Scenarios Generation for Multi-Agent simulation of Electricity Markets based on Intelligent Data Analysis

This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.

MASCEM Restructuring: Ontologies For Scenarios Generation in Power Systems Simulators

The electricity market restructuring, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in an rising complexity in power systems operation. Various power system simulators have been introduced in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex environment. This paper focuses on the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The restructuring of MASCEM (Multi-Agent System for Competitive Electricity Markets), and this system’s integration with MASGriP (Multi-Agent Smart Grid Platform), and ALBidS (Adaptive Learning Strategic Bidding System) provide the means for the exemplification of the usefulness of this ontology. A practical example is presented, showing how common simulation scenarios for different simulators, directed to very distinct environments, can be created departing from the proposed ontology.

Load Profiling Tool to Support Smart Grid Operation Scenarios

This paper presents the characterization of high voltage (HV) electric power consumers based on a data clustering approach. The typical load profiles (TLP) are obtained selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The choice of the best partition is supported using several cluster validity indices. The proposed data-mining (DM) based methodology, that includes all steps presented in the process of knowledge discovery in databases (KDD), presents an automatic data treatment application in order to preprocess the initial database in an automatic way, allowing time saving and better accuracy during this phase. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ consumption behavior. To validate our approach, a case study with a real database of 185 HV consumers was used.

Realistic Traffic Scenarios Using a Census Methodology: Vila Real Case Study

This paper presents the first phase of the redevelopment of the Electric Vehicle Scenario Simulator (EVeSSi) tool. A new methodology to generate traffic demand scenarios for the Simulation of Urban MObility (SUMO) tool for urban traffic simulation is described. This methodology is based on a Portugal census database to generate a synthetic population for a given area under study. A realistic case study of a Portuguese city, Vila Real, is assessed. For this area the road network was created along with a synthetic population and public transport. The traffic results were obtained and an electric buses fleet was evaluated assuming that the actual fleet would be replaced in a near future. The energy requirements to charge the electric fleet overnight were estimated in order to evaluate the impacts that it would cause in the local electricity network.

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.

The International Multilateral System: Imperatives of Change, Potential Scenarios and Suggestions for the Future

Thesis presented to satisfy the necessary requirements for obtaining a PhD degree in International Relation with specialization in Globalization and the Environment,

Multi-robot cooperative stereo for outdoor scenarios

13th International Conference on Autonomous Robot Systems (Robotica), 2013

Impacts of climate change scenarios on terrestrial productivity and biomass for energy in the Iberian Peninsula: assessment through the JSBACH model

Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente, Perfil de Gestão e Sistemas Ambientais

Credit risk stress testing: The Portuguese environment, macroeconomic scenarios and the estimation of losses for corporate sectors

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Clearing the cloudy crystal balls: Hybrid modelling for energy and climate change mitigation scenarios – A case study for Portugal

Dissertação para obtenção do Grau de Doutor em Ambiente

Toxicity of carcinogenic and non-carcinogenic Polycyclic Aromatic Hydrocarbons and their mixtures to aquatic organisms under ecologically-relevant scenarios

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous priority pollutants that tend to be trapped in aquatic sediments due to their high hydrophobicity. Nonetheless, the differential toxicological effects and mechanisms between the various classes of PAHs and their mixtures, as they invariably occur in the environment, are scarcely known, especially under ecologically-relevant scenarios. This thesis aimed at establishing a bridge between the study of mechanistic pathways and environmental monitoring of carcinogenic and non-carcinogenic PAHs, by introducing ecological-relevance in the research with model PAHs. A first bioassay conducted in situ with the mussel Mytilus edulis demonstrated that, dredging operations in harbours increase PAH bioavailability, eliciting genotoxicity, and showed that established environmental guidelines underestimate risk. Subsequent ex situ bioassays were performed with the carcinogenic benzo[b]fluoranthene (B[b]F) and non-carcinogenic phenantrene (Phe), selected following preceding results, and revealed that low-moderate concentrations of these PAHs in spiked sediments induce genotoxic effects to the clam Ruditapes decussatus, therefore contradicting the general notion that bivalves are less sensitive to PAHs than vertebrates due to inefficient bioactivation. Also, it was demonstrated that passive samplers permit inferring on PAH bioavailability but not on bioaccumulation or toxic effects. On the other hand, sea basses (Dicentrarchus labrax), yielded a complex pattern of effects and responses, relatively to genotoxicity, oxidative stress and production of specific metabolites, especially when exposed to mixtures of the PAHs which led to additive, if not synergistic, effects. It was shown that Phe may elicit significant genotoxicity especially in presence of B[b]F, even though the low, albeit realistic, exposure concentrations diluted dose- and time-independent relationships. The present work demonstrated that environmental quality guidelines underestimate the effects of PAHs in realistic scenarios and showed that the significant genotoxic and histopathological effects caused by mixed PAHs may not be reflected by oxidative stress- or CYP-related biomarkers. Besides important findings on the metabolism of PAH mixtures, the work calls for the need to re-evaluate the criteria for assessing risk and for the disclosure of more efficient indicators of toxicological hazard.

