Adapting Meeting Tools to Agent Decision

Electricity markets are complex environments comprising several negotiation mechanisms. MASCEM (Multi- Agent System for Competitive Electricity Markets) is a simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. ALBidS (Adaptive Learning Strategic Bidding System) is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM it considers several different methodologies based on very distinct approaches. The Six Thinking Hats is a powerful technique used to look at decisions from different perspectives. This paper aims to complement ALBidS strategies usage by MASCEM players, providing, through the Six Thinking Hats group decision technique, a means to combine them and take advantages from their different perspectives. The combination of the different proposals resulting from ALBidS’ strategies is performed through the application of a Genetic Algorithm, resulting in an evolutionary learning approach.

Strategic Bidding for Electricity Markets Negotiation Using Support Vector Machines

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which simulates the electricity markets environment. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. This paper presents the application of a Support Vector Machines (SVM) based approach to provide decision support to electricity market players. This strategy is tested and validated by being included in ALBidS and then compared with the application of an Artificial Neural Network, originating promising results. The proposed approach is tested and validated using real electricity markets data from MIBEL - Iberian market operator.

Elspot: Nord Pool Spot Integration in MASCEM Electricity Market Simulator

The energy sector in industrialized countries has been restructured in the last years, with the purpose of decreasing electricity prices through the increase in competition, and facilitating the integration of distributed energy resources. However, the restructuring process increased the complexity in market players' interactions and generated emerging problems and new issues to be addressed. In order to provide players with competitive advantage in the market, decision support tools that facilitate the study and understanding of these markets become extremely useful. In this context arises MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), a multi-agent based simulator that models real electricity markets. To reinforce MASCEM with the capability of recreating the electricity markets reality in the fullest possible extent, it is crucial to make it able to simulate as many market models and player types as possible. This paper presents a new negotiation model implemented in MASCEM based on the negotiation model used in day-ahead market (Elspot) of Nord Pool. This is a key module to study competitive electricity markets, as it presents well defined and distinct characteristics from the already implemented markets, and it is a reference electricity market in Europe (the one with the larger amount of traded power).

Particle Swarm Optimization of Electricity Market Negotiating Players Portfolio

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which performs realistic simulations of the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from each market context. However, it is still necessary to adequately optimize the players’ portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering different market opportunities (bilateral negotiation, market sessions, and operation in different markets) and the negotiation context such as the peak and off-peak periods of the day, the type of day (business day, weekend, holiday, etc.) and most important, the renewable based distributed generation forecast. The proposed approach is tested and validated using real electricity markets data from the Iberian operator – MIBEL.

Gestão do conhecimento e cultura organizacional: barreiras e facilitadores

Este trabalho incide sobre a gestão do conhecimento e cultura organizacional, as suas barreiras os seus facilitadores na Parque Escolar E.P.E. Este estudo teve por base o método quadripolar. Várias foram as atividades ao longo deste trabalho, inicialmente foi recolhida a documentação interna, nomeadamente diplomas legais, regulamentos, manuais de procedimentos, manuais de formações internas, entre outros documentos, que serviram de base ao reconhecimento da instituição, a sua evolução estrutural e de funcionamento. Para identificar as barreiras e os facilitadores na recuperação da informação nos três principais meios para o efeito: arquivo físico, file system e aplicações informáticas foram aplicados inquéritos aos produtores/ utilizadores de informação da Parque Escolar, E.P.E. Com base neste estudo foi possível identificar qual o recurso de recuperação de informação que traz mais dificuldades na sua utilização, se existem documentos exclusivos em papel ou exclusivos em formato digital, se os mesmos são recuperáveis com facilidade. Foi possível averiguar se os colaboradores da Parque Escolar, E.P.E. consideram os documentos que constam no Arquivo Físico mais fidedignos do que os documentos em formato digital guardados no file system ou nas aplicações informáticas. Em relação às aplicações informáticas foi ainda possível averiguar se os colaboradores consideram uteis as suas atualizações, ou se demonstram alguma resistência à mudança, e se consideram que tiveram o acompanhamento necessário para compreender e aplicar as alterações. Com este estudo esperamos ter contribuído para dar uma maior visibilidade à temática da gestão do conhecimento e como a cultura organizacional pode influenciar, criando barreiras ou facilitadores.

Os sistemas de apoio à decisão na área dos cuidados primários: implementação de um sistema de apoio à decisão numa unidade de saúde familiar

Saber qual o papel de um Sistema de Apoio à Decisão na gestão estratégica de uma Unidade de Saúde Familiar; perceber qual a importância, no desempenho deste tipo de instituições, que estes Sistemas de Informação poderão assumir e identificar de que forma este gênero de software pode auxiliar a tomada de decisões estratégica da gestão das Unidades de Cuidados de Saúde Primários, são algumas das interrogações cuja relevância se verifica ser cada vez mais crescente e que se irão analisar no presente estudo. Para dar resposta às interrogações supra citadas é necessário conhecer o contexto no qual a organização está inserida, assim como perceber se a visão dos seus colaboradores (realizando-se para isso um inquérito por questionário aos colaboradores da Unidade de Saúde Familiar) é idêntica à realidade demonstrada através dos dados do histórico da instituição (recolhendo, estudando e efetuando estudos analíticos com o auxílio de um Sistema de Apoio à Decisão escolhido para o efeito – Weka). Tendo em conta o percurso anteriormente referido é assim possível inferir que é notória a positividade que os Sistemas de Apoio à Decisão podem ter no que é o dia-a-dia de uma Unidade de Saúde Familiar, tendo em conta que facilitam a análise de dados e podem até antecipar cenários futuros analisando o passado da instituição.

