Statistical classification of road pavements using near field vehicle rolling noise measurements

Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.

Análise dos métodos de medição dos parâmetros geométricos de via e correlação entre os dados obtidos

A razão atribuída à escolha do tema do T.F.M. em Caminhos-de-ferro, tem a ver com o facto de ser uma via de comunicação específica. Contrariamente ao que acontece na execução de auto-estradas, no caminho-de-ferro, a gestora da infra-estrutura responsabiliza-se pela execução, exploração (sinalização e controlo de circulação), abastecimento de energia fornecida às vias que dispõem de catenária (tracção eléctrica), manutenção e conservação da via. O processo de análise e inspecção de geometria de via, é usado quando e necessário preservar a infra-estrutura. Este processo iniciou-se nos caminhos-de-ferro portugueses, há muitos anos, depois da inauguração do primeiro troco de linha férrea. A primeira viagem ocorre em Outubro de 1856, sendo o início do processo em 1968, com a dresina “Matisa PV-6”. Em 1991 a C.P. adquiriu outro veículo de inspecção de via, tendo sido escolhido o VIV02 EM 120 da marca Plasser & Theurer, para substituir “Matisa PV-6”. O tema Análise dos Métodos de Medição dos Parâmetros Geométricos de Via e Correlação entre os Dados Obtidos está directamente relacionado com a manutenção e conservação de via. Na Unidade Operacional Sul (hoje ROS – Região Operacional Sul), local onde desenvolvi o T.F.M., não existem obras de construção de caminhos-de-ferro que pudesse acompanhar e constituir tema para o meu trabalho. Na realidade, com a falta de investimento que se perspectiva no futuro próximo, a manutenção da infra-estrutura passa a ser a actividade principal desenvolvida pela REFER, de modo a assegurar a comodidade, segurança e rapidez na deslocação de cargas e pessoas. A Analise Geométrica de Via e actualmente uma das principais actividades no âmbito da manutenção, que é feita por diagnóstico, contrariamente ao que acontecia no passado em que a conservação metódica era realizada num determinado ano num troço seleccionado independentemente da necessidade ou não da mesma. Uma ajuda preciosa, no que se refere à decisão de se realizar um determinado trabalho de conservação, e a do veículo VIV02 EM 120 que faz inspeções ao longo de toda a rede ferroviária e permite recolher dados e classificar através do desvio padrão, troços com extensão de 200 metros, obtendo os dados relevantes sobre a necessidade de intervenção. Para além do referido veículo existem também equipamentos ligeiros de inspecção dos parâmetros geométricos de via. Um desses equipamentos designa-se por Trólei, não sendo motorizado, pois o mesmo é movido manualmente por um operador. Obviamente que este equipamento não faz a inspecção a toda a rede pois a operação de medição é morosa, sendo contudo utilizado para análise de defeitos geométricos em pequenos trocos, tornando-se assim uma mais-valia, evitando o deslocar de um equipamento “pesado” como o VIV 02 EM 120. Para atingir os objectivos deste trabalho realizaram-se testes de medição com ambos (veiculo e equipamento ligeiro), no mesmo espaço temporal e com as mesmas características físicas, como a temperatura, humidade etc. Os resultados, de acordo com os objectivos, são a comparação entre as medições de ambos, com vista a comprovar a sua utilidade e necessidade, de acordo com os vários tipos de superstruturas constituintes da rede ferroviária nacional.

Geostatistical Mapping of Outfall Plume Dispersion Data gathered with an autonomous underwater vehicle

The main purpose of this study was to examine the applicability of geostatistical modeling to obtain valuable information for assessing the environmental impact of sewage outfall discharges. The data set used was obtained in a monitoring campaign to S. Jacinto outfall, located off the Portuguese west coast near Aveiro region, using an AUV. The Matheron’s classical estimator was used the compute the experimental semivariogram which was fitted to three theoretical models: spherical, exponential and gaussian. The cross-validation procedure suggested the best semivariogram model and ordinary kriging was used to obtain the predictions of salinity at unknown locations. The generated map shows clearly the plume dispersion in the studied area, indicating that the effluent does not reach the near by beaches. Our study suggests that an optimal design for the AUV sampling trajectory from a geostatistical prediction point of view, can help to compute more precise predictions and hence to quantify more accurately dilution. Moreover, since accurate measurements of plume’s dilution are rare, these studies might be very helpful in the future for validation of dispersion models.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.

Integrated vehicle classification system

This paper presents an integrated system for vehicle classification. This system aims to classify vehicles using different approaches: 1) based on the height of the first axle and_the number of axles; 2) based on volumetric measurements and; 3) based on features extracted from the captured image of the vehicle. The system uses a laser sensor for measurements and a set of image analysis algorithms to compute some visual features. By combining different classification methods, it is shown that the system improves its accuracy and robustness, enabling its usage in more difficult environments satisfying the proposed requirements established by the Portuguese motorway contractor BRISA.

Particle swarm optimization based approaches to vehicle-to-grid scheduling

This paper addresses the problem of energy resources management using modern metaheuristics approaches, namely Particle Swarm Optimization (PSO), New Particle Swarm Optimization (NPSO) and Evolutionary Particle Swarm Optimization (EPSO). The addressed problem in this research paper is intended for aggregators’ use operating in a smart grid context, dealing with Distributed Generation (DG), and gridable vehicles intelligently managed on a multi-period basis according to its users’ profiles and requirements. The aggregator can also purchase additional energy from external suppliers. The paper includes a case study considering a 30 kV distribution network with one substation, 180 buses and 90 load points. The distribution network in the case study considers intense penetration of DG, including 116 units from several technologies, and one external supplier. A scenario of 6000 EVs for the given network is simulated during 24 periods, corresponding to one day. The results of the application of the PSO approaches to this case study are discussed deep in the paper.

