Modified Discrete PSO to Increase the Delivered Energy Probability in Distribution energy Systems

This paper proposes a PSO based approach to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The statistical failure and repair data of distribution components is the main basis of the proposed methodology that uses a fuzzyprobabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A Modified Discrete PSO optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

Increase of the Delivered Power Probability in Distribution Networks using Pareto DC Programming

A methodology to increase the probability of delivering power to any load point through the identification of new investments in distribution network components is proposed in this paper. The method minimizes the investment cost as well as the cost of energy not supplied in the network. A DC optimization model based on mixed integer non-linear programming is developed considering the Pareto front technique in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power for any customer in the distribution system at the minimum possible cost for the system operator, while minimizing the energy not supplied cost. Thus, a multi-objective problem is formulated. To illustrate the application of the proposed methodology, the paper includes a case study which considers a 180 bus distribution network

Stress Ratio Effects on the fatigue Properties of Biaxially Loaded Tubular FRP-Specimens – Experimental Study

In this work tubular fiber reinforced specimens are tested for fatigue life. The specimens are biaxially loaded with tension and shear stresses, with a load angle β of 30° and 60° and a load ratio of R=0,1. There are many factors that affect fatigue life of a fiber reinforced material and the main goal of this work is to study the effects of load ratio R by obtaining S-N curves and compare them to the previous works (1). All the other parameters, such as specimen production, fatigue loading frequency and temperature, will be the same as for the previous tests. For every specimen, stiffness, temperature of the specimen during testing, crack counting and final fracture mode are obtained. Prior to testing, a study if the literature regarding the load ratio effects on composites fatigue life and with that review estimate the initial stresses to be applied in testing. In previous works (1) similar specimens have only been tested for a load ratio of R=-1 and therefore the behaviour of this tubular specimens for a different load ratio is unknown. All the data acquired will be analysed and compared to the previous works, emphasizing the differences found and discussing the possible explanations for those differences. The crack counting software, developed at the institute, has shown useful before, however different adjustments to the software parameters lead to different cracks numbers for the same picture, and therefore a better methodology will be discussed to improve the crack counting results. After the specimen’s failure, all the data will be collected and stored and fibre volume content for every specimen is also determinate. The number of tests required to make the S-N curves are obtained according to the existent standards. Additionally are also identified some improvements to the testing machine setup and to the procedures for future testing.

Investment optimization in distribution network based on fuzzy outage parameters

This paper presents a methodology that aims to increase the probability of delivering power to any load point of the electrical distribution system by identifying new investments in distribution components. The methodology is based on statistical failure and repair data of the distribution power system components and it uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A mixed integer non-linear optimization technique is developed to identify adequate investments in distribution networks components that allow increasing the availability level for any customer in the distribution system at minimum cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a real distribution network.

Increase of the delivered energy probability in DES using a fuzzy probabilistic modeling

The paper proposes a methodology to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The proposed methodology is based on statistical failure and repair data of distribution components and it uses a fuzzy-probabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A mixed integer nonlinear programming optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

Probability distribution functions

This technical report describes the PDFs which have been implemented to model the behaviours of certain parameters of the Repeater-Based Hybrid Wired/Wireless PROFIBUS Network Simulator (RHW2PNetSim) and Bridge-Based Hybrid Wired/Wireless PROFIBUS Network Simulator (BHW2PNetSim).

Numerical prediction of delamination onset in carbon/epoxy composites drilling

Despite the fact that their physical properties make them an attractive family of materials, composites machining can cause several damage modes such as delamination, fibre pull-out, thermal degradation, and others. Minimization of axial thrust force during drilling reduces the probability of delamination onset, as it has been demonstrated by analytical models based on linear elastic fracture mechanics (LEFM). A finite element model considering solid elements of the ABAQUS® software library and interface elements including a cohesive damage model was developed in order to simulate thrust forces and delamination onset during drilling. Thrust force results for delamination onset are compared with existing analytical models.

