Electricity Markets Simulation: MASCEM Contributions to the Challenging Reality

Electricity Markets are not only a new reality but an evolving one as the involved players and rules change at a relatively high rate. Multi-agent simulation combined with Artificial Intelligence techniques may result in sophisticated tools very helpful under this context. Some simulation tools have already been developed, some of them very interesting. However, at the present state it is important to go a step forward in Electricity Markets simulators as this is crucial for facing changes in Power Systems. This paper explains the context and needs of electricity market simulation, describing the most important characteristics of available simulators. We present our work concerning MASCEM simulator, presenting its features as well as the improvements being made to accomplish the change and challenging reality of Electricity Markets.

Optimal location of gas supply units in natural gas system network

Natural gas industry has been confronted with big challenges: great growth in demand, investments on new GSUs – gas supply units, and efficient technical system management. The right number of GSUs, their best location on networks and the optimal allocation to loads is a decision problem that can be formulated as a combinatorial programming problem, with the objective of minimizing system expenses. Our emphasis is on the formulation, interpretation and development of a solution algorithm that will analyze the trade-off between infrastructure investment expenditure and operating system costs. The location model was applied to a 12 node natural gas network, and its effectiveness was tested in five different operating scenarios.

Metalearning in ALBidS: A Strategic Bidding System for electricity markets

Metalearning is a subfield of machine learning with special pro-pensity for dynamic and complex environments, from which it is difficult to extract predictable knowledge. The field of study of this work is the electricity market, which due to the restructuring that recently took place, became an especially complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotia-tion entities. The proposed metalearner takes advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that pro-vides decision support to electricity markets’ participating players. Using the outputs of each different strategy as inputs, the metalearner creates its own output, considering each strategy with a different weight, depending on its individual quality of performance. The results of the proposed meth-od are studied and analyzed using MASCEM - a multi-agent electricity market simulator that models market players and simulates their operation in the market. This simulator provides the chance to test the metalearner in scenarios based on real electricity market´s data.

Adaptive learning in multiagent systems: a forecasting methodology based on error analysis

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

A short-term risk management tool applied to OMEL electricity market using particle swarm optimization

Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, are presented and discussed in detail.

MASDScheGATS: a prototype system for dynamic scheduling

A manufacturing system has a natural dynamic nature observed through several kinds of random occurrences and perturbations on working conditions and requirements over time. For this kind of environment it is important the ability to efficient and effectively adapt, on a continuous basis, existing schedules according to the referred disturbances, keeping performance levels. The application of Meta-Heuristics and Multi-Agent Systems to the resolution of this class of real world scheduling problems seems really promising. This paper presents a prototype for MASDScheGATS (Multi-Agent System for Distributed Manufacturing Scheduling with Genetic Algorithms and Tabu Search).

Optimization model for medium term natural gas commitment

In this paper we study the optimal natural gas commitment for a known demand scenario. This study implies the best location of GSUs to supply all demands and the optimal allocation from sources to gas loads, through an appropriate transportation mode, in order to minimize total system costs. Our emphasis is on the formulation and use of a suitable optimization model, reflecting real-world operations and the constraints of natural gas systems. The mathematical model is based on a Lagrangean heuristic, using the Lagrangean relaxation, an efficient approach to solve the problem. Computational results are presented for Iberian and American natural gas systems, geographically organized in 65 and 88 load nodes, respectively. The location model results, supported by the computational application GasView, show the optimal location and allocation solution, system total costs and suggest a suitable gas transportation mode, presented in both numerical and graphic supports.

A influência da publicidade na escolha de antigripais por parte dos utentes de farmácias do distrito do Porto

