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A significant part of the housing stock in southern Europe is obsolete and in need of extensive retrofitting to improve its energy performance and thermal comfort. However, before adequate retrofit measures can be proposed for this housing stock, the characterization of current building performance is fundamental. Although the simulation tools frequently used and widely accepted by the scientific community ensure accurate results, these require high computational times. The main aim of this paper is the development of a surrogate model to speed up the thermal comfort prediction for any member of a building category, ensuring high reliability by testing the entire simulation process with real data measured in-situ. To this end, an artificial neural network (ANN) is generated under MATLAB® environment using the data obtained from EnergyPlus simulations for linear-type social housing multi-family buildings in southern Spain, which were constructed in the post-war period. The developed ANN provides a regression coefficient between simulation targets and ANN outputs of 0.96, with a relative error between monitored and simulated data below 9%. A further result is that the building category characterization shows a general lack of suitable indoor thermal comfort conditions, thereby showing the great need for effective retrofit strategies.

Facing the climate change is a common priority, due to ethical issues related to general concept of sustainability and livable future for the next generations. Moreover, ethical aims for contrasting energy poverty, heat-related diseases and deaths, availability of food and water, infections and viral-bacteriological risks, meteorological extreme phenomena, such as floods and intense and destructive precipitations, are stringent and pressing targets. All serious and independent investigations reveal future scenarios of an overall global warming that surely make worrying the evolution of quality of life on this earth. Each one has to do his part. In this study, the research is focused on renewable technologies for the passive cooling of buildings. Indeed, the space cooling is a strongly increasing use of energy and induces a vicious circle, being, at the same time, a cause and an effect of the anthropogenic overheating of the planet. The paper mainly reviews techniques for suitably governing the energy interaction between buildings and surrounding environment. The energy efficiency concerns the building envelope design, the use of efficient HVAC systems, adoption of renewable energy on-site. On the other hand, every energy conversion process determines waste heat, so that also a ‘free of operational cost’ solar cooling system however causes dissipation of heat into the ambient. Finally, renewables cannot be the unique solutions for supplying the energy required for the building use. Conversely, strategies for reducing the building cooling are needed, and these are reviewed in this study. In thermodynamics terms, the building is seen as part of the system and not the mere control volume. Greenery of facades and roofs, phase change materials, nocturnal convective cooling, evaporative and ground cooling, solar systems such as chimneys for improving the building ventilation are here discussed, as well as emerging technologies such as breathing walls and dynamic insulation. The reviewed studies, selected on the basis of more recent progresses concerning the investigated technologies, revealed potentialities but also criticalities in the design.

Building activity is the sector that affects for the most part the anthropogenic climate change. Indeed, even if differences can be found among countries, according to the level of development and climates, buildings require about 30–40% of the overall energy demand, with similar share concerning the greenhouse emissions. According to the more recent EU Directives in matter of energy efficiency in energy use, a great attention has to be paid to energy refurbishments of existing buildings. Indeed, the turnover rate of the EU building stock is generally low in fully-developed countries, so that the energy retrofits are also more important compared to new nearly zero-energy buildings. The proposed investigation concerns the demonstrative role of the public hand, whose necessity is underlined by the EU Directives 2010/31/EU and 2012/27/EU, through a multi-step and multi-objective optimization of an educational building of an Italian University. All preliminary investigations aimed at a reliable modelling, the iterative method that combines genetic algorithms and transient energy simulations tailored on calibrated numerical models make the investigation complete and repeatable. All levers of energy efficiency have been pressed, and thus the refurbishment of building envelope, HVAC systems, integration of energy supply by renewables. The multi objective optimisation concerns costs, incentives, indoor comfort, energy demands for heating and cooling and a novel approach is proposed for choosing the best configuration of retrofit. It is resulted that the most profitable energy efficiency measures involve the modernization of energy systems, even if also the retrofit of the building envelope can be profitable under favourable financial conditions. The cost-effective refurbishment reduces the primary energy demand up to a value of 12 kWh/m2a, so that the building can be surely considered as nZEB.

