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Along the roadmap to a Sustainable Real Estate-Scape, energy retrofit campaigns on wide city compartments represent a pivotal task, where the importance of the collaboration between the public and private sectors is crucial. Energy retrofit programs on building assets are subject to multiple uncertainty factors (e.g., climate, energy-economy forecasts, etc.) that act as a primary barrier to investment in this field. This paper aims to discuss risk management techniques to understand better how to deal with this kind of uncertainty. The research specifically addresses the techniques of sensitivity analysis and Monte Carlo simulation, focusing first on the phase of variables selection and their probability definition, including climatic, environmental, energy, economic, financial, and stochastic parameters. In this article, it is suggested to include correlation coefficients in the input variables of risk analysis, preferring the two-dimension Monte Carlo simulation to its simple version, since the results are more reliable when separating aleatory from epistemic uncertainty; thus, the results are more reliable. Moreover, it is seen how a sensitivity analysis based on percentile variations of the inputs provides a more accurate representation of risk if compared to the most common sensitivity analysis based on percentage deviations of the inputs. Conducting a sensitivity analysis using percentile variations gives realistic and reliable results, reflecting the tailored definition of uncertainty around the inputs on the basis of specific market analyses or historical series.

In temperate climates, such as most Italian ones, the need to limit both winter heat losses of buildings and their overheating in other periods is present. The second requirement is particularly relevant in the presence of high internal and solar gains. In these climates, it is not convenient to exceed the insulation thickness. Therefore, when the energy renovation of an old building with heavy masonry is performed it is a question of optimizing the position (internal or external) and the thickness of the additional insulation. Another question is the choice of a solar control strategy, if extended glazed surfaces are present. Both of these problems are present in old Italian public buildings, particularly in schools. This paper presents a computerized methodology for optimizing these choices. The case study consists in a typical school building from the early 1900s with a heavy structure and large glass surfaces in a climate of Northern Italy (Bologna), with cold winter and hot summer. The results show that the external insulation is the best performing, and that there is an optimal thickness when the building is a school. If the building is reused for offices, due to the lower internal gains, the energy convenience of the external insulation increases, but its optimal thickness becomes excessive. Small slats inserted between the glasses are the best performing solar control device from both an energy and visual comfort point of view; on the other hand, the external slats provide better thermal comfort in the warmer period.

This research aims to understand how market transparency and data reliability can influence valuation procedures and decision-making processes in the Italian real estate market. Through the analysis of three different real estate markets and the validation of the information collected, this paper’s goal is to understand whether and to what extent the use of asking prices instead of actual purchase and sale prices can lead to valuation errors, increase the uncertainty of valuation, and undermine investment decision-making processes. The research results highlight the primary sources of information opacity in the Italian real estate market, classifying them according to their impact on real estate value. The novelty of this research lies in the integrated use of machine learning techniques, computer programming and multi-parametric valuation procedures to understand and manage information opacity in the Italian real estate market, particularly regarding the estimation of the market value of properties belonging to the residential segment. Questa ricerca si pone come obiettivo il comprendere come la trasparenza del mercato e correttezza delle informazioni influenzino i procedimenti di stima e i proessi decisionali nel mercato immobiliare italiano. Attraverso l’analisi di tre differenti mercati immobiliari e la verifica delle informazioni relative ai prezzi di offerta, il presente contributo vuole capire se, e in quale dimensione, l’impiego dei prezzi di offerta in luogo dei reali prezzi di compravendita possano portare a commettere errori valutativi, ad aumentare l’incertezza nelle stime e a pregiudicare il processo decisionale negli investi- menti. I risultati della ricerca evidenziano quali sono le fonti primarie di opacità informativa nel mercato immobiliare italiano, classificandole in base al loro impatto sulla stima del valore immobiliare. La novità di questa ricerca risiede nell’uso integrato di tecniche di machine learning, programmazione informatica e procedure di stima multi-parametrica al fine di comprendere e gestire l’opacità informativa nel mercato immobiliare italiano, in particolare riguardo la stima del più probabile valore di mercato degli immobili appartenenti al segmento residenziale.