Introdução: A publicidade tem como objetivo informar e despertar o interesse do consumidor pela compra de um produto ou serviço. É uma forma de comunicação cada vez mais utilizada pelas grandes organizações, inclusive as farmacêuticas, para elevar o consumo dos medicamentos. Do grupo de Medicamentos Não Sujeitos a Receita Médica (MNSRM), os antigripais, são os mais publicitados, sobretudo durante a época de Inverno. Inúmeras investigações dão conta de que qualquer medicamento acarreta algum risco, dependendo da forma de administração, quantidade, período de utilização e das características de cada organismo, não constituindo os antigripais exceção à regra. Objetivo: Identificar os fatores e meios publicitários que mais contribuem para a escolha de antigripais. Material e Métodos: Trata-se de um estudo transversal, observacional e descritivo que teve como base uma amostra constituída por 385 utentes de Farmácias do Distrito do Porto. A recolha dos dados, que foi feita com recurso à aplicação de um questionário, decorreu de Fevereiro a Março de 2012. As informações recolhidas foram analisadas com a metodologia estatística usual, no programa SPSS. Da totalidade de inquiridos, 76,3% eram do sexo feminino e 23,7% eram do sexo masculino. Tinham em média 35 anos de idade (DP±15,1) eram, na sua maioria, solteiros (48,3%) e possuíam como habilitações literárias o Ensino Secundário (36,4%) e o Ensino Superior (34,8%). Quanto à situação profissional, 51,7% estavam no ativo, sendo que destes, 24,7% exerciam uma profissão na área da Saúde. Resultados: Cerca de 90% (345) dos inquiridos afirmaram utilizar, com regularidade, Antigripais. A televisão foi considerada o instrumento publicitário mais poderoso na aquisição de qualquer MNSRM. A maioria dos utentes considera a qualidade publicitária boa ou muito boa (61,3%) e afirma que grande parte da publicidade visionada ou audível é sobre dores, febre e tosse (72,7%). Quando aparecem os primeiros sintomas de gripe ou constipações, o utente, geralmente, dirige-se à farmácia (79,7%) e a escolha recai na maioria das vezes sobre o Antigripine (61,8%). A informação prestada pelo Profissional de Farmácia, o preço e o já conhecer o medicamento, são os fatores que mais contribuem para a escolha de um antigripal. Discussão e Conclusão: Apesar da publicidade, especialmente, a transmitida pela televisão, ser valorizada na escolha de um antigripal, existe a necessidade expressa por parte do utente de se dirigir à Farmácia para aconselhamento do medicamento a tomar.

Virtual power producers market strategies

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper detail some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study.

Transmission price simulator in a liberalized electricity market

This paper presents a software tool (SIM_CMTP) that solves congestion situations and evaluates the taxes to be paid to the transmission system by market agents. SIM_CMTP provides users with a set of alternative methods for cost allocation and enables the definition of specific rules, according to each market and/or situation needs. With these characteristics, SIM_CMTP can be used as an operation aid for Transmission System Operator (TSO) or Independent System Operator (ISO). Due to its openness, it can also be used as a decision-making support tool for evaluating different options of market rules in competitive market environment, guarantying the economic sustainability of the transmission system.

Multi-agent electricity market simulation with dynamic strategies & virtual power producers

Distributed energy resources will provide a significant amount of the electricity generation and will be a normal profitable business. In the new decentralized grid, customers will be among the many decentralized players and may even help to co-produce the required energy services such as demand-side management and load shedding. So, they will gain the opportunity to be more active market players. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. In this paper we propose the improvement of MASCEM, a multi-agent simulation tool to study negotiations in electricity spot markets based on different market mechanisms and behavior strategies, in order to take account of decentralized players such as VPP.

An intelligent tutoring approach to support students and technicians in electrical installation design

Designing electric installation projects, demands not only academic knowledge, but also other types of knowledge not easily acquired through traditional instructional methodologies. A lot of additional empirical knowledge is missing and so the academic instruction must be completed with different kinds of knowledge, such as real-life practical examples and simulations. On the other hand, the practical knowledge detained by the most experienced designers is not formalized in such a way that is easily transmitted. In order to overcome these difficulties present in the engineers formation, we are developing an Intelligent Tutoring System (ITS), for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students.

An efficient method for optimal location and sizing of fixed and switched shunt capacitors in large distribution systems

This paper proposes a computationally efficient methodology for the optimal location and sizing of static and switched shunt capacitors in large distribution systems. The problem is formulated as the maximization of the savings produced by the reduction in energy losses and the avoided costs due to investment deferral in the expansion of the network. The proposed method selects the nodes to be compensated, as well as the optimal capacitor ratings and their operational characteristics, i.e. fixed or switched. After an appropriate linearization, the optimization problem was formulated as a large-scale mixed-integer linear problem, suitable for being solved by means of a widespread commercial package. Results of the proposed optimizing method are compared with another recent methodology reported in the literature using two test cases: a 15-bus and a 33-bus distribution network. For the both cases tested, the proposed methodology delivers better solutions indicated by higher loss savings, which are achieved with lower amounts of capacitive compensation. The proposed method has also been applied for compensating to an actual large distribution network served by AES-Venezuela in the metropolitan area of Caracas. A convergence time of about 4 seconds after 22298 iterations demonstrates the ability of the proposed methodology for efficiently handling large-scale compensation problems.