A new comprehensive approach is proposed to support cost-optimal design of building envelope’s thermal characteristics and HVAC (heating, ventilating and air-conditioning) systems in presence of a simulation-based model predictive control (MPC) for heating and cooling operations. The cost-optimal solution is identified through a main mono-objective genetic algorithm (GA) that minimizes global costs for space conditioning. The explored solutions represent building thermal designs integrated with the MPC of HVAC systems. For defining the MPC strategies, the main GA launches two secondary bi-objective GAs that optimize heating and cooling operations, respectively. These secondary GAs perform Pareto optimizations by minimizing operating costs and thermal discomfort. They provide the optimal hourly set point temperatures for heating and cooling operations, with a day-ahead planning horizon, by considering the forecasts of weather conditions and building use. The optimal control strategies are found based on requirements of users, who set a minimum comfort level to be fulfilled. The GAs are implemented by coupling MATLAB ® with EnergyPlus. The methodology is applied to a new multi-zone residential building in Naples (Southern Italy). It yields primary energy savings around 35.4 kW h/m 2 a and global cost savings around 7000 €, ensuring the same satisfying comfort level, compared to a standard design approach.

How to predict building energy performance with low computational times and good reliability? The study answers this question by employing artificial neural networks (ANNs) to assess energy consumption and occupants' thermal comfort for any member of a building category. Two families of ANNs are generated: the first one addresses the existing building stock (as is), the second one addresses the renovated stock in presence of energy retrofit measures (ERMs). The ANNs are generated in MATLAB ® by using the outcomes of EnergyPlus simulations as targets for networks' training and testing. A preliminary ‘Simulation-based Large-scale sensitivity/uncertainty Analysis of Building Energy performance’ (SLABE) is conducted to optimize the ANNs' generation. It allows to identify the networks' inputs and to properly select the ERMs. The developed ANNs can replace standard building performance simulation tools, thereby producing a substantial reduction of computational efforts and times. This can allow a wide diffusion of rigorous approaches for retrofit design, which are currently hampered by the excessive computational burden. As case study, office buildings built in South Italy during 1920–1970 are investigated. Comparing the ANNs' predictions with EnergyPlus targets, the regression coefficient is between 0.960 and 0.995 and the average relative error is between 2.0% and 11%.

Design criteria for a residential nZEB in Mediterranean climate are discussed. The integrated design procedure focuses on the problem of a large number of available building variants concerning the building envelope. The aim is to search the ones that minimize winter and summer energy demand without compromising thermal comfort. The adopted methodological approach combines the use of dynamic energy simulation tool (EnergyPlus), based on a one-dimensional conduction finite difference solution method, and a constrained multi-objective optimization algorithm. For four cities (Madrid, Nice, Naples, Athens), several passive strategies are compared: thermal properties of the building envelope, adoption of phase change materials with different melting temperatures, cool roof solutions, several window/wall ratio values, some external and internal shading systems. The results allow to evidence that it is difficult to understand the best trade-off between summer and winter performance, by assuring high standard of thermal comfort when the aim is to reach NZEB objectives in Mediterranean climate. However, some guidelines are indicated, starting from the discussed results.

Nowadays the study of Net Zero Energy Buildings (NZEBs) is fundamental, because they are the main strategy to reduce the building energy demand and CO2-equivalent emissions. This paper analyses a case study concerning a multipurpose building located in Palermo (Southern Italy), and evaluates the benefits related to the use of an earth-to-air heat exchanger in a NZEB, in terms of energy saving and reduction of CO2-equivalent emissions, for a Mediterranean climate. The chosen building envelope is thermally performing. The HVAC system consists in fan-coil units connected to an air-to-water heat pump, and mechanical ventilation. The energy demand is reduced by an earth-to-air heat exchanger that pre-heats the ventilation outside air in winter and cools it in summer. The optimization of the heat exchange with the ground is a key-element to reduce the primary energy requirements and CO2-equivalent emissions, especially during summer. Moreover, this paper assesses the possibility to obtain a NZEB using only on-site renewable energy (on the roof of the building), with and without the earth-to-air heat exchanger. The energy analysis is carried out by means of a dynamic building simulation engine, namely EnergyPlus. In addition, a thermal performance and an environmental analysis are performed.

Public energy policies must support the deep energy retrofit of buildings in order to fight climate change and energy poverty. Assessing the impact of such policies is extremely important because the supported energy retrofit measures (ERMs) can ensure huge energy, economic and environmental benefits. However, the energy investigation of wide building stocks is very complex. This issue is here tackled by using and enhancing the methodology SLABE ('Simulation-based Large-scale uncertainty/sensitivity Analysis of Building Energy performance'), which conducts reliable analyses of energy retrofitting building categories. SLABE employs Latin hypercube sampling to generate Representative Building Samples (RBSs), which represent the energy behaviour of the explored building stock. Then, post-processing is applied to assess the impact of proper ERMs on energy consumption, polluting emissions and lifecycle costs. Thus, the cost-optimal retrofit solutions are found in absence and presence of financial incentives, respectively. The outcomes are exploited to assess the effectiveness of current energy policies and to propose potential improvements for harmonizing the public and private perspectives. The methodology combines EnergyPlus and MATLAB®. As case study, it is applied to the Italian office building stock. The outcomes show huge potential energy and cost savings as well as polluting emission reductions.

