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Solar systems based on the coupling of parabolic concentrating collectors and thermal engines (i.e. dish-Stirling systems) are among the most efficient generators of solar power currently available. This study focuses on the modelling of functioning data from a 32 kWe dish-Stirling solar plant installed at a facility test site on the University of Palermo campus, in Southern Italy. The proposed model, based on real monitored data, the energy balance of the collector and the partial load efficiency of the Stirling engine, can be used easily to simulate the annual energy production of such systems, making use of the solar radiation database, with the aim of encouraging a greater commercialisation of this technology. Introducing further simplifying assumptions based on our experimental data, the model can be linearised providing a new analytical expression of the parameters that characterise the widely used Stine empirical model. The model was calibrated against data corresponding to the collector with clean mirrors and used to predict the net electric production of the dish-Stirling accurately. A numerical method for assessing the daily level of mirror soiling without the use of direct reflectivity measures was also defined. The proposed methodology was used to evaluate the history of mirror soiling for the observation period, which shows a strong correlation with the recorded sequence of rains and dust depositions. The results of this study emphasise how desert dust transport events, frequent occurrences in parts of the Mediterranean, can have a dramatic impact on the electric power generation of dish-Stirling plants. © 2019 Elsevier Ltd

Historic and traditional buildings, including rural ones, are a territorial resource in Europe and constitute an integral part of the European’s cultural heritage. However they are often characterized by poor energy performances and a large potential for energy retrofit actions. On the other hand, the hardest part of retrofitting such buildings is the limited invasiveness that such actions need to have on the historical and heritage value of the building itself. The paper describes an experience of re-design of an existing rural building located in Sicily, inside the ancient Greeks “Valley of the Temples”. An energy audit was performed on the building, its energy uses thoroughly investigated. A building model was developed in TRNSYS environment and its performances validated. The validated model was used for redesign studies aimed towards the improvement of the energy performances of the building in compliance to legislation. The best performing solutions to be applied to a case-study like the Sanfilippo House are those regarding the management of the building, as in the case of the natural ventilation and the HVAC setpoints, that would allow a large impact (up to 10% reductions in energy uses) on the energy performances of the building with no invasiveness, and those with very limited invasiveness and high impact on the energy efficiency of the building, as in the lighting scenario (up to 30% energy uses reduction). The most invasive actions can only be justified in the case of high energy savings as in the case of the insulation of the roof, otherwise should be disregarded.

Il contributo descrive il lavoro effettuato dagli operatori dell’USSM di Palermo relativamente ai minori sex offenders. Considerata la specificità dell’azione violenta posta in atto, da alcuni anni l’Ufficio si è dotato di una “task force” interna (gruppo E.O.S.) che sperimenta e implementa modalità di comprensione del fenomeno, presa in carico congiunta, creazione di un modello condiviso di lavoro sul target. Nello specifico, un focus verrà aperto sulle strategie operative principali adottate e sull’attività necessaria, quanto mai faticosa, di intervenire sui meccanismi di negazione dei rei e delle famiglie degli stessi. In questo senso l’approccio con le famiglie appare una “conditio sine qua non” per avviare una migliore rielaborazione dell’evento, il ripristino di una comunicazione più efficace sul background del reato nonché sulla vittima e i suoi vissuti.

The purpose of this paper is to illustrate a procedure that permits, starting from a sufficiently long database of time series, the construction of a Reference Year (RY) of hourly weather data according to the rules of ISO 15927-4 standard. In order to facilitate the management of the weather database and to allow the users to easily generate the file, an algorithm has been implemented in Microsoft Visual Basic for Application (VBA). By this way, the application of the ISO 15927-4 is possible even using a popular software tool such as Microsoft Excel or Access without any other expensive specialized software. Such tool allows to fulfil all the procedures mentioned in ISO 15927- 4 giving as result a time series of 8760 values of several weather variables, ready to be used in any software for energy simulation of buildings.

A PC-based instrument has been developed for the monitoring and control of a concentrated photovoltaic and thermal (CPVT) power plant. The instrument allows acquiring both electrical and thermal quantities. Moreover it implements the solar tracking algorithm used to optimize the power production.

