View all publicly available RINNO journal articles and conference papers here.

The building stock accounts for a significant portion of worldwide energy consumption and greenhouse gas emissions. While the majority of the existing building stock has poor energy performance, deep renovation efforts are stymied by a wide range of human, technological, organisational and external environment factors across the value chain. This paper presents a roadmap for an open renovation platform for managing and delivering deep renovation projects for residential buildings based on seven design principles.

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Buildings have a significant impact on energy consumption and carbon emissions. Smart buildings are deemed to play a crucial role in improving the energy performance of buildings and cities. Managing a smart building requires the modelling of data concerning smart systems and components. This study aimed to develop and test a solution for modelling and managing smart building information using an industry foundation classes (IFCs)-based BIM process.

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District heating is an efficient and promising way to cover the residential space-heating and domestic hot water needs, resulting in economic and environmental benefits, especially if operated by renewable power stations, when compared to fossil fuels. In this direction, the present study investigates in detail a district heating network with novel decentralized storage for domestic hot water (enerboxx scenario), over centralized storage systems, applying a specific schedule-based approach for the coordinated hot water tank charging. The goal of this design is to properly control the system by charging it at predetermined time periods during the day aiming at i) diminishing the thermal losses and ii) reducing the thermal demand from the grid, over the period of a day. The simulation is conducted with a newly developed component-based tool, called INTEMA, which is based on the Modelica language. This encompasses the ability to discretize with high temporal resolution and adjustable time steps the overall grid configuration, with the support of customizable level of detail models for simulating key system components such as the storage tanks, the piping and the dwelling needs, as well as the application of an advanced control system over the district heating network and the dwellings. More specifically, a combined control system that controls both operating parameters in the network and inside the dwellings is applied. The developed system model is verified against available data for a standard centralized storage system (reference scenario) and afterwards, the novel decentralized design is compared against corresponding results of the standard system, as concerns key operational parameters; indicatively the temperature levels of the hot water and the heat load demand. The analysis is conducted for a heating network of 9 dwellings in Austria, which have an underfloor heating system, a system for covering the domestic hot water demand, considering also that each of these 9 dwellings is characterized by a unique demand profile. It was found that the decentralized approach leads to lower demand and there are energy savings of 18 % compared to the reference scenario, while the thermal losses are reduced by about 22 %. Moreover, a parametric study regarding the storage tank volume and the heat exchanger thermal transmittance in the tank is conducted, in order to examine the impact of these design parameters on the system dynamic behavior.

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Building stock retrofitting is essential to achieve the ambitious sustainability goals of the building sector due to its high energy consumption rates. The evaluation of the various building interventions shall be holistically assessed in terms of environmental and costing impact. The aim of this paper is twofold: First, it presents the innovative characteristics of a developed online tool (Virtual intEgrated platfoRm on LIfe cycle AnalYsis – VERIFY) able to perform dynamic life cycle analysis and global warming impact assessments by capitalizing on the well-known LCA and LCC methodologies, applicable in the case of building renovation. VERIFY is able to analyse dynamic life cycle inventories that consider the temporal profiles of energy consumption, and the time-dependent temperature changes, while being also interoperable in terms of exchanging data with other available energy simulation engines, or even using real-time monitoring data from sensors, processing any data time granulation. Second, the paper evaluates, from a life cycle perspective, the impact of specific energy retrofitting measures, meeting the Passive House Standard, for the case of a multi-family residential building in Athens, Greece. The proposed energy-retrofitting scenario examines actions related to the deep retrofitting of the building envelope and the upgrade of the thermal components as well as to the incorporation of clean electricity generation based on renewable energy systems; all aiming to drastically reduce the environmental impact of the building, rendering it almost near zero energy. Through the planned infrastructure installations, the primary energy needs and CO2eq emissions were reduced by 91 % and by 95 % respectively, while for a building operational lifespan of 25 years, savings up to 515 k€ compared to the baseline scenario, can be achieved.

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Building Information Modelling (BIM) is now a globally recognised phenomenon, though its adoption remains inconsistent and variable between and within the construction sectors of different countries. BIM technology has enabled a wide range of functional applications, one of which, ‘4D BIM’, involves linking the tasks in a project’s construction schedule to its object-orientated 3D model to improve the logistical decision making and delivery of the project. Ideally, this can be automatically generated but in reality, this is not currently possible, and the process requires considerable manual effort. The level of maturity and expertise in the use of BIM amongst the project participants still varies considerably; adding further obstacles to the ability to derive full benefits from BIM. Reflecting these challenges, two case studies are presented in this paper. The first describes a predominantly manual approach that was used to ameliorate the implementation of 4D BIM on a project in Paris. In fact, there is scope for automating the process: a combination of BIM and Artificial Intelligence (AI) could exploit newly-available data that are increasingly obtainable from smart devices or IoT sensors. A prerequisite for doing so is the development of dedicated ontologies that enable the formalisation of the domain knowledge that is relevant to a particular project typology. Perhaps the most challenging example of this is the case of renovation projects. In the second case study, part of a large European research project, the authors propose such an ontology and demonstrate its application by developing a digital tool for application within the context of deep renovation projects.

