1,721,080 research outputs found
Gli effetti degli incendi sul popolamento a Molluschi Gasteropodi di macchia mediterranea.
No full textAlcuni indici per la valutazione dei sistemi di controllo per l’illuminazione
Full text linkGli edifici smart hanno visto negli ultimi anni una sempre più ampia diffusione. Per questo motivo ricercatori, progettisti e tecnici, hanno posto una crescente attenzione sull’utilizzo di sistemi di controllo automatici per l’illuminazione. Questa tipologia di sistemi gioca, infatti, un ruolo chiave nel raggiungimento di significativi riduzioni dei consumi elettrici e dei benefici legati all’utilizzo della luce naturale (ad esempio il comfort visivo degli occupanti, il benessere e la produttività). È prassi comune, durante la fase progettuale, correlare il risparmio energetico con la disponibilità della luce diurna, poiché risulta un obiettivo rilevante per progettisti e architetti
Energy performances and life cycle assessment of an Italian wind farm
No full textRenewable energy sources are often presented as clean. A more correct definition is that they are cleaner than ones based on fossil fuel conversion. When the energy consumption and the environmental impacts related to the plant's life-cycle are considered, a more comprehensive assessment of these technologies can be carried out. This paper aims to evaluate the energy and the environmental performances of the electricity production of a wind farm. The impacts related to all the phases of the wind farm construction and operation have been compared to the environmental benefits due to the green electricity generation during its useful life. In other terms, the goal is to trace the ecoprofile of the production of 1 kWh of electricity.A life cycle assessment (LCA) has been performed based on data related to an Italian wind farm: production and deliver of energy and raw materials, components manufacturing, transports, installation, maintenance, disassembly and disposal have been analysed. The attention focused to those life cycle steps generally neglected or not adequately investigated as installation, civil works and maintenance. The results can be assumed as representative of the Italian context and they can represent a further incentive to the diffusion of wind farms. In fact, the environmental performances of the wind farm have been compared to other power energy generation systems. The results showed a great environmental convenience of the inquired technology
Modelling and analysis of real-world wind turbine power curves: Assessing deviations from nominal curve by neural networks
Full text linkThe 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 power of 2.05 MW. The first phase was focused on statistical analyses, using the most common and reliable probability density functions. The second phase was focused on the analysis and modelling of real power curves obtained on site during one year of operation by fitting processes on real production data. The third was focused on the development of a model based on the use of an Artificial Neural Networks that can predict the amount of delivered power. The actual power curve modelled with a multi-layered neural network was compared with nominal characteristics and the performances assessed by the turbine SCADA. For the studied device, deviations are below 1% for the producibility and below 0.5% for the actual power curves obtained with both methods. The model can be used for any wind turbine to verify real performances and to check fault conditions helping operators in understanding normal and abnormal behaviour
Thermal dynamic models using z-transform coefficients: an algorithm to improve the reliability of simulations
No full textRegression analysis to design a solar thermal collector for occasional use
Full text linkOptimal design of a solar thermal system is necessary to minimize payback time and to diffuse renewable energy use for Domestic Hot Water production in residential areas. More accurate design is crucial in the case of seasonal or occasional use of the system; indeed, the standard criteria generally applied to a design system for continuous use, can lead to considerable over-sizing. To speed up the design phase and to help the planner in the identification of the best solution without any complex evaluation or long computational time, it would be interesting to have available a simpler method than the standard procedures, but one that is reliable and accurate for the evaluation of the best configuration, taking into account occasional use, seasonal and monthly domestic hot water demand, orientation and primary flow rate. To this end, the authors investigated a methodology for the identification of some empirical correlations based on the analysis of data coming from a parametric simulation; in this way the identified correlations can indicate, with high reliability, the optimal design knowing only well-known parameters. In detail, the data output was extracted and processed to evaluate the best design configurations under any operative conditions. Determination of the best configuration identifies the operative parameters that maximize the Solar Fraction of the plant and minimize the auxiliary energy. To highlight the reliability of this methodology, in this work, the authors describe a case study of the Sicilian region proposing a set of simple, reliable correlations that allow the determination of the best tilt angle for monthly or seasonal use. Following the same steps the procedure can be replicate in any context and in any conditions
A methodology for optimisation of solar dish-Stirling systems size, based on the local frequency distribution of direct normal irradiance
