2011
Autores
Rodrigues, NF; Oliveira, N; Barbosa, LS;
Publicação
ON THE MOVE TO MEANINGFUL INTERNET SYSTEMS: OTM 2011 WORKSHOPS
Abstract
What sort of component coordination strategies emerge in a software integration process? How can such strategies be discovered and further analysed? How close are they to the coordination component of the envisaged architectural model which was supposed to guide the integration process? This paper introduces a framework in which such questions can be discussed and illustrates its use by describing part of a real case-study. The approach is based on a methodology which enables semi-automatic discovery of coordination patterns from source code, combining generalized slicing techniques and graph manipulation.
2011
Autores
Martins, A; Barbosa, LS; Rodrigues, NF;
Publicação
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract
Over the last decade component-based software development arose as a promising paradigm to deal with the ever increasing complexity in software design, evolution and reuse. Shacc is a prototyping tool for component-based systems in which components are modelled coinductively as generalized Mealy machines. The prototype is built as a Haskell library endowed with a graphical user interface developed in Swing. © 2011 Springer-Verlag.
2011
Autores
Vale, Z; Pinto, T; Morais, H; Praca, I; Faria, P;
Publicação
2011 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING
Abstract
The increase of distributed generation (DG) has brought about new challenges in electrical networks electricity markets and in DG units operation and management. Several approaches are being developed to manage the emerging potential of DG, such as Virtual Power Players (VPPs), which aggregate DG plants; and Smart Grids, an approach that views generation and associated loads as a subsystem. This paper presents a multi-level negotiation mechanism for Smart Grids optimal operation and negotiation in the electricity markets, considering the advantages of VPPs' management. The proposed methodology is implemented and tested in MASCEM - a multiagent electricity market simulator, developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations.
2011
Autores
Vale, Z; Pinto, T; Praca, I; Morais, H;
Publicação
IEEE INTELLIGENT SYSTEMS
Abstract
Electricity markets are complex environments, involving numerous entities trying to obtain the best advantages and profits while limited by power-network characteristics and constraints. This article proposes a new methodology integrated in MASCEM for bid definition in electricity markets. This methodology uses reinforcement learning algorithms to let players perceive changes in the environment, thus helping them react to the dynamic environment and adapt their bids accordingly. The system operator is usually responsible for managing the transmission grid and all the involved technical constraints. The market operator must assure that the economical dispatch accounts for the specified conditions, which might imply removing entities that have presented competitive bids but whose complex conditions were not satisfied. This result demonstrates that several algorithms can be combined with distinct characteristics.
2011
Autores
Pinto, T; Vale, Z; Rodrigues, F; Praca, I; Morais, H;
Publicação
2011 16th International Conference on Intelligent System Applications to Power Systems, ISAP 2011
Abstract
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 simulator 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 provides several dynamic strategies for agents' behavior. This paper presents a method that aims to provide market players with strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible bids. These bids are defined accordingly to the cost function that each producer presents. © 2011 IEEE.
2011
Autores
Vale, ZA; Canizes, B; Soares, J; Oliveira, P; Sousa, T; Pinto, T;
Publicação
2011 16th International Conference on Intelligent System Applications to Power Systems, ISAP 2011
Abstract
This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. © 2011 IEEE.
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