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Building renovation presents real challenges for project participants which frequently generate high cost and schedule overruns. The disruption caused to occupants is one of the main challenges for the planning and management of renovation works. To better manage occupant interference and enable the acceleration of renovation works, this study aims to develop a novel framework for the assessment and optimisation of renovation strategies using BIM. The concept of disruption is formalised through a renovation ontology using the UML language. To enable process automation, the renovation ontology is then populated, and knowledge related to renovation tasks, constraints, duration, cost, equipment, and disruption are captured, structured and validated with industry partners. A digital tool and a set of Key Performance Indicators are also developed so as to facilitate the identification, assessment and optimisation of renovation scenarios in terms of cost, project duration and disruptive potential. Using a step-by-step process, detailed descriptions of the methodologies and workflows of the proposed framework are finally provided and demonstrated on a live case study located in Greece. The findings show no spatial correlation exist for the disruption concept and also confirm the disruptive nature of building floor renovation which can lead to a low rate of retrofitting them. Furthermore, the findings question the general applicability of the Whiteman et al.’s heuristic suggesting to prioritise the planning and execution of the most disruptive renovation activities as early as possible in the renovation process, and of the preference of Fawcett for a one-off renovation strategy recommending to conduct renovation works in one go as quickly as possible. Ultimately, the TEA framework will be further demonstrated and tested by end-users on three additional European case studies within the RINNO project which will particularly help validating the added value and benefits of the TEA framework from a user perspective.

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The current research applies the SRI methodology in two typologies of typical residential buildings, Single-Family Houses and Multi-Family Houses, in five EU Countries, to evaluate the retrofitting cost towards buildings smartification and assess the SRI score when different retrofitting scenarios are applied. To that end, a three-step assessment process is adopted. First, the SRI is calculated for the baseline scenario representing the national minimum requirements according to the EPBD. Next, the SRI is calculated after applying a retrofitting scenario that includes market available technologies towards Nearly Zero Energy Buildings. Last, a more comprehensive retrofitting scenario of integrated technologies towards Positive Energy Buildings is assessed. Results indicate that buildings, constructed after the implementation of the EPBD, can increase smartness with a relatively low cost than older buildings, although their initial overall SRI score generally leads to an SRI Class G (0–20%), with buildings performing better in “Health, well-being and accessibility” and “Comfort” impact categories. Smart-orientated retrofitting scenarios focusing on building automation and control measures can increase such buildings class up to “C” (65–80%), performing better in optimizing energy efficiency when applying retrofits towards NZEB. Applying retrofitting scenarios that could potentially lead to energy positiveness mainly supports building interaction with the grid.

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This paper investigates numerically the deep renovation of a multi-family building in Greece to reduce dramatically its energy demand and also to incorporate renewable energy sources, rendering it a positive one; thus in position on an annual basis to offer net electricity to the grid. The examined building has 8 apartments of 75 m2 floor area each and is located in Moschato, a suburb of Athens in Greece. The goal of the present investigation is to determine the energy savings, but also to calculate the financial and environmental benefits through a life cycle analysis. The energy simulation of the building is conducted on annual basis by using a novel and detailed dynamic software tool (INTEMA.building), which is developed in the Dymola environment using the Modelica modeling language. This tool makes possible the detailed simulation of both passive and active systems in the building environment. Furthermore, it includes the control of the energy systems and can provide accurate enough results, encompassing detailed numerical models for the systems investigated, accounting for an adjustable time step of the dynamic analysis. According to the calculations, the proposed retrofitting scenario can achieve a reduction of the heating loads by 93% and of cooling loads by 78% respectively. The electrical demand for domestic hot water can be decreased by about 79%, while the electricity demand for appliances and lighting by about 60%. In terms of specific thermal needs, the specific heating demand can be reduced from 151.5 kWh/m2 down to 10.7 kWh/m2, while the cooling specific demand from 112.6 kWh/m2 to 24.4 kWh/m2. Moreover, it is calculated that the reduction in the primary energy demand after the renovation can be up to 88%, with the building providing around 5.3 MWh of net electricity to the grid on a yearly basis through a net-metering connection. Finally, the life cycle cost analysis indicated 622 k€ savings and specific CO2 avoidance per renovated floor area in the range of 2.64 tons CO2/m2.

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Building renovation was declared a key point for sustainable development, however, the renovation rate of residential buildings in the European Union is insufficient to meet the climate and energy targets set. This paper analyses the main circular economy models used in the construction sector, as well as the situation of the building renovation market, to set a framework for circular economy models in building renovation. Of all the existing strategies in this sector, design, material recovery, building renovation and end-of-life actions would be the best, respectively. It also includes a market analysis consisting of a literature review covering PEST perspectives (political, economic, social and technical) and a SWOT analysis (strengths, weaknesses, opportunities and threats), concluding with a market gap analysis. The results of these analyses allow the development of a series of suggestions and strategies to be followed in order to solve the main barriers that hinder the implementation of the circular economy in the building´s renovation sector.

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Building Information Modelling (BIM) can be defined as a set of tools, processes and technologies that are enabled by a digital multi-dimensional representation of the physical and functional characteristics of a built asset. The ‘fourth’ dimension (4D BIM) incorporates time-related project information in the 3D model to simulate and optimise the project construction process. To achieve this, the 3D objects within the aggregated design model must be linked with each activity in the construction schedule. However, the levels of maturity and expertise in using BIM amongst the project participants still varies considerably. This generates collaboration problems within the project and adds further obstacles to the ability to derive full benefits from BIM. Ideally, 4D BIM can be automatically generated, but in reality, because the 3D and 4D models are created separately and at different stages of the project, this is not currently possible, and the process requires considerable manual effort. The research reported in this paper was prompted by the construction of a new training and research building: the Nanterre 2 CESI building in France. It proposes an efficient approach that minimises the effort of creating 4D BIM construction schedules. The CESI four-phase process aims to help project participants to fully exploit the potential of 4D BIM and enables: 1) a clear expression of the 4D BIM objectives; 2) the identification of information requirements and relevant workflows to achieve these objectives; 3) the implementation of a project schedule; and 4) BIM model production to suit the 4D BIM use case. Although the CESI approach was developed in the context of the French contracting system, the observations and conclusions of this study are intended to be generally applicable.

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