Demand Response Programs Design and Use Considering Intensive Penetration of Distributed Generation

Further improvements in demand response programs implementation are needed in order to take full advantage of this resource, namely for the participation in energy and reserve market products, requiring adequate aggregation and remuneration of small size resources. The present paper focuses on SPIDER, a demand response simulation that has been improved in order to simulate demand response, including realistic power system simulation. For illustration of the simulator’s capabilities, the present paper is proposes a methodology focusing on the aggregation of consumers and generators, providing adequate tolls for the demand response program’s adoption by evolved players. The methodology proposed in the present paper focuses on a Virtual Power Player that manages and aggregates the available demand response and distributed generation resources in order to satisfy the required electrical energy demand and reserve. The aggregation of resources is addressed by the use of clustering algorithms, and operation costs for the VPP are minimized. The presented case study is based on a set of 32 consumers and 66 distributed generation units, running on 180 distinct operation scenarios.

Cost allocation model for distribution networks considering high penetration of distributed energy resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). The proposed model includes three distinct phases of operation. The first phase of the model consists in an economic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen's and Bialek's tracing algorithms are used and compared to evaluate the impact of each resource in the network. Finally, the MW-mile method is used in the third phase of the proposed model. A distribution network of 33 buses with large penetration of DER is used to illustrate the application of the proposed model.

A Communication Intervention for Training Southern European Oncologists to Recognize Psychosocial Morbidity in Cancer. I - Development of the Model and Preliminary Results on Physicians' Satisfaction

BACKGROUND: The detection of psychosocial distress is a significant communication problem in Southern Europe and other countries. Work in this area is hampered by a lack of data. Because not much is known about training aimed at improving the recognition of psychosocial disorders in cancer patients, we developed a basic course model for medical oncology professionals. METHODS: A specific educational and experiential model (12 hours divided into 2 modules) involving formal teaching (ie, journal articles, large-group presentations), practice in small groups (ie, small-group exercises and role playing), and discussion in large groups was developed with the aim of improving the ability of oncologists to detect emotional disturbances in cancer patients (ie, depression, anxiety, and adjustment disorders). RESULTS: A total of 30 oncologists from 3 Southern European countries (Italy, Portugal, and Spain) participated in the workshop. The training course was well accepted by most participants who expressed general satisfaction and a positive subjective perception of the utility of the course for clinical practice. Of the total participants, 28 physicians (93.3%) thought that had they been exposed to this material sooner, they would have incorporated the techniques received in the workshop into their practices; 2 participants stated they would likely have done so. Half of the doctors (n = 15) believed that their clinical communication techniques were improved by participating in the workshop, and the remaining half thought that their abilities to communicate with cancer patients had improved. CONCLUSIONS: This model is a feasible approach for oncologists and is easily applicable to various oncology settings. Further studies will demonstrate the effectiveness of this method for improving oncologists skills in recognizing emotional disorders in their patients with cancer.

Constraint-based verification of imperative programs

work presented in the context of the European Master’s program in Computational Logic, as the partial requirement for obtaining Master of Science degree in Computational Logic

Middleware for Large-scale Distributed Systems

Nos últimos anos o aumento exponencial da utilização de dispositivos móveis e serviços disponibilizados na “Cloud” levou a que a forma como os sistemas são desenhados e implementados mudasse, numa perspectiva de tentar alcançar requisitos que até então não eram essenciais. Analisando esta evolução, com o enorme aumento dos dispositivos móveis, como os “smartphones” e “tablets” fez com que o desenho e implementação de sistemas distribuidos fossem ainda mais importantes nesta área, na tentativa de promover sistemas e aplicações que fossem mais flexíveis, robutos, escaláveis e acima de tudo interoperáveis. A menor capacidade de processamento ou armazenamento destes dispositivos tornou essencial o aparecimento e crescimento de tecnologias que prometem solucionar muitos dos problemas identificados. O aparecimento do conceito de Middleware visa solucionar estas lacunas nos sistemas distribuidos mais evoluídos, promovendo uma solução a nível de organização e desenho da arquitetura dos sistemas, ao memo tempo que fornece comunicações extremamente rápidas, seguras e de confiança. Uma arquitetura baseada em Middleware visa dotar os sistemas de um canal de comunicação que fornece uma forte interoperabilidade, escalabilidade, e segurança na troca de mensagens, entre outras vantagens. Nesta tese vários tipos e exemplos de sistemas distribuídos e são descritos e analisados, assim como uma descrição em detalhe de três protocolos (XMPP, AMQP e DDS) de comunicação, sendo dois deles (XMPP e AMQP) utilzados em projecto reais que serão descritos ao longo desta tese. O principal objetivo da escrita desta tese é demonstrar o estudo e o levantamento do estado da arte relativamente ao conceito de Middleware aplicado a sistemas distribuídos de larga escala, provando que a utilização de um Middleware pode facilitar e agilizar o desenho e desenvolvimento de um sistema distribuído e traz enormes vantagens num futuro próximo.

Distributed processing of large remote sensing images using MapReduce - A case of Edge Detection

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Probabilistic constraint reasoning

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Informática, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

A modular distributed transactional memory framework

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Distributed replicated macro-components

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Partial replication in distributed software transactional memory

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Life (dis)satisfaction and the decision to migrate: Evidence from Central and Eastern Europe

This paper provides empirical evidence of the impact of life satisfaction on the individual intention to migrate. The impacts of individual characteristics and of country macroeconomic variables on the intention to migrate are analyzed jointly. Differently from other studies, we allow for life satisfaction to serve as a mediator between macroeconomic variables and the intention to migrate. Using the Eurobarometer Survey for 27 Central Eastern European (CEE) and Western European (non-CEE) countries, we find that people have a higher intention to migrate when dissatisfied with life. The socio-economic variables and macroeconomic conditions have an effect on the intention to migrate indirectly through life satisfaction. The impact of life satisfaction on the intention to migrate for middle-aged individuals with past experience of migration, low level of education, and with a low or average income from urban areas is higher in CEE countries than in non-CEE countries.

A distributed platform for the volunteer execution of workflows on a local area network

Thesis submitted in fulfilment of the requirements for the Degree of Master of Science in Computer Science

Constraint-based modelling of mixed microbial populations: Application to polyhydroxyalkanoates production

Dissertação para obtenção do Grau de Doutor em Engenharia Química e Bioquímica

Petri net based development of globally-asynchronous locally-synchronous distributed embedded systems

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores

Probabilistic constraint reasoning with Monte Carlo integration to robot localization

This work studies the combination of safe and probabilistic reasoning through the hybridization of Monte Carlo integration techniques with continuous constraint programming. In continuous constraint programming there are variables ranging over continuous domains (represented as intervals) together with constraints over them (relations between variables) and the goal is to find values for those variables that satisfy all the constraints (consistent scenarios). Constraint programming “branch-and-prune” algorithms produce safe enclosures of all consistent scenarios. Special proposed algorithms for probabilistic constraint reasoning compute the probability of sets of consistent scenarios which imply the calculation of an integral over these sets (quadrature). In this work we propose to extend the “branch-and-prune” algorithms with Monte Carlo integration techniques to compute such probabilities. This approach can be useful in robotics for localization problems. Traditional approaches are based on probabilistic techniques that search the most likely scenario, which may not satisfy the model constraints. We show how to apply our approach in order to cope with this problem and provide functionality in real time.