Search results for "renewable"
showing 10 items of 2395 documents
Fluorogenic detection of Tetryl and TNT explosives using nanoscopic-capped mesoporous hybrid materials
2013
[EN] A hybrid capped mesoporous material, which was selectively opened in the presence of Tetryl and TNT, has been synthesised and used for the fluorogenic recognition of these nitroaromatic explosives.
Artificial Neural Networks to Predict the Power Output of a PV Panel
2014
The paper illustrates an adaptive approach based on different topologies of artificial neural networks (ANNs) for the power energy output forecasting of photovoltaic (PV) modules. The analysis of the PV module’s power output needed detailed local climate data, which was collected by a dedicated weather monitoring system. The Department of Energy, Information Engineering, and Mathematical Models of the University of Palermo (Italy) has built up a weather monitoring system that worked together with a data acquisition system. The power output forecast is obtained using three different types of ANNs: a one hidden layer Multilayer perceptron (MLP), a recursive neural network (RNN), and a gamma m…
Assessment of the Operating Temperature of Crystalline PV Modules Based on Real Use Conditions
2014
Determining the operating temperatureTcof photovoltaic panelsPVis important in evaluating the actual performance of these systems. In the literature, different correlations exist, in either explicit or implicit forms, which often do not account for the electrical behaviour of panels; in this way, estimatingTcis based only on the passive behaviour of thePV. In this paper, the authors propose a new implicit correlation that takes into account the standard weather variables and the electricity production regimes of aPVpanel in terms of the proximity to the maximum power points. To validate its reliability, the new correlation was tested on two different PV panels (Sanyo and Kyocera panels) and…
Biodegradability Prediction of Fragrant Molecules by Molecular Topology
2016
Biodegradability is a key property in the development of safer fragrances. In this work we present a green methodology for its preliminary assessment. The structure of various fragrant molecules is characterized by computing a large set of topological indices. Those relevant to biodegradability are selected by means of a hybrid stepwise selection method to build a linear classifier. This model is compared with a more complex artificial neural network trained with the indices previously found. After validation, the models show promise for time and cost reduction in the development of new, safer fragrances. The methodology presented could easily be adapted to many quasi-big data problems in R…
Modelling and analysis of real-world wind turbine power curves: Assessing deviations from nominal curve by neural networks
2019
Abstract The power curve of a wind turbine describes the generated power versus instantaneous wind speed. Assessing wind turbine performance under laboratory ideal conditions will always tend to be optimistic and rarely reflects how the turbine actually behaves in a real situation. Occasionally, some aerogenerators produce significantly different from nominal power curve, causing economic losses to the promoters of the investment. Our research aims to model actual wind turbine power curve and its variation from nominal power curve. The study was carried out in three different phases starting from wind speed and related power production data of a Senvion MM92 aero-generator with a rated powe…
Deep learning strategies for automatic fault diagnosis in photovoltaic systems by thermographic images
2021
Abstract Losses of electricity production in photovoltaic systems are mainly caused by the presence of faults that affect the efficiency of the systems. The identification of any overheating in a photovoltaic module, through the thermographic non-destructive test, may be essential to maintain the correct functioning of the photovoltaic system quickly and cost-effectively, without interrupting its normal operation. This work proposes a system for the automatic classification of thermographic images using a convolutional neural network, developed via open-source libraries. To reduce image noise, various pre-processing strategies were evaluated, including normalization and homogenization of pi…
Artificial Neural Networks to assess energy and environmental performance of buildings: An Italian case study
2019
Abstract Approximately 40% of the European energy consumption and a large proportion of environmental impacts are related to the building sector. However, the selection of adequate and correct designs can provide considerable energy savings and reduce environmental impacts. To achieve this objective, a simultaneous energy and environmental assessment of a building's life cycle is necessary. To date, the resolution of this complex problem is entrusted to numerous software and calculation algorithms that are often complex to use. They involve long diagnosis phases and are characterised by the lack of a common language. Despite the efforts by the scientific community in the building sector, th…
Short term wind speed prediction using Multi Layer Perceptron
2012
Among renewable energy sources wind energy is having an increasing influence on the supply of energy power. However wind energy is not a stationary power, depending on the fluctuations of the wind, so that is necessary to cope with these fluctuations that may cause problems the electricity grid stability. The ability to predict short-term wind speed and consequent production patterns becomes critical for the all the operators of wind energy. This paper studies several configurations of Artificial Neural Networks (ANN), a well-known tool able to estimate wind speed starting from measured data. The presented ANNs, t have been tested through data gathered in the area of Trapani (Sicily). Diffe…
New European Wind Atlas: Microscale Atlas
2021
Wind Atlas layers from the New European Wind Atlas (NEWA) microscale atlas. The atlas was made by downscaling the NEWA mesoscale wind atlas using the Wind Atlas Analysis and Application Program (WAsP) microscale model.Data are accessible through doWIND, an instance of daTap (RESTfull API for data aggregation and subsetting)
The Sustainability of Cruise Tourism Onshore: The Impact of Crowding on Visitors’ Satisfaction
2019
The sustainability of cruise tourism has been questioned in relation to its negative effects on ports of call, among which crowding has recently become more pronounced. However, an understanding of how crowdedness influences cruise tourists&rsquo