Full text linkIn geographical areas where direct solar irradiation levels are relatively high, concentrated solar energy systems are one of the most promising green energy technologies. Dish-Stirling systems are those that achieve the highest levels of solar-to-electric conversion efficiency, and yet they are still among the least common commercially available technologies. This paper focuses on a strategy aimed at promoting greater diffusion of dish-Stirling systems, which involves optimizing the size of the collector aperture area based on the hourly frequency distributions of beam irradiance and defining a new incentive scheme with a feed-in tariff that is variable with the installed costs of the technology. To this purpose, a new numerical model was defined and calibrated on the experimental data collected for an existing dish-Stirling plant located in Palermo (Italy). Hourly-based simulations were carried out to assess the energy performance of 6 different system configurations located on 7 sites in the central Mediterranean area using two different solar databases: Meteonorm and PVGIS. A new simplified calculation approach was also developed to simulate the dish-Stirling energy production from the hourly frequency histograms of the beam irradiance. The results reveal that an optimised dish-Stirling system can produce 70–87 MWhe/year in locations with direct irradiation varying between 2000 and 2500 kWh/(m2·year). The proposed incentive scheme would guarantee a payback time for investment in this technology of about ten years and the effect of economies of scale could lead, over the years, to a levelized cost of energy similar to that of other concentrating power systems
Coupling a road solar thermal collector and borehole thermal energy storage for building heating: First experimental and numerical results
Full text linkThe adoption of more efficient technologies that integrate renewable resources for heating buildings is a key action for increasing sustainability in the residential sector in the European Union. Borehole thermal energy storage and road thermal collector systems, which have mainly been integrated in colder countries to develop renewable systems, aimed at preventing the freezing of road surfaces in winter, could also be used in warmer countries to develop sustainable heating systems for buildings. In this experimental–numerical study, the possibility of integrating these two systems for the heating of buildings located in the Mediterranean region is investigated for the first time. To this end, a pilot plant was built at the facility test site of the University of Palermo, with the aim of demonstrating the possibility of storing solar energy in summer and recovering it in winter. A new method is proposed to characterize both the thermal conductivity and diffusivity of the different materials in the design phase of the plant. The results of simulations conducted with a validated numerical model show that the proposed system, characterized by an average annual collector efficiency of 10% and a seasonal storage efficiency of 80%, can reduce the length of borehole heat exchangers by about three times compared with a conventional geothermal heat pump plant
Degree Days and Building Energy Demand
Full text linkDegree-days (DD) are a climatic indicator that can be used in the assessment and analysis of weather related to energy consumption of buildings. Essentially, degree-days are a summation of the differences between the outdoor temperature and some reference (or base) temperature over a specific time period. In literature, different method can be used for determining the DD value and generally the choice depends on the availability of climatic data of each location. In this paper, after a review and comparison of the most common approaches used to determine DD, the Italian procedure was deeply analyzed. The application of Italian technical rules is based on weather data calculated on a monthly time series monitored before 1994. The obsolescence of the used weather data leads to an incorrect assessment of energy performances. Taking into account the climatic change that in the last years has affected Italy land, the aim of the paper is to assess the impact of new DD values in calculating energy demand of buildings. For these reasons, in this paper the authors recalculated DD of some Italian cities, considering the average monthly temperatures of the last decade. Data were extracted from Meteonorm 7, one of the most popular software for the statistical processing of climate data. Furthermore, other datasets were
generated considering future scenarios defined by IPCC (Intergovernmental Panel on Climate Change). A comparison with the official DD issued by current legislation and new DD recalculated with more recent data highlighted how climate change have affected the calculation of this paramete
Application of optimized artificial intelligence algorithm to evaluate the heating energy demand of non-residential buildings at European level
No full textA reliable preliminary forecast of heating energy demand of a building by using a detailed dynamic simulation software typically requires an in-depth knowledge of the thermal balance, several input data and a very skilled user. The authors will describe how to use Artificial Neural Networks to predict the demand for thermal energy linked to the winter climatization of non-residential buildings. To train the neural network it was necessary to develop an accurate energy database that represents the basis of the training of a specific Artificial Neural Networks. Data came from detailed dynamic simulations performed in the TRNSYS environment. The models were built according to the standards and laws of building energy requirements in seven different European countries, for 3 cities in each country and with 13 different shape factors, obtaining 2184 detailed dynamic simulations of non-residential buildings designed with high energy performances. The authors identified the best ANN topology developing a tool for determining, both quickly and simply, the heating energy demand of a non-residential building, knowing only 12 well-known thermo-physical parameters and without any computational cost or knowledge of the thermal balance. The reliability of this approach is demonstrated by the low standard deviation less than 5 kWh/(m 2 ·year)
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