Data visualization has become relevant in the framework of the evolution of big data analysis. Being able to understand data collected in a dynamic, interactive, and personalized way allows for better decisions to be made when optimizing and improving performance. Although its importance is known, there is a gap in the research regarding its design, choice criteria, and uses in the field of building energy consumption. Therefore, this review discusses the state-of-the-art of visualization techniques used in the field of energy performance, in particular by considering two types of building analysis: simulation and monitoring. Likewise, data visualizations are categorized according to goals, level of detail and target users. Visualization tools published in the scientific literature, as well as those currently used in the IoT platforms and visualization software, were analyzed. This overview can be used as a starting point when choosing the most efficient data visualization for a specific type of building energy analysis.

Building energy modeling (BEM) is used to support (nearly) zero-energy building (ZEB) projects, since this kind of software represents the only available option to forecast building energy consumption with high accuracy. BEM may also be used during preliminary analyses or feasibility studies, but simulation results are usually too detailed for this stage of the project. Aside from that, when optimization algorithms are used, the implied high number of energy simulations causes very long calculation times. Therefore, designers could be discouraged from the extensive use of BEM to conduct optimization analyses. Thus, they prefer to study and compare a very limited amount of acknowledged alternative designs. In relation to this problem, the scope of the present study is to obtain an easy-to-use tool to quickly forecast the energy consumption of a building with no direct use of BEM to support fast comparative analyses at the early stages of energy projects. In response, a set of automatic energy assessment tools was developed based on machine learning techniques. The forecasting tools are artificial neural networks (ANNs) that are able to estimate the energy consumption automatically for any building, based on a limited amount of descriptive data of the property. The ANNs are developed for the Po Valley area in Italy as a pilot case study. The ANNs may be very useful to assess the energy demand for even a considerable number of buildings by comparing different design options, and they may help optimization analyses.

In real estate property valuation, the availability of comparables is crucial. The reliability of the valuation of the market value depends on the number and on the accuracy of data that a professional can rely on. International standards suggest using historical prices as comparable since they are real transactions of sale/rent of a property that actually happened in a specific market. However, in the Italian real estate market, historical transaction prices are not available for professionals, and they have to base their valuations, primarily, on the asking prices enclosed in the selling advertisements. Asking prices can change in the future as they are subject to negotiation. Besides, sell ads always contain incomplete data or even wrong information. In this research, we employ Artificial Neural Networks to estimate how much offer prices and selling advertisements are misleading in property valuation in Italy. We, in a way, assess the opacity of the Italian real estate market, and we designate the major sources of error. The present work is a first step towards developing a model fitted for estimating data accuracy used generally in real estate estimates, namely, asking prices.

Variable speed drive (VSD) technology can be introduced in heating, ventilation and air conditioning (HVAC) systems, normally sized for peak load conditions, to match actual load requirements. The paper presents a detailed assessment of the impact of the application of VSDs to HVAC components in a public building. The study was based on the data provided by a long term monitoring of the performances. As regards the electricity consumption of pumping and fans, the investigation has pointed out the achievement of a global annual energy saving of 38.9% in comparison with the alternative of a constant speed HVAC system.

The thermo-hygrometric treatment related to the air change in buildings requires a relevant quota of the total energy demand of HVAC systems, especially when the ventilation demand is significant. A correct energy saving strategy therefore should always focus on the use of suitable techniques to reduce this energy consumption. As proved by the modern theories on comfort, less strict values can be accepted for the internal humidity set points without compromising indoor comfort conditions. In addition, Demand Controlled Ventilation (DCV) gives the opportunity to reduce energy requirements. This paper investigates the opportunities offered by the installation of a DCV system and a Building Management System (BMS) able to perform long term monitoring of the HVAC system in a real case study. This refers to a historic building in Venice in the area of the harbour and recently transformed into a modern university facility. Starting from the experimental data recorded by BMS, an optimization of the control strategies and simple tuning actions of the DCV controller were possible. Results validate the use of more flexible set points of indoor relative humidity and long term on-line tuning even in absence of self-learning control systems, as well as they highlight the achievement of remarkable energy savings thanks to these actions. The research demonstrates the fundamental contribution of successive control performance assessments by long term monitoring to individuate possible weaknesses in DCV system management.