In the framework of international actions to reduce the energy requirements and greenhouse gases emissions due to buildings, a new International Energy Agency task has been recently established in order to study Net Zero Energy Buildings (NZEBs). The commonly shared concept of NZEB, is a building whose annual balance of energy consumptions tends to zero. This concept is still too imprecise and the authors of this paper participate to the activities of SubTask B of IEA Task40 with the aim of establishing an internationally agreed understanding on NZEBs. The task is based on a common methodology for identifying and refining design approaches and tools to support industry adoption of innovative demand/supply technologies for NZEBS. This goal is pursued through detailed modeling and analysis of specific NZEB case studies. Among the specific objectives of the Sub Task B it is possible to include the analysis of redesigned studies. Redesigned studies should identify better alternative solutions for plants, building envelope or impact on the environment that significantly modify the building. To provide high quality information about the design process of a NZEB, it was decided to examine in detail the specific case study of the Leaf House (LH) located in Ancona, Italy. The studied building is fully monitored in terms of thermal environment, energy production and consumption, water use and occupancy. The purpose of this paper is to present some optionsto improve the performance of the selected building, identified by using the collected data and analyzing a detailed TRNSYS model of plant-building complex. The model has allowed detailed evaluation of the effects of some changes in the design that can improve the behavior of the Leaf House in terms of consumptions of energy resources and environmental impact of the building. The performed analysis shows that the building envelope is already very effective in terms of thermal performance, while the redesign of the thermal plants and the PV system should permit to reach a nearly net zero energy performance.

In the framework of international actions to reduce the energy requirements and greenhouse gases emissions due to buildings, a new International Energy Agency task has been recently established in order to study Net Zero Energy Buildings (NZEBs). The commonly shared concept of NZEB, is a building whose annual balance of energy consumptions tends to zero. This concept is still too imprecise and the authors of this paper participate to the activities of SubTask B of IEA Task40 with the aim of establishing an internationally agreed understanding on NZEBs. The task is based on a common methodology for identifying and refining design approaches and tools to support industry adoption of innovative demand/supply technologies for NZEBS. This goal is pursued through detailed modeling and analysis of specific NZEB case studies. Among the specific objectives of the Sub Task B it is possible to include the analysis of redesigned studies. Redesigned studies should identify better alternative solutions for plants, building envelope or impact on the environment that significantly modify the building. To provide high quality information about the design process of a NZEB, it was decided to examine in detail the specific case study of the Leaf House (LH) located in Ancona, Italy. The studied building is fully monitored in terms of thermal environment, energy production and consumption, water use and occupancy. The purpose of this paper is to present some optionsto improve the performance of the selected building, identified by using the collected data and analyzing a detailed TRNSYS model of plant-building complex. The model has allowed detailed evaluation of the effects of some changes in the design that can improve the behavior of the Leaf House in terms of consumptions of energy resources and environmental impact of the building. The performed analysis shows that the building envelope is already very effective in terms of thermal performance, while the redesign of the thermal plants and the PV system should permit to reach a nearly net zero energy performance.

Nowadays, there is a great impulse in the field of photovoltaic cell systems (PV) to develop new devices with better energy conversion performances and higher cost effectiveness. This paper is focused on the design and development of a modified PV system, consisting of a normal PV panel coupled with a Phase Change Material (PCM). PCMs are "latent" energy storage materials, using chemical bonds to store and release heat. The system is based on the idea that decreasing the operating temperature of the panel causes an increase in its energy conversion efficiency. A theoretical analysis of the system was accomplished by using COMSOL MULTIPHYSICS, a partial differential equations (PDEs) solver. By using this software, the thermal behaviour of the PV-PCM system was simulated, thus allowing a better identification of the suitable thermo-physical parameters for the optimization of the panel efficiency. The numerical simulations accomplished showed that a PCM with a melting temperature between 28°C and 32°C in a typical summer day in Sicily induces a significant variation in the energy conversion efficiency. The experimental set-up realized to validate these results is also described in the paper, but the experimental tests have still not been run. Furthermore, the exploitation of this simple technology could permit to reduce CO2 emissions because the increasing of the energy conversion efficiency means more energy production and consequently less emission of greenhouse gases to produce energy by fossil fuel or normal PV panel.

Sustainability of energy supply strategies in small islands has been emerging as a severe issue, due to the large margins for improvement and rationalization of the most frequently adopted solutions. In most of the European islands, large amounts of heat are wasted by the operation of engine-based power plants; conversely, heat is produced by boilers (supplied by liquid fuels) or by electric equipment for a number of different uses, like domestic hot water production or space heating in winter. In this paper a techno-economic analysis is proposed to assess the feasibility of CHP-retrofit of the existing power plants and the possible utilization of the recovered heat to supply, via a district heating and/or cooling network, the energy requests of civil energy users (both in the tertiary and in the residential sector). The analysis is accurately performed for six islands located in Italy and characterised by different context conditions from a demographic, geographic and climatic viewpoint, so as to get a comprehensive understanding of the factors that favour/obstruct the economic feasibility of the examined technical solution. As expected, due to the low “linear heat density” usually observed in small islands and to the complex orographic profiles, the investment usually resulted “far from being attractive”; only in the case where public incentive or support mechanism is adopted, the possible integration of the existing power plants with heat recovery devices and a district heating network resulted in moderately attractive, especially in the largest examined islands due to their highest heat loads.

