Decision Support Concerning Demand Response Programs Design and Use – A Conceptual Framework and Simulation Tool

Demand response can play a very relevant role in the context of power systems with an intensive use of distributed energy resources, from which renewable intermittent sources are a significant part. More active consumers participation can help improving the system reliability and decrease or defer the required investments. Demand response adequate use and management is even more important in competitive electricity markets. However, experience shows difficulties to make demand response be adequately used in this context, showing the need of research work in this area. The most important difficulties seem to be caused by inadequate business models and by inadequate demand response programs management. This paper contributes to developing methodologies and a computational infrastructure able to provide the involved players with adequate decision support on demand response programs and contracts design and use. The presented work uses DemSi, a demand response simulator that has been developed by the authors to simulate demand response actions and programs, which includes realistic power system simulation. It includes an optimization module for the application of demand response programs and contracts using deterministic and metaheuristic approaches. The proposed methodology is an important improvement in the simulator while providing adequate tools for demand response programs adoption by the involved players. A machine learning method based on clustering and classification techniques, resulting in a rule base concerning DR programs and contracts use, is also used. A case study concerning the use of demand response in an incident situation is presented.

TV Recommendation and Personalization Systems: Integrating Broadcast and Video On-demand Services

he expansion of Digital Television and the convergence between conventional broadcasting and television over IP contributed to the gradual increase of the number of available channels and on demand video content. Moreover, the dissemination of the use of mobile devices like laptops, smartphones and tablets on everyday activities resulted in a shift of the traditional television viewing paradigm from the couch to everywhere, anytime from any device. Although this new scenario enables a great improvement in viewing experiences, it also brings new challenges given the overload of information that the viewer faces. Recommendation systems stand out as a possible solution to help a watcher on the selection of the content that best fits his/her preferences. This paper describes a web based system that helps the user navigating on broadcasted and online television content by implementing recommendations based on collaborative and content based filtering. The algorithms developed estimate the similarity between items and users and predict the rating that a user would assign to a particular item (television program, movie, etc.). To enable interoperability between different systems, programs characteristics (title, genre, actors, etc.) are stored according to the TV-Anytime standard. The set of recommendations produced are presented through a Web Application that allows the user to interact with the system based on the obtained recommendations.

Fractional Dynamics of Computer Virus Propagation

We propose a fractional model for computer virus propagation. The model includes the interaction between computers and removable devices. We simulate numerically the model for distinct values of the order of the fractional derivative and for two sets of initial conditions adopted in the literature. We conclude that fractional order systems reveal richer dynamics than the classical integer order counterpart. Therefore, fractional dynamics leads to time responses with super-fast transients and super-slow evolutions towards the steady-state, effects not easily captured by the integer order models.

Optimizing memory transactions for large-scale programs

Even though Software Transactional Memory (STM) is one of the most promising approaches to simplify concurrent programming, current STM implementations incur significant overheads that render them impractical for many real-sized programs. The key insight of this work is that we do not need to use the same costly barriers for all the memory managed by a real-sized application, if only a small fraction of the memory is under contention lightweight barriers may be used in this case. In this work, we propose a new solution based on an approach of adaptive object metadata (AOM) to promote the use of a fast path to access objects that are not under contention. We show that this approach is able to make the performance of an STM competitive with the best fine-grained lock-based approaches in some of the more challenging benchmarks. (C) 2015 Elsevier Inc. All rights reserved.

Static detection of anomalies in transactional memory programs

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática

Consumers Performance Evaluation of the Participation in Demand Response Programs Using Baseline Methods

Demand response has gain increasing importance in the context of competitive electricity markets environment. The use of demand resources is also advantageous in the context of smart grid operation. In addition to the need of new business models for integrating demand response, adequate methods are necessary for an accurate determination of the consumers’ performance evaluation after the participation in a demand response event. The present paper makes a comparison between some of the existing baseline methods related to the consumers’ performance evaluation, comparing the results obtained with these methods and also with a method proposed by the authors of the paper. A case study demonstrates the application of the referred methods to real consumption data belonging to a consumer connected to a distribution network.

Incentive-based demand response programs designed by asset-light retailers for day-ahead market

Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand.

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.

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.

Consumption Management of Air Conditioning Devices for the Participation in Demand Response Programs

Demand Response has been taking over the years an extreme importance. There’s a lot of demand response programs, one of them proposed in this paper, using air conditioners that could increase the power quality and decrease the spent money in many ways like: infrastructures and customers energy bill reduction. This paper proposes a method and a study on how air conditioners could integrate demand response programs. The proposed method has been modelled as an energy resources management optimization problem. This paper presents two case studies, the first one with all costumers participating and second one with some of costumers. The results obtained for both case studies have been analyzed.

Modelo de controlo difuso de um sistema de produção de energia com base em recursos renováveis