Refurbished buildings should also increase their energy efficiency, according with current regulation; however, in case of historical buildings, preservation orders are so strict to hamper usual energy efficient interventions on the building envelope side. As a consequence, in historical buildings, HVAC (Heating, Ventilation and Air-Conditioning) systems and control strategies should be further improved, since they are the only true means for energy efficiency. This paper presents the set of technologies implemented in the frame of the refurbishment of an historical building in the very center of Venice, in order to lower energy consumption and increase occupants’ comfort. The refurbishment consisted mainly in the application of the following technologies: Surface Water Heat Pump (SWHP), Demand Controlled Ventilation (DCV) and trigeneration. Furthermore, the paper proves the achieved energy savings by comparing the actual energy consumption against detailed building energy simulations for baseline HVAC system configurations. For such a purpose, the authors take advantage of the installed extensive building management system (BMS), which is able to record detailed data about flow rates (of air and water), temperature and humidity for all of the key devices of the HVAC system. The building used as a case study is very significant because of its energy intensive intended use as well as for the very strict preservation orders acting on it. In particular, global primary energy savings equal to 36% have been calculated, if compared with a traditional baseline HVAC system.

The United Nations as well as the European Union are strongly committed in promoting a transition towards more sustainable and resilient cities. Indeed, they are increasingly affected by different types of threats, among which the natural ones such as earthquakes, fires, and floods (shocks) and climate variability (stresses). Cities are quite often unable to cope with the adverse effects of such natural hazards. This circumstance leads to the need of introducing resilience-related criteria (besides commonly used sustainability indicators) in decision-making processes. This paper investigates at which extent the inclusion of such new indicators, within multi-criteria assessment tools for supporting the decision-making process by Public Administrations, modifies the prioritization processes of a given set of planned actions to be implemented in cities, which are based instead on the above-cited commonly used indicators. The outcomes of the analysis demonstrated that the introduction of resilience among the prioritization criteria significantly modifies the list of priorities established using only sustainability indicators.

Resilience represents a new important feature that the anthropic systems, and cities among them, are called to cope with. In fact, the increasing negative stresses to which urban contexts are exposed, and mainly the climatic pressures, call for the capability of adapting to these modifications and, possibly, to restore the ex-ante situations. The role of the buildings and their envelope components is of crucial importance to this aim. This paper analyses the features of resilience of the roofs of buildings by means of proper quantitative indexes. On purpose, the performances of green and cool roofs are compared. The possibility of adopting nonstructural solutions, like the windows shading devices, is also considered.

This paper deals with the behaviour of battery-supported residential photovoltaic (PV) systems connected to smart grids, with a special focus on the interface with electricity distributors. In particular, this paper is aimed at the assessment of the benefits resulting from two predictive control strategies managing the charge of the electrochemical storage unit, in comparison with the conventional control strategy and applied to various combinations of photovoltaic system and battery pack sizes in a parametric analysis. The proposed control strategies dispatch electricity to the battery pack or national grid depending on the state of charge and differ in the shape of the profile of exported electricity, hence adapting to different interface profiles required at the electricity distributor’s side. In particular, the research shows that, by the proposed control strategies, the frequencies of occurrence of high values of exported electricity may be decreased by almost 100%, whereas medium-high values of exported electricity by 50%. Moreover, both of the control strategies are shown to be able to lower the yearly quadratic effective imbalance coefficient by around 15% in case of PV systems sized for Zero Energy Buildings (ZEBs), thus showing opportunities in the mitigation of electricity grid stresses from PV systems.

Methods for building envelope inspection are well known since 70's. However, measurement instruments and software improve, making methods for building envelope inspection susceptible to further improvements. In particular, the present paper deals with building envelope assessments performed via heat flux meters and reports the outcomes of a monitoring campaign verifying a measurement procedure proposed by the authors. Such a procedure is aimed at the improvement of the accuracy and reliability in the on-field measurement of the U-value of building constructions. In detail, the proposed method exploits an experimental device providing controlled local heating aimed at speeding up the measurement process and limiting temperature fluctuations, with possible improvements over the calculation of the final U-value. The advantages and limits of this measurement procedure are explained in this paper, together with possible future improvements.