The paper proposes a multi-objective optimization approach to address the energy design of the building envelope. A genetic algorithm (GA) is implemented by means of the coupling between MATLAB® and EnergyPlus to minimize primary energy consumption (PEC), energy-related global cost (GC) and discomfort hours (DH). The design variables concern the set point temperatures, the radiative properties of plasters, the thermo-physical properties of envelope components, the window type, the building orientation. The GA performs a Pareto optimization and finally two optimal solutions are recommended: the nZEB (nearly zero energy building) optimal solution, which minimizes PEC, and the cost-optimal solution, which minimizes GC. These solutions provide the optimal design strategies for the public and private stakeholders, respectively, which represent the main actors involved in building design. The approach is applied for the design of a new typical Italian residential building. Four locations are considered to investigate the typical Italian climates. The outcomes can give precious indications to rebuild the Italian residential stock with a view to energy-efficiency and cost-optimality, given that the optimal solutions provide low values of PEC – between 62.0 and 91.9 kWhp/m2a – and of GC – between 456 and 665 €/m2 – depending on the location.

The comprehensive optimization of building energy design is fundamental to promote sustainability but it is an arduous issue that involves a huge domain of variables and objectives. The proposed investigation addresses this issue through a novel comprehensive framework – Harlequin – that performs a multi-phase and multi-objective design optimization. Three phases are carried out to optimize design variables related to the whole building-plants system, considering different energy, comfort, economic and environmental performance indicators. Phase 1 implements a genetic algorithm to achieve the Pareto optimization of envelope, geometry and space conditioning set points. Phase 2 performs a smart exhaustive sampling of design scenarios to find optimal energy systems. Phase 3 provides the most sustainable, the cost-optimal and the lowest investment (but energy-efficient) design solutions. Among these, the stakeholders can choose the best solution according to their wills and needs. Harlequin uses EnergyPlus (only in phase 1) and MATLAB® and it is so-called because building geometry and envelope are optimized for each exposure, thereby providing “Harlequin buildings”. The novelty and scientific significance consist in ensuring a reliable design optimization by investigating a domain of variables and objectives, as comprehensive as never before. As a case study, Harlequin is applied to design a typical Italian office in Milan. Compared to a reference design, significant reductions of primary energy consumption (PEC), global cost (GC) and CO 2 -eq emissions can be achieved, depending on the chosen solution. The maximum reductions are 43.9 kWh p /m 2 a for PEC, 63.9 €/m 2 for GC (discount rate of 3%) and 12.3 kg/m 2 a for CO 2 -eq. © 2019 Elsevier Ltd

A comprehensive multi-objective optimization framework is proposed to address the energy retrofit of typical villas on Mediterranean coastlines. Primary energy consumption and global cost are minimized using a Pareto approach. Two different construction technologies (i.e., a lightweight house in reinforced concrete and a massive tuff-made villa), in two different climates (i.e., Greek and Italian coasts), are investigated to provide robust optimal retrofit strategies according to two different criteria, i.e., the achievement of the nearly zero energy standard and the cost-optimality, respectively. The optimal energy retrofit strategies are achieved by coupling transient energy simulations and a genetic algorithm. They address all main factors affecting energy performance, i.e., building envelope (thermal insulation, reflectance of coatings, windows and solar shading), active energy systems (space conditioning devices) and renewable energy sources (solar photovoltaics). The investigation findings can provide useful generic guidelines for the retrofit of houses on the Mediterranean coastlines with a view to energy-efficiency and cost-effectiveness. The implementation of the suggested retrofit strategies to the case studies can yield substantial primary energy savings, up to 125 kWh/m2a, and global cost savings, up to 140 €/m2. The most energy-efficient and cost-effective retrofit solutions are the improvement of energy systems’ efficiency, the installation of full-roof photovoltaic systems, the replacement of windows and the roof thermal insulation.