DC Fuzzy Multicriteria Approach to Increase the Probability of Delivering Power in Distribution Networks

This paper proposes a methodology to increase the probability of delivering power to any load point through the identification of new investments. The methodology uses a fuzzy set approach to model the uncertainty of outage parameters, load and generation. A DC fuzzy multicriteria optimization model considering the Pareto front and based on mixed integer non-linear optimization programming is developed in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power to all customers in the distribution network at the minimum possible cost for the system operator, while minimizing the non supplied energy cost. To illustrate the application of the proposed methodology, the paper includes a case study which considers an 33 bus distribution network.

A Modular Programming Approach for IoTBased Wireless Sensor Networks

Poster presented in 12th European Conference on Wireless Sensor Network (EWSN 2015). 9 to 11, Feb, 2015. Porto, Portugal.

The Interpretation of Verbal Probability Expressions Used in the IAS/IFRS: the auditors Rrgistered with the portuguese securities market commission

One of the main arguments in favour of the adoption and convergence with the international accounting standards published by the IASB (i.e. IAS/IFRS) is that these will allow comparability of financial reporting across countries. However, because these standards use verbal probability expressions (v.g. “probable”) when establishing the recognition and disclosure criteria for accounting elements, they require professional accountants to interpret and classify the probability of an outcome or event taking into account those terms and expressions and to best decide in terms of financial reporting. This paper reports part of a research we carried out on the interpretation of “in context” verbal probability expressions used in the IAS/IFRS by the auditors registered with the Portuguese Securities Market Commission, the Comissão do Mercado de Valores Mobiliários (CMVM). Our results provide support for the hypothesis that culture affects the CMVM registered auditors’ interpretation of verbal probability expressions through its influence on the accounting value (or attitude) of conservatism. Our results also suggest that there are significant differences in their interpretation of the term “probable”, which is consistent with literature in general. Since “probable” is the most frequent verbal probability expression used in the IAS/IFRS, this may have a negative impact on financial statements comparability.

Identificação das categorias mais relevantes da classificação internacional de funcionalidade, incapacidade e saúde para os terapeutas ocupacionais que exercem funções em unidades de cuidados continuados integrados

As constantes alterações das realidades sociais e epidemiológicas em associação ao envelhecimento populacional conduziram a insuficiências dos Sistemas Social e de Saúde que requerem uma reestruturação ao nível da adequação dos cuidados de saúde a prestar, pelo que, em resposta a esta necessidade foi criada a Rede Nacional de Cuidados Continuados Integrados. O presente estudo, de natureza qualitativa e carácter exploratório, tem como objectivo compreender a percepção dos Terapeutas Ocupacionais que trabalham em Unidades de Cuidados Continuados Integrados relativamente às categorias que considerem mais relevantes da Classificação Internacional da Funcionalidade, Incapacidade e Saúde, tendo sido aplicada uma entrevista a 8 profissionais a exercer funções em Unidades da Zona Norte, resultante de um processo de amostragem não probabilística e de conveniência. Como método de recolha de dados foi aplicada uma entrevista semi-estruturada, cujo guião foi construído após revisão bibliográfica, tendo por base as categorias definidas pelo modelo da Classificação Internacional da Funcionalidade, Incapacidade e Saúde e, posteriormente, analisado por um painel de peritos, tendo-se procedido à realização de uma entrevista piloto a um elemento, sem que esta contasse para a análise. A partir da análise das entrevistas realizadas procedemos à identificação das unidades de significado, tendo os conceitos sido ligados às categorias da Classificação que o representam de uma forma mais adequada, de acordo com as linking rules, tendo sido identificadas as categorias mais relevantes para os Terapeutas Ocupacionais a exercer funções em Unidades de Cuidados Continuados Integrados. Com a realização deste estudo, que pretende ser um primeiro passo para a criação de um futuro Core Set em Cuidados Continuados, foi-nos possível verificar que o maior número de categorias foram observadas no componente Actividades e Participação, tendo sido contabilizadas 70 (40,7%). Por outro lado, o componente Estruturas do corpo é o que integra menor número, contando com 19 categorias (11,05%). Assim, pensamos que a criação de um Core Set em Cuidados Continuados poderá beneficiar e facilitar a comunicação entre os profissionais destas equipas. No entanto, é importante ressalvar que a terminologia desta Classificação deverá ser utilizada de uma forma concertada com a linguagem específica da Terapia Ocupacional. Palavras-chave: Classificação Internacional da Funcionalidade, Incapacidade e Saúde, Core Set, Terapeutas Ocupacionais, Unidades de Cuidados Continuados Integrados.