Purpose This paper aims to develop a forecasting tool for the automatic assessment of both environmental and economic benefits resulting from low-carbon investments in the real estate sector, especially when applied in large building stocks. A set of four artificial neural networks (NNs) is created to provide a fast and reliable estimate of the energy consumption in buildings due to heating, hot water, cooling and electricity, depending on some specific buildings’ characteristics, such as geometry, orientation, climate or technologies. Design/methodology/approach The assessment of the building’s energy demand is performed comparing the as-is status (pre-retrofit) against the design option (post-retrofit). The authors associate with the retrofit investment the energy saved per year, and the net monetary saving obtained over the whole cost after a predetermined timeframe. The authors used a NN approach, which is able to forecast the buildings’ energy demand due to heating, hot water, cooling and electricity, both in the as-is and in the design stages. The design stage is the result of a multiple attribute optimization process. Findings The approach here developed offers the opportunity to manage energy retrofit interventions on wide property portfolios, where it is necessary to handle simultaneously a large number of buildings without it being technically feasible to achieve a very detailed level of analysis for every property of a large portfolio. Originality/value Among the major accomplishments of this research, there is the creation of a methodology that is not excessively data demanding: the collection of data for building energy simulations is, in fact, extremely time-consuming and expensive, and this NN model may help in overcoming this problem. Another important result achieved in this study is the flexibility of the model developed. The case study the authors analysed was referred to one specific stock, but the results obtained have a more widespread importance because it ends up being only a matter of input-data entering, while the model is perfectly exportable in other contexts.

This article presents the economic performance of battery-supported residential photovoltaic systems connected to smart grids in the presence of a market-driven electricity tariff. In particular, the article deals with the economic benefit resulting on varied photovoltaic system and battery sizes, through a parametric analysis. Such an analysis is strongly dependent on the costs of photovoltaic systems and battery packs, which are prone to decrease in the coming years, according to many authors. In this context, the article investigates current and forecast economic scenarios, in order to show the expectable improvement in the financial performance in systems installed in the next few years. For this purpose, the article includes a review of photovoltaic system and battery prices forecasts for the coming years. The financial analysis takes into account two different (and conservative) feed-in tariffs: in the first case, the hourly national price of electricity is used as a feed in tariff, in the second ca...

Among the policies and regulations aimed at reducing the energy use in building stocks, the retrofit of historic buildings is one of the hardest challenges both for research and practice, because it is necessary to combine the traditional energy/economy targets with safeguard programs and conservation theories. In this paper, a decision support system is developed in order to plan and manage energy retrofit campaigns tailored for cultural heritage. Costs and energy uses are assessed, as well as the compatibility of interventions and their impact on indoor environmental quality. The energy use is seen under an economic, environmental, human and cultural perspective, providing a decision-making procedure that could be very useful for asset holders, public or private investors as well as for portfolio managers or agencies. The most important achievements in this work are the assessment of a so-called restoration score as a way to include conservation aspects in the selection procedure, and the integration of different appraisal techniques such as multi-attribute analysis, life cycle costing and analytic hierarchy process.

The research about energy efficiency in buildings has exponentially increased during the last few years. Nevertheless, both research and practice still cannot rely on complete methodologies tailored for building portfolios as a whole, because the attention has always been drawn to individual premises. Yet, energy efficiency analyses need to go beyond the single building perspective and incorporate strategic district approaches to optimize the retrofit investment. For this purpose, several aspects should be considered simultaneously, and new methodologies should also be promoted. Therefore, this paper aims to discuss energy retrofit campaigns in building portfolios, drawing an exhaustive and updated review about the challenge of jumping from the single-building perspective to a stock-based analysis. This research discusses the publications available on the topic from five key aspects that are all essential steps in achieving a complete and reliable study of energy efficiency at a portfolio level. They are energy modelling and assessment, energy retrofit design, decision-making criteria assessment, optimal allocation of (financial) resources and risk valuation. This review, therefore, advocates for joint consideration of the problem as a basis on which to structure further disciplinary developments. Research gaps are highlighted, and new directions for future research are suggested.

Future energy scenarios focus on electricity as the main energy vector, because of its easier management and flexibility, in conjunction with the reduced use of carbon fuels. In such a context, also Sustainable Energy and Climate Action Plans (SECAPs) are promoting electricity-based technologies also in services usually relying on fossil fuels, such as ambient heating and domestic hot water preparation (DHW), by means of heat pumps. Moreover, heat pumps both fit perfectly with the Zero Energy Building (ZEB) perspective and offer major opportunities in a regional and urban perspective, since they offer many ways to optimize the exploitation of renewable energy sources (RESs). This paper shows quantitative analyses on possible applications of heat pumps in combination with the most typical RES in urban contexts, i.e. solar photovoltaics (PV).

