A fuzzy clustering approach to a demand response model

This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers’ consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed.

A fuzzy clustering approach to a demand response model

This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers’ consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed.

One-dimensional Model for Fluids of Third-grade in Tubes with Constant Radius

Our goal in this paper is to extend previous results obtained for Newtonian and secondgrade fluids to third-grade fluids in the case of an axisymmetric, straight, rigid and impermeable tube with constant cross-section using a one-dimensional hierarchical model based on the Cosserat theory related to fluid dynamics. In this way we can reduce the full threedimensional system of equations for the axisymmetric unsteady motion of a non-Newtonian incompressible third-grade fluid to a system of equations depending on time and on a single spatial variable. Some numerical simulations for the volume flow rate and the the wall shear stress are presented.

Avaliação do potencial de desenvolvimento em meninos e meninas dos 4 aos 6 anos

Todos nós, educadores, devemos prestar uma atenção aprofundada às potencialidades e inclinações das crianças que constituem os nossos grupos, para que possamos estimular e desenvolver as suas competências. É nesse sentido que desenvolvemos este Estudo Exploratório, com o qual se pretende analisar a adaptação da avaliação de potencial derivada da Teoria das Inteligência Múltiplas ao contexto da Educação Pré-Escolar, com o objectivo de contribuir para a qualidade da intervenção educativa, articulando conceitos como Inteligência, Competência, Potencial, Currículo, Avaliação Dinâmica. Participam no estudo 42 crianças que frequentam Jardim de Infância e integram dois grupos heterogéneos e as respectivas educadoras. A metodologia é de natureza qualitativa e quantitativa, apoiando-se na aplicação dos seguintes instrumentos: modelo de avaliação de potencial baseado no Spectrum; Inventário de Quociente Emocional, versão para crianças e jovens (Bar-On Emocional Quotient Inventory: Youth Version), adaptado a educadores por Candeias e Monteiro (2010); questionário de Caracterização do ambiente educativo - Sala de Actividades, adaptado por Candeias e lglésias (2010); Teste de Avaliação de Habilidades Cognitivas de Solução de Problemas lnterpessoais (EVHACOSPI). Os resultados obtidos sugerem a importância de uma avaliação do potencial, baseada na Teoria das Inteligências Múltiplas, que utiliza instrumentos adequados a cada um dos domínios do potencial e da competência humana propostos por H. Gardner: verbal, Lógico-Matemática, Musical, Corporal-Cinestésica, Visuo-espacial, lnterpessoal, Intrapessoal e Naturalista. Apontam também para o papel que este tipo de avaliação pode desempenhar na intervenção educativa que se objectiva intencional e fundamentada. ABSTRACT: Ali of us, educators, must pay a special attention to the potentialities and inclinations of children who make up our groups, so enabling the stimulation and development of their competences. ln this sense we developed this Exploratory Study, through which is intended to analyse the adaptation of potential evaluation derived from the Theory of Multiple intelligences in the range of Pre-School Education, aiming at the contribution for the educative intervention: articulating concepts such as Intelligence, Competence Potential, Curriculum, and Dynamic Evaluation. The study involves 42 children attending Infant School, belonging to two heterogeneous groups and respective educators. Methodology is of qualitative and quantitative nature, supported by the following instruments: evaluation model based on Spectrum; Inventory of Emotional Quotient, version for children and youths, adapted to educators by Candeias e Monteiro (2010), Query of Characterization of Educative Environment - Activities Room, adapted by Candeias e lglésias (2010); Test for Evaluation of Cognitive Abilities of Interpersonal Problems Solution. (EVHACOSPI). The results suggest the importance of an assessment, based on the Theory of Multiple Intelligence, which uses instruments fitted to each of the domains of human potential and competence proposed by H. Gardiner: Verbal, Logical-Maths, Musical, Corporal¬ Kinaesthetic, Visuo-Spatial, Interpersonal, Intrapersonal and Naturalist. They also refer to the role that this type of assessment can play in the educational intervention aiming to be intentional and grounded.

Classi cation of new electricity customers based on surveys and smart metering data

This paper proposes a process for the classifi cation of new residential electricity customers. The current state of the art is extended by using a combination of smart metering and survey data and by using model-based feature selection for the classifi cation task. Firstly, the normalized representative consumption profi les of the population are derived through the clustering of data from households. Secondly, new customers are classifi ed using survey data and a limited amount of smart metering data. Thirdly, regression analysis and model-based feature selection results explain the importance of the variables and which are the drivers of diff erent consumption profi les, enabling the extraction of appropriate models. The results of a case study show that the use of survey data signi ficantly increases accuracy of the classifi cation task (up to 20%). Considering four consumption groups, more than half of the customers are correctly classifi ed with only one week of metering data, with more weeks the accuracy is signifi cantly improved. The use of model-based feature selection resulted in the use of a signifi cantly lower number of features allowing an easy interpretation of the derived models.

How well can models predict changes in species distributions? A 13-year-old otter model revisited

Species distribution and ecological niche models are increasingly used in biodiversity management and conservation. However, one thing that is important but rarely done is to follow up on the predictive performance of these models over time, to check if their predictions are fulfilled and maintain accuracy, or if they apply only to the set in which they were produced. In 2003, a distribution model of the Eurasian otter (Lutra lutra) in Spain was published, based on the results of a country-wide otter survey published in 1998. This model was built with logistic regression of otter presence-absence in UTM 10 km2 cells on a diverse set of environmental, human and spatial variables, selected according to statistical criteria. Here we evaluate this model against the results of the most recent otter survey, carried out a decade later and after a significant expansion of the otter distribution area in this country. Despite the time elapsed and the evident changes in this species’ distribution, the model maintained a good predictive capacity, considering both discrimination and calibration measures. Otter distribution did not expand randomly or simply towards vicinity areas,m but specifically towards the areas predicted as most favourable by the model based on data from 10 years before. This corroborates the utility of predictive distribution models, at least in the medium term and when they are made with robust methods and relevant predictor variables.