Zero-energy and zero-carbon buildings would be a huge opportunity for contrasting the climatic changes and, more in general, the deterioration of the microclimate inside and around cities. About it, a question appears compulsory: are zero-energy and zero-carbon concepts applicable at urban scale? This paper tries to answer to this question, by discussing the possible effects of the application of appropriate city planning techniques when a new settlement is designed. An integrated approach to urban planning is applied to a case study, for promoting the design of buildings with very low (or zero) energy needs, characterized by high indoor comfort conditions, by taking into consideration whole city areas, with different kinds of services. Passive heating, cooling and daylighting techniques have been combined, as well as the integration of renewable sources, in order to minimize the energy demand and environmental impact, for having a sustainable ‘urban balance’ and, in general, a sustainable urban growth. As real case study, the design of the holiday village ‘Olympiad’ is presented; it should be built in an unstructured seaside area in Greece. Several indexes are introduced to evaluate the global sustainability of the settlement, through the application of the definition of ‘on-grid ZEB’, with reference to each building as well as for the entire village. This kind of research could help city planners for a growth inspired to general goals of urban sustainability.

Efficient HVAC devices are not sufficient to achieve high levels of building energy performance, since the regulation/control strategy plays a fundamental role. This study proposes a simulation-based model predictive control (MPC) procedure, consisting of the multi-objective optimization of operating cost for space conditioning and thermal comfort. The procedure combines EnergyPlus and MATLAB ® , in which a genetic algorithm is implemented. The aim is to optimize the hourly set point temperatures with a day-ahead planning horizon, based on forecasts of weather conditions and occupancy profiles. The outcome is the Pareto front, and thus the set of non-dominated solutions, among which the user can choose according to his comfort needs and economic constraints. The critical issue of huge computational time, typical of simulation-based MPC, is overcome by adopting a reliable minimum run period. The procedure can be integrated in building automation systems for achieving a real-time optimized MPC. The methodology is applied to a multi-zone residential building located in the Italian city of Naples, considering a typical day of the heating season. Compared to a standard control strategy, the proposed MPC generates a reduction of operating cost up to 56%, as well as an improvement of thermal comfort.

During the cooling season, the beneficial effects of cool colors and cool paints are multiple and undebatable. Really, it is not well-know their impact during the heating season, when a heated external surface could be useful in order to reduce the heat losses. This paper, by means of experiments and numerical simulations, investigates the effect of high-reflective and high-emissive coatings on the building energy performance in Mediterranean climate. Four coatings are used; among these, an acrylic white paint of household appliances or automotive sector has been tested since it is characterized by very fast drying, good adhesion directly to different type of materials, greater durability than traditional paints and lower costs. The experiments have been carried out by using the test-room of the University of Sannio; the results of wintertime monitoring campaign are presented. By means of simulations, using as case study a typical office building, the effect of combination of roof reflectivity, roof technology and insulation thickness is discussed. Research results can support design strategies for optimizing the yearly energy performance of the building, reducing environmental impacts but these also demonstrate the performance of unconventional cool material, as the acrylic paint, with a lower aging and maintenance needs.

About 40% of global energy consumption is due to buildings. For this reason, many countries have established strict limits with regard to building energy performance. In fact, the minimization of energy consumption and related polluting emissions is undertaken in the public perspective with the main aim of fighting climate change. On the other hand, it is crucial to achieve financial benefits and proper levels of thermal comfort, which are the principal aims of the private perspective. In this paper, a multi-objective multi-stage approach is proposed to optimize building energy design by addressing the aforementioned public and private aims. The first stage implements a genetic algorithm by coupling MATLAB® and EnergyPlus pursuing the minimization of energy demands for space conditioning and of discomfort hours. In the second stage, a smart exhaustive sampling is conducted under MATLAB® environment with the aim of finding constrained cost-optimal solutions that ensure a drastic reduction of global costs as well as of greenhouse gas (GHG) emissions. Furthermore, the impact of such solutions on heat emissions into the external environment is investigated because these emissions highly affect urban overheating, external human comfort and the livability of our cities. The main novelty of this approach is the possibility to properly conjugate the public perspective (minimization of GHG emissions) and the private one (minimization of global costs). The focus on the reduction of heat emissions, in addition to the assessment of energy demands and GHG emissions, is novel too for investigations concerning building energy efficiency. The approach is applied to optimize the retrofit of a reference building related to the Italian office stock of the 1970s.