Research on using the decision tree method in order to select the best alternative for the pharmacies supply

Introduction / Aims: Adopting the important decisions represents a specific task of the manager. An efficient manager takes these decisions during a sistematic process with well-defined elements, each with a precise order. In the pharmaceutical practice and business, in the supply process of the pharmacies, there are situations when the medicine distributors offer a certain discount, but require payment in a shorter period of time. In these cases, the analysis of the offer can be made with the help of the decision tree method, which permits identifying the decision offering the best possible result in a given situation. The aims of the research have been the analysis of the product offers of many different suppliers and the establishing of the most advantageous ways of pharmacy supplying. Material / Methods: There have been studied the general product offers of the following medical stores: A&G Med, Farmanord, Farmexim, Mediplus, Montero and Relad. In the case of medicine offers including a discount, the decision tree method has been applied in order to select the most advantageous offers. The Decision Tree is a management method used in taking the right decisions and it is generally used when one needs to evaluate the decisions that involve a series of stages. The tree diagram is used in order to look for the most efficient means to attain a specific goal. The decision trees are the most probabilistic methods, useful when adopting risk taking decisions. Results: The results of the analysis on the tree diagrams have indicated the fact that purchasing medicines with discount (1%, 10%, 15%) and payment in a shorter time interval (120 days) is more profitable than purchasing without a discount and payment in a longer time interval (160 days). Discussion / Conclusion: Depending on the results of the tree diagram analysis, the pharmacies would purchase from the selected suppliers. The research has shown that the decision tree method represents a valuable work instrument in choosing the best ways for supplying pharmacies and it is very useful to the specialists from the pharmaceutical field, pharmaceutical management, to medicine suppliers, pharmacy practitioners from the community pharmacies and especially to pharmacy managers, chief – pharmacists.

Procedimento de distribuição de hemoderivados no Centro Hospitalar de São João, EPE

Introdução: A distribuição de Hemoderivados está associada a um circuito especial e que dá cumprimento ao Despacho Conjunto nº 1051/2000 (2ª série) de 14 de Setembro, publicado no Diário da República nº 251 de 30 de Outubro 2000 que regula o registo de medicamentos derivados do plasma. Isto acontece devido à natureza destes medicamentos que, por serem derivados do plasma humano, acarretam risco biológico, sendo sempre acompanhados de certificados de análise emitidos pelo INFARMED e que asseguram a sua segurança. Todas as actividades referentes à requisição, distribuição e administração de Hemoderivados têm de ser registadas num modelo de registo oficial, o que torna mais fácil a rastreabilidade da medicação dispensada e leva a um maior controlo desta. Desde a prescrição médica até à administração da medicação existem diversos passos que têm de ser realizados e que envolvem o preenchimento da requisição oficial, sendo indispensável a realização de todas as tarefas com o maior cuidado de forma a possibilitar uma dispensa de medicação correcta e eficaz, seguindo todos os parâmetros legislados. Material e Métodos: Realizou-se um estudo observacional, do tipo descritivo simples que permitiu verificar o conjunto de procedimentos compreendidos entre a realização da prescrição médica e a recepção da medicação preparada pelos Serviços Farmacêuticos, circuito que envolve diversos profissionais, nomeadamente Médicos, Técnicos de Diagnóstico e Terapêutica (TDT), Assistentes Operacionais (AO), Técnicos Superiores de Saúde (TSS), entre outros. Para a realização do estudo utilizou-se como base o período de estágio realizado nos circuitos especiais de distribuição de medicamentos no Centro Hospitalar de São João, EPE (CHSJ, EPE). Para a demonstração dos resultados realizou-se um fluxograma, utilizando o software Microsoft Office Visio 2010®, em que se pode verificar todos os passos necessários até a medicação ser administrada ao doente. Resultados: Os resultados encontram-se esquematizados na forma de um fluxograma que explica, de forma sucinta, todo o circuito especial de distribuição dos Hemoderivados desde a prescrição feita pelo médico até à recepção da medicação por parte dos serviços clínicos. Discussão / Conclusões: O circuito de distribuição de Hemoderivados adoptado pelo CHSJ, EPE segue todos os passos que permitem a correcta dispensa e administração da medicação. É imperativo que todas as partes envolvidas neste circuito tenham consciência de todos os aspectos que envolvem este tipo de distribuição, nomeadamente os aspectos burocráticos, ou seja, o correcto preenchimento do modelo oficial e que permite registar todas as actividades referentes à requisição, distribuição e administração de Hemoderivados.