ANN-Based LMP forecasting in a distribution network with large penetration of DG

In recent years, power systems have experienced many changes in their paradigm. The introduction of new players in the management of distributed generation leads to the decentralization of control and decision-making, so that each player is able to play in the market environment. In the new context, it will be very relevant that aggregator players allow midsize, small and micro players to act in a competitive environment. In order to achieve their objectives, virtual power players and single players are required to optimize their energy resource management process. To achieve this, it is essential to have financial resources capable of providing access to appropriate decision support tools. As small players have difficulties in having access to such tools, it is necessary that these players can benefit from alternative methodologies to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), and intended to support smaller players. In this case the present methodology uses a training set that is created using energy resource scheduling solutions obtained using a mixed-integer linear programming (MIP) approach as the reference optimization methodology. The trained network is used to obtain locational marginal prices in a distribution network. The main goal of the paper is to verify the accuracy of the ANN based approach. Moreover, the use of a single ANN is compared with the use of two or more ANN to forecast the locational marginal price.

Energy resource scheduling in a real distribution network managed by several virtual power players

Smart Grids (SGs) appeared as the new paradigm for power system management and operation, being designed to integrate large amounts of distributed energy resources. This new paradigm requires a more efficient Energy Resource Management (ERM) and, simultaneously, makes this a more complex problem, due to the intensive use of distributed energy resources (DER), such as distributed generation, active consumers with demand response contracts, and storage units. This paper presents a methodology to address the energy resource scheduling, considering an intensive use of distributed generation and demand response contracts. A case study of a 30 kV real distribution network, including a substation with 6 feeders and 937 buses, is used to demonstrate the effectiveness of the proposed methodology. This network is managed by six virtual power players (VPP) with capability to manage the DER and the distribution network.

Study of distribution network demand response events in the Portuguese system

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. Grid operators and utilities are taking new initiatives, recognizing the value of demand response for grid reliability and for the enhancement of organized spot markets’ efficiency. This paper proposes a methodology for the selection of the consumers that participate in an event, which is the responsibility of the Portuguese transmission network operator. The proposed method is intended to be applied in the interruptibility service implemented in Portugal, in convergence with Spain, in the context of the Iberian electricity market. This method is based on the calculation of locational marginal prices (LMP) which are used to support the decision concerning the consumers to be schedule for participation. The proposed method has been computationally implemented and its application is illustrated in this paper using a 937 bus distribution network with more than 20,000 consumers.

Dynamic artificial neural network for electricity market prices forecast

This paper presents an artificial neural network applied to the forecasting of electricity market prices, with the special feature of being dynamic. The dynamism is verified at two different levels. The first level is characterized as a re-training of the network in every iteration, so that the artificial neural network can able to consider the most recent data at all times, and constantly adapt itself to the most recent happenings. The second level considers the adaptation of the neural network���s execution time depending on the circumstances of its use. The execution time adaptation is performed through the automatic adjustment of the amount of data considered for training the network. This is an advantageous and indispensable feature for this neural network���s integration in ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to the market negotiating players of MASCEM (Multi-Agent Simulator of Competitive Electricity Markets).