Scientific literature about energy retrofit focuses on single buildings, but the investigation of whole building stocks is particularly worthy because it can yield substantial energy, environmental and economic benefits. Hence, how to address large-scale energy retrofit of existing building stocks? The paper handles this issue by employing a methodology that provides a robust energy analysis of building categories. This is denoted as SLABE, “Simulation-based Large-scale uncertainty/sensitivity Analysis of Building Energy performance”. It was presented by the same authors and is here enhanced to investigate a whole and heterogeneous building stock that includes various categories. Each category is represented via a Representative Building Sample (RBS), which is defined through Latin hypercube sampling and uncertainty analysis. Hence, optimal retrofit packages are found in function of building location, intended use and construction type. Two families of optimal solutions are achieved. The first one collects the most energy-efficient (and thus sustainable) solutions, among the ones that produce global cost savings, thereby addressing the public perspective. The second one collects cost-optimal solutions thereby addressing the private perspective. EnergyPlus is employed as a simulation tool and coupled with MATLAB® for data analysis and processing. The methodology is applied to a significant share of the Italian public administration building stock, which includes several building categories depending on location, use destination and construction type. The outcomes show huge potential energy and economic savings, and could support a deep energy renovation of the Italian building stock.

Most European buildings built before 1980s were constructed without any design concern for energy efficiency and environmental sustainability. In addition to this issue, over the last decades, the essential need of safer buildings has progressively attracted the interest of scientific community and government institutions. However, the strong interaction between energy and structural aspects in building retrofit design has never been handled via robust and reliable approaches. The present study explores this knowledge gap by introducing a novel multi-step approach that addresses the retrofit of existing buildings by integrating energy, structural and economic aspects. To this end, a multi-stage energy optimization is carried out by implementing a genetic algorithm and a smart research strategy. Thus, the cost-optimal energy retrofit solution is identified and the impact of the expected economic losses due to seismic damage is assessed throughout the building lifecycle. The methodology is applied to a multi-story residential building, considering the effects of two different building locations, namely Milan and Norcia. These latter are characterized by similar climatic conditions but by a different level of seismic risk, which is higher for Norcia. The outcomes show that the estimated seismic economic losses associated with the energy retrofit solutions are strongly affected by the building location. Thus, the selection of the optimal energy retrofit measures should be related to the building structural behavior in order to achieve reliable economic and sustainability benefits.

A previous study has evidenced the poor energy performances of a building owned by the University of Naples Federico II. In detail, a reliable energy audit, by means of calibrated input, has been performed, and it revealed energy requests, polluting emissions and energy costs very high. By taking into consideration the exemplary role of the public hand, according to the EU Directives 2010/31/EE and 2012/27/EU, here a cost-optimal energy refurbishment is proposed, by analysing several energy efficiency measures, firstly singularly analysed and then combined in order to evaluate the super-positon effect.

The public hand has a demonstrative role in matter of energy efficiency of owned or occupied buildings. Here, the energy audit of a high-rise university building is proposed. The methodology adopts the Cost-Optimal approach, as imposed by the European guidelines (EU Directive 2010/31/EU), based on feasibility studies performed with transient energy simulations. In particular, in situ surveys (infrared thermography and measurements of U-values) have been used for building, as detailed as possible, the building model for the numerical study. The analysis evidenced high-energy demands, mainly for the space heating and cooling. A second study discusses a cost-effective energy retrofit.

The climate evolution towards a progressive increase of Earth's temperature is leading to many worrying consequences, involving different aspects of World life. Among them, a specific focus should be given to the resilience of building energy design to global warming, since the efficiency and effectiveness of energy conservation measures over time can be highly affected by climate change. In this vein, the paper applies a multi-stage, multi-objective approach to find robust cost-optimal energy retrofit solutions and to assess their resilience to global warming. The approach combines the software EnergyPlus and MATLAB® to implement an optimization genetic algorithm and a smart research strategy. This framework allows to explore a huge solution domain by investigating sundry performance indicators, such as energy needs, polluting emissions and global costs, thereby ensuring a robust assessment of cost-optimality. Different cost-optimal retrofit solutions are found for different global warming and economic scenarios. Finally, a careful decision-making is performed to identify a recommended solution that provides the highest resilience to the cited scenarios, yielding the best trade-off among energy, environmental and economic performances. The approach is applied to a typical Mediterranean building, located in South Italy. The recommended solution includes the energy retrofit of the whole building envelope and the replacement of energy systems. It requires an investment around 100 €/m2 and, in most scenarios, produces high potential benefits in terms of primary energy savings (42 ÷ 44 kWh/m2a), polluting emission reductions (11.5 ÷ 12.0 kgCO2-eq/m2a) and global cost savings (5 ÷ 78 €/m2).

