HOT-SPOT PHENOMENON IN PV SYSTEMS WITH OVERHEAD LINES PARTIAL SHADING

This paper deals with the occurrence of hot-spot phenomenon in photovoltaic systems under PV partial shadowing. In an experimental campaign, the hot-spot phenomenon was revealed on a PV installation in Italy, caused my medium voltage overhead lines shadowing the PV cells. Starting from these practice case studies, at the SolarTech laboratory of Politecnico di Milano, the conditions for hot-spot phenomenon occurrence due to the overhead lines shading the PV cells were reproduced. Two experimental campaigns were carried out to investigate the current-voltage and power-voltage characteristics, and the energy production. In each experimental campaign, the built shadowing structure was considered fixed, and different shadowing conditions were created based on the natural displacement of the sun. Still, for occurring the hot- spot phenomenon during the laboratory tests, more PV modules must be connected in parallel

Analysis and validation of 24 hours ahead neural network forecasting of photovoltaic output power

In this paper an artificial neural network for photovoltaic plant energy forecasting is proposed and analyzed in terms of its sensitivity with respect to the input data sets. Furthermore, the accuracy of the method has been studied as a function of the training data sets and error definitions. The analysis is based on experimental activities carried out on a real photovoltaic power plant accompanied by clear sky model. In particular, this paper deals with the hourly energy prediction for all the daylight hours of the following day, based on 48 hours ahead weather forecast. This is very important due to the predictive features requested by smart grid application: renewable energy sources planning, in particular storage system sizing, and market of energy

Hybrid Predictive Models for Accurate Forecasting in PV Systems

The accurate forecasting of energy production from renewable sources represents an important topic also looking at different national authorities that are starting to stimulate a greater responsibility towards plants using non-programmable renewables. In this paper the authors use advanced hybrid evolutionary techniques of computational intelligence applied to photovoltaic systems forecasting, analyzing the predictions obtained by comparing different definitions of the forecasting error

PHOTOVOLTAIC PRODUCTION MANAGEMENT IN STOCHASTIC OPTIMIZED MICROGRIDS

The microgrids are composed of small scale fueled generation capacities, renewable energy sources, storage energy systems, controllable loads, and autonomously can connect or disconnect from the mains supply. The microgrids can operate connected to the upstream main grid, or in an islanded operation mode following a large perturbation in the upstream grid. The microgrid analyzed in this paper is composed of a photovoltaic system, a thermal engine, an electrochemical storage system, critical and interruptible loads. As backup generation is considered a classical generation engine and a small scale storage unit. The autonomous switching between grid-connected and islanding operation modes can occur, under an excess/deficit of generation and function of the electricity market price. The paper deals with an optimization model for minimizing the microgrid operation costs under intermittent generation and variable demand function of microgrid operation constrains. The optimization model is tested on a 24 hours horizon. The gridconnected optimized operation accounts also the exchanged power with the upstream grid function of the electricity price within the public network

Performance analysis of grid-connected wind turbines

The development of wind turbines (WT) and the capacities of wind power plants have increased significantly in the last years. Wind power plants (WPP) must provide the power quality required by new regulations and the reliability of the power system that is interconnected to. It is very important to analyze and understand the sources of disturbances that affect the power quality. In this paper is analyzed the performance of three different popular wind generators that are connected to the power system. Based on this analysis was made a comparison for the three wind turbines studied that are: The squirrel-cage induction generator (SCIG), the doubly-fed induction generator (DFIG), and the permanent-magnet synchronous generator (PMSG). The fixed speed system is more simple and reliable, but severely limits the energy production of a wind turbine and power quality. In case of variable speed systems, comparisons shows that generator of similar rating can significantly enhance energy capture as well as power quality. Moreover, performance of their output power leveling is validated by a new method numerically as maximum energy function and leveling function. The performances of these wind turbines and their characteristics are analysed in steady-state. Wind turbines systems are modeled in Matlab/Simulink environment. Simulation results matched well with the theoretical turbines operation

Light Unmanned Aerial Vehicles (UAVs) for cooperative inspection of PV plants

After a fast photovoltaic (PV) expansion in the past decade supported by many governments in Europe, in this postincentive era, one of the most significant open issues in the PV sector is to find appropriate inspection methods to evaluate real PV plant performance and failures. In this context, PV modules are surely the key components affecting the overall system performance; therefore, there is a main concern about the occurrence of any kind of failure in PV modules. This paper aims to propose a novel concept for monitoring PV plants by using light unmanned aerial vehicles (UAVs) or systems (UASs) during their operation and maintenance. The main objectives of this study are to explore and evaluate the use of different UAV technologies and to propose a reliable, cost-effective, and time-saving method for the inspection of PV plants. In this research, different UAVs were employed to inspect a PV array field. For this purpose, some thermal imaging cameras and a visual camera were chosen as monitoring tools to suitably scan PV modules. The first results show that the procedure of utilizing UAV was effective in the detection of different failures of PV modules. Moreover, such a process was much faster and cost effective than traditional methods

