Knowledge extraction from medium voltage load diagrams to support the definition of electrical tariffs

With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.

Voltage Magnitude Analysis Considering Load Curtailment Minimization in Sub-Transmission Networks with Distributed Generators

Most of distribution generation and smart grid research works are dedicated to the study of network operation parameters, reliability among others. However, many of this research works usually uses traditional test systems such as IEEE test systems. This work proposes a voltage magnitude study in presence of fault conditions considering the realistic specifications found in countries like Brazil. The methodology considers a hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzyprobabilistic models and a remedial action algorithm which is based on optimal power flow. To illustrate the application of the proposed method, the paper includes a case study that considers a real 12 bus sub-transmission network.

Voltage Analysis and Load Curtailment Minimization in Sub-transmission Networks with Distributed Generation

Most of distributed generation and smart grid research works are dedicated to network operation parameters studies, reliability, etc. However, many of these works normally uses traditional test systems, for instance, IEEE test systems. This paper proposes voltage magnitude and reliability studies in presence of fault conditions, considering realistic conditions found in countries like Brazil. The methodology considers a hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models and a remedial action algorithm which is based on optimal power flow. To illustrate the application of the proposed method, the paper includes a case study that considers a real 12-bus sub-transmission network.

Relatório de estágio. Terapia manual ortopédica

Objectivo: Descrever a intervenção em fisioterapia aplicada num paciente com o diagnóstico de entorse da Tíbio-társica de grau III. Participantes e Métodos: Paciente que em 1 de Dezembro de 2009 na sequência de uma disputa de bola, sofreu uma entorse da tíbio-társica. Iniciou fisioterapia a 4 de Janeiro de 2010, tendo sido utilizadas para o tratamento técnicas de Mulligan, nomeadamente MWM, mobilização articular, reforço muscular e treino proprioceptivo. O tratamento foi realizado diariamente durante 6 semanas. Resultados: Após a aplicação das técnicas de Mulligan MWM na 1ªsemana, o perónio encontra-se devidamente reposicionado, no entanto o calcâneo ainda se encontra posteriorizado. No fim da 2ªsemana, a amplitude articular aumentou significativamente, aproximando-se dos valores do membro contralateral, verificouse um ganho de força muscular progressivo. Na 3ª e 4ª semana progrediu-se o tratamento em termos de fortalecimento muscular e treino proprioceptivo. Na 5ª semana apresentava amplitudes de movimento de 17º de dorsiflexão, 43º de flexãoplantar, 15º de eversão e 18º de inversão. Relativamente à força, o músculo tibial anterior apresentava um grau 5 de força, longo e curto peronial e flexores plantares grau 4+. No fim de 6 semanas, terminada a sua recuperação encontrava-se sem qualquer limitação funcional, igual força muscular bilateral e proprioceptividade normal. Conclusão: Foi salientado o processo de raciocínio clínico desenvolvido pelo fisioterapeuta ao longo das 6 semanas de intervenção: a recolha e interpretação dos dados da história, levantamento das primeiras hipóteses, testes dessas hipóteses no exame objectivo, estabelecimento de um diagnóstico funcional e construção e implementação de um plano de intervenção com a colaboração do utente que permitiram uma recuperação funcional que foi de encontro aos objectivos traçados.

Definition of MV Load Diagrams via Weighted Evidence Accumulation Clustering using Subsampling

A definition of medium voltage (MV) load diagrams was made, based on the data base knowledge discovery process. Clustering techniques were used as support for the agents of the electric power retail markets to obtain specific knowledge of their customers’ consumption habits. Each customer class resulting from the clustering operation is represented by its load diagram. The Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) were applied to an electricity consumption data from a utility client’s database in order to form the customer’s classes and to find a set of representative consumption patterns. The WEACS approach is a clustering ensemble combination approach that uses subsampling and that weights differently the partitions in the co-association matrix. As a complementary step to the WEACS approach, all the final data partitions produced by the different variations of the method are combined and the Ward Link algorithm is used to obtain the final data partition. Experiment results showed that WEACS approach led to better accuracy than many other clustering approaches. In this paper the WEACS approach separates better the customer’s population than Two-step clustering algorithm.

Data mining contributions to characterize MV consumers and to improve the suppliers-consumers settlements

This paper deals with the establishment of a characterization methodology of electric power profiles of medium voltage (MV) consumers. The characterization is supported on the data base knowledge discovery process (KDD). Data Mining techniques are used with the purpose of obtaining typical load profiles of MV customers and specific knowledge of their customers’ consumption habits. In order to form the different customers’ classes and to find a set of representative consumption patterns, a hierarchical clustering algorithm and a clustering ensemble combination approach (WEACS) are used. Taking into account the typical consumption profile of the class to which the customers belong, new tariff options were defined and new energy coefficients prices were proposed. Finally, and with the results obtained, the consequences that these will have in the interaction between customer and electric power suppliers are analyzed.

Energy resource scheduling considering reactive power management

The reactive power management is an important task in future power systems. The control of reactive power allows the increase of distributed energy resources penetration as well as the optimal operation of distribution networks. Currently, the control of reactive power is only controlled in large power units and in high and very high voltage substations. In this paper a reactive power control in smart grids paradigm is proposed, considering the management of distributed energy resources and of the distribution network by an aggregator namely Virtual Power Player (VPP).