Planear e inovar : contributo para o planeamento de recursos com base nas necessidades auto-avaliadas pela população com 65 e mais anos

RESUMO - Enquadramento: O envelhecimento da população ocorre em todas as sociedades desenvolvidas, resultando num aumento da prevalência da dependência funcional, associado recorrentemente à presença de doenças crónicas. Estes novos padrões demográficos, epidemiológicos, implicando populações vulneráveis com necessidades específicas, resultam em desafios incontestáveis. Como resposta a este novo paradigma, em 2006, Portugal implementa a Rede Nacional de Cuidados Continuados Integrados (RNCCI). Finalidade/objectivos: Caracterização da população com base no perfil das necessidades auto-referidas pelas pessoas com ≥65 anos, com algum nível de independência/dependência nas actividades de vida diária e/ou com pelo menos uma doença crónica. Pretende-se, ainda, desenvolver uma metodologia que permita simular cenários que contribuam para o planeamento do número de camas para internamento de carácter permanente em Unidades de Longa Duração e Manutenção (ULDM) da RNCCI. Metodologia: Construção de dois indicadores: índice de independência/dependência e existência ou não de doenças crónicas. Análise estatística e caracterização, individual e conjunta, das variáveis sociodemográficas, socioeconómicas, auto-avaliação do estado de saúde, nível de independência/dependência e/ou existência de pelo menos uma doença crónica. Simulação de cenários com base nas metas definidas pela RNCCI para 2013. Resultados e Conclusões: Da aplicação do índice de independência/dependência, resulta que 78,8% são independentes na realização das actividades de vida diária e 21,2% apresentam algum nível de dependência. À excepção do Centro, todas as regiões apresentam padrões similares. Globalmente, os resultados obtidos vão de encontro aos enunciados na literatura internacional, realçando-se apenas alguns mais pertinentes: Observa-se uma predominância de mulheres idosas. Destaca-se também uma relação directa entre a idade e os níveis de dependência. As variáveis socioeconómicas indicam que a existência de algum nível de dependência tende a ser mais frequente entre os que têm menor escolaridade e rendimento. Em média o estado de saúde é auto-avaliado como mau, piorando com o aumento da idade e níveis de dependência mais acentuados e melhorando com o aumento da escolaridade. Da simulação de cenários destaca-se que, face às 4 camas previstas nas metas de 2013, seria de alocar em média 1,7 camas ou 1 cama ao internamento permanente em ULDM. Trabalhar em rede implica canais de comunicação. A incorporação da distribuição espacial das necessidades e serviços com recurso aos sistemas de informação geográfica torna-se numa mais-valia. Possibilita avaliar hipóteses, análises sustentadas e disseminação de informação e resultados, contribuindo para um planeamento, monitorização e avaliação mais eficaz e eficiente das actividades do sector da saúde. ---------------------------------- ABSTRACT - Background: Population aging occurs in all developed societies resulting in an increased prevalence of functional dependence, frequently associated with the presence of chronic diseases. These new demographic and epidemiological patterns, which include dependency ad vulnerability situations, with specific needs, result in undeniable challenges. In response to this new paradigm, in 2006, Portugal implements the National Network for Integrated Care (RNCCI). Aim/Objectives: Characterize the population based on the self-reported needs of ≥65 year’s people, with some level of independence/dependency in activities of daily living and/or with at least one chronic disease. Also intends to develop a methodological approach that allows scenarios simulation which contributes to the planning of the number of permanent inpatient beds in Long Term Care Units (ULDM) of RNCCI. Methods: Construction of two indicators: independence/dependence index and existence of chronic diseases. Statistical analysis and characterization, individually and jointly, of sociodemographics, socioeconomics, selfassessment of health status, level of independence/dependence and/or existence of at least one chronic disease variables. Scenarios simulation based on RNCCI targets set for 2013. Results and Conclusions: According with independence/dependence index, 78.8% are independent in carrying out the activities of daily living and 21.2% have some level of dependency. With the exception of the Centroregion, all regions have similar patterns. Generally, the results are concordant with international literature, highlighting here only some of the most relevant results: A predominance of older women is observed. A direct relationship between age and levels of dependence is emphasized. Socio-economic variables indicate that the existence of some level of dependency tends to be more frequent among those with lower income and education levels. On average, health status is self-assessed as poor, being even more critical with aging and higher dependency level. On the other hand, high education levels are related with better health status. Scenarios simulations highlights that, based on 4 beds considered in the 2013 planned goals, an average of 1.7 or 1 beds in ULDM should be allocated to permanent inpatient beds. Networking involves communication channels. The incorporation of spatial distribution of needs and services using geographical information systems becomes an added value. It enables hypothesis, evaluation, sustainable analysis and information and results dissemination, contributing to a more effective and efficient planning, monitoring and assessment of the health sector activities.

Scenarios Generation for Multi-Agent simulation of Electricity Markets based on Intelligent Data Analysis

This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.