Intelligent electric vehicle heuristic for energy resource management using simulated annealing

The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

Smart Electric Vehicle Charging System

In this work is proposed the design of a system to create and handle Electric Vehicles (EV) charging procedures, based on intelligent process. Due to the electrical power distribution network limitation and absence of smart meter devices, Electric Vehicles charging should be performed in a balanced way, taking into account past experience, weather information based on data mining, and simulation approaches. In order to allow information exchange and to help user mobility, it was also created a mobile application to assist the EV driver on these processes. This proposed Smart ElectricVehicle Charging System uses Vehicle-to-Grid (V2G) technology, in order to connect Electric Vehicles and also renewable energy sources to Smart Grids (SG). This system also explores the new paradigm of Electrical Markets (EM), with deregulation of electricity production and use, in order to obtain the best conditions for commercializing electrical energy.

Intelligent energy resource management considering vehicle-to-grid: A simulated annealing approach

This paper proposes a simulated annealing (SA) approach to address energy resources management from the point of view of a virtual power player (VPP) operating in a smart grid. Distributed generation, demand response, and gridable vehicles are intelligently managed on a multiperiod basis according to V2G user´s profiles and requirements. Apart from using the aggregated resources, the VPP can also purchase additional energy from a set of external suppliers. The paper includes a case study for a 33 bus distribution network with 66 generators, 32 loads, and 1000 gridable vehicles. The results of the SA approach are compared with a methodology based on mixed-integer nonlinear programming. A variation of this method, using ac load flow, is also used and the results are compared with the SA solution using network simulation. The proposed SA approach proved to be able to obtain good solutions in low execution times, providing VPPs with suitable decision support for the management of a large number of distributed resources.

Electric vehicle scenario simulator tool for smart grid operators

This paper presents a simulator for electric vehicles in the context of smart grids and distribution networks. It aims to support network operator´s planning and operations but can be used by other entities for related studies. The paper describes the parameters supported by the current version of the Electric Vehicle Scenario Simulator (EVeSSi) tool and its current algorithm. EVeSSi enables the definition of electric vehicles scenarios on distribution networks using a built-in movement engine. The scenarios created with EVeSSi can be used by external tools (e.g., power flow) for specific analysis, for instance grid impacts. Two scenarios are briefly presented for illustration of the simulator capabilities.

Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints

Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for dayahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle- o-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the user´s requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33 bus distribution network and V2G is used to illustrate the good performance of the proposed method.

The electric vehicle integration into the power system: an application to the portuguese case

Electric vehicles (EV) offer a great potential to address the integration of renewable energy sources (RES) in the power grid, and thus reduce the dependence on oil as well as the greenhouse gases (GHG) emissions. The high share of wind energy in the Portuguese energy mix expected for 2020 can led to eventual curtailment, especially during the winter when high levels of hydro generation occur. In this paper a methodology based on a unit commitment and economic dispatch is implemented, and a hydro-thermal dispatch is performed in order to evaluate the impact of the EVs integration into the grid. Results show that the considered 10 % penetration of EVs in the Portuguese fleet would increase load in 3 % and would not integrate a significant amount of wind energy because curtailment is already reduced in the absence of EVs. According to the results, the EV is charged mostly with thermal generation and the associated emissions are much higher than if they were calculated based on the generation mix.

Automatic vehicle detection and classification

This paper presents a proposal for an automatic vehicle detection and classification (AVDC) system. The proposed AVDC should classify vehicles accordingly to the Portuguese legislation (vehicle height over the first axel and number of axels), and should also support profile based classification. The AVDC should also fulfill the needs of the Portuguese motorway operator, Brisa. For the classification based on the profile we propose:he use of Eigenprofiles, a technique based on Principal Components Analysis. The system should also support multi-lane free flow for future integration in this kind of environments.

Sistema de visão para percepção e navegação de um UAV Quadrotor

Mestrado em Engenharia Electrotécnica e de Computadores

Coordenação de veículo de inspecção subaquática com veículo de superfície autónomo

O LSA/ISEP(Laboratório de sistemas Autónomos do Instituto Superior de Engenharia do Porto) tem vindo nos últimos anos a desenvolver sistemas robóticos inovadores para operação em ambiente marinho sendo o veículo de superfície autónomo ROAZ II um exemplo de renome internacional. Neste contexto, e tendo em vista a satisfação dos requisitos parciais conducentes à obtenção do grau de Mestre em Eng. Electrotécnica e de Computadores - Ramo de Sistemas Autónomos do ISEP, o presente trabalho visou a integração de um robô submarino operado remotamente (ROV) com o robô de superfície ROAZ II. Esta solução inovadora de operação coordenada e integrada de um ASV/ROV permite dotar o ASV de mobilidade e visão subaquática. Após a caracterização e análise de requisitos de diversos cenários operacionais foi apresentada uma arquitectura de controlo coordenado dos dois veículos baseada em manobras de controlo descritas por autómatos híbridos. Os dois veículos foram modelados e as manobras coordenadas projectadas foram validadas com um simulador em ambiente Matlab/Simulink. Foi desenvolvido um sistema de localização relativa do ROV através da fusão sensorial de um sistema INS com um sistema acústico USBL utilizando um filtro EKF. O veículo ROV (VideoRay) do LSA foi instrumentado com os sensores necessários e efectuada a integração de hardware e software com o ASV ROAZ II permitindo a operação remota. Foi realizada uma missão demonstrativa de inspecção de pilares subaquáticos em cenário real com a operação conjunta dos dois robôs.