The evaluation of performance of historical masonry buildings requires a multidisciplinary approach. Indeed, the use and functionality of a building is a multidisciplinary item related to various issues as structural and thermal aspects, acoustic requirements and efficiency of active energy systems. Since these buildings are often used for strategic, educational and recreational facilities (offices, hospital, barrack, school, university, library, museum) or as residences, they frequently need both structural interventions for warrant safety under static and dynamic actions and energy refurbishment for warrant a comfortable and optimal use of the building depending on its specific use. Since the energy refurbishment can be easily associated to structural consolidation or functional reorganization works, this paper is aimed to introduce a methodological approach with reference to both structural behavior and energy performance for the space heating and cooling. The main steps are the survey, the diagnosis, the creation of a numerical Finite Element model necessary for the verification of the structural safety, the validation of a dynamic model for energy performance assessment and the choice of criteria and techniques of interventions. The proposed approach combines both structural and energy analyses, based on a detailed identification of the building, carried out by means of in situ tests and surveys. As case study, the proposed approach has been applied to Palazzo Bosco Lucarelli, a historical masonry building located in the ancient center of Benevento (South Italy).

A key element of the Energy Performance of Building Directive 2010/31/EU is the introduction of nearly zero energy building (NZEB) standard for new constructions. However, considering the very low rate of new built volume, the major change for achieve the sustainable grow of the European economy, appears to be the renovation of existing building stock. But, is it possible to reach very low or nearly zero energy standard during refurbishment design? Proposed paper tries to answer this question, evaluating if the refurbishment of historic architectures to very low energy need is possible and economically feasible. With reference to a case study, this paper investigates the cost-optimal energy refurbishment of a Renaissance-style palace, located in the center of Naples, South Italy. The adopted methodology consists of various steps. Firstly, a model of the building has been accurately built and calibrated. Then, it has been used to evaluate possible interventions concerning both the envelope and the energy systems. The best solutions, chosen according to the European methodology of cost-optimality, have been combined in a last simulation. The results show that great energy savings as well as economic and environmental improvements are possible, although heritage buildings present a less flexibility in the proposal of energy efficiency measures. © 2017 The Authors.

The cost-optimal analysis provides the most cost-effective energy retrofit solutions. This can strongly support the deep renovation of buildings. However, an outstanding question arises: How to achieve the robust assessment of cost-optimal solutions, feasible for any building? The paper answers this question by proposing a new multi-stage framework for c ost-optimal a nalysis by multi-objective optimi s ation and a rtificial neural networks, called CASA. It couples EnergyPlus and MATLAB®. A genetic algorithm allows to select recommended retrofit packages by minimizing energy consumption and thermal discomfort. Among these packages, the cost-optimal solution is identified. It is robust because the algorithm explores a wide domain of retrofit scenarios. The optimization procedure uses artificial neural networks to predict building performance. Large-scale uncertainty and sensitivity analyses are conducted to support the generation of the networks. These latter are tested against data provided by current literature with excellent results. The networks’ applicability to whole building categories and rapidity of evaluation make the procedure feasible for any building. For demonstration, CASA is applied to a reference office building located in South Italy, by investigating the related category. The achieved cost-optimal solution produces global cost savings around 42.4 €/m2, and significant reductions of energy consumption, discomfort hours and polluting emissions.

The issue of the summer indoor overheating in modern buildings is investigated. Indeed, mainly for heating dominated climates, usually there is a great attention to the design of measures for reducing the energy losses in winter, while the summer comfort often is secondary or neglected. On the other hand, just where the warm season is not so hard, passive energy measures have to be deeply exploited, in order to avoid the installation of air-conditioning systems, with positive effects on both the building and city scales (e.g., the reduction of urban heat islands). After a general overview of the overheating phenomenon, a case report is proposed, where, even if the summer ambient conditions are not extreme, thermal discomfort has been registered during the first years of operations. The office building, recently built in Berlin, fulfils the German requirements of energy efficiency and heat protection in summer. It is not equipped with mechanical systems for the space cooling. According to the new international approach of the cost-optimality, this study investigates strategies for improving the indoor conditions – evaluated by means of the adaptive criteria – during the cooling season, by analyzing various solutions for reducing the heat gains. By means of calibrated numerical models, validated by comparisons with measurements of indoor air temperatures (free-running building), transient energy simulations have been performed. The target of investigation is the research of the optimal solution of solar shadings (i.e., typology and management), in order to find the best compromise in terms of thermally comfortable hours, use of artificial lighting, operational and investment costs.