The optimum PV plant for a given solar DC/AC converter

In recent years, energy production by renewable sources is becoming very important, and photovoltaic (PV) energy has became one of the main renewable sources that is widely available and easily exploitable. In this context, it is necessary to find correct tools to optimize the energy production by PV plants. In this paper, by analyzing available solar irradiance data, an analytical expression for annual DC power production for some selected places is introduced. A general efficiency curve is extracted for different solar inverter types, and by applying approximated function, a new analytical method is proposed to estimate the optimal size of a grid-connected PV plant linked up to a specific inverter from the energetic point of view. An exploitable energy objective function is derived, and several simulations for different locations have been provided. The derived analytical expression contains only the available data of the inverter (such as efficiency, nominal power, etc.) and the PV plant characteristics (such as location and PV nominal power)

Well-being of suckling calves under two different rearing systems: case study in the central milk basin of Argentina

En el presente trabajo se llevo a cabo un estudio de caso con enfoque cuantitativo. El objetivo de este estudio fue evaluar el bienestar en teneros lechales durante la época invernal bajo dos diferentes sistemas de crianza, que se utilizan en la zona. Los terneros, se alojaron en dos sistemas: en estaca los machos y en jaula las hembras. Los animales recibieron dos tomas diarias de leche (4 l/día), balanceado iniciador y agua ad libitum. Se registraron pesos iníciales y finales. La ganancia de peso se analizó mediante técnicas estadísticas descriptivas. Se tomaron muestra de saliva para determinar cortisol (CS) en cuatro momentos del día. Los datos fueron analizados para detectar variaciones horarias. El CS no mostró fluctuaciones diarias. Durante quince días y día por medio, se registraron las conductas: parado, echado, comiendo y otras. La metodología de observación y registro utilizada fue el muestreo de barrido a intervalos regulares. Los datos de analizaron con la prueba del c2. El efecto tratamiento fue significativo sobre el comportamiento (p<0,01). Los animales de los dos sistemas gastaron el 50% del tiempo en la conducta de reposo.Well-being of suckling calves under two different rearing systems. Case study in the central milk basin of Argentina. In this paper we conducted a case study with quantitative approach. The aim of this study was to assess welfare in suckling calves during the winter season under two different rearing systems, which are used in the area. Calves were housed in two systems: a stake in males and females cage. All animals received 4 L milk per day, in two servings. Water and a commercial starter were offered ad libitum. Initial and final weights were recorded, weight gain was analyzed using descriptive statistical techniques. Saliva samples were taken at four times over the day, to analyze saliva cortisol (SC). Data were analyzed for time variations. Neither daily fluctuations in SC concentrations nor system effects were detected in SC concentrations. Different behaviors: standing, lying, eating and "others" were observed every other day over a fortnight. Scan sampling at regular intervals was utilized. Data were analyzed by a c2 test. Systems effects were observed on behavioral conducts (p<0.01). Animals in both systems spent 50% of their time lying.Fil: Leva, Paula Edit. Universidad Nacional del Litoral. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: García, M. S.. Universidad Nacional del Litoral. Facultad de Ciencias Agrarias; ArgentinaFil: Toffoli Arnaudo, Guillermo Daniel. Universidad Nacional del Litoral. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rodríguez, A. G.. Universidad Nacional del Litoral. Facultad de Ciencias Agrarias; ArgentinaFil: Rey, Florencia. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Correlation between magnetic interactions and domain structure in A1 FePt ferromagnetic thin films

We have investigated the relationship between the domain structure and the magnetic interactions in a series of FePt ferromagnetic thin films of varying thickness. As-made films grow in the magnetically soft and chemically disordered A1 phase that may have two distinct domain structures. Above a critical thickness $d_{cr}\sim 30$ nm the presence of an out of plane anisotropy induces the formation of stripes, while for $d<d_{cr}$ planar domains occur. Magnetic interactions have been characterized using the well known DCD-IRM remanence protocols, $\delta M$ plots, and magnetic viscosity measurements. We have observed a strong correlation between the domain configuration and the sign of the magnetic interactions. Planar domains are associated with positive exchange-like interactions, while stripe domains have a strong negative dipolar-like contribution. In this last case we have found a close correlation between the interaction parameter and the surface dipolar energy of the stripe domain structure. Using time dependent magnetic viscosity measurements, we have also estimated an average activation volume for magnetic reversal, $\langle V_{ac}\rangle \sim 1.37\times 10^{4}$ nm$^{3},$ which is approximately independent of the film thickness or the stripe period.Comment: 25 pages, 11 figure