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.

Modelos geológicos estocásticos 3D e interface para modelos de simulação de fluxo: aplicação à área subjacente da antiga fábrica da SPEL

Dissertação para obtenção do grau de Mestre em Engenharia Geológica (Georrecursos)

Concepção de um aparelho de medição 3D da coluna vertebral: Desenvolvimento de um software de detecção de apófises espinhosas e cálculo da distância ântero-posterior

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Biomédica

Computational design with flexible backbone sampling for protein remodeling and scaffolding of complex binding sites

Dissertation presented to obtain the Doutoramento (Ph.D.) degree in Biochemistry at the Instituto de Tecnologia Qu mica e Biol ogica da Universidade Nova de Lisboa

Acceleration of physics simulation engine through OpenCL

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Interacções de proteínas do plasma com potenciais fármacos: estudos 3D a nível molecular

Dissertação para obtenção do Grau de Mestre em Biotecnologia

Desenvolvimento de um procedimento de Numerical Site Calibration para um Parque Eólico usando Dinâmica de Fluidos Computacional

Esta dissertação descreve o desenvolvimento e avaliação de um procedimento de \Numerical Site Calibration" (NSC) para um Parque Eólico, situado a sul de Portugal, usando Dinâmica de Fluídos Computacional (CFD). O NSC encontra-se baseado no \Site Calibration" (SC), sendo este um método de medição padronizado pela Comissão Electrónica Internacional através da norma IEC 61400. Este método tem a finalidade de quantificar e reduzir os efeitos provocados pelo terreno e por possíveis obstáculos, na medição do desempenho energético das turbinas eólicas. Assim, no SC são realizadas medições em dois pontos, no mastro referência e no local da turbina (mastro temporário). No entanto, em Parques Eólicos já construídos, este método não é aplicável visto ser necessária a instalação de um mastro de medição no local da turbina e, por conseguinte, o procedimento adequado para estas circunstâncias é o NSC. O desenvolvimento deste método é feito por um código CFD, desenvolvido por uma equipa de investigação do Instituto Superior de Engenharia do Porto, designado de WINDIETM, usado extensivamente pela empresa Megajoule Inovação, Lda em aplicações de energia eólica em todo mundo. Este código é uma ferramenta para simulação de escoamentos tridimensionais em terrenos complexos. As simulações do escoamento são realizadas no regime transiente utilizando as equações de Navier-Stokes médias de Reynolds com aproximação de Bussinesq e o modelo de turbulência TKE 1.5. As condições fronteira são provenientes dos resultados de uma simulação realizada com Weather Research and Forecasting, WRF. Estas simulações dividem-se em dois grupos, um dos conjuntos de simulações utiliza o esquema convectivo Upwind e o outro utiliza o esquema convectivo de 4aordem. A análise deste método é realizada a partir da comparação dos dados obtidos nas simulações realizadas no código WINDIETM e a coleta de dados medidos durante o processo SC. Em suma, conclui-se que o WINDIETM e as suas configurações reproduzem bons resultados de calibração, ja que produzem erros globais na ordem de dois pontos percentuais em relação ao SC realizado para o mesmo local em estudo.

System Level Simulation and Radio Resource Management for Distributed Antenna Systems with Cognitive Radio and Multi-Cell Cooperation

4th International Conference on Future Generation Communication Technologies (FGCT 2015), Luton, United Kingdom.

RoutesMobilityModel: easy realistic mobility simulation using external information services

Workshop on ns-3 (WNS '15). 13, May, 2015. Castelldefels, Spain.

A learning environment for robotic production line simulation

This paper presents a framework for a robotic production line simulation learning environment using Autonomous Ground Vehicles (AGV). An eLearning platform is used as interface with the simulator. The objective is to introduce students to the production robotics area using a familiar tool, an eLearning platform, and a framework that simulates a production line using AGVs. This framework allows students to learn about robotics but also about several areas of industrial management engineering without requiring an extensive prior knowledge on the robotics area. The robotic production line simulation learning environment simulates a production environment using AGVs to transport materials to and from the production line. The simulator allows students to validate the AGV dynamics and provides information about the whole materials supplying system which includes: supply times, route optimization and inventory management. The students are required to address several topics such as: sensors, actuators, controllers and an high level management and optimization software. This simulator was developed with a known open source tool from robotics community: Player/Stage. This tool was extended with several add-ons so that students can be able to interact with a complex simulation environment. These add-ons include an abstraction communication layer that performs events provided by the database server which is programmed by the students. An eLearning platform is used as interface between the students and the simulator. The students can visualize the effects of their instructions/programming in the simulator that they can access via the eLearning platform. The proposed framework aims to allow students from different backgrounds to fully experience robotics in practice by suppressing the huge gap between theory and practice that exists in robotics. Using an eLearning platform eliminates installation problems that can occur from different computers software distribution and makes the simulator accessible by all students at school and at home.

Improved Numerical Simulation for a Novel Adaptive Control Using Fractional Order Derivatives

A novel control technique is investigated in the adaptive control of a typical paradigm, an approximately and partially modeled cart plus double pendulum system. In contrast to the traditional approaches that try to build up ”complete” and ”permanent” system models it develops ”temporal” and ”partial” ones that are valid only in the actual dynamic environment of the system, that is only within some ”spatio-temporal vicinity” of the actual observations. This technique was investigated for various physical systems via ”preliminary” simulations integrating by the simplest 1st order finite element approach for the time domain. In 2004 INRIA issued its SCILAB 3.0 and its improved numerical simulation tool ”Scicos” making it possible to generate ”professional”, ”convenient”, and accurate simulations. The basic principles of the adaptive control, the typical tools available in Scicos, and others developed by the authors, as well as the improved simulation results and conclusions are presented in the contribution.