11 resultados para Multi-sector models
em Instituto Politécnico do Porto, Portugal
Resumo:
For efficient planning of waste collection routing, large municipalities may be partitioned into convenient sectors. The real case under consideration is the municipality of Monção, in Portugal. Waste collection involves more than 1600 containers over an area of 220 km2 and a population of around 20,000 inhabitants. This is mostly a rural area where the population is distributed in small villages around the 33 boroughs centres (freguesia) that constitute the municipality. In most freguesias, waste collection is usually conducted 3 times a week. However, there are situations in which the same collection is done every day. The case reveals some general and specific characteristics which are not rare, but are not widely addressed in the literature. Furthermore, new methods and models to deal with sectorization and routing are introduced, which can be extended to other applications. Sectorization and routing are tackled following a three-phase approach. The first phase, which is the main concern of the presentation, introduces a new method for sectorization inspired by Electromagnetism and Coulomb’s Law. The matter is not only about territorial division, but also the frequency of waste collection, which is a critical issue in these types of applications. Special characteristics related to the number and type of deposition points were also a motivation for this work. The second phase addresses the routing problems in each sector: new Mixed Capacitated Arc Routing with Limited Multi-Landfills models will be presented. The last phase integrates Sectoring and Routing. Computational results confirm the effectiveness of the entire novel approach.
Resumo:
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.
Resumo:
With the restructuring of the energy sector in industrialized countries there is an increased complexity in market players’ interactions along with emerging problems and new issues to be addressed. Decision support tools that facilitate the study and understanding of these markets are extremely useful to provide players with competitive advantage. In this context arises MASCEM, a multi-agent simulator for competitive electricity markets. It is essential to reinforce MASCEM with the ability to recreate electricity markets reality in the fullest possible extent, making it able to simulate as many types of markets models and players as possible. This paper presents the development of the Balancing Market in MASCEM. A key module to the study of competitive electricity markets, as it has well defined and distinct characteristics previously implemented.
Resumo:
Renewable based power generation has significantly increased over the last years. However, this process has evolved separately from electricity markets, leading to an inadequacy of the present market models to cope with huge quantities of renewable energy resources, and to take full advantage of the presently existing and the increasing envisaged renewable based and distributed energy resources. This paper proposes the modelling of electricity markets at several levels (continental, regional and micro), taking into account the specific characteristics of the players and resources involved in each level and ensuring that the proposed models accommodate adequate business models able to support the contribution of all the resources in the system, from the largest to the smaller ones. The proposed market models are integrated in MASCEM (Multi- Agent Simulator of Competitive Electricity Markets), using the multi agent approach advantages for overcoming the current inadequacy and significant limitations of the presently existing electricity market simulators to deal with the complex electricity market models that must be adopted.
Resumo:
The restructuring that the energy sector has suffered in industrialized countries originated a greater complexity in market players’ interactions, and thus new problems and issues to be addressed. Decision support tools that facilitate the study and understanding of these markets become extremely useful to provide players with competitive advantage. In this context arises MASCEM, a multi-agent system for simulating competitive electricity markets. To provide MASCEM with the capacity to recreate the electricity markets reality in the fullest possible extent, it is essential to make it able to simulate as many market models and player types as possible. This paper presents the development of the Complex Market in MASCEM. This module is fundamental to study competitive electricity markets, as it exhibits different characteristics from the already implemented market types.
Resumo:
Este trabalho visa apresentar um enquadramento da realidade económica e industrial do sector transformador de granitos ornamentais em Portugal e fazer uma análise do processo de serragem, com engenhos multi-lâminas e granalha de aço, na medida em que este é o método de seccionamento de blocos de granito mais utilizado pelas grandes indústrias do sector. Tendo em conta a importância económica desta operação produtiva na indústria em causa, foi definido como fito deste projecto a análise estatística dos custos de produção; a definição de fórmulas de cálculo que permitam prever o custo médio de serragem; e o estudo de soluções economicamente viáveis e ambientalmente sustentáveis para o problema das lamas resultantes do expurgo dos engenhos. Para a persecução deste projecto foi realizada uma recolha de dados implementando rotinas de controlo e registo dos mesmos, em quadros de produção normalizados e de fácil preenchimento, pelos operadores destes equipamentos. Esta recolha de dados permitiu isolar, quantificar e formular os factores de rentabilização do processo de serragem selecionando, dentro da amostra de estudo obtida, um conjunto de serragens com características similares e com valores próximos dos valores da média estatística. Apartir dos dados destas serragens foram geradas curvas de tendência polinomial com as quais se analisaram as variações provocadas no custo médio de serragem, pelas variações do factor em estudo. A formulação dos factores de rentabilização e os dados estatísticos obtidos permitiram depois o desenvolvimento de fórmulas de cálculo do custo médio de serragem que establecem o custo de produção diferenciado em função das espessuras com, ou sem, a incorporação dos factores de rentabilização. Como consequência do projecto realizado obteve-se um conjunto de conclusões util, para o sector industrial em causa, que evidencia a importancia da Ocupação dos engenhos e rentabilização de um espaço confinado, da Resistência oferecida à serragem pelos granitos, e da Diferença de altura entre os blocos de uma mesma carga, nos custos de transformação.
