Constrained Consumption Shifting Management in the Distributed Energy Resources Scheduling Considering Demand Response

Demand response concept has been gaining increasing importance while the success of several recent implementations makes this resource benefits unquestionable. This happens in a power systems operation environment that also considers an intensive use of distributed generation. However, more adequate approaches and models are needed in order to address the small size consumers and producers aggregation, while taking into account these resources goals. The present paper focuses on the demand response programs and distributed generation resources management by a Virtual Power Player that optimally aims to minimize its operation costs taking the consumption shifting constraints into account. The impact of the consumption shifting in the distributed generation resources schedule is also considered. The methodology is applied to three scenarios based on 218 consumers and 4 types of distributed generation, in a time frame of 96 periods.

Optimization of Generation and Aggregated Consumption Shifting for Demand Response Programs Definition

The concept of demand response has drawing attention to the active participation in the economic operation of power systems, namely in the context of recent electricity markets and smart grid models and implementations. In these competitive contexts, aggregators are necessary in order to make possible the participation of small size consumers and generation units. The methodology proposed in the present paper aims to address the demand shifting between periods, considering multi-period demand response events. The focus is given to the impact in the subsequent periods. A Virtual Power Player operates the network, aggregating the available resources, and minimizing the operation costs. The illustrative case study included is based on a scenario of 218 consumers including generation sources.

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.

O século XXI e o ensino da língua estrangeira: a era do pós-moderno

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Planning and implementing a new assessment strategy using an e-learning platform

One of the most difficult issues of e-Learning is the students’ assessment. Being this an outstanding task regarding theoretical topics, it becomes even more challenging when the topics under evaluation are practical. ISCAP’s Information Systems Department is composed of about twenty teachers who have been for several years using an e-learning environment (at the moment Moodle 2.3) combined with traditional assessment. They are now planning and implementing a new e-learning assessment strategy. This effort was undertaken in order to evaluate a practical topic (the use of spreadsheets to solve management problems) common to shared courses of several undergraduate degree programs. The same team group is already experienced in the assessment of theoretical information systems topics using the b-learning platform. Therefore, this project works as an extension to previous experiences being the team aware of the additional difficulties due to the practical nature of the topics. This paper describes this project and presents two cycles of the action research methodology, used to conduct the research. The first cycle goal was to produce a database of questions. When it was implemented in order to be used with a pilot group of students, several problems were identified. Subsequently, the second cycle consisted in solving the identified problems preparing the database and all the players to a broader scope implementation. For each cycle, all the phases, its drawbacks and achievements are described. This paper suits all those who are or are planning to be in the process of shifting their assessment strategy from a traditional to one supported by an e-learning platform.

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.

Persistent organic pollutant levels in human visceral and subcutaneous adipose tissue in obese individuals - Depot differences and dysmetabolism implications

Background: The role of persistent organic pollutants (POPs) with endocrine disrupting activity in the aetiology of obesity and other metabolic dysfunctions has been recently highlighted. Adipose tissue (AT) is a common site of POPs accumulation where they can induce adverse effects on human health. Objectives: To evaluate the presence of POPs in human visceral (vAT) and subcutaneous (scAT) adipose tissue in a sample of Portuguese obese patients that underwent bariatric surgery, and assess their putative association with metabolic disruption preoperatively, as well as with subsequent body mass index (BMI) reduction. Methods: AT samples (n=189) from obese patients (BMI ≥35) were collected and the levels of 13 POPs were determined by gas chromatography with electron-capture detection (GC-ECD). Anthropometric and biochemical data were collected at the time of surgery. BMI variation was evaluated after 12 months and adipocyte size was measured in AT samples. Results: Our data confirm that POPs are pervasive in this obese population (96.3% of detection on both tissues), their abundance increasing with age (RS=0.310, p<0.01) and duration of obesity (RS=0.170, p<0.05). We observed a difference in AT depot POPs storage capability, with higher levels of ΣPOPs in vAT (213.9±204.2 compared to 155.1±147.4 ng/g of fat, p<0.001), extremely relevant when evaluating their metabolic impact. Furthermore, there was a positive correlation between POP levels and the presence of metabolic syndrome components, namely dysglycaemia and hypertension, and more importantly with cardiovascular risk (RS=0.277, p<0.01), with relevance for vAT (RS=0.315, p<0.01). Finally, we observed an interesting relation of higher POP levels with lower weight loss in older patients. Conclusion: Our sample of obese subjects allowed us to highlight the importance of POPs stored in AT on the development of metabolic dysfunction in a context of obesity, shifting the focus to their metabolic effects and not only for their recognition as environmental obesogens.

Aumentar as oportunidades de comunicação nos momentos de brincadeira - descrição de um programa de intervenção

Objetivo: Partindo da análise da literatura realizada, em que é salientada a ideia de que o desenvolvimento e aprendizagem ocorrem a partir das experiências e influência dos contextos em que as crianças estão incluídas e a partir das interações que estabelecem nesses mesmos contextos, pretende-se compreender, neste estudo, se partindo do contexto natural, com diferentes materiais e atores, é possível aumentar as oportunidades de comunicação e participação de uma criança com restrições ao nível da linguagem, nos momentos de jogo. Método: Foi delineado e implementado um programa de intervenção, num estabelecimento de ensino, na valência de pré-escolar, onde estiveram envolvidas uma criança de 4 anos com restrições ao nível da linguagem oral, o grupo de crianças em que estava incluída e a educadora do grupo. Para monitorização do programa e avaliação da sua eficácia realizou-se um pré e pós teste, onde foi definida a linha de base da criança. Ao longo do programa foram registados, a partir de uma grelha de observação da frequência dos atos comunicativos da criança, nas situações de jogo planificadas. Os comportamentos e modelagem realizada por parte educador, foram igualmente registados e analisados. Recorreu-se a realização de entrevistas semiestruturadas para a recolha de dados relativos à criança e perceção do educador. Resultados/Discussão: Os dados recolhidos demonstram um aumento significativo das tomadas de iniciativa verbal e alternância entre turnos, ao longo da intervenção por parte da criança alvo. A presença do adulto e dos pares parecem revelar-se como facilitador dos atos comunicativos da criança com restrições ao nível da linguagem

Heurísticas de pesquisa local para problemas de máquina única

O escalonamento é uma das decisões mais importantes no funcionamento de uma linha de produção. No âmbito desta dissertação foi realizada uma descrição do problema do escalonamento, identificando alguns métodos para a optimização dos problemas de escalonamento. Foi realizado um estudo ao caso do problema de máquina única através do teste de várias instâncias com o objectivo de minimizar o atraso pesado, aplicando uma Meta-Heurística baseada na Pesquisa Local e dois algoritmos baseados no SB. Os resultados obtidos reflectem que os algoritmos baseados no SB apresentaram resultados mais próximos do óptimo, em relação ao algoritmo baseado na PL. Os resultados obtidos permitem sustentar a hipótese de não existirem algoritmos específicos para os problemas de escalonamento. A melhor forma de encontrar uma solução de boa qualidade em tempo útil é experimentar diferentes algoritmos e comparar o desempenho das soluções obtidas.