Multi-Agent Based Smart Grid Management and Simulation: Situation Awareness and Learning in a Test Bed with Simulated and Real Installations and Players

The rising usage of distributed energy resources has been creating several problems in power systems operation. Virtual Power Players arise as a solution for the management of such resources. Additionally, approaching the main network as a series of subsystems gives birth to the concepts of smart grid and micro grid. Simulation, particularly based on multi-agent technology is suitable to model all these new and evolving concepts. MASGriP (Multi-Agent Smart Grid simulation Platform) is a system that was developed to allow deep studies of the mentioned concepts. This paper focuses on a laboratorial test bed which represents a house managed by a MASGriP player. This player is able to control a real installation, responding to requests sent by the system operators and reacting to observed events depending on the context.

Real-Time Simulation of energy Management in a Domestic Consumer

Recent and future changes in power systems, mainly in the smart grid operation context, are related to a high complexity of power networks operation. This leads to more complex communications and to higher network elements monitoring and control levels, both from network’s and consumers’ standpoint. The present work focuses on a real scenario of the LASIE laboratory, located at the Polytechnic of Porto. Laboratory systems are managed by the SCADA House Intelligent Management (SHIM), already developed by the authors based on a SCADA system. The SHIM capacities have been recently improved by including real-time simulation from Opal RT. This makes possible the integration of Matlab®/Simulink® real-time simulation models. The main goal of the present paper is to compare the advantages of the resulting improved system, while managing the energy consumption of a domestic consumer.

Load Control Timescales Simulation in a Multi-Agent Smart Grid Platform

Environmental concerns and the shortage in the fossil fuel reserves have been potentiating the growth and globalization of distributed generation. Another resource that has been increasing its importance is the demand response, which is used to change consumers’ consumption profile, helping to reduce peak demand. Aiming to support small players’ participation in demand response events, the Curtailment Service Provider emerged. This player works as an aggregator for demand response events. The control of small and medium players which act in smart grid and micro grid environments is enhanced with a multi-agent system with artificial intelligence techniques – the MASGriP (Multi-Agent Smart Grid Platform). Using strategic behaviours in each player, this system simulates the profile of real players by using software agents. This paper shows the importance of modeling these behaviours for studying this type of scenarios. A case study with three examples shows the differences between each player and the best behaviour in order to achieve the higher profit in each situation.

Domestic Consumption Simulation and Management Using a Continuous Consumption Management and Optimization Algorithm

The recent changes concerning the consumers’ active participation in the efficient management of load devices for one’s own interest and for the interest of the network operator, namely in the context of demand response, leads to the need for improved algorithms and tools. A continuous consumption optimization algorithm has been improved in order to better manage the shifted demand. It has been done in a simulation and user-interaction tool capable of being integrated in a multi-agent smart grid simulator already developed, and also capable of integrating several optimization algorithms to manage real and simulated loads. The case study of this paper enhances the advantages of the proposed algorithm and the benefits of using the developed simulation and user interaction tool.

Towards a unified European electricity market: The contribution of data-mining to support realistic simulation studies

Worldwide electricity markets have been evolving into regional and even continental scales. The aim at an efficient use of renewable based generation in places where it exceeds the local needs is one of the main reasons. A reference case of this evolution is the European Electricity Market, where countries are connected, and several regional markets were created, each one grouping several countries, and supporting transactions of huge amounts of electrical energy. The continuous transformations electricity markets have been experiencing over the years create the need to use simulation platforms to support operators, regulators, and involved players for understanding and dealing with this complex environment. This paper focuses on demonstrating the advantage that real electricity markets data has for the creation of realistic simulation scenarios, which allow the study of the impacts and implications that electricity markets transformations will bring to the participant countries. A case study using MASCEM (Multi-Agent System for Competitive Electricity Markets) is presented, with a scenario based on real data, simulating the European Electricity Market environment, and comparing its performance when using several different market mechanisms.

Dynamic Approach and Testbed for Small and Medium Players Simulation in Smart Grid Environments

The Smart Grid environment allows the integration of resources of small and medium players through the use of Demand Response programs. Despite the clear advantages for the grid, the integration of consumers must be carefully done. This paper proposes a system which simulates small and medium players. The system is essential to produce tests and studies about the active participation of small and medium players in the Smart Grid environment. When comparing to similar systems, the advantages comprise the capability to deal with three types of loads – virtual, contextual and real. It can have several loads optimization modules and it can run in real time. The use of modules and the dynamic configuration of the player results in a system which can represent different players in an easy and independent way. This paper describes the system and all its capabilities.

Multi-agent Simulation of Bilateral Contracting in Competitive Electricity Markets

Traditional vertically integrated power utilities around the world have evolved from monopoly structures to open markets that promote competition among suppliers and provide consumers with a choice of services. Market forces drive the price of electricity and reduce the net cost through increased competition. Electricity can be traded in both organized markets or using forward bilateral contracts. This article focuses on bilateral contracts and describes some important features of an agent-based system for bilateral trading in competitive markets. Special attention is devoted to the negotiation process, demand response in bilateral contracting, and risk management. The article also presents a case study on forward bilateral contracting: a retailer agent and a customer agent negotiate a 24h-rate tariff.