The increased generation of electricity from renewable energy sources may imply issues in the management of national electric systems, due to the low predictability of electricity generation from renewable energy sources. In this regard, interesting opportunities come from the use of advanced control strategies for the management of electric devices such as heat pumps, able to exploit dynamic electricity prices aimed to induce users to absorb/generate electricity according with the electricity grid imbalance. In this paper, the results of building energy simulations applying tailored heat pump control strategies suitable for the integration within smart grids are presented. In particular, three heat pump control strategies are applied, whose action is based on the cost of electricity (absolute and relative to the following 12 h) and on the level of the local electricity generation from photovoltaics. The analyzed control strategies ensure relevant money savings (up to 30%) and increase the degree of energy self-consumption (up to 12% for exported electricity and 22% for imported electricity). The analysis considers also comfort issues and shows that the best results may be achieved commanding the heat pump basing on the generation of the photovoltaic system as well as on the simultaneous heating/cooling loads and electricity prices.

Tables of performance of installed HVAC (Heating, Ventilation and Air Conditioning) devices are important in the development of consistent building energy audits and appropriate control strategies. However, given the possible complexity of HVAC devices and the need for the deployment to computational environments, tables of performance should be passed in a more complete and flexible format, compared with the current practices in the HVAC sector. In such a context, this paper describes the phases of development and application of Artificial Neural Networks (ANNs) aimed at the assessment of the performance of a Dedicated Outdoor Air System (DOAS). ANNs are well renowned because of their applications in many important fields such as autonomous driving systems, speech recognition, etc. However, they may be used also to calculate the output of complex phenomena (like the ones involved in HVAC components) and are characterized by a very flexible and comprehensive formulation which would be able to adapt to any HVAC component or system. In the frame of this study, three ANNs have been developed and tested, for the full description of the performance of a DOAS. The developed ANNs were trained by means of data coming from a proprietary software. The achieved ANNs showed robust and reliable behavior and ensure high accuracy (mean absolute errors usually below 0.1 K on temperatures and 0.3% on capacity and power) and flexibility. Moreover, in some cases, they may be used also for the identification of anomalous data present among the sets of training and validation data.

CO2 based ventilation control is an eligible technology to reduce energy consumptions concerning ventilation air treatment and its distribution in particular in presence of highly variable occupancy. An experimental assessment of the performances of this control strategy is illustrated in this paper. The study refers to a historic building in Venice recently refurbished and subject to a preservation order. It concerns a demand controlled ventilation (DCV) system installed in a part of the building transformed in a university library and based on the use of CO2 sensors. A building management system (BMS) able to measure and record the required data was used as a tool for long term monitoring of the HVAC system. A comparison with alternative solutions was also carried on. The results permit to quantify remarkable energy savings, particularly strategic in the energy retrofit of historic buildings especially in presence of preservation orders. But the investigation highlights also the peculiarities of CO2 based ventilation control in meeting the indoor comfort requirement which suggest a systematic use of long term assessment to verify control efficacy in different operating conditions.

In the last years the importance of part load conditions in the estimation of chiller performance in real world operation has been completely acknowledged. As a matter of fact, chillers are sized for peak loads, so they usually run under part load conditions, far from the full load ones, taken as references in catalogues. Some methods for these calculations already exist, both in Standards and in building energy simulation programs, but they lack an extensive validation in actual HVAC systems. In this regard, the present paper compares the chiller performance estimated via the calculation method contained in Standard EN 14825 against monitored data taken along an entire cooling season, both in a small HVAC plant and in a large one. In the present paper a variation of the calculation method contained in Standard EN 14825 is used indeed. In particular, in this variation of the EN 14825 calculation method, the interpolation between the values of EER rated under part load conditions is performed by means of intermediate parameter Z , equal to the ratio of the electrical power consumption under part load conditions to the electrical power consumption under full load conditions. This interpolation method allows the HVAC designer to draw more reliable profiles of PLF (Part Load Factor) versus the capacity ratio (CR), in order to increase the accuracy in performance prediction under part load conditions. As a matter of fact, this interpolation method allows the HVAC designer to achieve a better estimation of the EER at low values of the part load ratio, especially when compared with the linear interpolation method suggested in Standard EN 14825.

