Assessment of construction cost reduction of nearly zero energy dwellings in a life cycle perspective

Concerning Nearly Zero Energy Buildings, it is important to guarantee energy efficiency, thermal comfort and indoor environmental quality, while keeping construction and operational costs low. In this framework, this paper explores the efficacy of applying different scenarios, for reducing construction costs of new nearly zero energy multi-family houses in a life cycle perspective. Conversely to the standard cost-optimal approach, a real Italian case study building was chosen. Alternative and unconventional combinations of solutions for envelope and technical systems were adopted. Calculations were performed in two Italian cities (Rome and Turin). Three types of analysis were developed thermal comfort, energy performance and financial calculation. Results of the thermal analysis show that the installation of active cooling to prevent summer overheating can be avoided by applying low-cost passive strategies. All the proposed low-cost scenarios (4 alternative scenarios in Rome and 5 in Turin)reached the highest grade of energy performance, with a reduction of the non-renewable primary energy consumption up to 46% compared to the base case in Rome and 18% in Turin. From the economic perspective, all the scenarios in the two climate zones allow both reductions in the construction costs, up to 26% in Rome and 15% in Turin, and a Net Present Value after 50 years up to 163 €/m2 in Rome and 158 €/m2 in Turin

A decision support system for fostering smart energy efficient districts

The role of ICT is becoming prominent in tackling some of the urban societal challenges such as energy wastage and increasing carbon emissions. In this context, the concept of DAREED aims to deliver an integrated decision support system (DSS) to drive energy efficiency and low carbon activities at both a building and district level. The main aim of this paper is to present the technical concept of the Best Practices recommendation component of the DAREED system. This component seeks to compare and identify existing best practices to recommend practical actions to various stakeholders (e.g. building managers, citizens) in order to improve energy performance considering the global needs of a building. This paper also discusses the context of the three field trial sites (based in UK, Spain and Italy) in which the DAREED platform along with the best practices tool is to be tested and validated.This work evolved in the context of the project DAREED (Decision support Advisor for innovative business models and useR engagement for smart Energy Efficient Districts), www.dareed.eu, a project cofunded by the EC within FP7, Grant agreement no: 609082

Cool Roof Impact on Building Energy Need: The Role of Thermal Insulation with Varying Climate Conditions

Cool roof effectiveness in improving building thermal-energy performance is affected by different variables. In particular, roof insulation level and climate conditions are key parameters influencing cool roofs benefits and whole building energy performance. This work aims at assessing the role of cool roof in the optimum roof configuration, i.e., combination of solar reflectance capability and thermal insulation level, in terms of building energy performance in different climate conditions worldwide. To this aim, coupled dynamic thermal-energy simulation and optimization analysis is carried out. In detail, multi-dimensional optimization of combined building roof thermal insulation and solar reflectance is developed to minimize building annual energy consumption for heating-cooling. Results highlight how a high reflectance roof minimizes annual energy need for a small standard office building in the majority of considered climates. Moreover, building energy performance is more sensitive to roof solar reflectance than thermal insulation level, except for the coldest conditions. Therefore, for the selected building, the optimum roof typology presents high solar reflectance capability (0.8) and no/low insulation level (0.00-0.03 m), except for extremely hot or cold climate zones. Accordingly, this research shows how the classic approach of super-insulated buildings should be reframed for the office case toward truly environmentally friendly buildings.The work was partially funded by the Spanish government (RTI2018-093849-B-C31). This work was partially supported by ICREA under the ICREA Academia programme. Dr. Alvaro de Gracia has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 712949 (TECNIOspring PLUS) and from the Agency for Business Competitiveness of the Government of Catalonia. This publication has emanated from research supported (in part) by Science Foundation Ireland (SFI) under the SFI Strategic Partnership Programme Grant Number SFI/15/SPP/E3125

Engineering design applications of surrogate-assisted optimization techniques

The construction of models aimed at learning the behaviour of a system whose responses to inputs are expensive to measure is a branch of statistical science that has been around for a very long time. Geostatistics has pioneered a drive over the last half century towards a better understanding of the accuracy of such ‘surrogate’ models of the expensive function. Of particular interest to us here are some of the even more recent advances related to exploiting such formulations in an optimization context. While the classic goal of the modelling process has been to achieve a uniform prediction accuracy across the domain, an economical optimization process may aim to bias the distribution of the learning budget towards promising basins of attraction. This can only happen, of course, at the expense of the global exploration of the space and thus finding the best balance may be viewed as an optimization problem in itself. We examine here a selection of the state of-the-art solutions to this type of balancing exercise through the prism of several simple, illustrative problems, followed by two ‘real world’ applications: the design of a regional airliner wing and the multi-objective search for a low environmental impact hous

Towards a lean model for production management of refurbishment projects, VTT Technology: 94

