On Real-Time Monitoring And Control For Efficient Management Of Drinking Water Networks: Barcelona Case Study

Drinking water utilities in urban areas are focused on finding smart solutions facing new challenges in their real-time operation because of limited water resources, intensive energy requirements, a growing population, a costly and ageing infrastructure, increasingly stringent regulations, and increased attention towards the environmental impact of water use. Such challenges force water managers to monitor and control not only water supply and distribution, but also consumer demand. This paper presents and discusses novel methodologies and procedures towards an integrated water resource management system based on advanced ICT technologies of automation and telecommunications for largely improving the efficiency of drinking water networks (DWN) in terms of water use, energy consumption, water loss minimization, and water quality guarantees. In particular, the paper addresses the first results of the European project EFFINET (FP7-ICT2011-8-318556) devoted to the monitoring and control of the DWN in Barcelona (Spain). Results are split in two levels according to different management objectives: (i) the monitoring level is concerned with all the aspects involved in the observation of the current state of a system and the detection/diagnosis of abnormal situations. It is achieved through sensors and communications technology, together with mathematical models; (ii) the control level is concerned with computing the best suitable and admissible control strategies for network actuators as to optimize a given set of operational goals related to the performance of the overall system. This level covers the network control (optimal management of water and energy) and the demand management (smart metering, efficient supply). The consideration of the Barcelona DWN as the case study will allow to prove the general applicability of the proposed integrated ICT solutions and their effectiveness in the management of DWN, with considerable savings of electricity costs and reduced water loss while ensuring the high European standards of water quality to citizens.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Applied models to biodegradation kinetics of lubricant and vegetable oils in wastewater

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Non-linear growth models for bullfrog tadpoles

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Laser interferometric characterization of a vibrating speaker system

An experiment that combines opto-mechanical and electrical measurements for the characterization of a loudspeaker is presented. We describe a very simple laser vibrometer for evaluating the amplitude of the vibration (displacement) of the speaker cone. The setup is essentially a Michelson-type interferometer operated by an inexpensive semiconductor laser (diode laser). It is shown that the simultaneous measurements of three amplitudes (displacement, electrical current, and applied voltage), as functions of the frequency of vibration, allow us to characterize the speaker system. The experiment is easy to perform, and it demonstrates several useful concepts of optics, mechanics, and electricity, allowing, students to gain an intuitive physical insight into the relations between mathematical models and, an actual speaker system. (C) 2003 American Association of Physics Teachers.

Evaluation and identification of lightning models by artificial neural networks

This paper describes a novel approach for mapping lightning models using artificial neural networks. The networks acts as identifier of structural features of the lightning models so that output parameters can be estimated and generalized from an input parameter set. Simulation examples are presented to validate the proposed approach. More specifically, the neural networks are used to compute electrical field intensity and critical disruptive voltage taking into account several atmospheric and structural factors, such as pressure, temperature, humidity, distance between phases, height of bus bars, and wave forms. A comparative analysis with other approaches is also provided to illustrate this new methodology.

Distribution line models analysis for loss calculation within three-phase three-wire power flow algorithms

Three-phase three-wire power flow algorithms, as any tool for power systems analysis, require reliable impedances and models in order to obtain accurate results. Kron's reduction procedure, which embeds neutral wire influence into phase wires, has shown good results when three-phase three-wire power flow algorithms based on current summation method were used. However, Kron's reduction can harm reliabilities of some algorithms whose iterative processes need loss calculation (power summation method). In this work, three three-phase three-wire power flow algorithms based on power summation method, will be compared with a three-phase four-wire approach based on backward-forward technique and current summation. Two four-wire unbalanced medium-voltage distribution networks will be analyzed and results will be presented and discussed. © 2004 IEEE.

