No abstract

In accordance with national regulations, the renovation of the residential sector is an urgent task for achieving significant reductions in energy consumption and CO2 emissions of the existing building stock. Social housing is particularly in need of such interventions, given the higher vulnerability of its inhabitants and its crucial role in furthering social welfare and environmental sustainability objectives. Both passive and active strategies have proved their efficacy in advancing towards these goals and also in mitigating increasing fuel poverty in low-income families. However, to optimize the best combination of such retrofit strategies, advanced optimization methodologies can be applied. Here, a multi-objective optimization methodology is implemented by a genetic algorithm (aNSGA-II) coupled to EnergyPlus dynamic energy simulations. Then, the energy consumption of the optimal solution is considered by means of EnergyPLAN simulations for the further application of active strategies. The two-step method is tested on a relevant case study, a social housing building in Rome, Italy. Results show that the applied method reduced the energy demand by 51% with passive strategies only. Active strategy implementation allowed for a further reduction of 69% in CO2 emissions and 51% in energy costs. The two-step method proved effective in mitigating fuel poverty and decarbonizing the residential sector.

The application of digital modeling for safeguarding the built heritage is a consolidated research field and carries substantial operational interest. The methodological aspects of this application are theoretically outlined but far from being commonly applied. In the perspective of delineating a more straightforward method for implementing these practices among the built heritage, modern Italian architectural production constitutes an ideal field of investigation, both for the significance of the built heritage and for the construction problems that characterize them. Indeed, in the case of stone cladding – which is typical of the Fascist period – the decay conditions and the peculiarity of the material make the investigation specific and paradigmatic of the implementation of the above-mentioned digital methodologies. The Casa delle Armi built heritage by Luigi Moretti in Rome, which has been the research subject of the Authors for years, features a marbled envelope detailed by the designer in every aspect, not only during the design phase but also during construction. This uniqueness makes the recovery of the envelope extremely challenging, as it should not alter its extremely complex nature, while today, the marble envelope is profoundly degraded by natural and anthropogenic factors. Digital modeling appears to be an optimal operational solution for guiding the recovery, but it presents many issues illustrated in this article and to which we have begun to give answers in this contribution. In particular, we delineate the knowledge of the case mentioned above study-built heritage, pursued through documentary analysis integrated by direct and instrumental observation on site.

Nowadays, the energy retrofit of the building sector is identified as a major instrument toward a climate-neutral Europe by 2050. In accordance with the European Renovation Wave program, deep energy renovations are needed, starting from public and less efficient buildings. Furthermore, the renovation of the social housing building stock is also an important response to energy poverty, as it could contribute safeguarding health and well-being of vulnerable citizens. In particular, buildings from the 1960–1980, which constitute a large portion of cities, often have high energy demand and low indoor comfort because most of them have been built before energy-efficiency regulations. In this context, the paper aims to propose a multi-objective approach toward energy renovation of the social housing building stock, by means of an innovative digital workflow. The objective functions are minimizing energy consumption, CO2 emissions, investment, and operational costs. Toward these contrasting objectives, numerous passive strategies are taken into account, which are compatible with the considered architecture. The optimal solutions are found by means of a genetic algorithm coupled with energy performance simulation software. The methodology is applied and verified on a significant and relevant case study, pertaining to the social housing building stock of Rome, Italy (Mediterranean climate). The outputs of the workflow are a set of optimal solutions among which to choose the fittest one depending on the need of the different stakeholders. The proposed multi-objective approach allows reducing the energy consumption for heating by 31% and for cooling by 17% and the CO2 emissions up to 27.4%. The proposed methodology supports designers and policymakers toward an effective building stock renovation, which can answer the urgent energy and environmental targets for the coming decades.