The ideal orientation of PV panels is a widely debated topic. However, the relevant decrease in photovoltaic (PV) system costs and their consequent rapid spread are moving the attention from the achievement of the maximum areal electricity generation to a PV generation profile in agreement with building energy needs. In fact, national subsidies are going to promote electricity self–consumption in PV systems, in order to avoid imbalances in the grid, already relevant at the present market status, i.e. with a still low share of PV in national yearly electricity generation. For all of these reasons, in the next years PV systems will not be designed just to generate the amount of electricity as high as possible, but even to limit electricity exportation from the building perspective. Thus, orientations and PV configurations with lower electricity generation might be preferred, if they allow the user to achieve a higher degree of electricity self-consumption. Of course, in the achievement of this aim, the PV systems will be supported by electrochemical storages as well. This paper shows the analysis of various configurations of PV systems supported by electrochemical storages, aiming at the increase of electricity self-consumption, considering two Italian climates: Venice, in the northeast (Latitude: 45° 26’ N), and Trapani, in southern Italy (Latitude: 38° 01’ N). As regards the detailed simulation of the PV system, the analysis took advantage of program Ener_Lux, while the building energy system was simulated via EnergyPlus.

The interest of the building energy sector is leaning towards the measurement of building actual performance, as regards both indoor environment quality and energy consumption. Sensors and central elaboration units aimed at monitoring indoor environment and HVAC system parameters can also provide the basic infrastructure for further applications such as predictive and neuro-fuzzy controls. However, the cost of such systems is high, so they are mainly used in large buildings. This paper describes the main features and expected applications for a low-budget monitoring platform currently under development and tuning. In particular, the monitoring system was developed based on electronic prototyping platform Arduino and on sensors and devices usually available in the retail market of electronics. The monitoring platform has been designed with the following characteristics in mind: replicability, full remote control, portability, versatility, reliability and affordability.

The Zero Energy Building (ZEB) target and the higher affordability of photovoltaic (PV) systems are pushing Governments and large Companies operating in electricity generation and distribution network management to develop tools able to better define the potential productivity of PV systems on a large scale, such as solar maps. However, solar maps mainly consider phenomena related to weather and geometry, with a low level of detail on second order effects. This research aims at the integration of additional technical aspects into solar maps, by means of diagrams able to increase the reliability in the assessment of potential electricity generation. For this purpose, more technical factors are taken into account, such as the variation of PV panel efficiency with cell temperature, the shadow cast by the preceding PV panel array, here including the action of by-pass diodes, and the ratio of active area over the area available for installation.

In this paper an improvement of the model CaRM (CApacity Resistance Model) is presented to consider the borehole thermal capacitance, both of the filling material of the borehole and of the heat carrier fluid inside the ground heat exchanger. Several models, numerical and analytical, are available in literature for short time step analyses of ground-coupled heat pump systems. According to the modelling for the surrounding ground, the new approach for the inside of the borehole is based on electrical analogy. In this study the double U-tube ground heat exchanger is analyzed. The new model has been validated by means of a commercial software based on the finite elements method as well as measurements of ground response test, using a suitable plant system. In this last comparison, the contribution of the thermal capacitance of the circulating fluid is investigated, since it is frequently neglected in short time step simulations. In both cases, there is agreement between the CaRM results and data from numerical simulations and measurements as well.

This paper considers the topic of natural ventilation in school buildings that is faced not only for energy saving, but also for the fundamental exigency of the indoor comfort. This analysis is developed by measuring the concentration of carbon dioxide as a significant indicator of IAQ when pollution is mainly due to the presence of people. In this paper are presented the results of a monitoring campaign of the CO 2 levels carried on in classrooms. The measures show the criticality of IAQ with values often much higher than the limits specified by standard, but also the possibility to act effectively with the manual ventilation without excesses that could create comfort problems or waste of energy.

This paper shows the results of a monitoring campaign on an invertible ground source heat pump (GSHP) with borehole heat exchangers installed in the historical center of Venice in the frame of the renovation of an ancient building where other renewable energy systems, such as solar energy systems, are not admitted because of historical preservation regulations. Despite the coastal position, the use of surface or ground water was not achievable in this case. In fact, the withdrawal from wells is absolutely forbidden in Venice, due to the risk of subsidence of the soil. In addition, as often happens in Venice, the internal channels next to the building have insufficient water flow rate. The experimental analysis highlights very satisfactory performance especially in comparison with the alternative use of air source heat pumps. The high humidity of the soil and the underground water flow present even in the surface layers of the soil promote the quick thermal rebalancing in the borehole field. For the same reason, although there is unbalance between the heat rejected in summer and the one extracted during winter, no consequent thermal degradation of the ground heat exchange is encountered.