This is the Stage 3 Report for the ApRemodel project, which aims at improving processes for multi-occupancy retrofit by generating a lean model for project delivery. In this respect, a process-driven approach has been adopted to investigate what can be done to improve the way that retrofits projects are delivered. An initial literature review, focused on the management of refurbishment works, revealed that the research on this matter is scarce. There are plenty of studies related to the broad refurbishment area, however only a small number refer to the way that those construction projects are delivered. According to the literature, construction organisations have predominantly used traditional methods for managing the production of refurbishment projects. The problem is that those tools and techniques are not often appropriate to cope with the complex characteristics inherent to construction projects, especially in the case of refurbishments. Moreover, they have often not been based on a clear theoretical foundation. As a result, numerous types of waste have been identified in refurbishment projects such as waiting time, disruptions in performing tasks on site, rework, among others. This has led to unsatisfactory project performance in terms of low productivity, project delays, and cost overrun. The first step towards better production management in refurbishment projects is recognising the complexity of the sector in order to adopt the correct approach to cope with this specific scenario. In this respect, lean construction is identified as an appropriate way to deal with the complexity and uncertainty inherent in refurbishment projects, given that this management philosophy fully integrates the conversion, flow, and value views. This document builds on the findings from the literature review as well as evidence from case studies. Managerial practices based on lean construction principles have presented successful results in the management of complex projects. Case studies available in the literature report the feasibility and usefulness of this theoretical foundation. Moreover, the evidence from these studies show considerable potential for improving the management of refurbishment works. A list of methods, tools, and techniques are identified. This report may be used by construction refurbishment organisations and housing associations as a starting point for improving the efficiency in managing production of refurbishment projects. To this end, partnerships between industry and academia are strongly recommended. 4 Although the usefulness of lean principles in complex projects is already proved, further work is needed to check what practices are best for the respective refurbishment context, as well as identifying enablers and barriers for practical adoption. Furthermore, additional studies would be also necessary to better understand the extent to which the implementation of lean philosophy might influence performance of refurbishment projects. This report should be seen as work in progress with much more to learn, as detailed research work around the sustainable retrofit process in a lean way is further developed

Multi-objective optimisation of bio-based thermal insulation materials in building envelopes considering condensation risk

The reduction in energy demand for heating and cooling with insulation materials increases the material related environmental impact. Thus, implementing low embodied energy materials may equilibrate this trade-off. Actual trends in passive house postulate bio-based materials as an alternative to conventional ones. Despite that, the implementation of those insulators should be carried out with a deeper analysis due to their hygroscopic properties. The moisture transfer, the associated condensation risk and the energy consumption for seven biobased materials and polyurethane for a building-like cubicle are analysed. The performance is evaluated combining a software application to model the cubicle (EnergyPlus) and a tool to optimize its performance (jEPlus). The novelty of this optimization approach is to include and evaluate the effects of moisture in these insulation materials, taking into account the mass transfer through the different layers and the evaporation of the different materials. This methodology helps optimise the insulation type and thickness verifying the condensation risk, preventing the deterioration of the materials. The total cost of the different solutions is quantified, and the environmental impact is determined using the life cycle assessment methodology. The effect of climate conditions and the envelope configuration, as well as the risk of condensation, are quantified. The results show that cost and environmental impact can be reduced if bio-based materials are used instead of conventional ones, especially in semiarid climates. Condensation risk occurs for large thicknesses and in humid climates. In our case studies, hemp offered the most balanced solution.The authors would like to acknowledge financial support from the Spanish Government (CTQ2016-77968-C3-1-P, ENE2015-64117-C5-1-R, ENE2015-64117-C5-3-R, MINECO/FEDER, UE). The research leading to these results has received funding from the European Commission Seventh Framework Programme under grant agreement no. PIRSES-GA-2013-610692 (INNOSTORAGE). This project has received funding the European Union's Horizon 2020 Research and Innovation Program under grant agreement No 657466 (INPATH-TES). This article has been possible with the support of the Ministerio de Economía y Competitividad (MINECO) and the Universitat Rovira i Virgili (URV) (FJCI-2016-28789). Authors would like to acknowledge the Brazilian Government for their support by the CNPq (National Council for Scientific and Technological Development). M.P. would like to thank the Brazilian Education Ministry for the financial support received under the PNPD/Capes fellowship. L.F.C. would like to thank the Catalan Government for the quality accreditation given to her research group GREA (2014 SGR 123)

Modelling indoor air carbon dioxide concentration using grey-box models

Predictive control is the strategy that has the greatest reported benefits when it is implemented in a building energy management system. Predictive control requires low-order models to assess different scenarios and determine which strategy should be implemented to achieve a good compromise between comfort, energy consumption and energy cost. Usually, a deterministic approach is used to create low-order models to estimate the indoor CO2 concentration using the differential equation of the tracer-gas mass balance. However, the use of stochastic differential equations based on the tracer-gas mass balance is not common. The objective of this paper is to assess the potential of creating predictive models for a specific room using for the first time a stochastic grey-box modelling approach to estimate future CO2 concentrations. First of all, a set of stochastic differential equations are defined. Then, the model parameters are estimated using a maximum likelihood method. Different models are defined, and tested using a set of statistical methods. The approach used combines physical knowledge and information embedded in the monitored data to identify a suitable parametrization for a simple model that is more accurate than commonly used deterministic approaches. As a consequence, predictive control can be easily implemented in energy management systems.Peer ReviewedPostprint (author's final draft