensores desenvolvidos prossigam estudos adicionais tendo em vista a sua aplicação em amostras de indivíduos doentes.

Artificial Intelligence in geospatial analysis: applications of self-organizing maps in the context of geographic information science.

A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Systems.

Validação de tecnologias de informação e comunicação no suporte a um sistema integrado de gestão orientado para o setor agroalimentar

Dissertação de Mestrado em Gestão Integrada da Qualidade, Ambiente e Segurança

HEART ANEURYSM IN CHAGAS' DISEASE

This prospective study on 41 autopsy collected human hearts concerns the "apical" lesion in Chagas' disease. Previous report did not show a correlation between lesion frequency and heart weight then discarding a vascular factor in its pathogenesis. The present paper involves other variables besides the heart weight to evaluate the relative coronary insufficiency. Distinct colored gel (green and red) injected through the capillary beds of both coronary arteries defined the extent of both vessels before separating the atria and removing the sub-epicardium fat. The Right Ventricle (RV) and Left Ventricle (LV) free walls furnished the RV/LV mass ratio. The myocardium mass colored green (right coronary artery - RC) and the whole Ventricular Weight (VW) determined the RC/VW mass ratio. The heart weight plus these mass ratios, graded and added, composed a score inversely proportional to the myocardium irrigation condition. It intended to be a more sensitive morphologic evaluation of the relative ischaemia to correlate to the apical lesion. This study showed a right deviation for the relative accumulated frequency of lesions plotted as a score function and a significant difference for higher scores in hearts with aneurysm. It suggests a ischaemic factor intervening in the apical lesion pathogenesis in Chagas' cardiopathy.