Nowadays the heat pump is gaining new interest thanks to recent regulations which include this technology among those able to exploit renewable energy sources in addition to the already acknowledged opportunity to achieve significant energy and economic benefits if well applied In particular the use of geothermal energy as heat source/sink looks very promising. Besides the use of ground heat exchangers and water from wells, an adequate availability of surface water can suggest its use for the heat pump especially when it is impossible the application of the other two alternatives. This is the case of the plant here reported. A heat pump installed in the historical centre of Venice and using lagoon water for the HVAC plant of a historical structure refurbished for hotel use. The plant characteristics and the adopted technical solutions are here illustrated as well as the results of an annual monitoring of the building-plant system. The experimental data have also permitted a comparison with the performances of alternative plant solutions simulated in front of the same operative conditions. For this aim the two case studies of a corresponding air source heat pump and a more traditional solution, based on condensing boilers and air cooled chillers, have been considered. The performance analysis shows a net superiority for the surface water heat pump.

The spread of diffuse energy generation systems such as photovoltaics and combined heat and power generators will convert buildings from sole energy consumers into energy prosumers, i.e. energy producers and consumers. This will involve a much more dynamical interaction between buildings and the energy grid. As a consequence, electric distribution networks will be required to coordinate the energy draw/supply in order to optimize the use of renewable energy sources and preserve the reliability of the energy dispatch system, thus becoming smart grids. Smart grids will be able to act as coordinators of energy flows between diffuse energy producers and consumers, but buildings will be mainly managed in order to minimize their interaction with energy grids, thus minimizing the volatility of energy supply/draw, thus they will integrate energy management systems aimed at taking advantage of locally generated energy. In fact, buildings will be required to locally generate as much energy as possible, towards a Zero Energy Building perspective. For this purpose they will exploit technologies able to modulate energy demand and production by a suitable design of the building. So how will buildings, and consequently the related architecture, evolve in order to achieve these goals? In this paper the present status of the art as well as building configurations, procedures and energy management strategies able to ensure the best integration of typical residential and office buildings into smart grids are analysed.

In recent years living walls have increasingly spread, thus becoming a diffuse architectural envelope cladding technology. Consequently, a more precise understanding of their thermal behavior and impact on the building energy balance are needed. One of the most important effects provided by the use of living walls is the shading of the building envelope, with clear benefits during the cooling period. Furthermore, many features characterize the thermal behavior of living walls, namely plant species, leaf area index (LAI), evapotranspiration, emissivity and air cavity type. All these particular characteristics have been accounted in the mathematical model developed in the frame of the presented research, whose aim is to provide a tool for the prediction of the thermal behavior of living walls. Two kinds of living walls, one with grass and closed air cavity and the other one with vertical garden and open air cavity were considered. The results achieved by means of the developed model show a good agreement with the measurements also supported by model efficiency indexes such as Nash–Sutcliffe efficiency index (NSEC). Values of around 0.7 were obtained for the NSEC index for both the investigated living walls.

Ground source heat pump (GSHP) systems are spreading also in Southern Europe, due to their high energy efficiency both in heating and in cooling mode. Moreover, they are particularly suitable in historical cities because of difficulties in the integration of heating/cooling systems into buildings subjected to historical preservation regulations. In these cases, GSHP systems, especially the ones provided with borehole heat exchangers, are a suitable solution instead of gas boilers, air-cooled chillers or cooling towers. In humid soils, GSHP systems are even more interesting because of their enhanced performance due to higher values of soil thermal conductivity and capacity. In this paper, GSHP systems operating under these boundary conditions are analyzed through a specific case study set in Venice and related to the restoration of an historical building. With this analysis the relevant influences of soil thermal conductivity and yearly balanced heat transfer in the design of the borehole field are shown. In particular, the paper shows the possibility to achieve higher compactness of the borehole field footprint area when yearly balanced heat transfer in the borehole field is expected. Then, the second set of results contained in the paper shows how GSHP systems designed for high humidity soils and yearly balanced heat loads at the ground side, even if characterized by a compact footprint area, may still ensure better performance than other available and more common technologies such as boilers, air-cooled chillers, chillers coupled with cooling towers and heat pumps and chillers coupled with lagoon water. As a consequence, in this last comparison, the efficiency of GSHP systems is confirmed even when compact borehole installation areas are used. The analysis is performed in terms of both input energy consumption ratio and primary energy ratio and takes into account the energy consumption of auxiliary devices as well. The conclusions are drawn in terms of percentage, thus allowing the reader to extend the results achieved in this paper to systems operating in other contexts under similar boundary conditions.