Clinical research monitoring: scenarios and challenges

Clinical research is essential for the development of new drugs, diagnostic tests and new devices. Clinical monitoring is implemented to improve the quality of research and attain high ethical and scientific standards. This review discusses the role of clinical monitors, taking into account the variety of scenarios in which medical research is developed, and highlights the challenges faced by research teams to ensure that patients rights are respected and that the social role of scientific research is preserved. Specific emphasis is given to the ethical dilemmas related to the multiple roles which clinical monitors play in the research framework, mainly those involving the delicate equilibrium between the loyalty to the sponsor and to the research subjects. The essential role of clinical monitoring for research developed in poor healthcare scenarios is highlighted as an approach to get the local infrastructure strengthening needed to achieve an adequate level of good clinical practices.

China and India’s Maritime Geostrategies:: Implications for International Maritime Security and Scenarios for 2030

Dissertação de Mestrado em Estratégia

Un modelo contable para la evaluación económico-financiera en escenarios futuros de la empresa agropecuaria. An accounting model for the economic and financial evaluation of future scenarios in farm enterprises.

El problema: En todo momento y sobre todo cuando estamos en presencia de escenarios económicos turbulentos resulta imprescindible utilizar herramientas que permitan realizar análisis de sensitividad sobre las distintas situaciones que podrían plantearse. La elaboración de modelos matemáticos deterministas desde las aplicaciones realizadas por Richard Mattessich han constituido un instrumento idóneo para el caso de empresas comerciales o industriales. Los modelos informáticos utilizados para las empresas agropecuarias han abordado fundamentalmente la temática relacionada con la producción, no así las otras variables económicas y financieras. Por lo tanto, entendemos que se hace necesario trabajar con modelos agropecuarios que comprendan todas las variables económicas y financieras, de manera de observar otro tipo de cuestiones, tales como: el modo de financiarse, los costos financieros, necesidades de capital de trabajo. Hipótesis: Es posible, a través de la utilización de la información contable en sentido prospectivo, interpretar adecuadamente los escenarios futuros de las organizaciones agropecuarias, cuantificando los impactos que generan tanto las estrategias y políticas aplicables, como las distorsiones del contexto. Objetivo general: determinar la incidencia de las decisiones internas y las que provengan del funcionamiento del sistema económico, a través de la información contable prospectiva. Objetivos específicos: a. Describir los impactos que se producen en la estructura patrimonial, financiera y en los resultados, como consecuencia de los cambios en las estrategias y políticas de la empresa agropecuaria, así como los efectos macroeconómicos en la estructura de la empresa que pudieran estar conmoviendo la gestión económico-financiera. b. Identificar mecanismos y proponer criterios para la elaboración de modelos que permitan visualizar los impactos en los escenarios futuros y las adecuaciones necesarias en la estructura que permitan soportar las modificaciones. Metodología: será un estudio a nivel teórico, donde una vez identificadas las variables y planteados los modelos, se propondrán distintas situaciones y se testearán las respuestas. Resultados esperados: lograr un avance en la evaluación económico-financiera prospectiva de empresas agropecuarias y constituir un avance para futuras investigaciones. Importancia del proyecto: La producción agropecuaria es vital tanto para el desarrollo económico de Argentina, como en particular para la provincia de Córdoba. Elaborar herramientas que eficientizen la administración de este tipo de empresas, redundará en beneficio colectivo. Pertinencia: El producto verificable será la construcción de un modelo distinto a los actuales, tanto en su desarrollo, objetivo al que está destinado y sencillez de su aplicación, posibilitando la inserción del productor en el proceso de planificación, reduciendo el riesgo en la toma de decisiones. Esperando generar un avance sobre los modelos preexistente.

Statistical pattern recognition for audio-forensics : empirical investigations on the application scenarios audio steganalysis and microphone forensics

Magdeburg, Univ., Fak. für Informatik, Diss., 2013