The combination/integration of renewable energy and storage systems appears to have significant potential, achieving high-energy results with lower costs and emissions. One way to cover the thermal needs of a building is through solar energy and its seasonal storage in the ground. The SMARTEP project aims to create an experimental area that provides for the construction of a road solar thermal collector directly connected to a seasonal low-temperature geothermal storage with vertical boreholes. The storage can be connected to a ground-to-water heat pump for building acclimatization. This system will meet the requirements of visual impact and reduction of the occupied area. Nevertheless, several constraints related to the radiative properties of the surfaces and the lack of proper thermal insulation have to be addressed. The project includes the study of several configurations and suitable materials, the set-up of a dynamic simulation model and the construction of a small-scale road thermal collector. These phases allowed for an experimental area to be built. Thanks to careful investigation in the field, it will be possible to identify the characteristics and the best operation strategy to maximize the energy management of the whole system in the Mediterranean area.

In 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.

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 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.

Multiple-chillers systems represent viable solutions for medium/large-scale air conditioning applications characterized by variable cooling demand. The energy efficiency of such systems is influenced by the number of chillers, the combination of cooling capacities, and the load-sharing among the units. Large efforts have been devoted to developing efficient operation strategies for these systems, but rules of thumb are usually adopted for selecting cooling capacities thus leaving room for energy and economic savings. In this paper, exergoeconomic analysis is proposed as a promising method to identify near-optimal design and operation strategies, due to the capability of exergoeconomic indicators to account simultaneously for capital and operating costs. The potential of the method is illustrated for a hydronic system supplying an air-handling unit installed in an office building. Design alternatives are compared, with chillers of equal or different capacities operated in a parallel or series configuration, and the cost-effectiveness of different load sharing strategies is also investigated. A thermoeconomic model for multiple-chillers systems is formulated, considering the actual performance of chillers under full- and part-load conditions derived by a plant simulator. Results show that the exergoeconomic cost of chilled water reduced by about 7% and 30% when passing from evenly to unevenly sized systems in both series and parallel configurations. It is also found that the symmetric load sharing strategy leads to a 14–18% reduction in the cost of chiller water compared to the sequential one. The study confirms that this method may represent systematic and thermodynamically-sound support for engineers in this field.

Optimal 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.

Different ways to evaluate the building energy balance can be found in literature, including comprehensive techniques, statistical and machine-learning methods and hybrid approaches. The identification of the most suitable approach is important to accelerate the preliminary energy assessment. In the first category, several numerical methods have been developed and implemented in specialised software using different mathematical languages. However, these tools require an expert user and a model calibration. The authors, in order to overcome these limitations, have developed an alternative, reliable linear regression model to determine building energy needs. Starting from a detailed and calibrated dynamic model, it was possible to implement a parametric simulation that solves the energy performance of 195 scenarios. The lack of general results led the authors to investigate a statistical method also capable of supporting an unskilled user in the estimation of the building energy demand. To guarantee high reliability and ease of use, a selection of the most suitable variables was conducted by careful sensitivity analysis using the Pearson coefficient. The Multiple Linear Regression method allowed the development of some simple relationships to determine the thermal heating or cooling energy demand of a generic building as a function of only a few, well-known parameters. Deep statistical analysis of the main error indices underlined the high reliability of the results. This approach is not targeted at replacing a dynamic simulation model, but it represents a simple decision support tool for the preliminary assessment of the energy demand related to any building and any weather condition.

Italy is celebrated in the world for its agri-food industries while the process of production of pasta is highly energy demanding and requires both electrical and thermal energy simultaneously. Because most of the Italian factories producing pasta are located in the Southern part of the country, the direct use of thermal energy generated from the sun would be particularly profitable. In this study, the authors examine the possibility of generating by a Solar Industrial Process Heating plant the thermal energy required annually by an existing factory that produces durum wheat pasta located in Sicily (Italy). The hypothesized plant scheme consists of an array of Fresnel linear solar collectors and a concrete thermal energy storage system in which a heat transfer diathermal fluid circulates. This particular combination, although not the most efficient from the thermodynamic point of view, determines a lower visual impact and easier maintenance during the life span of the system. The use of food graded thermal oil ensures a high level of safety. A TRNSYS model has been developed in order to simulate the energy performance of the above described plant with the aim of optimizing the design of the solar heat for industrial process systems in terms of solar collectors and thermal energy storage dimensions taking into account the available space in the specific location. The obtained results show that the direct use of the thermal energy generated with the Fresnel solar collectors can significantly contribute to increase the sustainability of the most thermal energy-demanding factories working in the food industry, a strategic sector in the Mediterranean Area. The average annual solar contribution can reach about 40% of the total thermal energy requirement, maximizing the solar energy production during the summer season. Moreover, the proposed study allowed the determination of the maximum investment cost of the plant linked to a simple payback time, without external incentives, of 8 years.