A satisfação das necessidades energéticas mundiais, cada vez mais exigentes, bem como a necessidade urgente de procurar caminhos que permitam usufruir de energia, da forma menos poluente possível, levam à necessidade de serem explorados caminhos que permitam cumprir estes pressupostos. A escolha da utilização das energias renováveis na produção de energia, torna-se cada vez mais interessante, quer do ponto de vista ambiental quer económico. O fundamento da lógica difusa está associado à recolha de informações vagas, que são no fundo uma linguagem falada por seres humanos, possibilitando a passagem deste tipo de linguagem para formato numérico, permitindo assim uma manipulação computacional. Elementos climáticos como o sol e o vento, podem ser descritos em forma de variáveis linguísticas, como é o caso de vento forte, temperatura baixa, irradiação fraca, etc. Isto faz com que a aplicação de um controlo a partir destes fenómenos, justifique ser realizado com recurso a sistemas de inferência difusa. Para a realização do trabalho proposto, foram consumados estudos relativos às energias renováveis, com particular enfoque na solar e na eólica. Também foi realizado um estudo dos conceitos pertencentes à lógica difusa e a sistemas de inferência difusa com o objetivo de perceber os diversos parâmetros constituintes desta matéria. Foi realizado o estudo e desenvolvimento de um sistema de aquisição de dados, bem como do controlador difuso que é o busílis do trabalho descrito neste relatório. Para tal, o trabalho foi efetuado com o recurso ao software MATLAB, a partir do qual foram desenvolvidas aplicações que possibilitaram a obtenção de dados climáticos, com vista à sua utilização na toolbox Fuzzy Logic a qual foi utilizada para o desenvolvimento de todo o algoritmo de controlo. Com a possibilidade de aquisição de dados concluída e das variáveis que iriam ser necessárias definidas, foi implementado o controlador difuso que foi sendo sintonizado ao longo do trabalho por forma a garantir os melhores resultados possíveis. Com o recurso à ferramenta Guide, também do MATLAB, foi criada a interface do sistema com o utilizador, sendo possível a averiguação da energia a ser produzida, bem como das contribuições de cada uma das fontes de energia renováveis para a obtenção dessa mesma energia. Por último, foi feita uma análise de resultados através da comparação entre os valores reais esperados e os valores obtidos pelo controlador difuso, bem como assinaladas conclusões e possibilidades de desenvolvimentos futuros deste trabalho.

Laboratório remoto para monitorização e controlo baseado em MATLAB/Simulink e LabVIEW

Dissertação submetida à Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e Computadores

Sistema de deteção de arritmias

Esta dissertação apresenta o trabalho realizado no âmbito da unidade curricular de Tese/Dissertação (TEDI), do 2º ano, do Mestrado em Engenharia Eletrotécnica e de Computadores no ramo de Automação e Sistemas. O principal objetivo desta dissertação consiste no desenvolvimento de um sistema que permita efetuar a deteção de um determinado número de anomalias num sinal eletrocardiográfico. O coração é um dos órgãos mais importantes do corpo humano. É ele que recebe e bombeia o sangue pelo organismo. Isto é, recebe sangue pobre em oxigénio, encaminha-o para os pulmões onde será enriquecido em oxigénio. O sangue enriquecido em oxigénio é então encaminhado novamente para o coração que será enviado para todas as partes do corpo humano. O eletrocardiograma desempenha um papel fundamental de modo a diagnosticar eventuais anomalias no correto funcionamento do coração. Estas anomalias podem dever-se a diversos fatores como tabaco, colesterol, pressão sanguínea alta ou diabetes entre outros. As anomalias associadas ao ritmo cardíaco são denominadas de arritmias. As arritmias são fundamentalmente originadas pela alteração da frequência ou do ritmo cardíaco. Utilizando a lógica difusa, pretendeu-se desenvolver um sistema que fizesse a identificação de um determinado número de tipos de batimentos entre os quais: o bloqueio do ramo esquerdo (LBBB), bloqueio do ramo direito (RBBB), contração prematura ventricular (VPC) e contração prematura auricular (APC). Todos os desenvolvimentos efetuados, a nível de programação, são neste documento relatados de forma a constituírem um possível guia para a utilização deste tipo de sistemas. Mais ainda, descrevem-se nele toda a pesquisa efetuada e as alternativas de desenvolvimento selecionadas. O Sistema de Deteção de Arritmias (SDA) desenvolvido mostrou-se eficaz desde que o utilizador consiga identificar corretamente os parâmetros que lhe são pedidos. A interface gráfica desenvolvida permitiu também uma maior facilidade durante a análise do sinal eletrocardiográfico.

Strategic Drivers for Implementing Sustainability Programs in Portuguese Organizations– Let’s Listen to Aristotle: From Triple to Quadruple Bottom Line

This article describes a study that investigated the main strategic drivers that influence the implementation of sustainability/social responsibility programs. An online survey was administered to managers of Portuguese organizations with certified management systems. The findings suggest that the implementation of such programs is mainly correlated to: 1.) the approach to understanding and working toward the satisfaction of the community’s needs (in the broad sense of social responsibility); 2.) how systematically sustainability within the organization is identified and managed (e.g., pollution prevention, improved environmental performance, and compliance with the applicable environmental laws); and 3.) the degree to which the organization tries to understand the needs of the employees and works toward satisfying them. In addition to the survey, five interviews with top managers of the surveyed organizations provided some useful insights. There was no consensus on the meaning of sustainability and social responsibility: some described it as an instrumental approach for obtaining better organizational results, while others regarded it as the right thing to do (i.e., it is values driven). In all cases, however, the managers supported a kind of umbrella construct under which different size corporations use different models (for example, the Dow Jones Sustainability Index (DJSI), Global Reporting Initiative (GRI), ISO 14001 environmental management systems), although some managers reported that they simply do not know what to do. All of those surveyed agreed that the lack of a systematic approach could represent a major threat to their organization, making them willing to pay more attention and take more action on the issue of sustainability. An additional suggestion made by managers was to change from a triple bottom line (economic dimension, environmental dimension, social equity dimension) to a quadruple bottom line by adding another dimension: personal and family happiness. This fourth dimension was recognized by the Greek philosopher/thinker Aristotle (384-322 BCE) who thought of happiness as the highest good (virtue) and ultimate goal and purpose of life, achieved through living well, in harmony. Such harmony suggests a balance and a lack of excess—in other words a sustainable existence.