Remarks on orthotropic elastic models applied to wood

Wood is generally considered an anisotropic material. In terms of engineering elastic models, wood is usually treated as an orthotropic material. This paper presents an analysis of two principal anisotropic elastic models that are usually applied to wood. The first one, the linear orthotropic model, where the material axes L (Longitudinal), R(radial) and T(tangential) are coincident with the Cartesian axes (x, y, z), is more accepted as wood elastic model. The other one, the cylindrical orthotropic model is more adequate of the growth caracteristics of wood but more mathematically complex to be adopted in practical terms. Specifically due to its importance in wood elastic parameters, this paper deals with the fiber orientation influence in these models through adequate transformation of coordinates. As a final result, some examples of the linear model, which show the variation of elastic moduli, i.e., Young's modulus and shear modulus, with fiber orientation are presented.

Thermoeconomic model considering the environment impacts on thermoelectric power plants: Natural gas versus diesel

In this paper a comparative analysis of the environmental impact caused by the use of natural gas and diesel in thermoelectric power plants utilizing combined cycle is performed. The objective is to apply a thermoeconomical analysis in order to compare the two proposed fuels. In this analysis, a new methodology that incorporates the economical engineering concept to the ecological efficiency once Cardu and Baica [1, 2], which evaluates, in general terms, the environmental impacts caused by CO2, SO2, NOx and Particulate Matter (PM), adopting as reference the air quality standards in vigour is employed. The thermoeconomic model herein proposed utilizes functional diagrams that allow the minimization the Exergetic Manufacturing Cost, which represents the cost of production of electricity incorporating the environmental impact effects to study the performance of the thermoelectric power plant [3,4], It follows that it is possible to determine the environmental impact caused by thermoelectric power plants and, under the ecological standpoint, the use of natural gas as a fuel is the best option compared to the use of the diesel, presenting ecological efficiency values of 0.944 and 0.914 respectively. From the Exergoeconomic point of view of, it was found out that the EMC (Exergetic Manufacturing Cost) is better when natural gas is used as fuel compared to the diesel fuel. Copyright © 2006 by ASME.

Damage detection in a benchmark structure using AR-ARX models and statistical pattern recognition

Structural health monitoring (SHM) is related to the ability of monitoring the state and deciding the level of damage or deterioration within aerospace, civil and mechanical systems. In this sense, this paper deals with the application of a two-step auto-regressive and auto-regressive with exogenous inputs (AR-ARX) model for linear prediction of damage diagnosis in structural systems. This damage detection algorithm is based on the. monitoring of residual error as damage-sensitive indexes, obtained through vibration response measurements. In complex structures there are. many positions under observation and a large amount of data to be handed, making difficult the visualization of the signals. This paper also investigates data compression by using principal component analysis. In order to establish a threshold value, a fuzzy c-means clustering is taken to quantify the damage-sensitive index in an unsupervised learning mode. Tests are made in a benchmark problem, as proposed by IASC-ASCE with different damage patterns. The diagnosis that was obtained showed high correlation with the actual integrity state of the structure. Copyright © 2007 by ABCM.

Generating VHDL-AMS models of digital-to-analogue converters from MATLAB®/SIMULINK®

Today, the trend within the electronics industry is for the use of rapid and advanced simulation methodologies in association with synthesis toolsets. This paper presents an approach developed to support mixed-signal circuit design and analysis. The methodology proposed shows a novel approach to the problem of developing behvioural model descriptions of mixed-signal circuit topologies, by construction of a set of subsystems, that supports the automated mapping of MATLAB®/SIMULINK® models to structural VHDL-AMS descriptions. The tool developed, named MS 2SV, reads a SIMULINK® model file and translates it to a structural VHDL-AMS code. It also creates the file structure required to simulate the translated model in the System Vision™. To validate the methodology and the developed program, the DAC08, AD7524 and AD5450 data converters were studied and initially modelled in MATLAB®/ SIMULINK®. The VHDL-AMS code generated automatically by MS 2SV, (MATLAB®/SIMULINK® to System Vision™), was then simulated in the System Vision™. The simulation results show that the proposed approach, which is based on VHDL-AMS descriptions of the original model library elements, allows for the behavioural level simulation of complex mixed-signal circuits.