The German Federal Government put its first net zero office building in operation in 2013 anticipating EU requirements for all public administrations to solely built “nearly zero energy buildings” from 2019 onwards. The two-storey building is situated in Berlin and has been designed for having an overall annual energy demand lower than the in-situ conversion of renewable energies. The paper shows the results of the first year of the operation. The overall annual electric usage is near to the expected value. Nevertheless, intensive monitoring showed differences between the expected and the measured electric usage in the areas of heating and domestic hot water (+172%), ventilation (−36%), lighting (−33%), equipment and auxiliaries (−14% and −13%, respectively), yield of the PV-system (+32%). A numerical model was created to investigate these deviations as well as to evaluate the impact of possible actions aimed at further improving the energy demand of the building. The model was calibrated with measured data, data from surveys, occupancy schedules, and validated by means of different indexes, among which the mean bias error (MBE). The MBE between monitored and simulated energy performance is below ±2% for all stated areas of energy usage. Analogously, the energy needs for cooling, monitored and simulated, as well as the trends of the indoor air temperature in both heating and cooling seasons, are in a very good agreement. In detail, the monthly MBE for the indoor temperature, in specific summer and winter periods and in the considered rooms, is below the threshold of ±5%, with values slightly higher (anyway lower than ±6%) only at the ground floor. Finally, the paper shows that the reasons for the detected deviations in electric energy usage can mainly be related to the usage pattern of the building and to the occupants’ behavior. In order to ensure energy efficiency as high as planned, a suitable monitoring of the energy performance is fundamental. It enables the calibration and validation of tailored energy models to detect possible malfunctions as well as propose actions aimed at further reducing the energy usage of the building.

The ‘Energy Performance of Buildings Directive’ Recast (i.e., 2010/31/EU) establishes that building energy retrofit should pursue “cost-optimal levels”. However, a reliable and rigorous cost-optimal analysis is an arduous and computationally-expensive issue, especially for complex buildings such as hospitals. The paper tackles this issue by providing a novel methodology to identify robust cost-optimal energy retrofit solutions. Multi-stage and multi-objective (Pareto) optimization is performed with the aim of minimizing the computational burden required to achieve reliable outcomes. The methodology combines EnergyPlus and MATLAB® and includes two optimization stages, preceded by a preliminary energy investigation that performs Latin hypercube sampling and sensitivity analysis. The preliminary investigation and the first optimization stage, which runs a genetic algorithm, aim at detecting efficient energy retrofit measures (ERMs) to reduce thermal energy demand for space heating and cooling. In the second optimization stage, these ERMs are combined with further ERMs, addressed to improve the efficiency of energy systems and to exploit renewable energy sources. Investment cost, primary energy consumption and global cost related to the resulting retrofit packages are investigated by means of smart exhaustive sampling. Finally, the cost-optimal solution is identified both in presence of a limitless economic availability and of limited budgets. The methodology is applied to a hospital reference building (RB), which represents hospitals built in South Italy between 1991 and 2005. The RB is defined by using an original approach, as required by the complexity of the examined building category. The achieved cost-optimal retrofit packages imply a reduction of primary energy consumption up to 67.9 kW h/m2 a (12.2%) and of global cost up to 2932 k€ (24.5%) with a maximum investment of 1236 k€.

Today, it is not well-known the impact of cool roofs during heating season in balanced climates. Proposed study tries to quantify the increase of energy demands of buildings characterized by high-reflective and high-emissive coatings of roof, by means of experiments and numerical simulations. Three coatings are investigated with different solar absorptance and thermal emittance. The experiments have been carried out at the living lab of the University of Sannio, a full-scale test-room, provided with a large flexibility in terms of variability of the thermal envelope and air-conditioning system. Moreover, numerical evaluations of heating and annual energy consumptions are presented.