A detailed assessment of building energy performance requires a large amount of input data concerning building typology, environmental conditions, envelope thermophysical properties, geometry, control strategies, and several other parameters. Notwithstanding, the use of specialized software tools poses many challenges in regards to the retrieval of reliable and detailed information, setting a steep learning curve for engineers and energy managers. To speed up the preliminary assessment phase, it might be more convenient to resort to a simplified model that allows the evaluation of heating energy demand with a good level of accuracy and without excessive computational cost or user expertise. Dimensional analysis is a means of simplifying a physical problem by appealing to dimensional homogeneity to reduce the number of relevant variables. In this work, the authors investigated an alternative approach to assess the thermal energy demand of a high-performance-non-residential building. It was possible to define some dimensionless numbers that synthetically describe the links between the main characteristic parameters of the thermal balance by applying the Buckingham π theorem. After a detailed description of the Buckingham π theorem and of its application concerning the evaluation of the building energy balance, the authors identified nine “ad hoc” dimensionless numbers. The proposed methodology has been validated by the comparison of the heating energy demand calculated by detailed dynamic simulations carried out in TRNSYS according to the standards and laws of building energy requirements in seven different European countries. Applying a set of criteria, it was possible to employ a dimensionless number to determine, immediately and without any calculation or use of steady/dynamic software, the heating energy demand with an reliability >90%.

The public buildings sector represents one of the most intensive items of EU energy consumption; the application of retrofit solutions in existing buildings is a crucial way to reduce its impact. To facilitate the knowledge of the energy performance of existing non-residential buildings and the choice of the more adequate actions, Public Administrations (PA) should have the availability of proper tools. Within the Italian project "POI 2007-13", a database and a decision support tool, for easy use, even to a non-technical user, have been developed. A large set of data, obtained from the energy audits of 151 existing public buildings located in four regions of South Italy have been analysed, elaborated, and organised in a database. This was used to identify the best architectures of two ANNs and to train them. The first ANN provides the actual energy performance of any building; the second ANN assesses key economic indicators. A decision support tool, based on the use of these ANNs is conceived for a fast prediction of the energy performance of buildings and for a first selection of energy retrofit actions that can be applied.

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 pixels, greyscaling, thresholding, discrete wavelet transform, and Sobel Feldman and box blur filtering. These techniques allow the classification of thermographic images of differen quality and acquired using different equipments, without specific protocols. Several tests with different parameters and overfitting reduction techniques were carried out to assess the performance of the neural networks: images acquired by unmanned aerial vehicles and ground-based operators were compared for the network performance and for the time required to execute the thermographic inspection. Our tool is based on a convolutional neural network that allows to immediately recognize a failure in a PV panel reaching a very high accuracy. Considering a dataset of 1000 images that refer to different acquisition protocols, it was reached an accuracy of 99% for a convolutional neural network with 30 min of computational time on Low Mid-Range CPU. While a dataset of 200 sectioned images, the same tool achieved 90% accuracy with a multi-layer perceptron architecture and 100% accuracy for a convolutional neural network. The proposed methodology offers an open alternative and a valid tool that improves the resolution of image classification for remote failure detection problems and that can be used in any scientific sector.

The weather is one of the main factors to consider when designing a building because it represents the most important boundary condition to affect the dynamic behaviour of the building. In the literature, many studies use the degree day to predict building energy demand. However, linking the results obtained from a generic building simulation tool with defined degree days, will not give reliable energy evaluation. The goal of this study is to demonstrate that the assessment of building energy demand through the use of the degree day is correct only if the determination of the climate index is a function of the same weather data. The relationship between Heating Degree-Day and heating energy performance was identified by determining some simple correlations, in order to obtain a preliminary evaluation of energy demands. The authors used Heating Degree Days based on three climate data-sets, developing different relationships and feedback. For the extraction of these correlations, numerous dynamic simulations on non-residential buildings characterized by high-energy performance were carried out. From the analysis of the results, it is clear that the relationships with higher correlation coefficients (higher than 0.9) are those that are a function of the degree calculated from the same climatic file used during the simulations. The proposed methodology, validated in this work for an Italian case study can be extended to any country and can be used to improve the reliability of any decision support tool based on climatic indexes.

A 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/(m2·year).

This article presents a procedure for the producibility curve identification of a dish-Stirling plant, starting from experimental data. The producibility data was measured, recorded, analysed, filtered and monthly aggregated. Moreover, the incidence of the ambient temperature and of the mirrors cleaning on producibility data is highlighted and a procedure to normalize the measured data in temperature and cleaning level was developed. To provide a validation of the developed procedure the producibility curves at 25 °C have been obtained and compared with the one issued by the manufacturer. The two curves are in good agreement, presenting a maximum deviation of the 7 %.