Statistics for Spatial Data.

With digital equipment becoming increasingly networked, either on wired or wireless networks, for personal and professional use alike, distributed software systems have become a crucial element in information and communications technologies. The study of these systems forms the core of the ARLES' work, which is specifically concerned with defining new system software architectures, based on the use of emerging networking technologies. In this context, we concentrate on the study of distributed systems which bring to life the vision of ubiquitous computing systems, also known as ambient intelligence.

반도체 공정 overview

http://ieeexplore.ieee.org/iel5/5610941/5624686/05624745.pdf

Power electronics

Solar photovoltaic generation forecasting methods: A review

A Maximum Power Point Tracking (MPPT) for PV system using Cuckoo Search with partial shading capability

Photovoltaic field emulation including dynamic and partial shadow conditions

Modeling of photovoltaic sources and their emulation by means of power electronic converters are challenging issues. The former is tied to the knowledge of the electrical behavior of the PV generator; the latter consists in its realization by a suitable power amplifier. This extensive introduction to the modeling of PV generators and their emulation by means of power electronic converters will aid in understanding and improving design and set up of new PV plants. The main benefit of reading Photovoltaic Sources is the ability to face the emulation of photovoltaic generators obtained by the design of a suitable equipment in which voltage and current are the same as in a real source. This is achieved according to the following steps: the source electrical behavior modeling, the power converter design, including its control, for the laboratory emulator. This approach allows the reader to cope with the creation of an indoor virtual photovoltaic plant, in which the environmental conditions can be imposed by the user, for testing real operation including maximum power point tracking, partial shading, control for the grid or load interfacing, etc. Photovoltaic Sources is intended to meet the demands of postgraduate level students, and should prove useful to professional engineers and researchers dealing with the problems associated with modeling and emulation of photovoltaic sources.

Photovoltaic Sources: Modeling and Emulation

This paper presents the design of an electromagnetic interference (EMI) filter for a low-voltage high-current induction-motor drives supplied by dc power grids. In order to effectively design the EMI filter, a suitable common-mode/differential-mode (CM/DM) separation technique has been used. Due to the high operating currents, the software-based separation technique using time-domain measurements has been applied. The proposed technique allows the CM and DM sections of the EMI filter to be properly selected in a more economical way, i.e., without the need of a dedicated hardware or costly radio frequency (RF) instrumentation. The design has been done according to a power-density criterion. The effectiveness of the proposed CM/DM separation technique and the EMI filter features/performance has been assessed by experimental tests, carried out with an 1.1-kW pulsewidth modulation (PWM) inverter-fed induction-motor drive, supplied by a 48-V dc power grid.

/pdf/design-and-performance-evaluation-of-a-high-power-density-514uzj2lc0.pdf

Design and Performance Evaluation of a High Power-Density EMI Filter for PWM Inverter-Fed Induction-Motor Drives

The nonlinear autoregressive network with exogenous input (NARX) is used to perform hourly solar irradiation and wind speed forecasting, according to a multi-step ahead approach. Temperature has been considered as the exogenous variable. The NARX topology selection is supported by a combined use of two techniques: (1) a genetic algorithm (GA)-based optimization technique and (2) a method that determines the optimal network architecture by pruning (optimal brain surgeon (OBS) strategy). The considered variables are observed at hourly scale in a seven year dataset and the forecasting is done for several time horizons in the range from 8 to 24 h ahead.

/pdf/solar-and-wind-forecasting-by-narx-neural-networks-1ynhvr5okk.pdf

Solar and wind forecasting by NARX neural networks

Recent literature proposes some approaches that employ explicit equations for identifying the five parameters of the single-diode model describing a photovoltaic (PV) panel These methods avoid the iterative solution of a nonlinear system of equations, whose convergence is very sensitive to the guess solution Therefore, they are particularly suitable to perform parameter identification in real time and to be implemented on low-cost, low-performance processing platforms In this paper, the applicability of some explicit methods, previously validated under standard test conditions, is analyzed for a large class of panels under operating conditions that are different from the standard ones The study considers both a consolidated method for translating the PV model parameters as well as a novel approach The analysis allows assessing the most suitable parameter translation equations for each considered explicit identification method, highlighting the effectiveness of such explicit approaches under different operating conditions An in-depth validation based on experimental data concerning two commercial PV panels corroborates the analysis

Maria Carmela Di Piazza

Papers

Photovoltaic field emulation including dynamic and partial shadow conditions

Photovoltaic Sources: Modeling and Emulation

Design and Performance Evaluation of a High Power-Density EMI Filter for PWM Inverter-Fed Induction-Motor Drives

Solar and wind forecasting by NARX neural networks

Translation of the Single-Diode PV Model Parameters Identified by Using Explicit Formulas