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.

A user-centered interface for scheduling problem definition

In this paper we present a user-centered interface for a scheduling system. The purpose of this interface is to provide graphical and interactive ways of defining a scheduling problem. To create such user interface an evaluation-centered user interaction development method was adopted: the star life cycle. The created prototype comprises the Task Module and the Scheduling Problem Module. The first one allows users to define a sequence of operations, i.e., a task. The second one enables a scheduling problem definition, which consists in a set of tasks. Both modules are equipped with a set of real time validations to assure the correct definition of the necessary data input for the scheduling module of the system. The usability evaluation allowed us to measure the ease of interaction and observe the different forms of interaction provided by each participant, namely the reactions to the real time validation mechanism.

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.

Using data mining techniques to support DR programs definition in smart grids

In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.

Demand response programs definition supported by clustering and classification techniques

The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

Bid definition method for electricity markets based on an adaptive multiagent system

Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. Each agent has the knowledge about a different method for defining a strategy for playing in the market, the main agent chooses the best among all those, and provides it to the market player that requests, to be used in the market. This paper also presents a methodology to manage the efficiency/effectiveness balance of this method, to guarantee that the degradation of the simulator processing times takes the correct measure.

An integrated system to support electricity tariff contract definition

This paper presents an integrated system that helps both retail companies and electricity consumers on the definition of the best retail contracts and tariffs. This integrated system is composed by a Decision Support System (DSS) based on a Consumer Characterization Framework (CCF). The CCF is based on data mining techniques, applied to obtain useful knowledge about electricity consumers from large amounts of consumption data. This knowledge is acquired following an innovative and systematic approach able to identify different consumers’ classes, represented by a load profile, and its characterization using decision trees. The framework generates inputs to use in the knowledge base and in the database of the DSS. The rule sets derived from the decision trees are integrated in the knowledge base of the DSS. The load profiles together with the information about contracts and electricity prices form the database of the DSS. This DSS is able to perform the classification of different consumers, present its load profile and test different electricity tariffs and contracts. The final outputs of the DSS are a comparative economic analysis between different contracts and advice about the most economic contract to each consumer class. The presentation of the DSS is completed with an application example using a real data base of consumers from the Portuguese distribution company.

Melhoria do processo produtivo numa metalomecânica

Este projeto foi realizado na Empresa Fernando Jesus Mourão & Cª Lda, durante o ano de 2012, e teve como objetivo a melhoria do processo produtivo. Esta melhoria assentou na identificação de possíveis pontos de desperdício, no estudo e avaliação de soluções e por fim na definição de propostas de melhoria globais que visem ajustar o fluxo do processo produtivo à procura e simultaneamente minimizar custos operacionais. De forma a atingir estas metas, foi feito um levantamento exaustivo do processo produtivo e das respetivas operações. Neste estudo, apesar do elevado numero de oportunidades de melhoria, foi possível identificar duas áreas que se revelaram criticas e fundamentais para a introdução da filosofia de melhoria continua na empresa. Estas áreas que são o objeto de estudo desta dissertação são: o corte laser e a organização do pavilhão 3. Uma vez identificados as áreas críticas, procedeu-se a uma análise e definição das ações de melhoria a empreender de modo a melhorar o fluxo produtivo e a sua organização, e simultaneamente reduzir custos. Na área de corte laser procurou-se implementar a filosofia de produção “Lean” nomeadamente através da ferramenta de análise PDCA (Plan-Do-Check-Act), como ferramenta auxiliar do estudo para elaborar um plano de ação, implementar as ações, analisar os resultados e procurar a manutenção dos mesmos. Na intervenção do pavilhão 3 foi usada a técnica dos 5S para organizar e agilizar o funcionamento do mesmo. Todo o trabalho assenta na filosofia Lean e nos seus princípios, tendo-se por isso utilizado as ferramentas especificas Lean na concretização das tarefas executadas no seu âmbito. Para medir os resultados, antes e depois das ações implementadas, foi utilizada o indicador de eficiência (Overall Equipment Effectiveness) para o caso do processo de corte laser. Após a implementação das medidas definidas no processo de corte laser foi possível observar uma melhoria do indicador OEE de cerca de 20 por cento. Por outro lado as melhorias implementadas através da ferramenta dos 5S no pavilhão 3, trouxe ganhos visíveis de aumento de produtividade que beneficiaram o tempo de resposta da empresa.

Extending the learning object definition to represent programming problems

The present generation of eLearning platforms values the interchange of learning objects standards. Nevertheless, for specialized domains these standards are insufficient to fully describe all the assets, especially when they are used as input for other eLearning services. To address this issue we extended an existing learning objects standard to the particular requirements of a specialized domain, namely the automatic evaluation of programming problems. The focus of this paper is the definition of programming problems as learning objects. We introduce a new schema to represent metadata related to automatic evaluation that cannot be conveniently represented using existing standards, such as: the type of automatic evaluation; the requirements of the evaluation engine; or the roles of different assets - tests cases, program solutions, etc. This new schema is being used in an interoperable repository of learning objects, called crimsonHex.