In the urban area the air temperature has been growing at a faster rate (Urban Heat Island UHI) leading to greater use of air-conditioning and energy demand. One possible strategy to lower ambient temperature is to increase the amount of greenery in the city. In this context we have assisted recently in a rediscovering of buildings envelopes claddings by green walls, living walls and green roofs. Green walls may consist of green facades made up of traditional creepers and living walls are vertical claddings with plants, installed on the building facade. A very detailed field measurement campaign was performed on a living wall with the aim of evaluating its performance versus a traditional envelope. The field measurements were performed between June and September 2011. Hourly measurements of surface temperatures, heat fluxes, ambient and internal temperatures, ambient and internal relative humidity, air velocity in the living wall cavity and climatic variables have been collected for the bare and covered wall. Using a numerical model, validated via field measurements, a multiparametric analysis has been performed considering the effect on energy consumption and temperature behaviour for different orientations of the living wall in different locations.

The EPBD (Energy Performances of Buildings Directive) updated on 9 July 2010 imposes new rules for energy savings in buildings. By 31 December 2020 all new buildings must be nearly Zero Energy Buildings (nZEB) with reference to the consumption of fossil fuels. The roadmap that each nation is adopting for this purpose imposes a further significant increase in the share of the building energy requirement covered by renewable energy. Achieving this goal at acceptable costs for the communities represents a real challenge considering the current state of the art. The role of Eco-Architecture will be fundamental in this phase of introduction and spread of innovative techniques in the design of building-plant system. For this aim, the installation of heat pumps for building heating is able to contribute significantly in terms of better energy performance and exploitation of renewable energy. In fact, in the EPBD the energy from heat sources of heat pumps (air, ground, water) is considered renewable energy. An assessment about the possibilities and limits of the electric heat pump installation in dwellings is here reported for different case studies and climates in Europe.

HVAC plant designers and energy auditors often face the problem to calculate the performance of heat pumps under various boundary conditions. In this paper a model aimed at that purpose is presented. In particular, the model presented is aimed at the simulation of vapor compression based heat pumps or chillers driven by volumetric compressors. It is a numerical model tracing a reference thermodynamic inverse cycle consistent with the specific heat pump or chiller under the requested boundary conditions. The input data necessary are few and easy-to-find, especially if compared with the other simulation models proposed in literature. The proposed simplified model makes it possible to use catalog data in order to get reliable results. Even if the amount of input data required is low, the numerical model showed a good accuracy (within 10%) contrasted against performance declared by manufacturers. Moreover, the model has low sensitivity to user assumptions so it is valid also for the prediction of the performance in old HVAC plants. Moreover, this numerical model is fast and suitable for integration within building energy simulation tools. The present model does not take into account air dehumidification at the evaporator nor defrost cycles, whose implementation is currently in progress.

Water based surface embedded heating and cooling systems have gained appreciable interest and success for a variety of applications in new buildings and renovations. Some problems related to the correct design of these systems were solved a long time ago, but some uncertainties still remain, especially as regards the thermal behaviour under transient conditions. In this context a numerical model able to perform the detailed simulation of the dynamic behaviour of water based surface embedded heating and cooling systems developed by authors is presented in this paper. It is validated versus test room measurements. In order to perform the validation under real use boundary conditions, the test room was subjected to heating/cooling load profiles aimed to simulate different climatic conditions which have to be faced by ceiling radiant panels. The results achieved show that the presented model can predict the real room conditions and that results are not affected by the use of variable or fixed convective heat transfer coefficients.

The improvement of the energy efficiency of building stocks mostly consisting of heritage-listed buildings is a crucial issue from the environmental and economic points of view. However, the related interventions must take into account the non-monetary value due to their importance in the field of heritage preservation. As such, the interventions must be compatible with restoration principles aimed at preserving the main characteristics of the building (dimensions, materials and aspect). Moreover, when Institutions and large Companies act on large building stocks, they need procedures and decision tools able to define the most convenient set of interventions dedicated to each building. In such a context, it is very useful to merge restoration compatibility with energy (and, consequently, economic) assessments. This paper shows the results coming from the application of such an approach, by tracking the main steps of the following procedure and by showing its main advantages. In particular, we evaluate the compatibility of retrofit interventions through the assessment of a restoration compatibility score, which comes from a multi-criteria procedure.