Realistic Multi-Agent Simulation of Competitive Electricity Markets

The dynamism and ongoing changes that the electricity markets sector is constantly suffering, enhanced by the huge increase in competitiveness, create the need of using simulation platforms to support operators, regulators, and the involved players in understanding and dealing with this complex environment. This paper presents an enhanced electricity market simulator, based on multi-agent technology, which provides an advanced simulation framework for the study of real electricity markets operation, and the interactions between the involved players. MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) uses real data for the creation of realistic simulation scenarios, which allow the study of the impacts and implications that electricity markets transformations bring to different countries. Also, the development of an upper-ontology to support the communication between participating agents, provides the means for the integration of this simulator with other frameworks, such as MAN-REM (Multi-Agent Negotiation and Risk Management in Electricity Markets). A case study using the enhanced simulation platform that results from the integration of several systems and different tools is presented, with a scenario based on real data, simulating the MIBEL electricity market environment, and comparing the simulation performance with the real electricity market results.

Real-Time Simulation of Real-Time Pricing Demand Response to Meet Wind Variations

Recent changes of paradigm in power systems opened the opportunity to the active participation of new players. The small and medium players gain new opportunities while participating in demand response programs. This paper explores the optimal resources scheduling in two distinct levels. First, the network operator facing large wind power variations makes use of real time pricing to induce consumers to meet wind power variations. Then, at the consumer level, each load is managed according to the consumer preferences. The two-level resources schedule has been implemented in a real-time simulation platform, which uses hardware for consumer’ loads control. The illustrative example includes a situation of large lack of wind power and focuses on a consumer with 18 loads.

Data Mining Approach to support the Generation of Realistic Scenarios for Multi-Agent simulation of Electricity Markets

This paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players’ characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market environment, especially when coupled with a multi-agent electricity markets simulator. The generation of realistic scenarios is performed using mechanisms for intelligent data analysis, which are based on artificial intelligence and data mining algorithms. These techniques allow the study of realistic scenarios, adapted to the existing markets, and improve the representation of market entities as software agents, enabling a detailed modeling of their profiles and strategies. This work contributes significantly to the understanding of the interactions between the entities acting in electricity markets by increasing the capability and realism of market simulations.

Distributed Intelligent Management of Microgrids using a Multi-Agent Simulation Platform

Multi-agent approaches have been widely used to model complex systems of distributed nature with a large amount of interactions between the involved entities. Power systems are a reference case, mainly due to the increasing use of distributed energy sources, largely based on renewable sources, which have potentiated huge changes in the power systems’ sector. Dealing with such a large scale integration of intermittent generation sources led to the emergence of several new players, as well as the development of new paradigms, such as the microgrid concept, and the evolution of demand response programs, which potentiate the active participation of consumers. This paper presents a multi-agent based simulation platform which models a microgrid environment, considering several different types of simulated players. These players interact with real physical installations, creating a realistic simulation environment with results that can be observed directly in the reality. A case study is presented considering players’ responses to a demand response event, resulting in an intelligent increase of consumption in order to face the wind generation surplus.

Modelação e identificação de motor DC

O modelo matemático de um sistema real permite o conhecimento do seu comportamento dinâmico e é geralmente utilizado em problemas de engenharia. Por vezes os parâmetros utilizados pelo modelo são desconhecidos ou imprecisos. O envelhecimento e o desgaste do material são fatores a ter em conta pois podem causar alterações no comportamento do sistema real, podendo ser necessário efetuar uma nova estimação dos seus parâmetros. Para resolver este problema é utilizado o software desenvolvido pela empresa MathWorks, nomeadamente, o Matlab e o Simulink, em conjunto com a plataforma Arduíno cujo Hardware é open-source. A partir de dados obtidos do sistema real será aplicado um Ajuste de curvas (Curve Fitting) pelo Método dos Mínimos Quadrados de forma a aproximar o modelo simulado ao modelo do sistema real. O sistema desenvolvido permite a obtenção de novos valores dos parâmetros, de uma forma simples e eficaz, com vista a uma melhor aproximação do sistema real em estudo. A solução encontrada é validada com recurso a diferentes sinais de entrada aplicados ao sistema e os seus resultados comparados com os resultados do novo modelo obtido. O desempenho da solução encontrada é avaliado através do método das somas quadráticas dos erros entre resultados obtidos através de simulação e resultados obtidos experimentalmente do sistema real.

Synthesis of biodiesel from wastes of food industry via direct transesterification with methanol/carbon dioxide mixtures

Dissertation presented at Faculdade de Ciências e Tecnologia from Universidade Nova de Lisboa to obtain the degree of Master in Chemical and Biochemical Engineering