Conditional probability applied to the definition of limestone geochemical facies: A new Methodological Approach

A new method, based on linear correlation and phase diagrams was successfully developed for processes like the sedimentary process, where the deposition phase can have different time duration - represented by repeated values in a series - and where the erosion can play an important rule deleting values of a series. The sampling process itself can be the cause of repeated values - large strata twice sampled - or deleted values: tiny strata fitted between two consecutive samples. What we developed was a mathematical procedure which, based upon the depth chemical composition evolution, allows the establishment of frontiers as well as the periodicity of different sedimentary environments. The basic tool isn't more than a linear correlation analysis which allow us to detect the existence of eventual evolution rules, connected with cyclical phenomena within time series (considering the space assimilated to time), with the final objective of prevision. A very interesting discovery was the phenomenon of repeated sliding windows that represent quasi-cycles of a series of quasi-periods. An accurate forecast can be obtained if we are inside a quasi-cycle (it is possible to predict the other elements of the cycle with the probability related with the number of repeated and deleted points). We deal with an innovator methodology, reason why it's efficiency is being tested in some case studies, with remarkable results that shows it's efficacy. Keywords: sedimentary environments, sequence stratigraphy, data analysis, time-series, conditional probability.

Demand Response Programs Definition Using Demand Price Elasticity to Define Consumers Aggregation for an Improved Remuneration Structure

The positioning of the consumers in the power systems operation has been changed in the recent years, namely due to the implementation of competitive electricity markets. Demand response is an opportunity for the consumers’ participation in electricity markets. Smart grids can give an important support for the integration of demand response. The methodology proposed in the present paper aims to create an improved demand response program definition and remuneration scheme for aggregated resources. The consumers are aggregated in a certain number of clusters, each one corresponding to a distinct demand response program, according to the economic impact of the resulting remuneration tariff. The knowledge about the consumers is obtained from its demand price elasticity values. The illustrative case study included in the paper is based on a 218 consumers’ scenario.

Definition of Distribution Network Tariffs Considering Distribution Generation and Demand Response

The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the whole system. The work presented in this paper comprises a methodology able to define the cost allocation in distribution networks considering large integration of DG and DR resources. The proposed methodology is divided into three phases and it is based on an AC Optimal Power Flow (OPF) including the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity.

Remuneration Structure Definition for Distributed Generation Units and Demand Response Participants Aggregation

The implementation of competitive electricity markets has changed the consumers’ and distributed generation position power systems operation. The use of distributed generation and the participation in demand response programs, namely in smart grids, bring several advantages for consumers, aggregators, and system operators. The present paper proposes a remuneration structure for aggregated distributed generation and demand response resources. A virtual power player aggregates all the resources. The resources are aggregated in a certain number of clusters, each one corresponding to a distinct tariff group, according to the economic impact of the resulting remuneration tariff. The determined tariffs are intended to be used for several months. The aggregator can define the periodicity of the tariffs definition. The case study in this paper includes 218 consumers, and 66 distributed generation units.

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.

Melhoria do Processo Produtivo da Pietec Através das Ferramentas Kaizen

Esta Tese de Mestrado foi realizada na empresa Pietec Cortiças S.A.. A empresa Pietec Cortiças S.A. é a unidade industrial responsável pela produção de rolhas técnicas de cortiça do Grupo Piedade. O objetivo desta tese prende-se com a melhoria do processo produtivo de uma das suas secções, a secção da Marcação. Esta secção é responsável pela marcação da superfície da rolha, pela aplicação do tratamento de superfície e pelo embalamento das rolhas. A otimização do processo da secção de Marcação, na qualidade de última secção do processo produtivo, permitirá à empresa obter vantagens competitivas. De forma a atingir o objetivo proposto, foi realizado um levantamento exaustivo do processo produtivo e das respetivas operações. Esta análise permitiu a identificação dos possíveis pontos de desperdício, a sua avaliação e a definição de possíveis melhorias que visam o aumento de produtividade e a redução do número de produtos não conformes. Uma vez identificados os pontos críticos do processo, procedeu-se à definição das ações de melhoria a implementar de forma a melhorar o processo produtivo. As ações tomadas assentam na filosofia Lean e nos seus princípios, utilizando-se algumas das ferramentas desta filosofia para concretizar os objetivos traçados. A ferramenta de análise Plan-Do-Check-Act (PDCA) foi a ferramenta base do projeto, acompanhando na elaboração do plano de ação, na implementação das ferramentas 5S e Single Minute Exchange of Die (SMED), na verificação dos resultados e no plano de manutenção das melhorias alcançadas. Após a implementação das medidas definidas no processo de marcação da superfície das rolhas, foi mensurada uma melhoria de 23 % no tempo médio de setup da máquina de marcação. Esta melhoria global foi alcançada através de intervenções no processo de vazamento do circuito da máquina de marcação, no procedimento de armazenamento dos moldes de marcação e na alteração dos mecanismos de ajuste da máquina de marcar e de orientar. No processo de embalamento das rolhas, as medidas implementadas produziram um aumento de 1,7 % no número de rolhas produzidas e uma redução do número de rolhas não conformes de 3,6 %. Os resultados obtidos no projeto demonstram que é possível continuar a melhorar o estado atual dos processos. Constatou-se ainda que, com a adoção de ferramentas de análise e de proposta de melhoria adequadas, é possível atuar sobre os processos e obter melhorias a curto prazo, sem que para isso seja necessário efetuar grandes investimentos.