An Innovative Multi-objective Optimization Digital Workflow for Social Housing Deep Energy Renovation Design Process

Abstract

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.