Resumo:
A set of radiation measurements were carried out in several public and private institutions. These were selected with basis on the people affluence and passage to these sites. These measurements were registration formed either indoor, outdoor or underground and were compiled in three Case Studies. Radiation doses measurements were also made, surface and underground locations, and compiled in other two Case Studies. There were sampled, at the same time, humidity, temperature, atmospheric pressure and relevant construction materials at sampling locations. They were collected and registration formed to analyse if there is any relation or contribution for the measured value in each specific place. Geostatistical models were used to elaborate maps of the results both for radiation values and for doses. Preliminary relations were established among the measured parameters.
Resumo:
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.
Risk Acceptance in the Furniture Sector: Analysis of Acceptance Level and Relevant Influence Factors
Resumo:
Risk acceptance has been broadly discussed in relation to hazardous risk activities and/or technologies. A better understanding of risk acceptance in occupational settings is also important; however, studies on this topic are scarce. It seems important to understand the level of risk that stakeholders consider sufficiently low, how stakeholders form their opinion about risk, and why they adopt a certain attitude toward risk. Accordingly, the aim of this study is to examine risk acceptance in regard to occupational accidents in furniture industries. The safety climate analysis was conducted through the application of the Safety Climate in Wood Industries questionnaire. Judgments about risk acceptance, trust, risk perception, benefit perception, emotions, and moral values were measured. Several models were tested to explain occupational risk acceptance. The results showed that the level of risk acceptance decreased as the risk level increased. High-risk and death scenarios were assessed as unacceptable. Risk perception, emotions, and trust had an important influence on risk acceptance. Safety climate was correlated with risk acceptance and other variables that influence risk acceptance. These results are important for the risk assessment process in terms of defining risk acceptance criteria and strategies to reduce risks.
Resumo:
A globalização dos sistemas financeiros, ao longo dos anos, tem estimulado uma crescente necessidade de supervisão bancária nas instituições financeiras. O Comité de Supervisão Bancária de Basileia tem tido um papel crucial nesta área, estabelecendo princípios por via dos seus acordos entre as várias entidades nacionais de regulação e supervisão das maiores economias mundiais. Em 1988, foi criado o Acordo de Basileia (Basileia I) pelo Comité de Supervisão Bancária de forma a harmonizar os padrões de supervisão bancária. Este acordo estabeleceu mínimos de solvabilidade para o sistema bancário internacional no sentido de reforçar a sua solidez e estabilidade. Com o desenvolvimento de novas potências económicas e novas necessidades regulamentares, em Junho de 2004, foi publicado o novo Acordo de Capital – o Basileia II. Este acordo pretendia tornar os requisitos de capital mais sensíveis ao risco, promover a atuação das autoridades de supervisão e a disciplina de mercado (através do seu Pilar II) e encorajar a capacidade de cada instituição mensurar e gerir o seu risco. Em Setembro de 2010, o Acordo de Basileia III, com adoção prevista até 2019, veio reforçar estas medidas com a criação de um quadro regulamentar e de supervisão mais sólido, por parte das instituições de crédito. Surge, assim neste contexto, o Modelo de Avaliação de Risco (MAR) para o sector bancário. Em Portugal, o MAR tem como objetivo avaliar o perfil de risco das instituições de crédito, sujeitas à supervisão do Banco de Portugal, assim como apresentar o perfil de risco e a solidez da situação financeira de cada instituição de crédito. Este trabalho pretende avaliar o surgimento e a caracterização deste modelo e identificar as variáveis a ter em conta nos modelos de avaliação de risco a nível qualitativo e quantitativo.
Resumo:
Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.