Apoio à gestão na tomada de decisão na ATAHCA: um estudo de caso

A informação assume, hoje em dia, uma importância crescente. Desde a sua constituição, as organizações produzem diariamente informação que alimenta o seu sistema de informação organizacional. Este, passa por um ciclo de vida que abrange processos relacionados com o seu planeamento e desenvolvimento, sem o qual não seria possível tomar decisões e dar resposta às solicitações do meio envolvente, devido ao enorme volume de dados a processar pelas organizações. Com este estágio pretende-se abordar a importância da informação na gestão do património da associação ATAHCA – Associação de Desenvolvimento das Terras Altas do Homem, Cávado e Ave, onde se incluem edifícios, mobiliário, obras de arte, máquinas, utensílios, ferramentas, meios de transporte e documentos. Assim, o objetivo deste trabalho consiste em desenvolver um sistema de apoio à tomada de decisão baseado na inventariação de todo o património. A criação de um manual de procedimentos é essencial para garantir o correto manuseamento do sistema e servirá de contributo à gestão eficaz da informação. O sistema de informação a desenvolver será um modelo de apoio à decisão que permita fazer a gestão do inventário/património, mas também que possibilite a quantificação e o valor patrimonial do mesmo. Pretende-se, ainda, discutir e analisar o contributo da gestão da informação no apoio à tomada de decisão assertiva e rentável para a organização.

Multi-agent simulation of competitive electricity markets: Autonomous systems cooperation for European market modeling

The electricity market restructuring, and its worldwide evolution into regional and even continental scales, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in a rising complexity in power systems operation. Several power system simulators have been developed in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex and constantly changing environment. The main contribution of this paper is given by the integration of several electricity market and power system models, respecting to the reality of different countries. This integration is done through the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The continuous development of Multi-Agent System for Competitive Electricity Markets platform provides the means for the exemplification of the usefulness of this ontology. A case study using the proposed multi-agent platform is presented, considering a scenario based on real data that simulates the European Electricity Market environment, and comparing its performance using different market mechanisms. The main goal is to demonstrate the advantages that the integration of various market models and simulation platforms have for the study of the electricity markets’ evolution.

Gestão de Redes e Sistemas: Estudo de um caso

A gestão e monitorização de redes é uma necessidade fundamental em qualquer organização, quer seja grande ou pequena. A sua importância tem de ser refletida na eficiência e no aumento de informação útil disponível, contribuindo para uma maior eficácia na realização das tarefas em ambientes tecnologicamente avançados, com elevadas necessidades de desempenho e disponibilidade dos recursos dessa tecnologia. Para alcançar estes objetivos é fundamental possuir as ferramentas de gestão de redes adequadas. Nomeadamente ferramentas de monitorização. A classificação de tráfego também se revela fundamental para garantir a qualidade das comunicações e prevenir ataques indesejados aumentando assim a segurança nas comunicações. Paralelamente, principalmente em organizações grandes, é relevante a inventariação dos equipamentos utilizados numa rede. Neste trabalho pretende-se implementar e colocar em funcionamento um sistema autónomo de monitorização, classificação de protocolos e realização de inventários. Todas estas ferramentas têm como objetivo apoiar os administradores e técnicos de sistemas informáticos. Os estudos das aplicações que melhor se adequam à realidade da organização culminaram num acréscimo de conhecimento e aprendizagem que irão contribuir para um melhor desempenho da rede em que o principal beneficiário será o cidadão.

An architecture for an effective usage of data mining in business intelligence systems

Business Intelligence (BI) is one emergent area of the Decision Support Systems (DSS) discipline. Over the last years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. Therefore, a lack of an effective usage of DM in BI can be found in some BI systems. An architecture that pretends to conduct to an effective usage of DM in BI is presented.

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.

Multi-criteria short-term maintenance outage scheduling in smart distribution systems

Effective legislation and standards for the coordination procedures between consumers, producers and the system operator supports the advances in the technologies that lead to smart distribution systems. In short-term (ST) maintenance scheduling procedure, the energy producers in a distribution system access to the long-term (LT) outage plan that is released by the distribution system operator (DSO). The impact of this additional information on the decision-making procedure of producers in ST maintenance scheduling is studied in this paper. The final ST maintenance plan requires the approval of the DSO that has the responsibility to secure the network reliability and quality, and other players have to follow the finalized schedule. Maintenance scheduling in the producers’ layer and the coordination procedure between them and the DSO is modelled in this paper. The proposed method is applied to a 33-bus distribution system.

Balancing market integration in MASCEM electricity market simulator

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.

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).

A simulation tool for demand response programs implementation

The design and development of simulation models and tools for Demand Response (DR) programs are becoming more and more important for adequately taking the maximum advantages of DR programs use. Moreover, a more active consumers’ participation in DR programs can help improving the system reliability and decrease or defer the required investments. DemSi, a DR simulator, designed and implemented by the authors of this paper, allows studying DR actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. DemSi considers the players involved in DR actions, and the results can be analyzed from each specific player point of view.