Technology transfer, scientific research and education could have a key role in Mediterranean regions, in order to reduce the environmental impact of the building sector. Recently, the Department of Engineering of University of Sannio has developed a laboratory suitable for performing researches on the dynamic interactions between building envelope components, indoor environment and mechanical systems for a typical climate of south of Italy. The work described within this paper is a part of this large-scale project. Its goals are: (a) to design, test and validate a poly-equipped test room, (b) to perform transient tests to determine performances of common and innovative building components and alternative HVAC systems. More in detail, this paper focuses on the first goal, with the aim to generalize the design approach, requirements and capabilities of calibrated outdoor test facilities, specifically thought for Mediterranean climate. The facility has undergone a substantial amount of characterization tests, aimed at determining its response under yearly operations. The primary conclusions are that the new test facility is usable for a wide range of environmental and indoor conditions, it is functional and has been validated through characterization and preliminary investigations of the behavior of the thermal envelope. Moreover, some experimental results are here analyzed, by evidencing the potentialities of vacuum insulation panels for improving the performances of the thermal envelope, for what concerns both winter and summer seasons. Then, some numerical analyses have been carried out. A 3D CFD model has been calibrated for studying the real distribution of temperatures and water vapor partial pressures within VIP panels. Furthermore, a dynamic energy model of the test cell has been developed by means of Energy Plus, with the aim to use its capability to compare potential configurations that would be installed in future researches, or to evaluate energy, environmental and economic issues.

Topic of the study is the investigation of potentialities of energy simulation for optimizing the building refurbishment, by taking into account impacts of both envelope renovation and HVAC system selection. Energy audit and refurbishment of the Day-Hospital building of a great Italian health care facility are proposed. A meticulous energy diagnosis of the base case building and design of a complete renovation- by improving both building envelope and HVAC systems- are presented. All data and boundary conditions for dynamic energy investigations have been carefully selected, also by means of in-situ studies, in order to provide a reliable model. In particular, several energy efficiency measures, with reference to building envelope and HVAC systems, are analyzed and it will be evidenced that, step-by-step, a proper design, supported by the adoption of numerical studies, may optimize the energy performances of the building, as well as the indoor microclimatic control.

The urbanization has negative effects on the environment, mainly related to the generation of pollution, the modification of the properties of the atmosphere, the covering of the soil surface. The cumulative effects produce the so-called phenomenon of 'Urban Heat Island' (UHI). Cool roofs have a positive impact on the global environment, by reducing the energy required for interior cooling and related greenhouse gas emissions. Moreover these help to mitigate the UHI effect. A cool roofing material is characterized by higher solar reflectance in comparison to conventional roof coatings and high infrared emittance values. This paper is aimed to investigate the potentialities of high reflective commercial products not specialized for cool roofing. Three paints of the automotive sector have been selected. These products have very fast drying, good adhesion directly to different type of materials, good gloss and appearance, greater durability than traditional, lower cost and application time. Laboratory measurements are performed for the characterization of thermal-optical properties of different prototype samples, by considering application on different substrates (aluminum, ceramic tile, bitumen membrane, polyvinyl chloride sheet) as well as different configurations (evaluating the adoption of gripping and external gloss). Only the white acrylic paint shows good values for spectral reflectance (77-80%) and thermal emissivity (92%) that are comparable with commercial products. The artificial accelerated weather resistance tests and natural exposure effects have been also evaluated. Then, several numerical analyses are proposed for a real case study and some roof technologies also with different insulation level. The main evaluated indexes are the seasonal and annual energy savings, the reduction of polluting emissions and the cost effectiveness. Globally summer benefits are very satisfying meanwhile the annual energy saving varies between 0.3% and 3.0%. © 2016 Elsevier Ltd. All rights reserved.

Significant attention is currently being paid to reducing building energy demand and improving indoor thermal conditions, as required by European directives. In school buildings, a significant part of the winter energy demand is related to high airflow rates required for ventilating classrooms. Moreover, the correlation between comfortable indoor thermal-hygrometric conditions, healthy indoor air quality and satisfying student performance is well known. Few research works have investigated different types of air conditioning systems for typical school buildings, from the point of view of both energy and thermal-hygrometric performances. This kind of analysis is carried out in this paper. A typical school building located in southern Italy is analysed by using dynamic building energy simulation software. Different types of heating, ventilation and air conditioning (HVAC) systems are simulated for both winter and summer conditions. Indoor air temperature, relative humidity and predicted mean vote values are evaluated. The annual energy requirements, energy costs and related emissions are calculated. Finally, a multi-criteria analysis for the examined HVAC systems is proposed, considering different weighting for the main performance criteria (winter thermal comfort, plant costs, energy costs and emissions), in order to support decision making.