Towards forecasting and mitigating ionospheric scintillation effects on GNSS

The effect of the ionosphere on the signals of Global Navigation Satellite Systems (GNSS), such as the Global Positionig System (GPS) and the proposed European Galileo, is dependent on the ionospheric electron density, given by its Total Electron Content (TEC). Ionospheric time-varying density irregularities may cause scintillations, which are fluctuations in phase and amplitude of the signals. Scintillations occur more often at equatorial and high latitudes. They can degrade navigation and positioning accuracy and may cause loss of signal tracking, disrupting safety-critical applications, such as marine navigation and civil aviation. This paper addresses the results of initial research carried out on two fronts that are relevant to GNSS users if they are to counter ionospheric scintillations, i.e. forecasting and mitigating their effects. On the forecasting front, the dynamics of scintillation occurrence were analysed during the severe ionospheric storm that took place on the evening of 30 October 2003, using data from a network of GPS Ionospheric Scintillation and TEC Monitor (GISTM) receivers set up in Northern Europe. Previous results [1] indicated that GPS scintillations in that region can originate from ionospheric plasma structures from the American sector. In this paper we describe experiments that enabled confirmation of those findings. On the mitigation front we used the variance of the output error of the GPS receiver DLL (Delay Locked Loop) to modify the least squares stochastic model applied by an ordinary receiver to compute position. This error was modelled according to [2], as a function of the S4 amplitude scintillation index measured by the GISTM receivers. An improvement of up to 21% in relative positioning accuracy was achieved with this technnique.

Modelo AC para el despacho combinado de contratos bilaterales y bolsa de energía considerando restricciones de seguridad

Reliability is a key aspect in power system design and planning. Maintaining a reliable power system is a very important issue for their design and operation. Under the new competitive framework of the electricity sector, power systems find ever more and more strained to operate near their limits. Under this new scenario, it is crucial for the system operator to use tools that facilitate an energy dispatch that minimizes possible power cuts. This paper presents a mathematical model to calculate an energy dispatch that considers security constraints (single contingencies in transmission lines and transformers). The model involves pool markets and fixed bilateral contracts. Traditional methodologies that include security constraints are usually based in multistage dispatch processes. In this case, we propose a single-stage model that avoids the economic inefficiencies which result when conventional multi-stage dispatch approaches are applied. The proposed model includes an AC representation of the transport system and allows calculating the cost overruns incurred in due to reliability restrictions. We found that complying with fixed bilateral contracts, when they go above certain levels, might lead to congestion problems in transmission lines.

Improving the grid operation and reliability cost of distribution systems with dispersed generation

In this work, a mathematical model to analyze the impact of the installation and operation of dispersed generation units in power distribution systems is proposed. The main focus is to determine the trade-off between the reliability and operational costs of distribution networks when the operation of isolated areas is allowed. In order to increase the system operator revenue, an optimal power flow makes use of the different energy prices offered by the dispersed generation connected to the grid. Simultaneously, the type and location of the protective devices initially installed on the protection system are reconfigured in order to minimize the interruption and expenditure of adjusting the protection system to conditions imposed by the operation of dispersed units. The interruption cost regards the unsupplied energy to customers in secure systems but affected by the normal tripping of protective devices. Therefore, the tripping of fuses, reclosers, and overcurrent relays aims to protect the system against both temporary and permanent fault types. Additionally, in order to reduce the average duration of the system interruption experienced by customers, the isolated operation of dispersed generation is allowed by installing directional overcurrent relays with synchronized reclose capabilities. A 135-bus real distribution system is used in order to show the advantages of using the mathematical model proposed. © 1969-2012 IEEE.

Modelos matemáticos aplicados a problemas na cultura da cana-de-açúcar e no aproveitamento da energia da biomassa

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)