PV systems linked to the grid: parameter identification with a heuristic procedure

This paper focuses on a PV system linked to the electric grid by power electronic converters, identification of the five parameters modeling for photovoltaic systems and the assessment of the shading effect. Normally, the technical information for photovoltaic panels is too restricted to identify the five parameters. An undemanding heuristic method is used to find the five parameters for photovoltaic systems, requiring only the open circuit, maximum power, and short circuit data. The I- V and the P- V curves for a monocrystalline, polycrystalline and amorphous photovoltaic systems are computed from the parameters identification and validated by comparison with experimental ones. Also, the I- V and the P- V curves under the effect of partial shading are obtained from those parameters. The modeling for the converters emulates the association of a DC-DC boost with a two-level power inverter in order to follow the performance of a testing commercial inverter employed on an experimental system. © 2015 Elsevier Ltd.

Simulation of a-Si PV system grid connected by boost and inverter

This paper is about a PV system connected to the electric grid by power electronic converters, using classical PI controller. The modelling for the converters emulates the association of a DC-DC boost with a two-level power inverter (TwLI) or three-level power inverter (ThLI) in order to follow the performance of a testing experimental system. Pulse width modulation (PWMo) by sliding mode control (SMCo) associated with space vector modulation (SVMo) is applied to the boost and the inverter. The PV system is described by the five parameters equivalent circuit. Parameter identification and simulation studies are performed for comparison with the testing experimental system.

Measuring and Controlling the Chaotic Motion of Profits

The study of economic systems has generated deep interest in exploring the complexity of chaotic motions in economy. Due to important developments in nonlinear dynamics, the last two decades have witnessed strong revival of interest in nonlinear endogenous business chaotic models. The inability to predict the behavior of dynamical systems in the presence of chaos suggests the application of chaos control methods, when we are more interested in obtaining regular behavior. In the present article, we study a specific economic model from the literature. More precisely, a system of three ordinary differential equations gather the variables of profits, reinvestments and financial flow of borrowings in the structure of a firm. Firstly, using results of symbolic dynamics, we characterize the topological entropy and the parameter space ordering of kneading sequences, associated with one-dimensional maps that reproduce significant aspects of the model dynamics. The analysis of the variation of this numerical invariant, in some realistic system parameter region, allows us to quantify and to distinguish different chaotic regimes. Finally, we show that complicated behavior arising from the chaotic firm model can be controlled without changing its original properties and the dynamics can be turned into the desired attracting time periodic motion (a stable steady state or into a regular cycle). The orbit stabilization is illustrated by the application of a feedback control technique initially developed by Romeiras et al. [1992]. This work provides another illustration of how our understanding of economic models can be enhanced by the theoretical and numerical investigation of nonlinear dynamical systems modeled by ordinary differential equations.

Análise energética, otimização e modernização dos sistemas de um grande edifício de serviços na ótica da melhoria da eficiência energética

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica Perfil Energia, Refrigeração e Climatização

Water-Based Cellulose Liquid Crystal System Investigated by Rheo-NMR

Water-based cellulose cholesteric liquid crystalline phases at rest can undergo structural changes induced by shear flow. This reflects on the deuterium spectra recorded when the system is investigated by rheo-nuclear magnetic resonance (rheo-NMR) techniques. In this work, the model system hydroxypropylcellulose (HPC)+water is revisited using rheo-NMR to clarify unsettled points regarding its behavior under shear and in relaxation. The NMR spectra allow the identification of five different stable ordering states, within shear and relaxation, which are well integrated in a mesoscopic picture of the system's structural evolution under shear and relaxation. This picture emerging from the large body of studies available for this system by other experimental techniques, accounts well for the NMR data and is in good agreement with the three distinct regions of steady shear flow recognized for some lyotropic LC polymers. Shear rates in between 0.1 and 1.0 s(-1) where investigated using a Taylor-Couette flow and deuterated water was used as solvent for the deuterium NMR (DNMR) analysis.

PV system modeling by five parameters and in situ test

This paper focuses on a novel formalization for assessing the five parameter modeling of a photovoltaic cell. An optimization procedure is used as a feasibility problem to find the parameters tuned at the open circuit, maximum power, and short circuit points in order to assess the data needed for plotting the I-V curve. A comparison with experimental results is presented for two monocrystalline PV modules.

Effect of technical parameters on dose and image quality in a computed radiography system

The discovery of X-rays was undoubtedly one of the greatest stimulus for improving the efficiency in the provision of healthcare services. The ability to view, non-invasively, inside the human body has greatly facilitated the work of professionals in diagnosis of diseases. The exclusive focus on image quality (IQ), without understanding how they are obtained, affect negatively the efficiency in diagnostic radiology. The equilibrium between the benefits and the risks are often forgotten. It is necessary to adopt optimization strategies to maximize the benefits (image quality) and minimize risk (dose to the patient) in radiological facilities. In radiology, the implementation of optimization strategies involves an understanding of images acquisition process. When a radiographer adopts a certain value of a parameter (tube potential [kVp], tube current-exposure time product [mAs] or additional filtration), it is essential to know its meaning and impact of their variation in dose and image quality. Without this, any optimization strategy will be a failure. Worldwide, data show that use of x-rays has been increasingly frequent. In Cabo Verde, we note an effort by healthcare institutions (e.g. Ministry of Health) in equipping radiological facilities and the recent installation of a telemedicine system requires purchase of new radiological equipment. In addition, the transition from screen-films to digital systems is characterized by a raise in patient exposure. Given that this transition is slower in less developed countries, as is the case of Cabo Verde, the need to adopt optimization strategies becomes increasingly necessary. This study was conducted as an attempt to answer that need. Although this work is about objective evaluation of image quality, and in medical practice the evaluation is usually subjective (visual evaluation of images by radiographer / radiologist), studies reported a correlation between these two types of evaluation (objective and subjective) [5-7] which accredits for conducting such studies. The purpose of this study is to evaluate the effect of exposure parameters (kVp and mAs) when using additional Cooper (Cu) filtration in dose and image quality in a Computed Radiography system.

PV system modeling by five parameters and in Situ test

This paper focuses on a novel formalization for assessing the five parameter modeling of a photovoltaic cell. An optimization procedure is used as a feasibility problem to find the parameters tuned at the open circuit, maximum power, and short circuit points in order to assess the data needed for plotting the I-V curve. A comparison with experimental results is presented for two monocrystalline PV modules.

Embedded system for individual recognition based on ECG biometrics

Biometric recognition is emerging has an alternative solution for applications where the privacy of the information is crucial. This paper presents an embedded biometric recognition system based on the Electrocardiographic signals (ECG) for individual identification and authentication. The proposed system implements a real-time state-of-the-art recognition algorithm, which extracts information from the frequency domain. The system is based on a ARM Cortex 4. Preliminary results show that embedded platforms are a promising path for the implementation of ECG-based applications in real-world scenario.

Biometric recognition system using low bandwidth ECG signals

Biometric recognition has recently emerged as part of applications where the privacy of the information is crucial, as in the health care field. This paper presents a biometric recognition system based on the Electrocardiographic signal (ECG). The proposed system is based on a state-of-the-art recognition method which extracts information from the frequency domain. In this paper we propose a new method to increase the spectral resolution of low bandwidth ECG signals due to the limited bandwidth of the acquisition sensor. Preliminary results show that the proposed scheme reveals a higher identification rate and lower equal error rate when compared to previous approaches.